The Cardiovascular System
I just finished the book, which is published by Britannica Educational Publishing and edited by Kara Rogers.
It’s a little bit repetitive, but it’s really quite good. I knew a lot about the subject already, but this is my first textbook dealing specifically with this topic and there were a few places where I had ‘aha-moments’ and suddenly understood everything a lot better – I really enjoy reading books that give me such experiences.
I should point out that Khan Academy has a lot of good stuff on this subject, and the videos there go into a lot more detail than does the book – I haven’t seen all those videos, but I’ve seen enough of them to know that this is mostly good stuff. I should perhaps also point out that each link above is to a topic covered at Khan Academy, each with multiple videos of coverage. Wikipedia also has some stuff on this subject.
As an intro textbook to the subject I think the book is a decent choice, though the illustrations are somewhat lacking. All concepts are properly introduced and defined, and definitions will sometimes be repeated other places in the book (which is part of what makes it repetitive) so you don’t necessarily need to memorize everything to keep track of what’s going on. My main points of criticism would be the unnecessary amount of repetition and the fact that it doesn’t actually go into much detail. The latter point of criticism can however also be considered a plus if you don’t know very much about the subjects covered, and of course the somewhat superficial treatment of the material also means that this is by no means a hard textbook to read.
I found it hard to blog stuff from the book, because most of it is just definitions, ‘how does it all work?’, ‘what can go wrong and how does it go wrong?’, disease progression, treatment options, etc. Not a lot of numbers in there, or a lot of stuff that can easily be quoted ‘out of context’. But I figured I couldn’t blog the book without at least posting a few bits from the book, so below a few quotes (none of these are ‘old numbers’; the book was published in 2011):
“of those likely to die during the first two weeks after a major heart attack, nearly half will die within one hour of the onset of
symptoms.”
“less than half of the persons who die from heart attacks each year in the United States survive long enough to reach the hospital.”
“While life expectancy following a heart transplant is difficult to predict, the average recipient will live 8 to 10 years.” [...] The survival rate at one year is now about 84 percent and at three years about 77 percent.”
“The renal arteries deliver to the kidneys of a normal person at rest 1.2 litres (2.5 pints) of blood per minute, a volume equivalent to approximately one-quarter of the heart’s output. Thus, a volume of blood equal to all that found in the body of an adult human is processed by the kidneys once every four to five minutes.”
“In general, the rate of heartbeat varies inversely with the size of the animal. In elephants it averages 25 beats per minute, in canaries about 1,000. In humans the rate diminishes progressively from birth (when it averages 130) to adolescence but increases slightly in old age. The average adult rate is 70 beats at rest.”
A big part of the book is available at the link.
Khan Academy videos of interest
I assume that not all of the five videos below are equally easy to understand for people who’ve not watched the previous ones in the various relevant playlists, but this is the stuff I’ve been watching lately and you should know where to look by now if something isn’t perfectly clear. I incidentally covered some relevant background material previously on the blog – if concepts from chemistry like ‘oxidation states’ are a bit far away, a couple of the videos in that post may be helpful.
I stopped caring much when I reached the 1 million mark (until they introduced the Kepler badge – then I started caring a little again until I’d gotten that one), but I noticed today that I’m at this point almost at the 1,5 million energy points mark (1.487.776). I’ve watched approximately 400 videos at the site by now.
Here’s a semi-related link with some good news: Khan Academy Launches First State-Wide Pilot In Idaho.
Stuff
i. PLOS ONE: Till Death (Or an Intruder) Do Us Part: Intrasexual-Competition in a Monogamous Primate.
“Polygynous animals are often highly dimorphic, and show large sex-differences in the degree of intra-sexual competition and aggression, which is associated with biased operational sex ratios (OSR). For socially monogamous, sexually monomorphic species, this relationship is less clear. Among mammals, pair-living has sometimes been assumed to imply equal OSR and low frequency, low intensity intra-sexual competition; even when high rates of intra-sexual competition and selection, in both sexes, have been theoretically predicted and described for various taxa. Owl monkeys are one of a few socially monogamous primates. Using long-term demographic and morphological data from 18 groups, we show that male and female owl monkeys experience intense intra-sexual competition and aggression from solitary floaters. Pair-mates are regularly replaced by intruding floaters (27 female and 23 male replacements in 149 group-years), with negative effects on the reproductive success of both partners. Individuals with only one partner during their life produced 25% more offspring per decade of tenure than those with two or more partners. The termination of the pair-bond is initiated by the floater, and sometimes has fatal consequences for the expelled adult. The existence of floaters and the sporadic, but intense aggression between them and residents suggest that it can be misleading to assume an equal OSR in socially monogamous species based solely on group composition. Instead, we suggest that sexual selection models must assume not equal, but flexible, context-specific, OSR in monogamous species.”
You sort of want to extrapolate out of sample (/…out of species?) here, but be careful:
“Our findings differ from those reported for some monogamous birds, where remaining life-time reproductive success (i.e., the expected future gains) of the individual that initiates or tolerates a ‘divorce’ was higher than if it remained with its initial partner. For example, in kittiwakes (Rissa tridactyla) and many other pair-living birds, but also in some human societies, it is sometimes advantageous to ‘divorce’, if partners prove incompatible [25], [27], [35]. In contrast, our data strongly indicate that break-ups were associated with factors extrinsic to the pair, and that partners did not voluntarily leave or “divorce” as it has been reported for birds, gibbons, and (in at least one case) brown titi monkeys (Callicebus brunneus) [25]–[27], [36], [37]. On the other hand, in some species (oystercatchers, Haematopus ostralegus), the reproductive success of stable pairs is not only higher, but there are also accrued benefits with increased duration of the pair-bond, independent of effects of age or experience [38]. This was not the case for owl monkeys, since the number of offspring produced did not change with increased duration of the pair-bond (Fig. 2).”
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ii. Smbc (click to watch in a higher resolution):
Just to remind you that SMBC is still awesome. Here are a couple of related comics from the site.
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“The ability to control fire was a crucial turning point in human evolution, but the question when hominins first developed this ability still remains. Here we show that micromorphological and Fourier transform infrared microspectroscopy (mFTIR) analyses of intact sediments at the site of Wonderwerk Cave, Northern Cape province, South Africa, provide unambiguous evidence—in the form of burned bone and ashed plant remains—that burning took place in the cave during the early Acheulean occupation, approximately 1.0 Ma. To the best of our knowledge, this is the earliest secure evidence for burning in an archaeological context.”
[Another reminder that SMBC is awesome: Here's a recent comic which is very handy here - it explains what a Fourier transform is, in case you don't know... (If you actually want to know there's always wikipedia...)]
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iv. I never covered this here and though some of you may already have read it I thought I might as well link to Ed Yong’s write-up on replication studies in Nature published last year. A few quotes from the article:
“Positive results in psychology can behave like rumours: easy to release but hard to dispel. They dominate most journals, which strive to present new, exciting research. Meanwhile, attempts to replicate those studies, especially when the findings are negative, go unpublished, languishing in personal file drawers or circulating in conversations around the water cooler. “There are some experiments that everyone knows don’t replicate, but this knowledge doesn’t get into the literature,” says Wagenmakers. The publication barrier can be chilling, he adds. “I’ve seen students spending their entire PhD period trying to replicate a phenomenon, failing, and quitting academia because they had nothing to show for their time.
These problems occur throughout the sciences, but psychology has a number of deeply entrenched cultural norms that exacerbate them. It has become common practice, for example, to tweak experimental designs in ways that practically guarantee positive results. And once positive results are published, few researchers replicate the experiment exactly, instead carrying out ‘conceptual replications’ that test similar hypotheses using different methods. This practice, say critics, builds a house of cards on potentially shaky foundations.
These problems have been brought into sharp focus by some high-profile fraud cases, which many believe were able to flourish undetected because of the challenges of replication. Now psychologists are trying to fix their field.”
Good luck with that. I don’t see a fix happening anytime soon. A few numbers:
“In a survey of 4,600 studies from across the sciences, Daniele Fanelli, a social scientist at the University of Edinburgh, UK, found that the proportion of positive results rose by more than 22% between 1990 and 2007 (ref. 3). Psychology and psychiatry, according to other work by Fanelli4, are the worst offenders: they are five times more likely to report a positive result than are the space sciences, which are at the other end of the spectrum [...]. The situation is not improving. In 1959, statistician Theodore Sterling found that 97% of the studies in four major psychology journals had reported statistically significant positive results5. When he repeated the analysis in 1995, nothing had changed6.”
But maybe other fields are just as bad? Well, as already mentioned the space sciences do better – and that goes for other fields too (though I’d say there seems to be major problems in many areas besides psychology and psychiatry):
A major problem here is that unless you’re actually a researcher in the field or know whom to ask, the file drawer effect can be completely invisible to you.
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v. Globalization of Diabetes – The role of diet, lifestyle, and genes. A new publication in Diabetes Care. As usual when they say ‘diabetes’ they mean ‘type 2 diabetes’. Some numbers from the article:
“According to the International Diabetes Federation (1), diabetes affects at least 285 million people worldwide, and that number is expected to reach 438 million by the year 2030, with two-thirds of all diabetes cases occurring in low- to middle-income countries. The number of adults with impaired glucose tolerance will rise from 344 million in 2010 to an estimated 472 million by 2030.
Globally, it was estimated that diabetes accounted for 12% of health expenditures in 2010, or at least $376 billion—a figure expected to hit $490 billion in 2030 (2). [...] Asia accounts for 60% of the world’s diabetic population. [Do note that this does not mean that Asian countries are on average overrepresented in the diabetes statistics. Asia also has roughly 60% of the World's population. - US] [...] In 1980, less than 1% of Chinese adults had the disease. By 2008, the prevalence had reached nearly 10% [...] in urban areas of south India, the prevalence of diabetes has reached nearly 20% [...] Compared with Western populations, Asians develop diabetes at younger ages, at lower degrees of obesity, and at much higher rates given the same amount of weight gain [...]
If current worldwide trends continue, the number of overweight people (BMI >25 kg/m^2) is projected to increase from 1.3 billion in 2005 to nearly 2.0 billion by 2030 (6). [...] the prevalence of overweight and obesity in Chinese adults increased from 20% in 1992 to 29.9% in 2002 (8) [...]
In the NHS (26), each 2-h/day increment of time spent watching television (TV) was associated with a 14% increase in diabetes risk. [...] Each 1-h/day increment of brisk walking was associated with a 34% reduction in risk [...] Cigarette smoking is an independent risk factor for type 2 diabetes. A meta-analysis found that current smokers had a 45% increased risk of developing diabetes compared with nonsmokers (29). Moreover, there was a dose-response relationship between the number of cigarettes smoked and diabetes risk. [That one I did not know about!] [...] Light-to-moderate alcohol consumption is associated with reduced risk of diabetes. A meta-analysis of 370,000 individuals with 12 years of follow-up showed a U-shaped relationship, with a 30–40% reduced risk of the disease among those consuming 1–2 drinks/day compared with heavy drinkers or abstainers (37). [...]
common variants of the TCF7L2 gene that are significantly associated with diabetes risk are present in 20–30% of Caucasian populations but only 3–5% of Asians [...] Conversely, a variant in the KCNQ1 gene associated with a 20–30% increased risk of diabetes in several Asian populations (43,44) is common in East Asians, but rare in Caucasians [...]
Several randomized clinical trials have demonstrated that diabetes is preventable. One of the first diabetes prevention trials was conducted in Daqing, China (58). After 6 years of active intervention, risk was reduced by 31, 46, and 42% in the diet-only, exercise-only, and diet-plus-exercise groups, respectively, compared with the control group. In a subsequent 14-year follow-up study, the intervention groups were combined and compared with control subjects to assess how long the benefits of lifestyle change can extend beyond the period of active intervention (59). Compared with control subjects, individuals in the combined lifestyle intervention group had a 51% lower risk of diabetes during the active intervention period, and a 43% lower risk over a 20-year follow-up.”
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vi. Why chess sucks.
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Stuff
I thought I should update the blog even though these days I don’t do a lot of blogging-worthy stuff.
i. A blog I recently discovered: Empirical Zeal. There’s some interesting posts there, for example I liked this one on the state of Indian rural education (though the findings reported are not exactly worthy of celebration).
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ii. The acquisition of language by children. From the introduction:
“Imagine that you are faced with the following challenge. You must discover the internal structure of a system that contains tens of thousands of units, all generated from a small set of materials. These units, in turn, can be assembled into an infinite number of combinations. Although only a subset of those combinations is correct, the subset itself is for all practical purposes infinite. Somehow you must converge on the structure of this system to use it to communicate. And you are a very young child.
This system is human language. The units are words, the materials are the small set of sounds from which they are constructed, and the combinations are the sentences into which they can be assembled. Given the complexity of this system, it seems improbable that mere children could discover its underlying structure and use it to communicate. Yet most do so with eagerness and ease, all within the first few years of life.”
It’s actually pretty wild, once you start thinking about it.
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iii. The Null Ritual – What You Always Wanted to Know About Significance Testing but Were Afraid to Ask (via Gwern? I no longer remember how I found this.). An excerpt from the article:
“Question 1: What Does a Significant Result Mean?
What a simple question! Who would not know the answer? After all, psychology students spend months sitting through statistics courses, learning about null hypothesis tests (significance tests) and their featured product, the p-value. Just to be sure, consider the following problem (Haller & Krauss, 2002; Oakes, 1986):
Suppose you have a treatment that you suspect may alter performance on a certain task. You compare the means of your control and experimental groups (say, 20 subjects in each sample). Furthermore, suppose you use a simple independent means t-test and your result is signifi cant (t = 2.7, df = 18, p = .01). Please mark each of the statements below as “true” or “false.” False means that the statement does not follow logically from the above premises. Also note that several or none of the statements may be correct.
(1) You have absolutely disproved the null hypothesis (i.e., there is no difference between the population means). ® True False ®
(2) You have found the probability of the null hypothesis being true. ® True False ®
(3) You have absolutely proved your experimental hypothesis (that there is a difference between the population means). ® True False ®
(4) You can deduce the probability of the experimental hypothesis being true. ® True False ®
(5) You know, if you decide to reject the null hypothesis, the probability that you are making the wrong decision. ® True False ®
(6) You have a reliable experimental finding in the sense that if, hypothetically, the experiment were repeated a great number of
times, you would obtain a significant result on 99% of occasions. ® True False ®
Which statements are true? If you want to avoid the I-knew-it-all-along feeling, please answer the six questions yourself before continuing to read. When you are done, consider what a p-value actually is: A p-value is the probability of the observed data (or of more extreme data points), given that the null hypothesis H0 is true, defined in symbols as p(D |H0).Th is defi nition can be rephrased in a more technical form by introducing the statistical model underlying the analysis (Gigerenzer et al., 1989, chap. 3). Let us now see which of the six answers are correct:
Statements 1 and 3: Statement 1 is easily detected as being false. A significance test can never disprove the null hypothesis. Significance tests provide probabilities, not definite proofs. For the same reason, Statement 3, which implies that a significant result could prove the experimental hypothesis, is false. Statements 1 and 3 are instances of the illusion of certainty (Gigerenzer, 2002).
Statements 2 and 4: Recall that a p-value is a probability of data, not of a hypothesis. Despite wishful thinking, p(D |H0) is not the same as p(H0 |D), and a significance test does not and cannot provide a probability for a hypothesis. One cannot conclude from a p-value that a hypothesis has a probability of 1 (Statements 1 and 3) or that it has any other probability (Statements 2 and 4). Therefore, Statements 2 and 4 are false. The statistical toolbox, of course, contains tools that allow estimating probabilities of hypotheses, such as Bayesian statistics (see below). However, null hypothesis testing does not.
Statement 5: The “probability that you are making the wrong decision” is again a probability of a hypothesis. This is because if one rejects the null hypothesis, the only possibility of making a wrong decision is if the null hypothesis is true. In other words, a closer look at Statement 5 reveals that it is about the probability that you will make the wrong decision, that is, that H0 is true. Thus, it makes essentially the same claim as Statement 2 does, and both are incorrect.
Statement 6: Statement 6 amounts to the replication fallacy. Recall that a p-value is the probability of the observed data (or of more extreme data points), given that the null hypothesis is true. Statement 6, however, is about the probability of “significant” data per se, not about the probability of data if the null hypothesis were true. The error in Statement 6 is that p = 1% is taken to imply that such significant data would reappear in 99% of the repetitions. Statement 6 could be made only if one knew that the null hypothesis was true. In formal terms, p(D |H0) is confused with 1 – p(D). The replication fallacy is shared by many, including the editors of top journals. [...] To sum up, all six statements are incorrect. Note that all six err in the same direction of wishful thinking: They overestimate what one can conclude from a p-value. [...]
We posed the question with the six multiple-choice answers to 44 students of psychology, 39 lecturers and professors of psychology, and 30 statistics teachers [...] How many students and teachers noticed that all of the statements were wrong? As Figure 1 shows, none of the students did. [...] Ninety percent of the professors and lecturers also had illusions, a proportion almost as high as among their students. Most surprisingly, 80% of the statistics teachers shared illusions with their students.”
The article has much more.
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“More than 25% of the U.S. population aged [>65] years has diabetes (1), and the aging of the overall population is a significant driver of the diabetes epidemic. [...] The incidence of diabetes increases with age until about age 65 years, after which both incidence and prevalence seem to level off”. I should have known the first number was in that neighbourhood, but somehow I had failed to realize that it was that high; most often prevalence estimates are calculated/reported using the entire population in the denominator, but of course such estimates can be deceiving if you do not think about how they are calculated and I clearly hadn’t. At least 1 in 4 in the above-65 age bracket. That’s a lot of people. The article doesn’t have a lot of data, it’s a ‘consensus report’ handling mostly various treatment guideline suggestions and similar stuff.
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v. What is the most uncomfortable situation have you ever been put in- by a guy? Any kind of unwanted flirtation- or something of that nature (Reddit). Lots of really horrible stuff; reading stuff like this makes what might be perceived of as some females’ ‘somewhat overcautious’ behaviour towards members of the opposite sex easier to understand. An example from the link:
“The last stranger-danger moment I will share tonight was at an end-of-midterms party sponsored by the student union at a local bar. I was there with my best friend, and she’s very pretty and very friendly, so we’d very quickly attracted a group of four or five men who were hanging around with us for most of the night. I hadn’t seen any of them before, so I assumed they were students from a different department, and we end up getting a table together and talking for a while. Once my friend mentions that she has a boyfriend, most of them shift their attention to me, though there’s one who still seems interested in her. As I’m talking to them, I find that they’re not students at our university, but that they’re a group of friends visiting from the a couple towns over. Nothing too creepy, so far.
My friend finishes her drink, so the guy she’s talking to goes to buy her another. She’s a little suspicious, so she starts drinking it VERY slowly. Meanwhile, I’m getting distracted talking to one of the guys who works in the same field I’ll be entering soon, and we end up talking for a while about that. He keeps telling me that I’m very beautiful, which I keep brushing off because I knew he was interested in my friend initially, and I was interested in someone else at the time, anyway. Somewhere in the middle of all this, my friend has stopped drinking the drink that was bought for her, and someone asks if she’s going to finish it. She says no.
Eventually, the guy I’m talking to apologizes for his “bad” English, saying that he hasn’t really had to use it since he was in school, which was OVER TEN YEARS AGO. At about the same time, my friend is telling the guy she’s talking to that it’s funny that they decided to visit our city on that particular weekend, because this is a student end-of-midterm party, and he answers, “I know. That’s kind of why we came here.” Someone else asks my friend if she’s going to finish her drink, and she says no, but he can have it if he wants. The drink ‘accidentally’ gets spilled in the process, and she’s signalling me to get the fuck out of there, so I take the opportunity to drag her to the bathroom. I start to notice that she’s acting really fucked up – she can usually drink a ton more than I can, and she’d only had one drink of her own and maybe a third (probably less than that, actually) of the one that guy bought for her. She says she thinks the drink they gave her was drugged, and then she gets sick. I ended up staying the night at her place to keep an eye on her, but I didn’t think to take her to the hospital or anything, so I guess we’ll never know what exactly happened…”
Of course if you’re like me you don’t engage in risky behaviours like drinking with strangers and in that case it doesn’t really matter much if you’re male or female, but then again I’m not like normal people. Most males probably significantly underestimate how risky some of their behaviours – behaviours they would not ever even think of as ‘particularly risky’ – are when a female engages in them. Note that even males that fall into the “I can’t imagine you raising your voice”-category (a female friend said this about me in a conversation I had with her earlier today) are likely to be affected by the behaviours of the (type of) males described in the link; once a female has been through situations like the ones described at the link, she’s less likely to give males the benefit of the doubt and more likely to misinterpret behaviour and the motivations driving behaviour. Reading this stuff has made me believe that the behaviour of ‘overcautious’ females may be better justified and less ‘irrational’ than males tend to think it is.
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vi. I haven’t commented on the new DSM-5 – let’s just say I’ve had better things to do. Here’s one take on it (“It’s arcane, contradictory and talks about invisible entities which no-one can really prove. Yes folks, the new psychiatric bible has been finalised.”). The most ‘relevant’ change to me is the fact that they’ll remove the Asperger Syndrome diagnosis, and instead merge it with other autism spectrum disorders. If you’re asking me what I think about that, the answer is that I don’t really care.
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vii. Cheetahs on the Edge (via Ed Yong). A must-see:
“Using a Phantom camera filming at 1200 frames per second while zooming beside a sprinting cheetah, the team captured every nuance of the cat’s movement as it reached top speeds of 60+ miles per hour.
The extraordinary footage that follows is a compilation of multiple runs by five cheetahs during three days of filming.”
Adult development and aging: Biopsychosocial Perspectives, 4th edition (II)
The first post about the book is here. Below some stuff from chapters 4 and 5, which I liked a lot better than the first ones because they had a lot more data:
“The overall pattern of body weight in adulthood shows an upside-down U-shaped trend reflecting the fact that most people increase in their weight from the 20s until the mid-50s, after which their weight decreases. Most of the weight gain that occurs through the years of middle adulthood is due to an increase in BMI (Ding, Cicuttini, Blizzard, Scott, & Jones, 2007), which is manifested mainly as the accumulation of body fat around the waist and hips (commonly referred to as the ‘‘middle-aged spread’’). The loss of body weight in the later years of adulthood is not, however, due to a loss of this accumulated fat and so does not mean that older adults necessarily become healthier or more fit. Instead, older adults lose pounds because they suffer a reduction of FFM [fat-free mass] due to loss of muscle mass, even if they maintain high levels of activity (Manini et al., 2009).
At the other end of the spectrum, some older adults continue to gain weight to the point of developing a BMI that places them in the overweight or obese categories. Between the mid-1990s and mid-2000s, the percent of older adults classified as overweight increased from 60 to 69% and as obese from 22 to 31% (Houston, Nicklas, & Zizza, 2009). [...]
You are able to move around in your environment due to the actions of the structures that support this movement, including the bones, joints, tendons, and ligaments that connect the muscles to the bones, and the muscles that control flexion and extension. In the average person, all these structures undergo age-related changes that compromise their ability to function effectively. Beginning in the 40s (or earlier in the case of injury), each component of mobility undergoes significant age-related losses. Consequently, a gradual reduction of walking speed occurs (Shumway-Cook et al., 2007). [...] The adult years are characterized by a progressive age-related loss of muscle tissue, a process known as sarcopenia. There is a reduction in the number and size of muscle fibers, especially the fast-twitch fibers involved in speed and strength. As indicated by research from cross-sectional studies, muscle strength (as measured by maximum force) reaches a peak in the 20s and 30s, remains at a plateau until the 40s to 50s, and then declines at a faster rate of 12 to 15% per decade (Kostka, 2005), with more pronounced decreases, at least cross-sectionally, for men. Muscular endurance (as measured by isometric strength) is, however, generally maintained throughout adulthood (Lavender & Nosaka, 2007). [...] The loss of muscle mass brings with it a set of negative consequences including increased risk of falling, limitations in mobility, and reduced quality of everyday life. Unfortunately, sarcopenia can become part of a vicious cycle because the greater the loss of muscle mass, the greater the difficulty in undertaking exercise, causing an exacerbation of muscle loss and further weakening (Lang et al., 2009). [...]
Bone is living tissue that constantly reconstructs itself through a process of bone remodeling in which old cells are destroyed and replaced by new cells. The general pattern of bone development in adulthood involves an increase in the rate of bone destruction compared to renewal and greater porosity of the calcium matrix, leading to loss of bone mineral content. [...] Estimates of the decrease in bone mineral content over adulthood are about .5% per year for men and 1% per year for women (Emaus, Berntsen, Joakimsen, & Fonnebo, 2006). Further weakening occurs due to microcracks that develop in response to stress placed on the bones (Diab, Condon, Burr, & Vashishth, 2006). Part of the older bone’s increased susceptibility to fracture can be accounted for by a loss of collagen, which reduces the bone’s flexibility when pressure is put upon it (Saito & Marumo, 2009). [...]
Cardiovascular efficiency is indexed by aerobic capacity, the maximum amount of oxygen that can be delivered through the blood, and cardiac output, the amount of blood that the heart pumps perminute. Both indices decline consistently at a rate of about 10% per decade from age 25 and up so that the average 65-year-old has 40% lower cardiovascular efficiency than the young adult (Betik & Hepple, 2008). The decline is more pronounced in males than females (Goldspink et al., 2009). Maximum heart rate, the heart rate achieved at the point of maximum oxygen consumption, also shows a linear decrease across the years of adulthood. Declines in aerobic capacity occur even in highly trained athletes, but those who continue to exercise at a high level of intensitymaintain their aerobic capacity longer than non-athletes (Tanaka&Seals, 2003). [...] With regard to aerobic functioning, exercise is one of the best ways you can slow down the rate of your body’s aging process. [...]
Approximately 30% of all adults 65 and older suffer from urge incontinence, a form of urinary incontinence in which the individual experiences a sudden need to urinate, and often results in urine leakage. Stress incontinence involves loss of urine experienced during exertion. The prevalence of daily incontinence ranges from 12% in women 60 to 64 years old to 21% in women 85 years old or older [...] A variety of treatments are available to counteract incontinence, but because people often mistakenly assume that bladder dysfunction is a normal part of aging, they are less likely to seek active treatment. In one study of more than 7.2 million patients diagnosed with overactive bladder, 76% went untreated (Helfand, Evans,&McVary, 2009). Medications such as tolderodine (Detrol LA) are becoming increasingly available to help control bladder problems. [...]
Although men do not experience a loss of sexual function comparable to the menopause (despite what you might hear about the ‘‘male menopause’’), men undergo andropause, which refers to age-related declines in the male sex hormone testosterone. The decline in testosterone is equal to 1% per year after the age of 40, a decrease observed in longitudinal as well as cross-sectional studies (Feldman et al., 2002). The term ‘‘late-onset hypogonadism’’ or ‘‘age-associated hypogonadism’’ has begun to replace the term andropause, although all three terms are currently in use. [...] Erectile dysfunction (ED), a condition in which a man is unable to achieve an erection sustainable for intercourse, is estimated to increase with age in adulthood, from a rate of 31% among men 57–65 to 44% of those 65 and older. ED is related to health problems in older men, including metabolic syndrome (Borges et al., 2009). [...]
Normal aging seems to have major effects on the prefrontal cortex, the area of the brain most involved in planning and the encoding of information into long-term memory, as well as in the temporal cortex, involved in auditory processing (Fjell et al., 2009). The hippocampus, the structure in the brain responsible for consolidating memories, becomes smaller with increasing age, although this decline is more pronounced in abnormal aging such as in Alzheimer’s disease (Zhang et al., 2010). [...]
Most people require some form of corrective lenses by the time they reach their 50s or 60s. Presbyopia, or loss of the ability to focus vision on near objects, is the primary culprit for the need for reading glasses, and is the visual change that most affects people in midlife and beyond.
Presbyopia is caused by a thickening and hardening of the lens, the focusing mechanism of the eye (Sharma & Santhoshkumar, 2009). As a result, the lens cannot adapt its shape when needed to see objects up close to the face. By the age of 50, presbyopia affects the entire population. Treatment for the cause of presbyopia does not exist, and although bifocals were the only correction since the time of Benjamin Franklin (who invented them) newer multifocal contact lenses are increasingly becoming available on the market (Woods, Woods, & Fonn, 2009). Though you cannot cure presbyopia, you may be able to alter its onset because lifestyle habits seem to affect the rate at which the presbyopic aging process occurs. For example, smoking accelerates the aging of the lens (Kessel, Jorgensen, Glumer, & Larsen, 2006).
Older adults are also likely to experience the loss of visual acuity, or the ability to see details at a distance. The level of acuity in an 85-yearold individual is approximately 80% less than that of a person in their 40s. [...]
Loss of balance is one of the main factors responsible for falls in older adults (Dickin, Brown, & Doan, 2006). In 2007 alone, more than 15,800 people 65 and older were known to have died directly from injuries related to falls (Kung, Hoyert, Xu, & Murphy, 2008); 1.8 million were treated in emergency departments for fall-related nonfatal injuries, and about 460,000 of these people were hospitalized (Stevens, Ryan, & Kresnow, 2006). [...]
Smell and taste belong to the chemical sensing system referred to as chemosensation. The sensory receptors in these systems are triggered when molecules released by certain substances stimulate special cells in the nose, mouth, or throat. Despite the fact that the olfactory receptors constantly replace themselves, the area of the olfactory epithelium shrinks with age, and ultimately the total number of receptors becomes reduced throughout the adult years. At birth, the olfactory epithelium covers a wide area of the upper nasal cavities, but by the 20s and 30s, its area has started to shrink noticeably.
Approximately one third of all older adults suffer some form of olfactory impairment (Shu et al., 2009) with almost half of those 80 years and older having virtually no ability to smell at all (Lafreniere & Mann, 2009). The loss of olfactory receptors reflects intrinsic changes associated with the aging process, as well as damage caused by disease, injury, and exposure to toxins. Research suggests that these environmental toxins may play a larger role in olfactory impairment than changes due to the aging process. [...]
A sedentary lifestyle is the first major risk factor for heart disease. The relationship between leisure activity and heart disease is well established (Yung et al., 2009), with estimates ranging from a 24% reduction in the risk of myocardial infarction among non-strenuous exercisers to a 47% reduced risk among individuals engaging in a regular pattern of strenuous exercise (Lovasi et al., 2007). As it happens, the majority of adults at highest risk for heart disease (i.e., those 75 and older) are the least likely to exercise. Only about 36% of people 65 to 74 and 16% of those 75 and older engage in vigorous leisure activity (National Health Interview Survey, 2009). [...] Approximately one fifth of all adults in the United States are current smokers. The rates of current smokers decrease across age groups of adults to 10% of those 65 and older (National Health Interview Survey, 2009). [...]
In 2009, it was estimated that nearly 1.5 million Americans received a diagnosis of cancer (not including skin cancer or noninvasive cancers) and that about 10.5 million are living with the disease. The lifetime risk of developing cancer is about 1 in 2 for men and 1 in 3 for women (American Cancer Society, 2009). [...] All cancer is genetically caused in the sense that it reflects damage to the genes that control cell replication. [...this is actually, I think, a very good way to put it.] [...]
A nationwide study of over 900,000 adults in the United States who were studied prospectively (before they had cancer) from 1982 to 1998 played an important role in identifying the role of diet. During this period of time, there were more than 57,000 deaths within the sample from cancer. The people with the highest BMIs had death rates from cancer that were 52% higher for men and 62% higher for women compared with men and women of normal BMI. The types of cancer associated with higher BMIs included cancer of the esophagus, colon and rectum, liver, gallbladder, pancreas, and kidney. Significant trends of increasing risk with higher BMIs were observed for death from cancers of the stomach and prostate in men and for death from cancers of the breast, uterus, cervix, and ovary in women (Calle, Rodriguez, Walker-Thurmond, & Thun, 2003). We can conclude from this research that maintaining a low BMI is a critical preventive step in lowering your risk of cancer.
In addition to BMI, eating specific foods seems to play a role in cancer prevention. Stomach cancer is more common in parts of the world—such as Japan, Korea, parts of Eastern Europe, and Latin America—in which people eat foods that are preserved by drying, smoking, salting, or pickling. By contrast, fresh foods, especially fresh fruits and vegetables, may help protect against stomach cancer. Similarly, the risk of developing colon cancer is thought to be higher in people whose diet is high in fat, low in fruits and vegetables, and low in highfiber foods such as whole-grain breads and cereals. [...]
It is estimated that 8 million women and 2 million men in the United States suffer from osteoporosis (Sweet, Sweet, Jeremiah, & Galazka, 2009). Women are at higher risk than men because they have lower bone mass in general but nevertheless, osteoporosis is a significant health problem in men. Rates of osteoporosis-related bone fracture are equivalent to the rates of myocardial infarction (Binkley, 2009). Women vary by race and ethnicity in their risk of developing osteoporosis; White and Asian women have the highest risk, whereas Blacks and Hispanics the lowest. In addition, women who have small bone structures and are underweight have a higher risk for osteoporosis than heavier women. [...]
According to the World Health Organization, the number of people suffering from diabetes worldwide is approximately 171 million in 2010, a number that will double by 2030. [...]
Approximately 20% of cases of dementia are due to cerebrovascular disease (Knopman, 2007). [...] In vascular dementia, progressive loss of cognitive functioning occurs as the result of damage to the arteries supplying the brain. Dementia can follow a stroke, in which case it is called acute onset vascular dementia, but the most common form of vascular dementia is multi-infarct dementia or MID, caused by transient ischemic attacks. In this case, a number of minor strokes (‘‘infarcts’’) occur in which blood flow to the brain is interrupted by a clogged or burst artery. Each infarct is too small to be noticed, but over time, the progressive damage caused by the infarcts leads the individual to lose cognitive abilities. There are important differences between MID and Alzheimer’s disease. The development of MID tends to be more rapid than Alzheimer’s disease, and personality changes are less pronounced. The higher the number of infarcts, the greater the decline in cognitive functioning (Saczynski et al., 2009). [...]
People who develop Parkinson’s disease show a variety of motor disturbances, including tremors (shaking at rest), speech impediments, slowing of movement, muscular rigidity, shuffling gait, and postural instability or the inability to maintain balance. Dementia can develop during the later stages of the disease, and some people with Alzheimer’s disease develop symptoms of Parkinson’s disease. Patients typically survive 10 to 15 years after symptoms appear.”
Adult development and aging: Biopsychosocial Perspectives, 4th edition
“Everyone ages. This very fact should be enough to draw you into the subject matter of this course, whether you are the student or the instructor. Yet, for many people, it is difficult to imagine the future in 50, 40, or even 10 years from now. The goal of our book is to help you imagine your future and the future of your family, your friends, and your society. We have brought together the latest scientific findings about aging with a more personal approach to encourage you to take this imaginative journey into your future. [...]
Our goal is to engage you by presenting you with information that is of both personal and professional interest. We will explore the variety of ways individuals can affect their own aging process, such as through incorporating behaviors and activities designed to maintain high levels of functioning well into the later decades of life.”
From the introduction and first part of chapter 1. You can find the book here. I thought the subject would be interesting to read about, and apparently this is the kind of stuff that’s available. I’m not super impressed at this point as there’s a lot of ‘talk’ included in the first chapters of the book – they tend to use many words to say very little. And quite a bit of the talk stuff is just unscientific theorizing without data. But there’s some interesting stuff here as well. Below some stuff from the first 3 chapters (click to view figures in a higher resolution):
“In 1900, the number of Americans over the age of 65 years made up about 4% of the population [...] People 65 and older now represent 12.3% of the total U.S. population [...] In 1990, an estimated 37,306 people over the age of 100 lived in the United States. By 2004 this number increased 73% to 64,658, and by 2050 there will be over 1.1 million of these exceptionally aged individuals.”
“Women over the age of 65 currently outnumber men, amounting to approximately 58% of the total over-65 population [in the US]. [...] In 2010, there were 531 million people worldwide over the age of 65. Predictions suggest that this number will triple to 1.53 billion by the year 2050 (U.S. Bureau of the Census, 2010c). China currently has the largest number of older adults (106 million), but Japan has the highest percentage of people 65 and older (20%) (Kinsella & He, 2009). [...]
[...]
“The most compelling attempts to explain aging through genetics are based on the principle of replicative senescence, or the loss of the ability of cells to reproduce. Scientists have long known that there are a finite number of times (about 50) that normal human cells can proliferate in culture before they become terminally incapable of further division (Hayflick, 1994).
Until relatively recently, scientists did not know why cells had a limited number of divisions. It was only when the technology needed to look closely at the chromosome developed that researchers uncovered some of the mystery behind this process.
As we saw in Figure 2.6, the chromosome is made up largely of DNA. However, at either end of the chromosomes are telomeres, repeating sequences of proteins that contain no genetic information (see Figure 2.8). The primary function of the telomere is to protect the chromosome from damage. With each cell division, the telomeres become shorter, ultimately altering patterns of gene expression affecting the functioning of the cell and the organ system in which it operates. Once telomeres shorten to the point of no longer being able to protect the chromosome, adjacent chromosomes fuse, the cell cycle is halted, and ultimately the cell dies (Shin, Hong, Solomon, & Lee, 2006). Evidence linking telomere length to mortality in humans suggests that the telomeres may ultimately hold the key to understanding the aging process (Cluett & Melzer, 2009).
However, biology does not completely explain the loss of telomeres over the course of life. Supporting the idea of biopsychosocial interactions in development, researchers have linked telomere length to social factors. Analyzing blood samples from more than 1,500 female twins, researchers in the United Kingdom determined that telomere length was shorter in women from lower socioeconomic classes (Cherkas et al., 2006). There was a difference of seven ‘‘biological years’’ (measured in terms of telomeres) between twins with manual jobs and their co-twins in higher-ranking occupations. The researchers attributed this difference to the stress of being in a lower-level occupation in which people have less control over their day-to-day activities. Body mass index, smoking, and lack of exercise were additional factors influencing telomere length. A subsequent study on this sample provided further research of the important role of lifestyle factors. Even after the researchers adjusted for such factors as age, socioeconomic status, smoking, and body mass index, people who engaged in higher levels of physical activity had longer telomeres than those who did not (Cherkas et al., 2008). [...]
Random error theories are based on the assumption that aging reflects unplanned changes in an organism over time. The wear and tear theory of aging is one that many people implicitly refer to when they say they feel that they are ‘‘falling apart’’ as they get older. According to this view, the body, like a car, acquires more and more damage as it is exposed to daily wear and tear from weather, use, accidents, and mechanical insults. Programmed aging theories, in contrast, would suggest that the car was not ‘‘built to last,’’ but rather was meant to deteriorate over time in a systematic fashion. [...]
The free radical theory, or oxidative stress theory (Sohal, 2002), focuses on a set of unstable compounds known as free radicals, produced when certain molecules in cells react with oxygen. The primary goal of a free radical is to seek out and bind to other molecules. When this occurs, the molecule attacked by the free radical loses functioning. Although oxidation caused by free radicals is a process associated with increasing age, researchers have questioned the utility of this approach as a general theory of aging (Perez et al., 2009).”
Chapter 3 has some stuff on problems with making causal claims in this area of research and some stuff on longitudinal studies and cross-sectional studies in this area, including pros and cons of the two types of studies. After that they note that:
“considerable progress in some areas of research has been made through the application of sequential designs. These designs consist of different combinations of the variables age, cohort, and time of measurement. Simply put, a sequential design involves a ‘‘sequence’’ of studies, such as a cross-sectional study carried out twice (two sequences) over a span of 10 years. The sequential nature of these designs is what makes them superior to the truly descriptive designs conducted on one sample, followed over time (longitudinal design) or on different-aged samples, tested on one occasion (cross-sectional design). Not only do sequential studies automatically provide an element of replication, but when they are carried out as intended, statistical analyses can permit remarkably strong inferences to be drawn about the effect of age as distinct from cohort or time of measurement.”
Much of the stuff covered in chapter 3 on research methods should be known stuff to people reading a blog like this, because aging research isn’t that different from other types of research. I skimmed over some of this stuff because much of it is (a wordier and less formalized way to deal with) known stuff from introductionary statistics classes in my past.
Pathophysiology of Disease: An Introduction to Clinical Medicine (2nd edition) (II)
My first post about the book can be found here. In this post I’ll talk a little bit the chapters 4-5, which deal with infectious diseases and neoplasia.
When reading chapter 4 – on infectious diseases – it was a great help to have read chapter 3 first – that chapter had a lot of stuff on how the body defends itself against the kind of stuff they talk about in chapter 4, and even though they recap a bit of that stuff in chapter 4 it’s probably smart to read those two chapters in the order they appear in the book. I did not find chapter 4 particularly hard to read, in part probably because this stuff is closely related to the microbiology stuff I read in the past, which dealt in much more detail with the microorganisms causing these diseases. There’s a lot of important concepts covered: transmission mechanisms; factors impacting disease susceptibility; the normal microbial flora and how it relates to this topic at hand; constitutive defences the body (‘defence mechanisms which do not require prior contact with the microorganism – such as physical and chemical barriers to colonization, inflammatory response, the complement system, and phagocytosis); disease progression (to cause disease all microorganisms must go through four stages: they must encounter the host, gain entry, multiply and spread, and cause host tissue injury. The course of an infection may vary from asymptomatic to life threatening; an important distinction is between acute (and sub-acute) and chronic infections). Chronic infection is not the only outcome of a long-term colonization; an individual may also enter a carrier state, or the infection may become latent until reactivation.).
After the ‘general stuff’ has been covered in chapter 4, they deal with the pathophysiology of some examples of infectious diseases; infective endocarditis (bacterial or fungal infection of the interior of the heart), meningitis, pneumonia, infectious diarrhea, and sepsis/sepsis syndrome/septic shock. I’ll not go into much detail about these diseases, but I should probably note here that the names we use to describe infectious diseases like these may cause people to misunderstand how they work: To be clear, there isn’t just one ‘endocarditis bacterium’ or a specific ‘meningitis bacterium’. When specific sites/organ systems are invaded by microorganisms which spread and cause tissue damage (damage which can be caused both by the toxins released by the invading microorganisms and by the host response to the invasion), we have a name for that – but many different microorganisms may cause symptoms by invading the specific site or organ system in question, though some are more likely to affect specific sites than others. Sometimes the names of the microorganisms may even add to this confusion; for example one of the most common causes of bacterial meningitis (infection of the meninges) in children aged 2 months to 15 years is H Influenzae (which kind of sounds like, well…).
Chapter 5 deals with neoplasia. If you dont’ feel like reading this stuff, at least read Mukherjee. The chapter deals briefly with colon carcinoma as an example of an epithelial neoplasia; this stuff from Khan Academy is another great resource on this subject – it also deals a bit with cancer development more generally, and it’s a lot more accessible than is this chapter.
Anyway, the chapter… It starts out with a bit of a downer: “The recognition of overt malignancy by physical examination or imaging requires the presence in the body of about 1 billion malignant cells.” It goes on to note that: “A preclinical phase may sometimes be recognized” but even so, “More commonly, the preclinical phase goes undetected until invasive cancer, occasionally with regional or distant metastases, is already present.” That’s the way it is. The chapter then goes on to talk about many of the same things Mukherjee covers in the latter half of his book, like the role of tumor suppressor genes and oncogenes, the role of environmental triggers (carcinogens), inheritance, … In the field of oncology there seems to be a big focus on the role of genetic changes taking place in the cell(s), and: “A paradigm for sequential genetic alterations has been proposed as a necessary set of events leading to tumorigenesis.” Mukherjee also has more on this, if you’re interested. There are a lot of oncogenes and tumor suppressor genes that play a role in human cancers. In terms of the phenotypic changes they cause, this table is relevant (click to view full size):
A good related quote from the first part of the chapter:
“Molecular and cellular changes in tumor cells are, in a sense, a modification of normal physiology that benefits their growth and spread. The initial alterations may be “preprogrammed” in rare inherited malignancies, or they may be acquired as a consequence of mutations brought about by environmental exposure or occuring by chance during normal cell division. In a process akin to evolution, albeit in a fast time frame, additional genetic changes occur that favor further growth, invasion, and spread. Evasion of the host’s immune system, enhanced proliferative and invasive potential, and resistance to therapy are examples of early, middle, and late changes in the progression of neoplasia.”
The simple way to think about cancer is this: Cancer cells outcompete the surrounding cells because they’re better at growing and spreading, and they cause disease because the reason why they’re better at growing and spreading is that they’re no longer doing what they’re supposed to be doing, and because they’re taking up space and nutrients from the cells that still do their jobs.
The chapter also has some stuff on breast cancer and talks a bit about the BRCA mutations. After that they talk about mesenchymal, neuroendocrine and germ cell neoplasias, which are types of neoplasias the pathophysiology of which “can be described in terms of the embryonic tissue of origin.” The examples they include are carcinoid tumors, testicular cancer, and sarcomas. Again the naming of these diseases may be a bit confusing – tissue will often migrate during development and you can actually end up with, say, a testicular neoplasm which is not located anywhere near your testes (for example, the testicular tissue may have migrated to your chest..). Then they cover hematologic neoplasms (blood, bone marrow, or lymph nodes), and here they’ve included some stuff on lymphomas (“uncontrolled proliferation and potential dissemination of lymphocytes“) and AML, a type of leukemia (Mukherjee has a lot more stuff on that). I found it surprising that they did not spend more time on the last part, the systemic effects of neoplasia – basically they only spend one page on that stuff, though they do also include a few tables to illustrate these aspects of the diseases. I’ve included one of the figures below (click to view in a higher resolution):
Indirect systemic effects of cancer which are not caused by the local presence of cancer cells are what’s called pareneoplastic syndromes.
Phantoms in the brain
I’ve spent way too much money on books this autumn, as well as arguably too much time as well, so I’ve been feeling guilty about that. This guilty conscience has had as a consequence that I didn’t stock up on reading materials after I’d read the interesting stuff from the last amazon batch, something I usually do so that I always have a few books available that I’d potentially like to read if I find myself in the mood. I basically haven’t had many interesting unread books standing on my shelf, and so I haven’t read very much – a fact that I’ve also felt guilty about. Yesterday the contribution to my guilty conscience from not engaging in offline book-reading finally surpassed the contribution to it from spending money and time on reading too much ‘irrelevant stuff’ (i.e. non-exam-related-stuff), and so I ended up reading Ramachandran’s book.
Overall it’s better than Sacks, but I don’t really think that’s saying all that much. At least there aren’t any Wittgenstein quotes in this one (though there are Shakespeare quotes). I think this is the last book of this nature I’ll read – they’re too unsystematic, speculative and messy in their structure and I’d learn a lot more from just reading some chapters in a textbook like this (I probably won’t start out with that as I have this one standing on my shelf..). This is not to say that I didn’t learn anything from the book, and if you want to have a go at one of these easy-to-read introductory pop-sci neurology books, you can do worse (as I have realized). There’s less focus on patients and more focus on the specifics of the stuff that goes wrong and what those specifics tell us about how specific elements of the human brain works than in Sacks, and particularly important here is the fact that Ramachandran has included figures with illustrations of how the brain looks like and which structures are placed where, which was a big help to me during the reading.
I found the stuff on vision and how it works very interesting, so I’ll quote some stuff from that part of the book:
“The human brain contains multiple areas for processing images, each of which is composed of an intricate network of neurons that is specialized for extracting certain types of information from the image. [...] every act of perception, even something as simple as viewing a drawing of a cube, involves an act of judgment by the brain.
In making these judgments, the brain takes advantage of the fact that the world we live in is not chaotic and amorphous; it has stable physical properties. During evolution—and partly during childhood as a result of learning— these stable properties became incorporated into the visual areas of the brain as certain “assumptions” or hidden knowledge about the world that can be used to eliminate ambiguity in perception. For example, when a set of dots move in unison—like the spots on a leopard—they usually belong to a single object. So, any time you see a set of dots moving together, your visual system makes the reasonable inference that they’re not moving like this just by coincidence—that they probably are a single object. And therefore, that’s what you see.” [...]
“because of some quirk in our evolutionary history, each side of your brain sees the opposite half of the world (Figure 4.4). If you look straight ahead, the entire world on your left is mapped onto your right visual cortex and the world to the right of your center of gaze is mapped onto your left visual cortex. [...] this first map serves as a sorting and editorial office where redundant or useless information is discarded wholesale and certain defining attributes of the visual image—such as edges—are strongly emphasized. [...] This edited information is then relayed to an estimated thirty distinct visual areas in the human brain, each of which thus receives a complete and partial map of the visual world. [...] Why do we need thirty areas?6 We really don’t know the answer, but they appear to be highly specialized for extracting different attributes from the visual scene—color, depth, motion and the like. When one or more areas are selectively damaged, you are confronted with paradoxical mental states of the kind seen in a number of neurological patients. [...]
One of the most important principles in vision is that it tries to get away with as little processing as it can to get the job done. To economize on visual processing, the brain takes advantage of statistical regularities in the world—such as the fact that contours are generally continuous or that table surfaces are uniform—and these regularities are captured and wired into the machinery of the visual pathways early in visual processing. When you look at your desk, for instance, it seems likely that the visual system extracts information about its edges and creates a mental representation that resembles a cartoon sketch of the table (again, this initial extraction of edges occurs because your brain is mainly interested in regions of change, of abrupt discontinuity, at the edge of the desk, which is where the information is). The visual system might then apply surface interpolation to “fill in” the color and texture of the table, saying in effect, “Well, there’s this grainy stuff here; it must be the same grainy stuff all over.” This act of interpolation saves an enormous amount of computation; your brain can avoid the burden of scrutinizing every little section of the desk and can simply employ loose guesswork instead [...] what we call perception is really the end result of a dynamic interplay between sensory signals and high-level stored information about visual images from the past. Each time one of us encounters an object, the visual system begins a constant questioning process. Fragmentary evidence comes in and the higher centers say, “Hmmmmm, maybe this is an animal.” Our brains then pose a series of visual questions: as in a twenty questions game. Is it a mammal? A cat? What kind of cat? Tame? Wild? Big? Small? Black or white or tabby? The higher visual centers then project partial “best fit” answers back to lower visual areas including the primary visual cortex. In this manner, the impoverished image is progressively worked on and refined (with bits “filled in,” when appropriate). I think that these massive feed forward and feedback projections are in the business of conducting successive iterations that enable us to home in on the closest approximation to the truth.16 To overstate the argument deliberately, perhaps we are hallucinating all the time and what we call perception is arrived at by simply determining which hallucination best conforms to the current sensory input.”
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When I include quotes like the ones above in the post, I feel that I also have to quote some different stuff in order to give you a more complete picture. Here’s one quote which says a lot: “Contrary to what many of my colleagues believe, the message preached by physicians like Deepak Chopra and Andrew Weil is not just New Age psychobabble. It contains important insights into the human organism—ones that deserve serious scientific scrutiny.” So, yeah… Fortunately that quote was on page 221 (if it had been on page 20, I would not have read the rest of the book). In all fairness, he calls for rigorous tests but he also writes that “We have no idea which ones (if any) [of the alternative 'medicine' interventions] work and which ones do not” – which is a, problematic, claim. ‘Alternative medicine’ is ‘alternative’ because it doesn’t work – when health interventions of one kind or another can be shown to work in controlled experiments, they stop being ‘alternative’ treatments; the stuff that works is just called medicine. I know that there are institutional obstacles at play that keeps out treatment options which likely work but will never be profitable enough to justify trying to get through FDA approval, to take an example, but at least as a first approximation that’s how it works. You should probably also know, before you rush out to find the book, that I felt compelled to write words like ‘fool’ and ‘WTF’ in the margin at various occasions – the quote is not the only one of its kind. It’s safe to say that I very rarely do this when I read a book.
Stuff
File under: Stuff you probably didn’t know about that actually matters a great deal.
“Generation of electricity using coal started at the end of the 19th century. The first power stations had an efficiency of around 1%, and needed 12.3 kg of coal for the generation of 1 kWh. [...] With increasing experience, in combination with research and development, these low efficiency levels improved rapidly. Increased technical experience with coal processing and combustion technology enabled a steady increase in the steam parameters ‘pressure’ and ‘temperature’, resulting in higher efficiency. In the years 1910, efficiency had already increased to 5%, reaching 20% by 1920. In the fifty’s, power plants achieved 30% efficiency, but the average efficiency of all operating power plants was still a modest 17%. [...] continuous development resulted around the mid 80′s in an average efficiency of 38% for all power stations, and best values of 43%. In the second half of the nineties, a Danish power plant set a world record at 47%. [...] The average efficiency of all coal power stations in the world is around 31%. [...] In the next 10 years [the paper is from 2005, US], efficiencies up to 55% can be expected.” [...]
Often, the question is asked why the ‘other 45%’ cannot be converted into electricity. This relates to the laws of physics: the absolute maximum efficiency is the so-called ‘Carnot efficiency‘. For a turbine operating with gasses of 600°C, it is 67%. Then we need to take into account the exergy content of steam (around 94%). Also combustion has an efficiency less than 100% (around 95%). The transfer of combustion heat to steam in the boiler is for example 96% efficient. Losses due to friction can be around 5% (efficiency 95%). The efficiency of a generator is about 98% on average . . . .
To obtain the combined efficiency, one needs to multiply the efficiency of each process. Taking the above mentioned components, one obtains 0.67 x 0.94 x 0.95 x 0.96 x 0.95 x 0.98 = 0.535 or 53.5%.
This does not yet take into account the efficiency of all components. The power station’s own power use for motors to grind coal, pumps, ventilators, . . . further reduces efficiency. In practice, net efficiency will be around 40 and 45%. Continuous load changes, i.e. following the load, and start-up/shutdown procedures further lower efficiency. The increasing variability of the load, through increased use of intermittent sources such as wind, will lead to increased swings in the load of the power station, reducing efficiency.”
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ii. Allostatic load as a marker of cumulative biological risk: MacArthur studies of successful aging. From the abstract:
“Allostatic load (AL) has been proposed as a new conceptualization of cumulative biological burden exacted on the body through attempts to adapt to life’s demands. Using a multisystem summary measure of AL, we evaluated its capacity to predict four categories of health outcomes, 7 years after a baseline survey of 1,189 men and women age 70–79. Higher baseline AL scores were associated with significantly increased risk for 7-year mortality as well as declines in cognitive and physical functioning and were marginally associated with incident cardiovascular disease events, independent of standard socio-demographic characteristics and baseline health status. The summary AL measure was based on 10 parameters of biological functioning, four of which are primary mediators in the cascade from perceived challenges to downstream health outcomes. Six of the components are secondary mediators reflecting primarily components of the metabolic syndrome (syndrome X). AL was a better predictor of mortality and decline in physical functioning than either the syndrome X or primary mediator components alone. The findings support the concept of AL as a measure of cumulative biological burden.
In elderly populations, comorbidity in the form of multiple co-occurring chronic conditions is the norm rather than the exception. For example, in the U.S. 61% of women and 47% of men age 70–79 report two or more chronic conditions. These figures rise to 70% of women and 53% of men age 80–89 with 2+ chronic conditions (1). No single form of comorbidity occurs with high frequency, but rather a multiplicity of diverse combinations are observed (e.g., osteoarthritis and diabetes, colon cancer, coronary heart disease, depression, and hypertension). This diversity underscores the need for an early warning system of biomarkers that can signal early signs of dysregulation across multiple physiological systems.
One response to this challenge was the introduction of the concept of allostatic load (AL) (2–4) as a measure of the cumulative physiological burden exacted on the body through attempts to adapt to life’s demands. The ability to successfully adapt to challenges has been referred to by Sterling and Eyer (5) as allostasis. This notion emphasizes the physiological imperative that, to survive, “an organism must vary parameters of its internal milieu and match them appropriately to environmental demands” (5). When the adaptive responses to challenge lie chronically outside of normal operating ranges, wear and tear on regulatory systems occurs and AL accumulates.”
They conclude that: “The analyses completed to date suggest that the concept of AL offers considerable insight into the cumulative risks to health from biological dysregulation across multiple regulatory systems.” I haven’t come across the concept before but I’ll try to keep it in mind. There’s a lot of stuff on this.
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iii. Surviving a plane crash is surprisingly common.
“a few years ago, I learned that it’s actually pretty common to survive a plane crash. Like most people, I’d assumed that the safety in flying came from how seldom accidents happened. Once you were in a crash situation, though, I figured you were probably screwed. But that’s not the case.
Looking at all the commercial airline accidents between 1983 and 2000, the National Transportation Safety Board found that 95.7% of the people involved survived. Even when they narrowed down to look at only the worst accidents, the overall survival rate was 76.6%. Yes, some plane crashes kill everyone on board. But those aren’t the norm. So you’re even safer than you think. Not only are crashes incredibly rare, you’re more likely to survive a crash than not. In fact, out of 568 accidents during those 17 years, only 71 resulted in any fatalities at all.”
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iv. Now that we’re talking about planes: What does an airplane actually cost? Here’s one article on the subject:
“As for actual prices, airlines occasionally let numbers slip, either because of disclosure requirements or loose tongues.
Southwest Airlines Co., LUV +0.11% for example, recently published numbers related to its new order for Boeing 737 Max jetliners in a government filing. Mr. Liebowitz of Wells Fargo crunched the data and estimated an actual base price of roughly $35 million per plane, or a discount of around 64%. He noted that Southwest is one of Boeing’s best customers and that early buyers of new models get preferential pricing. A Southwest spokeswoman declined to comment.
Air India, in seeking funding last year for seven Boeing 787 Dreamliners it expects to receive this year, cited an average “net cost” of about $110 million per plane. The current list price is roughly $194 million, suggesting a 43% discount. Air India didn’t respond to a request for comment for this article.
In March 2011, Russian flag carrier Aeroflot mentioned in a securities filing that it would pay at most $1.16 billion for eight Boeing 777s…”
100+ million dollars for a plane. I had not seen that one coming. File under: Questions people don’t seem to be asking, which I think is sort of weird. Now that we’re at it, what about trains? Here’s a Danish article about our new IC4-trains. A conservative estimate is at $1,09 billion (6,4 billion kroner) for 83 trains, which is ~$13,2 million/train (or rather per trainset (US terminology) or ~77 million Danish kroner. That’s much cheaper than the big airplanes, but it sure is a lot of money. What about busses? I’ve often thought about this one, perhaps because it’s a mode of transportation I use far more frequently than the others. Here’s one bit of information about the situation in the US, which is surely different from the Danish one but not that different:
“Diesel buses are the most common type of bus in the United States, and they cost around $300,000 per vehicle, although a recent purchase by the Chicago Transit Authority found them paying almost $600,000 per diesel bus. Buses powered by natural gas are becoming more popular, and they cost about $30,000 more per bus than diesels do. Los Angeles Metro recently spent $400,000 per standard size bus and $670,000 per 45 foot bus that run on natural gas.
Hybrid buses, which combine a gasoline or diesel engine with an electric motor much like a Toyota Prius, are much more expensive than either natural gas or diesel buses. Typically, they cost around $500,000 per bus with Greensboro, NC’s transit system spending $714,000 per vehicle.”
So of course you can’t actually compare these things this way because of the different way costs are calculated, but let’s just for fun assume you can: When you use the average price of a standard US diesel bus and compare it to the price of the recently bought Danish trains, the conclusion is that you could buy 44 busses for the price of one train. And you could buy 367 busses for the price of one of the Dreamliners.
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v. A new blog you might like: Collectively Unconscious. A sort of ‘The Onion’ type science-blog.
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vi. I was considering including this stuff in a wikipedia-post, but I thought I’d include it here instead because what’s interesting is not the articles themselves but rather their differences: Try to compare this english language article, about a flame tank designed in the United States, with this article about the same tank but written in Russian. I thought ‘this is weird’ – anybody have a good explanation for this state of affairs?
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vii. The Emergence and Representation of Knowledge about Social and Nonsocial Hierarchies. I haven’t found an ungated version of the paper, but here’s the summary:
“Primates are remarkably adept at ranking each other within social hierarchies, a capacity that is critical to successful group living. Surprisingly little, however, is understood about the neurobiology underlying this quintessential aspect of primate cognition. In our experiment, participants first acquired knowledge about a social and a nonsocial hierarchy and then used this information to guide investment decisions. We found that neural activity in the amygdala tracked the development of knowledge about a social, but not a nonsocial, hierarchy. Further, structural variations in amygdala gray matter volume accounted for interindividual differences in social transitivity performance. Finally, the amygdala expressed a neural signal selectively coding for social rank, whose robustness predicted the influence of rank on participants’ investment decisions. In contrast, we observed that the linear structure of both social and nonsocial hierarchies was represented at a neural level in the hippocampus. Our study implicates the amygdala in the emergence and representation of knowledge about social hierarchies and distinguishes the domain-general contribution of the hippocampus.”
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viii.
I’ve only actually watched the first 15 minutes (and I’m not sure I’ll watch the rest), but I assume some of you will find this interesting.
Khan Academy videos of interest
There are other ressources than Khan Academy out there, so I thought I’d start out with a few remarks related to those. I’m about to start a course on coursera which I signed up for a long time ago, but I’m actually reconsidering now because I may not be able to find the time. If you don’t know about the site, go have a look around. A friend of mine also linked to this collection of videos from MIT on Electricity and Magnetism – looks very interesting. Anyway, a few Khan Academy videos below:
Just how sensitive blood flow is to vessel radius is an aspect I’d never given much thought, even though this is not exactly the first time I’ve done work on fluid dynamics (there’s also a largish section on that at Khan Academy) or the cardiovascular system. For some reason this video really made that link much more obvious to me, and these dynamics make it easier in my mind to understand why even relatively small changes in blood vessel composition over time can actually impede blood flow quite significantly and turn out to have rather large physiological effects. Math far more often than not helps me to think more clearly about stuff.
Some other videos:
The Voyage of the Beagle
I really hope you know who wrote the book.
I’m reading the second/1845 edition. I’m exactly half way through at this point (p. 225 out of 449). This book is awesome. Some quotes, the first two from the introduction and the rest from the book itself:
i. “You care for nothing but shooting, dogs, and rat-catching,” Dr. Darwin had said, “and you will be a disgrace to yourself and all your family.” (‘Dr. Darwin’ = Charles Darwins’ father. Who did he say this to? Well…)
ii. “The Beagle was a small ship, only ninety feet long, and it left England carrying 73 people.”
iii. “Not a single plant, not even a lichen, grows on this islet; yet it is inhabited by several insects and spiders. [...] The often repeated description of the stately palm and other noble tropical plants, then birds, and lastly man, taking possession of the coral islets as soon as formed, in the Pacific, is probably not correct; I fear it destroys the poetry of this story, that feather and dirt-feeding and parasitic insects and spiders should be the first inhabitants of newly formed oceanic land.”
iv. “As the moon rose early, we determined to start the same evening for our sleeping-place at the Lagoa Marica. As it was growing dark we passed under one of the massive, bare, and steep hills of granite which are so common in this country [Brazil]. This spot is notorious from having been, for a long time, the residence of some runaway slaves, who, by cultivating a little ground near the top, contrived to eke out a subsistence. At lenght they were discovered, and a party of soldiers being sent, the whole were seized with the exception of one old woman, who, sooner than again be led into slavery, dashed herself to pieces from the summit of the mountain. In a Roman matron this would have been called the noble love of freedom: in a poor negress it is mere brutal obstinacy. We continued riding for some hours. For the last miles the road was intricate, and it passed through a desert waste of marshes and lagoons.” (notice how he just carries on with ‘the main story’, sparing only a few sentences for such a gruesome event. It will become obvious to you why this is so if you read the book – there are far too many gruesome events taking place for all of them to get the attention they deserve.)
v. “While staying at this estate, I was very nearly being an eyewitness to one of those atrocious acts which can only take place in a slave country. Owing to a quarrel and a lawsuit, the owner was on the point of taking all the women and children from the male slaves, and selling them separately at the public auction at Rio. Interest, and not any feeling of compassion, prevented this act. Indeed, I do not believe the inhumanity of separating thirty families, who had lived together for many years, even occurred to the owner.”
vi. “I first visited the forest in which these Plenariae were found, in company with an old Portuguese priest who took me out to hunt with him. The sport consisted in turning into the cover a few dogs, and then patiently waiting to fire at any animal which might appear.”
vii. “this retired part of the country is seldom visited by foreigners. I was asked whether the earth or the sun moved; whether it was hotter or colder to the north; where Spain was, and many other such questions. The greater number of the inhabitants had an indistinct idea that England, London, and North America, were different names for the same place; but the better informed knew well that London and North America were separate countries close together, and that England was a large town in London!”
viii. “To the northward of the Rio Negro, between it and the inhabited country near Buenos Ayres, the Spaniards have only one small settlement, recently established at Bahia Blanca. The distance in a straight line to Buenos Ayres is very nearly five hundred British miles. The wandering tribes of horse Indians, which have always occupied the greater part of ths country, having of late much harassed the outlying estancias, the government at Buenos Ayres equipped some time since an army under the command of General Rosa for the purpose of exterminating them.”
ix. “The duty of the women [belonging to the tribes of Indian allies of General Rosa] is to load and unload the horses; to make the tents for the night; in short to be, like the wives of all savages, useful slaves. The men fight, hunt, take care of the horses, and make the riding gear.”
x. “My guide told me, that two months before he had a most narrow escape of his life: he was out hunting with two other men, at no great distance from this part of the country, when they were suddenly met by a party of Indians, who giving chase, soon overtook and killed his two friends. His own horse’s legs were also caught by the bolas; but he jumped off, and with his knife cut them free: while doing this he was obliged to dodge round his horse, and received two severe wounds from their chuzos. Springing on the saddle, he managed, by a most wonderful exertion, just to keep ahead of the long spears of his pursuers, who followed him to within the sight of the fort. From that time there was an order that no one should stray far away from the settlement. I did not know this when I started, and was surprised to observe how earnestly my guide watched a deer, which appeared to have been frigthened from a distant quarter.”
xi. “A few days afterwards I was another troop of these banditti-like soldiers start on an expedition against a tribe of Indians at the small Salinas, who had beeen betrayed by a prisoner cacique. The Spaniard who brough the orders for this expedition was a very intelligent man. He gave me an account of the last engagement at which he was present. Some Indians, who had been taken prisoners, gave information of a tribe living north of the Colorado. Two hundred soldiers were sent; and they first discovered the Indians by a cloud of dust from their horses’ feet, as they chanced to be travelling. The country was mountainous and wild, and it must have been far in the interior, for the Cordillera were in sight. The Indians, men, women, and children, were about one hundred and ten in number, and they were nearly all taken or killed, for the soldiers sabre every man. The Indians are now so terrified that they offer no resistance in a body, but each flies, neglecting even his wife and children; but when overtaken, like wild animals, they fight against any number to the last moment. [...] This is a dark picture; but how much more shocking is the unquestionable fact, that all the women who appear above twenty years old are massacred in cold blood! When I exclaimed that this appeared rather inhuman, he answered, “Why, what can be done? they breed so!”
Every one here is fully convinced that this is the most just war, because it is against barbarians. Who would believe in this age that such atrocities could be committed in a Christian civilized country? The children of the Indians are saved, to be sold or given away as servants, or rather slaves for as long a time as the owners can make them believe themselves slaves; but I believe in their treatment there is little to complain of. [...]
Not only have whole tribes been exterminated, but the remaining Indians have become more barbarous: instead of living in large villages, and being employed in the arts of fishing, as well as the chase, they now wander about the open plains, without home or fixed occupation.”
xii. “We passed a train of waggons and a troop of beasts on their road to Mendoza. The distance is about 580 geographical miles, and the journey is generally performed in fifty days.”
xiii. “A small green parrot (Conurus murinus), with a grey breast, appears to prefer the tall trees on the islands to any other situation for its building-place. A number of nests are placed so close together as to form one great mass of sticks. These parrots always live in flocks, and commit great ravages on the corn-fields. I was told, that near Colonia 2,500 were killed in the course of one year. [...] Animals are so abundant in these countries, that humanity and self-interest are not closely united; therefore I fear it is that the former is here scarcely known. One day, riding in the Pampas with a very respectable “estanciero,” my horse, being tired, lagged behind. The man often shouted to me to spur him. When I remonstrated that it was a pity, for the horse was quite exhausted, he cried out, “Why not?—Never mind—spur him—it is my horse.” I had then some difficulty in making him comprehend that it was for the horse’s sake, and not on his account, that I did not choose to use my spurs. He exclaimed, with a look of great surprise, “Ah, Don Carlos, que cosa!” It was clear that such an idea had never before entered his head.”
xiv. “The results of all the attempts to colonize this side of America south of 41°, has been miserable. Port Famine expresses by its name the lingering and extreme sufferings of several hundred wretched people, of whom one alone survived to relate their misfortunes. At St. Joseph’s Bay, on the coast of Patagonia, a small settlement was made; but during one Sunday the Indians made an attack and massacred the whole party, excepting two men, who remained captives during many years. At the Rio Negro I conversed with one of these men, now in extreme old age.”
xv. “The second day after our return to the anchorage, a party of officers and myself went to ransack an old Indian grave [...] We undermined the grave on both sides, but could not find any relics, or even bones.
xvi. “If I had space I could prove that South America was formerly here cut off by a strait, joining the Atlantic and Pacific oceans, like that of Magellan. But it may yet be asked, how has the solid basalt been moved? Geologists formerly would have brought into play, the violent action of some overwhelming debacle; but in this case such a supposition would have been quite inadmissible [...] Although we know that there are tides, which run within the Narrows of the Strait of Magellan at the rate of eight knots an hour, yet we must confess that it makes the head almost giddy to reflect on the number of years, century after century, which the tides, unaided by a heavy surf, must have required to have corrode so vast an area and thickness of solid basaltic lava. Nevertheless, we must believe that the strata undermined by the waters of this ancient strait, were broken up into huge fragments, and these lying scattered on the beach, were reduced first to smaller blocks, then to pebbles and lastly to the most impalpable mud, which the tides drifted far into the Eastern or Western Ocean.” [I've cut the description short here, but I hope I haven't cut too much. Remember that they had basically no clue how old the Earth was at this point in time. This is written decades before Kelvin came up with his '20-400 million years'-estimate.]
xvii. “While going one day on shore near Wollaston Island, we pulled alongside a canoe with six Fuegians. These were the most abject and miserable creatures I anywhere beheld. On the east coast the natives, as we have seen, have guanaco cloaks, and on the west they possess seal-skins. Amongst these central tribes the men generally have an otter-skin, or some small scrap about as large as a pocket-handkerchief, which is barely sufficient to cover their backs as low down as their loins. It is laced across the breast by strings, and according as the wind blows, it is shifted from side to side. But these Fuegians in the canoe were quite naked, and even one full-grown woman was absolutely so. It was raining heavily, and the fresh water, together with the spray, trickled down her body. In another harbour not far distant, a woman, who was suckling a recently-born child, came one day alongside the vessel, and remained there out of mere curiosity, whilst the sleet fell and thawed on her naked bosom, and on the skin of her naked baby! These poor wretches were stunted in their growth, their hideous faces bedaubed with white paint, their skins filthy and greasy, their hair entangled, their voices discordant, and their gestures violent. Viewing such men, one can hardly make one’s self believe that they are fellow-creatures, and inhabitants of the same world. It is a common subject of conjecture what pleasure in life some of the lower animals can enjoy: how much more reasonably the same question may be asked with respect to these barbarians! A night, five or six human beings, naked and scarcely protected from the wind and rain of this tempestuous climate, sleep on the wet ground coiled up like animals. [...] They often suffer from famine [...]
The different tribes when at war are cannibals. From the concurrent, but quite independent evidence of the boy taken by Mr. Low, and of Jemmy Button, it is certainly true, that when pressed in winter by hunger, they kill and devour their old women before they kill their dogs: the boy, being asked by Mr. Low why they did this, anwered, “Doggies catch otters, old women no.” This boy described the manner in which they are killed by being held over smoke and thus choked; he imitated their screams as a joke, and described the parts of their bodies which are considered best to eat. Horrid as such a death by the hands of their friends and relatives must be, the fears of the old women, when hunger begin to press, are more painful to think of; we are told that they then often run away into the mountains, but that they are pursued by the men and brought back to the slaughter-house at their own firesides!”
xviii. “During our stay at Port Famine, the Fuegians twice came and plagued us. As there were many instruments, clothes, and men on shore, it was thought necessary to frigthen them away. The first time a few great guns were fired, when they were far distant. It was most ludicrous to watch through a glass the Indians, as often as the shot struck the water, take up stones, and, as a bold defiance, throw them towards the ship, though about a mile and a half distant! A boat was sent with orders to fire a few musket-shots wide of them. The Fuegians hid themselves behind the trees, and for every discharge of the muskets they fired their arrows; all, however, fell short of the boat, and the officer as he pointed at them laughed. This made the Fuegians frantic with passion, and they shook their mantles in vain rage. At last, seeing the balls cut and strike the trees, they ran away, and we were left in peace and quietness.”
Sociosexuality from Argentina to Zimbabwe: A 48-nation study of sex, culture, and strategies of human mating
Real life takes up most of my time these days and I’m only posting this because I haven’t posted in a few days. Anyway, I found this paper and I thought some of you might be interested. Note that the sample sizes are generally very small (# of males from Brazil included? 39. Finland? 28. France? 47) and that “the ISDP samples were primarily college students” (p. 269) – so it’s probably a good idea to be very cautious when interpreting the results. Unfortunately Finland is the only Scandinavian country included in the analysis. Anyway, some stuff from the paper:
“Abstract: The Sociosexual Orientation Inventory (SOI; Simpson & Gangestad 1991) is a self-report measure of individual differences in human mating strategies. Low SOI scores signify that a person is sociosexually restricted, or follows a more monogamous mating strategy. High SOI scores indicate that an individual is unrestricted, or has a more promiscuous mating strategy. As part of the International Sexuality Description Project (ISDP), the SOI was translated from English into 25 additional languages and administered to a total sample of 14,059 people across 48 nations. Responses to the SOI were used to address four main issues. First, the psychometric properties of the SOI were examined in cross-cultural perspective. The SOI possessed adequate reliability and validity both within and across a diverse range of modern cultures. Second, theories concerning the systematic distribution of sociosexuality across cultures were evaluated. Both operational sex ratios and reproductively demanding environments related in evolutionary-predicted ways to national levels of sociosexuality. Third, sex differences in sociosexuality were generally large and demonstrated cross-cultural universality across the 48 nations of the ISDP, confirming several evolutionary theories of human mating. Fourth, sex differences in sociosexuality were significantly larger when reproductive environments were demanding but were reduced to more moderate levels in cultures with more political and economic gender equality. Implications for evolutionary and social role theories of human sexuality are discussed.” [...]
“On average, men tend to possess more positive attitudes toward casual, low-investment sex than women do (Carrol et al. 1985; Fisher et al. 1988; Hendrick et al. 1985; Oliver & Hyde 1993; Townsend 1995; Wilson 1987). Men also report that they fantasize about having sex with multiple partners more than women do (Ellis & Symons 1990; Malamuth 1996), and men behaviorally seek short-term mateships more than women do (Blumstein & Schwartz 1994; Eysenck 1976; Laumman et al. 1994; Wiederman 1997). Experimental tests have further confirmed that men are more likely than women to consent to sex with a stranger when approached in a community setting (Clark & Hatfield 1989), even when the stranger is “vouched for” by a participant’s same-sex friend (Clark 1990). [...]
This pervasive pattern of sexual differences – across attitudes, fantasy, and behavior – implies that men should be higher or more unrestricted on sociosexuality than women. Indeed, the direct evidence on this point is unequivocal, at least in United States. In every study published to date, American men report higher levels of sociosexuality than American women based on responses to the SOI. [...]
(click to view full size)
“sex differences in sociosexuality appear to be culturally universal (at least across the spectrum of modern ISDP nations) [...] The hypothesis that men should be more unrestricted than women across cultures is fundamental to several evolutionary theories of human mating (e.g., Buss & Schmitt 1993). In support of this perspective, men were more unrestricted than women across all nations of the ISDP. This tended to be true when looking at means, medians, and distributions; when looking at sociosexual attitudes and behaviors; and – most importantly – the magnitude of this difference was moderate to large in size regardless of the moderating effects of culture. Overall, the average mean-level man scored about three-quarters of a standard deviation higher on the SOI than the average mean-level woman – one of the largest and most robust cross-cultural differences ever documented in the sexuality literature (Oliver & Hyde 1994). In addition, based on ANOVA methods, the overall effect size of biological sex is quite large (η^2 = 0.15), more than double the more moderate effect size of nation (η^2 = 0.06).” [...]
Among the 48 nations of the ISDP, the five nations with the highest levels of gender equity ratings on the United Nations Gender Development Index are Australia (d = 0.66), Canada (d = 0.75), the United States (d = 0.73), Belgium (d = 0.69), and the Netherlands (d = 0.76). In each nation, sex differences in sociosexuality are conspicuous, ranging from moderate to large in size. Relatively egalitarian sexual standards and gender role beliefs for men and women in modern cultures, therefore, may attenuate sex differences in sociosexuality, but they appear unlikely to reduce them to less than moderately-sized magnitudes of effect. [...] The current findings do suggest that women’s sociosexual attitudes and behaviors will get closer to men’s as gender equality becomes more common, but it seems unlikely that men and women would ever possess precisely equal levels of sociosexuality.”
Do note that the study itself is only half or so of the text in the link – the latter half is commentary and criticism provided by other people in the field.
Stuff
i. I was considering covering this study in a bit more detail, but I decided against it because workplace filters probably would not like it very much – it would contain words such filters do not like (no, I’m not thinking of words like ‘sociodemographic characteristics’ or ‘multiple regression analyses’). I know a few people sometimes read my blog from work and if you’re one of them, let me just say that you should probably not read this while at work.
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ii. Population Trends in the Incidence and Outcomes of Acute Myocardial Infarction
“The age- and sex-adjusted incidence of myocardial infarction increased from 274 cases per 100,000 person-years in 1999 to 287 cases per 100,000 person-years in 2000, and it decreased each year thereafter, to 208 cases per 100,000 person-years in 2008, representing a 24% relative decrease over the study period. [...]
The proportion of patients who underwent revascularization within 30 days after myocardial infarction increased from 40.7% in 1999 to 47.2% in 2008 (P<0.001 for trend). Among patients with ST-segment elevation myocardial infarction, 49.9% underwent revascularization in 1999 as compared with 69.6% in 2008 (P<0.001 for trend). Among patients with non–ST-segment elevation myocardial infarction, 33.4% underwent revascularization in 1999 as compared with 41.3% in 2008 (P<0.001 for trend) [...]
The proportion of patients with myocardial infarction who were known to have undergone troponin I testing increased from 53% in 1999 to 84% in 2004, with stable testing rates between 2004 and 2008. [...]
The age- and sex-adjusted 30-day mortality after myocardial infarction decreased from 10.5% in 1999 to 7.8% in 2008 (P<0.001 for linear trend). This decrease was driven by the case fatality rate for non–ST-segment elevation myocardial infarction, which decreased from 10.0% to 7.6% (P<0.001 for trend); there was no significant change over time for ST-segment elevation myocardial infarction (P = 0.81). The multivariable adjusted odds ratio for death at 30 days after myocardial infarction was 0.76 (95% confidence interval [CI], 0.65 to 0.89) in 2008 as compared with 1999.”
Short version: Fewer people got a(n ST-segment elevation) myocardial infarction even though more people were subjected to fancy testing, more people got access to fancy treatment, and the people in the sample who got a non-ST-segment MI during the study period were less likely to die from it. But…
“observed reductions in case fatality rates could be attributable to secular trends in ascertainment of myocardial infarction and decreased severity on presentation, as well as any improvements in management of acute myocardial infarction.44 The observation that mortality after ST-segment elevation myocardial infarction (which is less influenced by the use of highly sensitive biomarkers) did not decrease over time provides support for this hypothesis.”
This could still be considered good news because if decreased severity on presentation reduces mortality it’s probably a good idea to at least have a closer look at that variable; on the other hand it’s bad news because fancy testing is expensive. Another thing:
“given the integrated medical care delivery structure in the health system that we studied and the magnitude of recent improvements in the control of risk factors within our population, our results may not be fully generalizable to other health care settings.”
Good luck finding MSM-coverage of the study including this part. I’d probably have removed the word ‘fully’. The population risk factor development during the period is a major confound.
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iii. International migration: A panel data analysis of the determinants of bilateral flows by Anna Maria Mayda.
Click to view full size. From the paper:
“According to the international migration model, pull and push factors have either similarsized effects (with opposite signs), when migration quotas are not binding, or they both have no (or a small) effect on emigration rates, when migration quotas are binding. It is not clear, ex ante, which one of the two scenarios characterizes actual flows. Migration policies in the majority of destination countries are very restrictive, which should imply binding constraints on the number of migrants. On the other hand, even countries with binding official immigration quotas often accept unwanted (legal) immigration.8 Restrictive immigration policies are often characterized by loopholes, that leave room for potential migrants to take advantage of economic incentives. [...]
My empirical analysis also finds that inequality in the source and host economies is related to the size of emigration rates as predicted by Borjas (1987) selection model. An increase in the origin country’s relative inequality has a non-monotonic effect on the size of the emigration rate: the impact is estimated to be positive if there is positive selection, negative if there is negative selection. Among the variables affecting the costs of migration, distance between destination and origin countries appears to be the most important one: Its effect is negative, significant and steady across specifications. On the other hand, there is no evidence that cultural variables related to each country pair play a significant role. Demographics – in particular, the share of the origin country’s population who is young – shape bilateral flows as predicted by the theory. Since the effect of geography and demographics works through the supply side of the model, their impact should be even stronger when migration quotas are relaxed, which is what I find in the data. [...]
Since immigrants are likely to receive support from other immigrants from the same origin country already established in the host country, they will have an incentive to choose destinations with larger communities of fellow citizens. Network effects imply that bilateral migration flows are highly correlated over time, which is what the data shows.”
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iv. Via npr:
“It’s a sound you would never want to hear in real life, but this a safe way to eavesdrop. Just one warning: For the first two minutes of this video, nothing happens, nothing I could hear, anyway. Then there’s a countdown, and at 2:24 from the top … the bomb bursts; at 2:54 the blast hits.”
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v. Does Thinking Really Hard Burn More Calories? Interesting piece. Unfortunately(?), “for most people, the body easily supplies what little extra glucose the brain needs for additional mental effort.”
I would be very interested in seeing a study on this including type 1 diabetics. Hard thinking for extended periods of time – like, say, a four-hour chess game or an exam – impacts my blood glucose in a very significant way; it drops like a stone if I don’t take precautions. This is despite the fact that hard thinking under such circumstances is often, as mentioned in the article, linked to stress and the release of cortisol, one of the primary functions of which is to increase blood sugar.
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vi. TV from a different world:
Stuff (updated)
(After Ed Yong published his latest post, I decided to add a couple of links – Monday, 10 a.m.)
i. Introduction to Evolutionary Biology (TalkOrigins)
I read this yesterday, I’m sure some of you will find it to be useful. Some quotes:
“Populations evolve. [evolution: a change in the gene pool] In order to understand evolution, it is necessary to view populations as a collection of individuals, each harboring a different set of traits. A single organism is never typical of an entire population unless there is no variation within that population. Individual organisms do not evolve, they retain the same genes throughout their life. When a population is evolving, the ratio of different genetic types is changing — each individual organism within a population does not change. For example, in the previous example, the frequency of black moths increased; the moths did not turn from light to gray to dark in concert. The process of evolution can be summarized in three sentences: Genes mutate. [gene: a hereditary unit] Individuals are selected. Populations evolve.
Evolution can be divided into microevolution and macroevolution. The kind of evolution documented above is microevolution. Larger changes, such as when a new species is formed, are called macroevolution. Some biologists feel the mechanisms of macroevolution are different from those of microevolutionary change. Others think the distinction between the two is arbitrary — macroevolution is cumulative microevolution.
The word evolution has a variety of meanings. The fact that all organisms are linked via descent to a common ancestor is often called evolution. The theory of how the first living organisms appeared is often called evolution. This should be called abiogenesis. And frequently, people use the word evolution when they really mean natural selection — one of the many mechanisms of evolution. [...]
Evolution can occur without morphological change; and morphological change can occur without evolution. Humans are larger now than in the recent past, a result of better diet and medicine. Phenotypic changes, like this, induced solely by changes in environment do not count as evolution because they are not heritable; in other words the change is not passed on to the organism’s offspring. [...]
Evolution is not progress. Populations simply adapt to their current surroundings. They do not necessarily become better in any absolute sense over time. A trait or strategy that is successful at one time may be unsuccessful at another.” [...]
Organisms are not passive targets of their environment. Each species modifies its own environment. At the least, organisms remove nutrients from and add waste to their surroundings. Often, waste products benefit other species. Animal dung is fertilizer for plants. Conversely, the oxygen we breathe is a waste product of plants. Species do not simply change to fit their environment; they modify their environment to suit them as well. [...]
Natural selection may not lead a population to have the optimal set of traits. In any population, there would be a certain combination of possible alleles that would produce the optimal set of traits (the global optimum); but there are other sets of alleles that would yield a population almost as adapted (local optima). Transition from a local optimum to the global optimum may be hindered or forbidden because the population would have to pass through less adaptive states to make the transition. Natural selection only works to bring populations to the nearest optimal point. This idea is Sewall Wright’s adaptive landscape. This is one of the most influential models that shape how evolutionary biologists view evolution. [...]
Sexual selection is natural selection operating on factors that contribute to an organism’s mating success. Traits that are a liability to survival can evolve when the sexual attractiveness of a trait outweighs the liability incurred for survival. A male who lives a short time, but produces many offspring is much more successful than a long lived one that produces few. The former’s genes will eventually dominate the gene pool of his species. In many species, especially polygynous species where only a few males monopolize all the females, sexual selection has caused pronounced sexual dimorphism. In these species males compete against other males for mates. The competition can be either direct or mediated by female choice. In species where females choose, males compete by displaying striking phenotypic characteristics and/or performing elaborate courtship behaviors. The females then mate with the males that most interest them, usually the ones with the most outlandish displays. There are many competing theories as to why females are attracted to these displays.” (In humans, females choose so this could be construed as another bit of dating advice to add to this post…) [...]
“Most mutations that have any phenotypic effect are deleterious. Mutations that result in amino acid substitutions can change the shape of a protein, potentially changing or eliminating its function. This can lead to inadequacies in biochemical pathways or interfere with the process of development. Organisms are sufficiently integrated that most random changes will not produce a fitness benefit. Only a very small percentage of mutations are beneficial.”
There’s a lot more at the link. Not all of it belongs in the ‘all people who know anything about evolutionary biology would agree on this 100 percent’-category [one example: "Genes are not the unit of selection (because their success depends on the organism's other genes as well); neither are groups of organisms a unit of selection. There are some exceptions to this "rule," but it is a good generalization." - not everybody 'in the field' would agree with that], but most of it is relatively incontestable and it covers a lot of ground; a huge number of key concepts are explained and elaborated upon here. Read it, but don’t start reading it before you’re in a situation where you have a decent amount of time to spare. No matter how well-read you are, unless you’ve actually read this piece before odds are you’ll not know everything which is covered here – for instance, you probably didn’t know that “over half of all named species are insects. One third of this number are beetles.” I know I didn’t. The article was written a while ago, so I decided to check up on the data – here’s what wikipedia has to say about the matter today: “Even though the true dimensions of species diversity remain uncertain, estimates are ranging from 1.4 to 1.8 million species. [...] About 850,000–1,000,000 of all described species are insects.” I should probably point out that even though it’s written in a manner-of-fact like way all the way through, he incidentally doesn’t exactly beat about the bush at the end:
“Scientific creationism is 100% crap. So-called “scientific” creationists do not base their objections on scientific reasoning or data. Their ideas are based on religious dogma, and their approach is simply to attack evolution. The types of arguments they use fall into several categories: distortions of scientific principles ( the second law of thermodynamics argument), straw man versions of evolution (the “too improbable to evolve by chance” argument), dishonest selective use of data (the declining speed of light argument) appeals to emotion or wishful thinking (“I don’t want to be related to an ape”), appeals to personal incredulity (“I don’t see how this could have evolved”), dishonestly quoting scientists out of context (Darwin’s comments on the evolution of the eye) and simply fabricating data to suit their arguments (Gish’s “bullfrog proteins”).
Most importantly, scientific creationists do not have a testable, scientific theory to replace evolution with. Even if evolution turned out to be wrong, it would simply be replaced by another scientific theory.”
As can also be inferred from the links at the end, this is not the only post of its kind at TalkOrigins. Go have a look if you’re even remotely interested!
…
ii. Two figures:
(link).
…
iii. How far do Danes commute to go to work? Answer: It varies.
The table includes the Danish municipalities with the ten highest and lowest average commuting distances. The distances given in the table are the distances between the homes of the commuters and their workplaces, not the distances travelled on an average day (which would be twice that number). Local or regional wage differentials and corresponding differences in opportunity cost of time definitely plays a role here. Note that ‘distance travelled’ is not necessarily a good proxy for ‘time spent commuting’, especially not when comparing the commutes of people living in urban areas with those of people living in rural areas (ceteris paribus, d(commuting time)/d(pop-density)>0). The numbers are from this new publication by Statistics Denmark, which also included this map of the gender differences across the country (yellow: the average male commute is less than 6 kilometers longer than the average female commute, etc. The darker, the bigger the difference between the genders..):
The national average commuting distance to work is ~20 km (19.7). The male average is 23.4 km, the female average is 15.9 km.
…
iv. This should all be known stuff to you guys, but in case it’s not:
…
v. A number: 27.5% of all inmates in Danish prisons are foreign citizens (article in Danish here). Foreign citizens make up about 7,7% of the population. If you look closer, I’m positive both that you’ll find huge variation across countries, and that you’ll also find that some immigrant groups are significantly less likely to commit crimes than are people with Danish citizenship.
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vi. The Long, Fake Life of J.S. Dirr. An internet hoax that survived for 11 years, from the very beginning of social medias almost to the present day. Interesting.
…
vii. Why You Can’t Kill a Mosquito with a Raindrop. Add this one to the list of questions I had never even thought about asking. Fascinating stuff, a few quotes:
“the consequence of getting hit by a raindrop depends on what part of the mosquito’s body takes the blow. Since the insects are so lanky, 75% of hits happen on the legs or wings. This can throw a mosquito into a brief tumble or even a barrel roll, but it recovers without much trouble.
Direct hits to mosquitos’ bodies are a different kind of carnival ride. The speeding raindrops glom onto the insects and propel them downward. Mosquitos captured on camera sometimes fell as far as 20 body lengths while being pushed by a raindrop. For a human, that would be a 12-story drop and a quick ending to the story. But mosquitos are able to pull away sideways from the raindrops and continue on their way, unharmed.
The only danger seems to come if mosquitos are flying close to the ground when they’re hit, leaving themselves too little time to escape. The authors note that one unlucky bug was driven into a puddle and “ultimately perished.” [...]
When the heavy drop hits the airy mosquito, it’s almost like hitting nothing at all. And this, the researchers found, is what keeps the mosquitos alive. By offering barely any resistance, a mosquito minimize the force of the collision. The raindrop doesn’t even splatter when it hits. [...]
Humans being hurled downward generally black out around 2 or 3 G’s. But a mosquito suddenly driven toward the ground by a raindrop experiences an acceleration of 100 to 300 G’s. The authors note that “insects struck by rain may achieve the highest survivable accelerations in the animal kingdom.”"
…
Most people do not understand music?
Well, it depends on how you define ‘music’ (see also my comments below), but either way… From lesswrong:
Comment by Will_Newsome: “‘Aren’t there people who can hear sounds but not music?’
FWIW I’ve read a study that says about 50% of people can’t tell the difference between a major and a minor chord even when you label them happy/sad. [ETA: Happy/sad isn't the relevant dimension, see the replies to this comment.] I have no idea how probable that is, but if true it would imply that half of the American population basically can’t hear music.”
[...]
Comment by army1987:
“http://languagelog.ldc.upenn.edu/nll/?p=2074
It shocked the hell out of me, too.”
…
The stuff in army1987′s link I found frankly incredible and I’ll probably do a bit of googling later on to see what pops up. It seems that whereas commenters to the article do not generally seem to have problems with distinguishing the isolated chords, quite a few of them do have significant problems with the sequence in the post. I’m flabbergasted that anyone would have any problems with either of the examples.
Knowing this will probably radically change how I think about e.g. giving concerts to ‘normal people’. Before I’ve basically assumed that people heard what I heard, more or less, when I played something. But if people have problems with stuff as simple as the sequence in the link, I should really take people at their word when they tell me that they ‘do not understand this kind of music’. I’ve always thought such a statement was best translated: ‘I couldn’t tell Beethoven from Mozart (‘I mentioned those two names because they are the only ones I know…’) and I do not feel comfortable judging types of music I don’t know very well.’ (or something along those lines) But maybe a better way to translate it would be: ‘I can’t hear what’s going on.’ People have quite a few times in the past told me that I shouldn’t worry about anything when playing for them because they wouldn’t be able to tell if I made a mistake or not anyway. I’ve always assumed they were just being nice and that of course they would be able to tell if I made a mistake; I’ve never seriously considered the possibility that some of them might actually have told me the truth.
They – including perhaps some of the readers of this blog (go have a look at the link if you’re curious) – really don’t know what they are missing out on. I framed the post title the way I did because it in my mind requires a lot more than just being able to distinguish notes to actually understand in any meaningful way at least most of the music I prefer to listen to. Learning to play (badly) has given me a much greater understanding of just how complex some music really is, how nuanced and detailed it is when you take that closer look you need to take to get to the bottom of it; and I’m well aware that ‘even someone like me’ will miss some details along the way. People much better than me do that as well.
Also, this makes it a little easier for me to understand how stuff like pop music ever got, well, popular. It has always been somewhat hard for me to explain the musical preferences of ‘the majority’ in a satisfactory way, and I’ve usually just used some implicit explanation involving ‘preferences…’ (which did not really explain much). Of course there are still a huge number of variables at play here, but it never really occured to me that part of the explanation for the diverging preferences might be that what I hear with my ears might not be what a lot of other people hear.
The effects of fishing on sharks, rays, and chimaeras (chondrichthyans), and the implications for marine ecosystems
“The impact of fishing on chondrichthyan stocks around the world is currently the focus of considerable international concern. Most chondrichthyan populations are of low productivity relative to teleost fishes, a consequence of their different life-history strategies. This is reflected in the poor record of sustainability of target shark fisheries.
Most sharks and some batoids are predators at, or near, the top of marine food webs. The effects of fishing are examined at the single-species level and through trophic interactions. We summarize the status of chondrichthyan fisheries from around the world. Some 50% of the estimated global catch of chondrichthyans is taken as by-catch, does not appear in official fishery statistics, and is almost totally unmanaged. When taken as by-catch, they are often subjected to high fishing mortality directed at teleost target species. Consequently, some skates, sawfish, and deep-water dogfish have been virtually extirpated from large regions. Some chondrichthyans are more resilient to fishing and we examine predictions on the vulnerability of different species based on their life-history and population parameters. At the species level, fishing may alter size structure and population parameters in response to changes in species abundance. We review the evidence for such density-dependent change. Fishing can affect trophic interactions and we examine cases of apparent species replacement and shifts in community composition. Sharks and rays learn to associate trawlers with food and feeding on discards may increase their populations.”
From the abstract of the study, which I found very interesting. Here’s some more stuff from the paper:
“Large-scale exploitation has led to changes in fish community structure. Fishers tend to remove the largest species first and then work their way down the food chain catching smaller species (Pauly et al., 1998). Consequently, changes in species composition of fished communities may be expected, with small, fastergrowing, and earlier-maturing species predominating. Small species may also be less desirable on the market, and may therefore be subjected to lower fishing mortality (Jennings and Kaiser, 1998; Jennings et al., 1999b). Within the chondrichthyans, the examples for skates discussed above reveal a broadly similar pattern. Similar patterns have also been reported in shark communities: as larger sharks were depleted smaller species proliferated (van der Elst, 1979). The general paradigm is that larger species decline while smaller species predominate.
There have also been declines in diversity associated with increasing fishing pressures, particularly in large predatory taxa (Jennings and Kaiser, 1998). Chondrichthyans tend to be high in the food web (Cortes, 1999) and, due to their greater vulnerability (relative to teleosts), are likely to be the first to decline from fishing. Rogers et al. (1999) suggested that fishing, through the differential vulnerability of elasmobranchs relative to teleosts, is responsible for major variations in fish diversity in the North-east Atlantic. [...]
Discards from fisheries affect the amount of food available to scavengers and thus may be expected to have an effect on certain components of the ecosystem. Although some studies conclude that Australian prawn trawling had few significant, long-term impacts (Kennelly, 1995), about 95% of the by-catch in the Northern Prawn fishery is discarded, and most of it is dead (Wassenberg and Hill, 1989; Hill and Wassenberg, 1990). About half of the discards float and are scavenged by birds, dolphins, and sharks. The other half sinks and is preyed upon by sharks in mid-water and teleosts, sharks, and crustaceans on the bottom. [...]
The predictions of the Venezuelan shelf ecosystem model under a mixed control assumption show that shark depletion could lead to strong and unforeseen changes in the abundances of many species (Fig. 4). According to the model, these changes would be permanent as long as shark populations remain depressed. Surprisingly, not all species whose abundances increased greatly are major prey of sharks. In fact, the species undergoing the greatest relative increases in abundance (croakers, snappers/groupers, grunts, catfish, and other demersals) are all minor components in the diet of the small triakid sharks, suggesting that shark depletion propagates through the food web in a complex way. Some changes are virtually demographic explosions of up to two and a half times the original biomass (i.e. croakers). Conversely, two of the major prey items of the sharks did not increase much in abundance; they even decreased (carangids and small pelagics). Squid and benthic producers, two groups not part of the diet, suffered abundance decreases of about 10% and 15%, respectively. Clearly, the outcomes are not as predictable as one might expect. [...]
Conclusions
Chondrichthyans, by nature of their K-selected lifehistory strategies and high position in trophic food webs, are more likely to be affected by intense fishing activity than most teleosts. The group may in fact be indicators of fishing pressure. There is sufficient evidence from the history of fisheries around the world, both targeting these fishes and taking them as by-catch, of major declines in population size. For some groups, particularly certain skate species and sawfishes, there is mounting evidence suggesting that local if not global extinction is a distinct possibility. This problem is especially acute for species with restricted distributions. The massive and uncontrolled catch of chondrichthyans in the Indo-West Pacific, coupled with the higher diversity and rates of endemism in this region, are cause for major concern. There is increasing evidence that indirect effects of fishing are affecting the composition and diversity of chondrichthyan and total fish assemblages through trophic interactions. Differential vulnerability to fishing exists among sharks and rays and large, late maturing species appear to be most vulnerable. This has caused changes in the community through competitive release, although there is little evidence for species replacement. There is good evidence that selective fishing mortality can lead to changes in growth and juvenile survival for both sharks and batoids, leading to changes in population dynamics. However, the effects of removing large numbers of these top predators on the marine ecosystem are still largely unknown. Attention needs to be focused on this poorly studied group of fishes, particularly in the ecosystem context in terms of understanding trophic interactions.”
Basic Pharmacology Principles
A very good introductionary lecture on pharmacology:
I decided to post some wikipedia links to a few of the concepts he covers in the lecture below (however I’m pretty sure the lecture is the more efficient way to learn this stuff, at least the basics):
Agonist.
Receptor antagonist.
Xenobiotic.
EC50 (half maximal effective concentration).
Dose-response relationship.
Pharmacokinetics.
Pharmacodynamics.
Khan Academy videos of interest
(I know there’s been a lot of video posts recently, this is almost turning into a vlog, but…)
Some additional data: I’ve previously blogged a Danish version of the ‘health care spending as a percentage of GDP’ -graph, going back to ~ 1970. The title is in Danish but it really shouldn’t be much of a problem for non-Danish speaking readers to figure out what’s going on:
Human Microbiology (ii)
First post in the series here. You can buy it here. I put it away temporarily a while ago, but this week I tried having another go at it. I’ve now read something like 2/3rds of the book, and I’ve taken a look at almost all chapters – which also means that I’ve skipped some stuff here and there. It’s a good book, and it’s actually reasonably accessible, though it’s not easy. Most of the stuff in the first post was about bacteria, but of course the book also has some stuff about viruses and fungi. Some more material below, I’ve decided to limit myself to dealing with stuff related to viruses in this post. They are actually quite interesting (things? …buggers?):
i. “Viruses are succesful parasites; they infect all the main types of living organisms from animals, plants and insects to fungi and bacteria. Viruses that infect bacteria are called bacteriophages.
Viruses are obligate intracellular parasites. They have an absolute requirement on the host cell for manufacture of new virus components. Viruses do not multiply by binary fission but instead are assembled from component parts (nucleic acid and protein). This can only occur inside the host cell. Hence, viruses are inert outside of their hosts. With no need for a basal metabolic activity to retain viability, viruses have no need to carry ribosomes or other organelles or metabolic pathways. They simply are particles that can be copied and built by the cells that they infect. [...]
In the process of becoming entirely parasitic, certain viruses have lost the minimum amount of genetic information such that they are unable to replicate outside the host cell unless aided by another virus. Such viruses are called defective viruses. [...] Certain viruses have lost so much nucleic acid that they are simply infectious strands of RNA. Called viroids, these agents lack even a protective protein coat surrounding the RNA strand yet are able to infect plants, transmitted following mechanical abrasion of the plant surface. [...]
Viruses resemble living organisms in that they have a genome and are able to replicate and evolve. Indeed, they have biological properties such as particular host ranges, routes of transmission and tissue tropism. Viruses, however, do not create or store free energy in compounds such as ATP and have no intrinsic metabolic activity outside their host cells (unlike spores or seeds) and are therefore not alive, at least for part of their existence. These comparisons place viruses in between chemicals and true living organisms. Attempting to include the important features, a definition of a virus is thus:
A microscopic organism that invades and only reproduces inside living cells. Viruses possess one type of nucleic acid, are unable to replicate by binary fission but are assembled and do not undertake independent energetic metabolism.” [...]
“One of the most unusual features of viruses is the presence of only one type of nucleic acid. Whereas other organisms possess both DNA and RNA, viruses have only one nucleic acid, DNA or RNA, never both.”
ii. “The virus-infected cell should be seen as a controlled hijacking of the normal cell by an intruder. The replication strategy will depend on the type of genome, and the release of the virus will determine the pattern of infection within the host.
A number of differences are apparent when comparing viral replication with bacterial replication (Figure 3.8) [a good figure, not going to draw it]. A virus replicates itself from scratch, starting from the transcription of its nucleic acid, whereas a new bacterial cell is derived from a pre-existing bacterial cell as it doubles its cellular components and divides, a process not driven from nucleic acid transcription. This is partly reflected in the time taken to form new viruses and bacteria. A bacterium dividing in culture can be a relatively short event (20 minutes for Esch. coli), whereas the replication of a virus takes roughly 8 hours to complete. Whilst the bacterial cell doublings can be estimated during exponential bacterial growth, numbers of viruses produced from a single virus within one host cell cannot be predicted. The integration of the host cell machinery with that of the virus makes the targets for antiviral compounds all the more difficult.” [...]
The replication of the virus can be divided into five stages, reflecting the general sequence of events:
*attachment,
*internalization,
*transcription of the genome,
*virus assembly,
*virus release. [the book spends 8 pages on these five concepts, so I'm not going into details about this part here.
iii. "If a virus grows intracellularly and does not kill the cell one might expect that infected cells remain indistinguishable from uninfected cells. Fortunately, certain viruses betray their presence by causing such disruption to the cells that they cause visible cytopathic effect (CPE). This is a general term for any alteration in the morphology of the cells caused by the virus. Not all viruses induce cytopathic effects. [...] Examples of various cytopathic effects are shown in Figure 3.14, and discussed below.
*Formation of inclusion bodies. Unusual organelles may appear within virus-infected cells and are described as ‘inclusion bodies‘. [...]
*Changes in the shape of the infected cells. [...]
*Cell lysis. The lysis of cells by a virus is a feature of several viruses when grown in cell lines. The pattern of the gaps left by the detached dead cells from the cell monolayer is called a ‘plaque’. [...] Lytic viruses cause the cell to disrupt, typically when non-enveloped virus particles are released. Clearly this is fatal to the cell in question.
*Cell fusion. Infected cells may fuse and form multinucleate cells called syncytia when infected with certain viruses. [...]
*Haemadsorption. [...]
*Immunofluorescence.”
iv. “At a conservative estimate, there are at least thirty different viruses from fifteen taxonomic families that are common causes of human illness. This number does not take into consideration the serological types that exist in many of these viruses. So the common cold we are taking as one virus, whereas there are over eighty serological types of rhinovirus. As every human will be infected by viruses in their lifetime, we must concede that viruses are efficient parasites of humans.” [...]
“Because it is only those people with symptoms who come to our attention, it is easy to overlook the fact that most viral infections are asymptomatic. [...] The proportion of susceptible people who develop illness from those who are infected is called the attack rate“
The book makes it clear in a table and a figure neither of which I can easily reproduce that there are basically four types of viral infections, when using duration as the decision parameter: Acute, persistent, latent and slow. Examples given of the four types are: Rhinovirus (common cold), chronic hepatitis B, Herpes simplx and BSE (mad cow disease). Their strategies differ somewhat:
“The acute infections rely on rapid multiplication of virus in order to manufacture and shed (transmit) new virus before the host has had time to mount a neutralising immunity. [...] Persistent infections in the host (not the environment) are those in which the virus is not eliminated but, having established itself, will persist for the lifetime of the host. The virus is either replicating at a very low level continually, such as chronic hapatitis virus infections, or is latent for most of the time but periodically undergoes a short burst of full replication in which infectious virus is manufactured and released, e.g. Herpes simplex in cold sores. Many persistent virus infections are acquired as children with little or no pathology and then persist for life.” [...]
“Viruses have adopted various strategies to out-manoeuvre the host, in particular to evade or suppress the immune response that attempts to develop antiviral products. It is useful to consider the broader strategies before looking at cellular mechanisms.
*Evasion of immune response. Viruses can replicate in tissues that are relatively protected from surveillance by immune cells (e.g. brain, dermis). Alternatively, they can avoid extracellular states in the course of infection. [...]
*Suppression of immune response. Some virus infections infect the immune cells that mount the immune response in order to suppress them. [...]
The following list illustrates how viruses have attempted to modulate various points of the immune response.
*Minimise recognition by the host. For viruses that cause systemic infections, the first entry of virus into the bloodstream during a viraemic phase will attract the attention of Complement components. Certain viruses produce molecular mimics (homologues) of Complement components which will block the Complement cascade attacking the free virion. These homologues are termed viroceptors. Mimicry is also used by enveloped viruses which include host proteins in the viral envelope to mask their recognition as ‘foreign’. [...]
*Inhibit production of interferon. Interferon production is an important early step in the defence against viral infections. Viruses need to interfere with the action of interferon to establish an infection. One way to counter the action of interferon, is for viruses to secrete molecular mimics of IFN receptors. In this way IFN binds to the competing mimic receptor, rather than real receptor on the virus-infected cell. [...]
*Modulation of cytokine action. [...]
*Prevent apoptosis. Apoptosis, programmed cell suicide, occurs only if a cell receives a signal to proceed. That signal may be triggered by the presence of a virus. In general, viruses try to prevent the cell from carrying out this self-destruction and numerous examples exist of viruses producing proteins that inhibit apoptosis.”
A Natural History Of Ourselves (2)
Here’s the first post in the series. There are lots of interesting ‘bites of an apple from the tree of knowledge’ in the book, so I’ll just go ahead and post some of them here. From the first three chapters (~100 pages) :
i. “Two centuries after Captain James Smith (five four, perhaps) dropped anchor at Jamestown in 1607, the average U.S. male had gained two or three inches, depending on whose data you use.”
ii. This explanation neglects the problematic hair on my head, though. The best theory here relates to my massive brain [...]. Theory goes: The head of my ancestral hominids, as they reared upright, was exposed to the tropical sun. As the brain of hominids evolved larger, this head fur grew in importance. A brain is a steaming wad of fat, a three-pound radiator. It’s vulnerable to high temperatures and will fry out at 107.6°F (42°C). So it’s insulated against the sun with a mop of fur, and it’s cooled with a surfeit of sweat glands. That’s the predominant theory, anyway: We shucked the body fur in order to cool our bodies better, but kept the head hair to prevent the brain from baking. My tresses shield my brain from the sun, the way a sheep’s fleece keeps it cool in the desert. And the rest of my skin is open to the wind so I can sweat cool as I sprint after hamburgers on the plains of South Portland.”
iii. “Until you give the human animal tools, it is pitifully armed, and not dangerous. This isn’t normal, among primates. Cousin Chimp’s weapon of choice is his large teeth. [...] Gorillas and orangutangs, as well as the other primates, also rely primarily on their teeth to wound and kill their rivals [and prey]. [...] I don’t believe my jaws are up to the challenge of biting off human fingers, let alone severing an ankle. Humans don’t fight much with our teeth. Generally, we prefer metal tools, and generally the longer the reach of the tool, the better. When a human does tangle without tools, the weapon of choice is the hands. [...] the male fist is the most common cause of broken jaws. [...] In my culture, only one killing in fourteen is accomplished without tools.”
iv. “A running chimp is as graceful as a tumbling brick.”
v. “This animal [humans] perceives the world foremost with its eyes. As in many predators, the eyes are forward oriented. This produces three-dimensional vision but narrows the total field. Inside the eye, the human (like many of its fellow primates) has three cones rather than two, producing color vision much richer than that perceived by most mammals. [...] Taste and smell, the chemical senses, are rather weak. The tongue can, however, identify poisons with passable accuracy and is sensitive to high-calorie sugars and fats. [...] Females demonstrate a slight edge over males in the speed at which their brains process sensory information – especially during the fertile phases of their menstrual cycles.”
vi. “The eyes of all animals had a humble beginning. Some single-celled somebody probably got the vision thing rolling when a DNA flub granted it a light-sensitive chemical. This dab of chemistry may have allowed an ancestral Mr. Microbe to eat better, or to better avoid being eaten, and thus he [it] thrived. And everyone who evolved from him was grateful for his revolutionary photopigment.
Today, each species packages its photopigment a little differently (or a lot differently), but the general rule is the same: You collect a subset of the light spectrum and use the data to plot your next move. You don’t even require a brain to do this – the marine brittle star is paved with crystals that detect a predator’s shadow and signal its five arms to scramble for shelter. [...] As for processing speed, my eyes are rather indolent. When I sit watching a movie, the series of still images blends together to form motion. But to a fly, a movie plays like a plodding slide show. [...] A fly can process two hundred different images in a second. I can handle twenty before they start to blur.”
vii. “Just as my predator’s eyes leave me blind behind, my ears leave me with a “deaf spot.” Humans have trouble locating noises that are directly fore, aft, or above our heads. [...] As for ear location, I’m pretty normal. Most mammals separate their ears to maximize their triangulating potential. Still, they keep them handy to the brain that processes sound data. [...] My own ears are so far apart that a sound wave registers first in one, then a split second later in the other. The sound level drops, too, in the time it takes to reach the second ear. Between the time lag and the pinnae’s input, my brain can calculate where to point my eyes.”
viii. “the male and female human perceive pain differently – even after accounting for the COMT gene. The sex hormones that soak our respective brains seem to dictate how each sex will experience life’s cuts and contusions. Generally, females have a lower threshold: It takes less burning, freezing, poking, or pinching to make them yelp. They also have a lower tolerance for pain: They’re quicker to capitulate and pull their hands from a bucket of ice water or a heat beam. (These are common tools of torture for pain researchers.)
Other differences hint at the separate ways that male and female bodies react to pain. During painful times, a male’s heart beats faster but not the female’s. A male’s cortisol and endorphins (stress chemical and painkiller) rise, but for some reason, a female brain neither stresses out nor self-medicates for pain. [...] Why? Most theories cluster around a female’s role in reproduction: She must avoid harm “for two,” so to speak.
Curiously, the human female’s pain sensitivity goes dull when her estrogen level rises toward the fertile days of her monthly cycle.”
ix. “Female siblings who live together will, like mice, rapidly synchronize their menstrual cycles in about half of cases studied. About one-third of close friends who spend lots of time together will synchronize, too.”
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