## Kinematics of Circumgalactic Gas – Crystal Martin

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A few links related to the lecture coverage:

The green valley is a red herring: Galaxy Zoo reveals two evolutionary pathways towards quenching of star formation in early- and late-type galaxies (Schawinski et al, 2014).

The Large, Oxygen-Rich Halos of Star-Forming Galaxies Are A Major Reservoir of Galactic Metals (Tumlinson et al, 2011).

Gas in galactic halos (Dettmar, 2012).

Gaseous Galaxy Halos (Putman, Peek & Joung, 2012).

The kinematic connection between QSO-absorbing gas and galaxies at intermediate redshift (Steidel et al. 2002).

W. M. Keck Observatory.

Sloan Digital Sky Survey.

Virial mass.

Kinematics of Circumgalactic Gas (the lecturer is a co-author of this presentation).

Kinematics of Circumgalactic Gas: Quasars Probing the Inner CGM of z=0.2 Galaxies (-ll-). Here’s the paper: Quasars Probing Galaxies. I. Signatures of Gas Accretion at Redshift z ≈ 0.2 (Ho, Martin, Kacprzak & Churchill, 2017).

MAGIICAT III. Interpreting Self-Similarity of the Circumgalactic Medium with Virial Mass using MgII Absorption (Nielsen et al, 2013).

Fiducial marker.

Gas kinematics, morphology and angular momentum in the FIRE simulations (El-Badry et al, 2018).

## Black Hole Magnetospheres

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The lecturer says ‘ah’ and ‘ehm’ a lot, especially in the beginning (it gets much better later in the talk), but this is not a good reason for not watching the lecture. The last five minutes of the lecture after the wrap-up can safely be skipped without missing out on anything.

I’ve added some links related to the coverage below.

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Astrophysical jet.

Magnetosphere.

The Optical Variability of the Quasar 3C 279: The Signature of a Decelerating Jet? (Böttcher & Principe, 2009).

The slope of the black-hole mass versus velocity dispersion correlation (Tremaine et al., 2002).

Radio-Loudness of Active Galactic Nuclei: Observational Facts and Theoretical Implications (Sikora, Stawarz & Lasota, 2007).

Jet Launching Structure Resolved Near the Supermassive Black Hole in M87 (Doeleman et al., 2012).

Event Horizon Telescope.

The effective acceleration of plasma outflow in the paraboloidal magnetic field (Beskin & Nokhrina, 2006).

Toroidal magnetic field.

Current sheet.

No-hair theorem.

Frame-dragging.

Alfvén velocity.

Lorentz factor.

Magnetic acceleration of ultrarelativistic jets in gamma-ray burst sources (Komissarov et al., 2009).

Asymptotic domination of cold relativistic MHD winds by kinetic energy flux (Begelman & Li, 1994).

Magnetic nozzle.

Mach cone.

Collimated beam.

Magnetohydrodynamic simulations of gamma-ray burst jets: Beyond the progenitor star (Tchekhovskoy, Narayan & McKinney, 2010).

## Supermassive BHs Mergers

This is the first post I’ve posted in a while; as mentioned earlier the blogging hiatus was due to internet connectivity issues secondary to me moving. Those issues should now have been solved and I hope to soon get back to blogging regularly.

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Some links related to the lecture’s coverage:

Supermassive black hole.

Binary black hole. Final parsec problem.

LIGO (Laser Interferometer Gravitational-Wave Observatory). Laser Interferometer Space Antenna (LISA).

Dynamical friction.

Science with the space-based interferometer eLISA: Supermassive black hole binaries (Klein et al., 2016).

Off the Beaten Path: A New Approach to Realistically Model The Orbital Decay of Supermassive Black Holes in Galaxy Formation Simulations (Tremmel et al., 2015).

Dancing to ChaNGa: A Self-Consistent Prediction For Close SMBH Pair Formation Timescales Following Galaxy Mergers (Tremmel et al., 2017).

Growth and activity of black holes in galaxy mergers with varying mass ratios (Capelo et al., 2015).

Tidal heating. Tidal stripping.

Nuclear coups: dynamics of black holes in galaxy mergers (Wassenhove et al., 2013).

The birth of a supermassive black hole binary (Pfister et al., 2017).

Massive black holes and gravitational waves (I assume this is the lecturer’s own notes for a similar talk held at another point in time – there’s a lot of overlap between these notes and stuff covered in the lecture, so if you’re curious you could go have a look. As far as I could see all figures in the second half of the link, as well as a few of the earlier ones, are figures which were also included in this lecture).

## Nephrology Board Review

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Some links related to the lecture’s coverage:

Diabetic nephropathy.

Henoch–Schönlein purpura.

Leukocytoclastic Vasculitis.

Glomerulonephritis. Rapidly progressive glomerulonephritis.

Nephrosis.

Analgesic nephropathy.

Azotemia.

Allergic Interstitial Nephritis: Clinical Features and Pathogenesis.

Nonsteroidal anti-inflammatory drugs: effects on kidney function (Whelton & Hamilton, J Clin Pharmacol. 1991 Jul;31(7):588-98).

Goodpasture syndrome.

Creatinine. Limitations of serum creatinine as a marker of renal function.

Hyperkalemia.

U wave.

Nephrolithiasis. Calcium oxalate.

Calcium gluconate.

Bicarbonate.

Effect of various therapeutic approaches on plasma potassium and major regulating factors in terminal renal failure (Blumberg et al., 1988).

Effect of prolonged bicarbonate administration on plasma potassium in terminal renal failure (Blumberg et al., 1992).

Renal tubular acidosis.

Urine anion gap.

Metabolic acidosis.

Contrast-induced nephropathy.

Rhabdomyolysis.

Lipiduria. Urinary cast.

Membranous glomerulonephritis.

Postinfectious glomerulonephritis.

## Lyapunov Arguments in Optimization

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I’d say that if you’re interested in the intersection of mathematical optimization methods/-algorithms and dynamical systems analysis it’s probably a talk well worth watching. The lecture is reasonably high-level and covers a fairly satisfactory amount of ground in a relatively short amount of time, and it is not particularly hard to follow if you have at least some passing familiarity with the fields involved (dynamical systems analysis, statistics, mathematical optimization, computer science/machine learning).

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Some links:

Dynamical system.

Euler–Lagrange equation.

Continuous optimization problem.

Gradient descent algorithm.

Lyapunov stability.

Condition number.

Fast (/accelerated-) gradient descent methods.

The Mirror Descent Algorithm.

Cubic regularization of Newton method and its global performance (Nesterov & Polyak).

A Differential Equation for Modeling Nesterov’s Accelerated Gradient Method: Theory and Insights (Su, Boyd & Candès).

A Variational Perspective on Accelerated Methods in Optimization (Wibisono, Wilson & Jordan).

Breaking Locality Accelerates Block Gauss-Seidel (Tu, Venkataraman, Wilson, Gittens, Jordan & Recht).

A Lyapunov Analysis of Momentum Methods in Optimization (Wilson, Recht & Jordan).

Bregman divergence.

Estimate sequence methods.

Variance reduction techniques.

Stochastic gradient descent.

Langevin dynamics.

## An introduction to Invariant Theory

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I was strongly considering not watching this one to the end (…such as it is – the video cuts off before the talk was completely finished, but I’m okay with missing out on the last 2 (?) minutes anyway) at several points during the lecture, mainly because this is definitely far from a ‘gentle’ introduction; this one is tough for an introductory lecture and I had to look up a lot of stuff to just sort-of-kind-of muddle along. One of the things that I recall kept me from giving the rest of the lecture a miss along the way was that some parts of the coverage made me review a few topics in group theory which I’d previously encountered, but did not remember at all well – basically I was reminded along the way that concepts X, Y, and Z existed, and that I’d forgot how they worked/what they were useful for.

I think most (…non-mathematicians? …people?) who watch this one will miss a lot of stuff and details, and although you by watching it might get some idea what this stuff’s about I’m quite sure I’d not recommend this lecture to non-mathematicians; I don’t think it’s really worth it to watch it.

I’ve posted some links below to things related to the lecture’s coverage.

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Invariant (mathematics).

Loop invariant.

Knot invariant.

Jones polynomial.

Homogeneous polynomial.

Invariant polynomial.

Invariant of a binary form.

Paul Gordan.

Polynomial ring.

Indeterminate (variable).

Ideal (ring theory).

Hilbert’s basis theorem.

Hilbert’s Nullstellensatz.

Group representation.

Group action.

Subalgebra.

Permutation matrix.

Symmetric polynomial.

Hilbert’s finiteness theorem.

Irreducible representation.

Multiplicative group.

One-parameter group.

Hilbert–Mumford criterion.

Strictly Upper Triangular Matrix.

Nilpotent matrix.

Characteristic polynomial.

## Mathematics in Cryptography III

As she puts it herself, most of this lecture [~first 47 minutes or so] was basically “an explanation by a non-expert on how the internet uses public key” (-cryptography). The last 20 minutes cover, again in her own words, “more theoretical aspects”.

Some links:

ARPANET.

NSFNET.

Hypertext Transfer Protocol (HTTP). HTTPS.

Project Athena. Kerberos (protocol).

Pretty Good Privacy (PGP).

Secure Sockets Layer (SSL)/Transport Layer Security (TLS).

IPsec.

Wireshark.

Cipher suite.

Elliptic Curve Digital Signature Algorithm (ECDSA).

Request for Comments (RFC).

Elliptic-curve Diffie–Hellman (ECDH).

The SSL/TLS Handshake: an Overview.

Advanced Encryption Standard.

Galois/Counter Mode.

XOR gate.

Hexadecimal.

IP Header.

Time to live (TTL).

Transmission Control Protocol. TCP segment structure.

TLS record.

Security level.

Birthday problem. Birthday attack.

Handbook of Applied Cryptography (Alfred J. Menezes, Paul C. van Oorschot and Scott A. Vanstone). (§3.6 in particular is mentioned/referenced as this is stuff she talks about in the last ‘theoretical’ part of the lecture).

## Mathematics in Cryptography II

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Some links to stuff covered in the lecture:

Public-key cryptography.

New Directions in Cryptography (Diffie & Hellman, 1976).

The history of Non-Secret Encryption (James Ellis).

Note on “Non-Secret Encryption” – Cliff Cocks (1973).

RSA (cryptosystem).

Discrete Logarithm Problem.

Diffie–Hellman key exchange.

AES (Advanced Encryption Standard).

Triple DES.

Trusted third party (TTP).

Key management.

Man-in-the-middle attack.

Digital signature.

Public key certificate.

Secret sharing.

Hash function. Cryptographic hash function.

Secure Hash Algorithm 2 (SHA-2).

Non-repudiation (digital security).

L-notation. L (complexity).

ElGamal signature scheme.

Digital Signature Algorithm (DSA).

Schnorr signature.

Identity-based cryptography.

Identity-Based Cryptosystems and Signature Schemes (Adi Shamir, 1984).

Algorithms for Quantum Computation: Discrete Logarithms and Factoring (Peter Shor, 1994).

Quantum resistant cryptography.

Elliptic curve. Elliptic-curve cryptography.

Projective space.

I have included very few links relating to the topics covered in the last part of the lecture. This was deliberate and not just a result of the type of coverage included in that part of the lecture. In my opinion non-mathematicians should probably skip the last 25 minutes or so as they’re – not only due to technical issues (the lecturer is writing stuff on the blackboard and for several minutes you’re unable to see what she’s writing, which is …unfortunate), but those certainly were not helping – not really worth the effort. The first hour of the lecture is great, the last 25 minutes are, well, less great, in my opinion. You should however not miss the first part of the coverage of ECC-related stuff (in particular the coverage ~55-58 minutes in), if you’re interested in making sense of how ECC works; I certainly found that part of the coverage very helpful.

## Computers, People and the Real World

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“An exploration of some spectacular failures of modern day computer-aided systems, which fail to take into account the real-world […] Almost nobody wants an IT system. What they want is a better way of doing something, whether that is buying and selling shares on the Stock Exchange, flying an airliner or running a hospital. So the system they want will usually involve changes to the way people work, and interactions with physical objects and the environment. Drawing on examples including the new programme for IT in the NHS, this lecture explores what can go wrong when business change is mistakenly viewed as an IT project.” (Quote from the video description on youtube).

Some links related to the lecture coverage:

Computer-aided dispatch.

London Ambulance Service – computerization.

Report of the Inquiry Into The London Ambulance Service (February 1993).

Sociotechnical system.

Tay (bot).

A few observations/quotes from the lecture (-notes):

“*The bidder who least understands the complexity of a requirement is likely to put in the lowest bid.*”

“It is a mistake to use a computer system to impose new work processes on under-trained or reluctant staff. – **Front line staff are often best placed to judge what is practical.**” [A quote from later in the lecture [~36 mins] is even more explicit: “The experts in any work process are usually the people who have been carrying it out.”]

“It is important to understand that in any system implementation the people factor is as important, and arguably more important, than the technical infrastructure.” (*This last one is a full quote from the report linked above; the lecture includes a shortened version – US*) [Quotes and observations above from ~16 minute mark unless otherwise noted]

“There is no such thing as an IT project”

“(almost) every significant “IT Project” is actually a business change project that is enabled and supported by one or more IT systems. Business processes are expensive to change. The business changes take at least as long and cost as much as the new IT system, and need at least as much planning and management” [~29 mins]

“Software packages are packaged business processes

*Changing a package to fit the way you want to work can cost more than writing new software” [~31-32 mins]

“Most computer systems interact with people: the *sociotechnical* view is that the people and the IT are two components of a larger system. Designing that larger system is the real task.” [~36 mins]

## Mathematics in Cryptography

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Some relevant links:

Caesar cipher.

Substitution cipher.

Frequency analysis.

Vigenère cipher.

ADFGVX cipher.

One-time pad.

Arthur Scherbius.

Enigma machine.

Permutation.

Cycle notation.

Permutation group.

Cyclic permutation.

Involution (mathematics).

An Application of the Theory of Permutations in Breaking the Enigma Cipher – Marian Rejewski.

## On the cryptographic hardness of finding a Nash equilibrium

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I found it annoying that you generally can’t really hear the questions posed by the audience (which includes people like Avi Wigderson), especially considering that there are quite a few of these, especially in the middle section of the lecture. There are intermittent issues with the camera’s focus occasionally throughout the talk, but those are all transitory problems that should not keep you from watching the lecture. The sound issue at the beginning of the talk is resolved after 40 seconds.

One important take-away from this talk, if you choose not to watch it: “to date, there is no known efficient algorithm to find Nash equilibrium in games”. In general this paper – coauthored by the lecturer – seems from a brief skim to cover many of the topics also included in the lecture. I have added some other links to articles and topics covered/mentioned in the lecture below.

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Nash’s Existence Theorem.

Reducibility Among Equilibrium Problems (Goldberg & Papadimitriou).

Three-Player Games Are Hard (Daskalakis & Papadimitriou).

3-Nash is PPAD-Complete (Chen & Deng).

PPAD (complexity).

NP-hardness.

On the (Im)possibility of Obfuscating Programs (Barak *et al*.).

On the Impossibility of Obfuscation with Auxiliary Input (Goldwasser & Kalai).

On Best-Possible Obfuscation (Goldwasser & Rothblum).

Functional Encryption without Obfuscation (Garg *et al.*).

On the Complexity of the Parity Argument and Other Inefficient Proofs of Existence (Papadimitriou).

Pseudorandom function family.

Revisiting the Cryptographic Hardness of Finding a Nash Equilibrium (Garg, Pandei & Srinivasan).

Constrained Pseudorandom Functions and Their Applications (Boneh & Waters).

Delegatable Pseudorandom Functions and Applications (Kiayias *et al.*).

Functional Signatures and Pseudorandom Functions (Boyle, Goldwasser & Ivan).

Universal Constructions and Robust Combiners for Indistinguishability Obfuscation and Witness Encryption (Ananth *et al.*).

## The Internet of Things

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Some links to stuff he talks about in the lecture:

The Internet of Things: making the most of the Second Digital Revolution – A report by the UK Government Chief Scientific Adviser.

South–North Water Transfer Project.

FDA approves first smart pill that tracks drug regimen compliance from the inside.

The Internet of Things (IoT)* units installed base by category from 2014 to 2020.

Share of the IoT market by sub-sector worldwide in 2017.

San Diego to Cover Half the City with Intelligent Streetlights.

IPv4 and IPv6 (specifically, he talks a little about the IPv4 address space problem).

General Data Protection Regulation (GDPR).

Shodan (website).

Mirai botnet.

Gait analysis.

Website reveals 73,000 unprotected security cameras with default passwords. (This was just an example link – it’s unclear if the site he used to illustrate his point in that part of the lecture was actually Insecam, but he does talk about the widespread use of default passwords and related security implications during the lecture).

Strava’s fitness heatmaps are a ‘potential catastrophe’.

‘Secure by Design’ (a very recently published proposed UK IoT code of practice).

## Safety-Critical Systems

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Some related links to topics covered in the lecture:

Safety-critical system.

Safety engineering.

Fault tree analysis.

Failure mode and effects analysis.

Fail-safe.

Value of a statistical life.

ALARP principle.

Hazards and Risk (HSA).

Software system safety.

Aleatoric and epistemic uncertainty.

*N*-version programming.

An experimental evaluation of the assumption of independence in multiversion programming (Knight & Leveson).

Safety integrity level.

Software for Dependable Systems – Sufficient Evidence? (consensus study report).

## Sieve methods: what are they, and what are they good for?

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Given the nature of the lecture it was difficult to come up with relevant links to include in this post, but these seemed relevant enough to include them here:

Sieve theory.

Inclusion–exclusion principle.

Fundamental lemma of sieve theory.

Parity problem (sieve theory).

Viggo Brun (the lecturer mentions along the way that many of the things he talks about in this lecture are things this guy figured out, but the wiki article is unfortunately very short).

As he notes early on, when working with sieves we’re: “*Interested in objects which are output of some inclusion-exclusion process & *Rather than counting precisely, we want to gain good bounds, but work flexibly.”

‘Counting’ should probably be interpreted loosely here, in the general scheme of things; sieves are mostly used in number theory, but as Maynard mentions presumably similar methods can be used in other mathematical contexts – thus the deliberate use of the word ‘objects’. It seems to be all about trying to ascertain some properties about some objects/sets/whatever, without necessarily imposing much structure (‘are we within the right order of magnitude?’ rather than ‘did we get them all?’). The basic idea behind restricting the amount of structure imposed is, as far as I gathered from the lecture, to make the problem you’re faced with more tractable.

## Some things you need to know about machine learning but didn’t know whom to ask (the grad school version)

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Some links to stuff related to the lecture’s coverage:

An overview of gradient descent optimization algorithms.

Rectifier (neural networks) [Relu].

Backpropagation.

Escaping From Saddle Points – Online Stochastic Gradient for Tensor Decomposition (Ge et al.).

How to Escape Saddle Points Efficiently (closely related to the paper above, presumably one of the ‘recent improvements’ mentioned in the lecture).

Linear classifier.

Concentration inequality.

A PAC-Bayesian Approach to Spectrally-Normalized Margin Bounds for Neural Networks (Neyshabur et al.).

Off the convex path (the lecturer’s blog).

## Analgesia and Procedural Sedation

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I didn’t actually like this lecture all that much, in part because I obviously disagree to some extent with the ideas expressed, but I try to remember to blog lectures I watch these days even if I don’t think they’re all that great. It’s a short lecture, but why not at least add a comment about urine drug screening and monitoring or patient selection/segmentation when you’re talking about patients whom you’re considering discharging with an opioid prescription? Recommending acupuncture in a pain management context? Etc.

Anyway, below a few links to stuff related to the coverage:

Pain Management in the Emergency Department.

Oligoanalgesia.

WHO analgesic ladder.

Nonsteroidal anti-inflammatory drug.

Ketorolac.

Fentanyl (“This medication should not be used to treat pain other than chronic cancer pain, especially short-term pain such as migraines or other headaches, pain from an injury, or pain after a medical or dental procedure.” …to put it mildly, that’s not the impression you get from watching this lecture…)

Parenteral opioids in emergency medicine – A systematic review of efficacy and safety.

Procedural Sedation (medscape).

## Concussion and Sequelae of Minor Head Trauma

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Some related links:

PECARN Pediatric Head Injury/Trauma Algorithm.

Canadian CT Head Injury/Trauma Rule.

ACEP – Traumatic Brain Injury (Mild – Adult).

AANS – concussion.

Guidelines for the Management of Severe Traumatic Brain Injury – 4th edition.

Return-to-play guidelines.

Second-impact syndrome.

Repetitive Head Injury Syndrome (medscape).

Traumatic Brain Injury & Concussion (CDC).

## Acute Coronary Syndromes

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A few quotes from the lecture, as well as some links to related stuff:

“You might say: Why doesn’t coronary stenting prevent heart attacks? You got an 80 % blockage causing some angina and you stent it, why doesn’t that prevent a heart attack? And the answer is very curious. The plaques that are most likely to rupture are mild. They’re typically less than 50 %. They have a thin fibrous cap, a lot of lipid, and they rupture during stress. This has been the real confusion for my specialty over the last 30 years, starting to realize that, you know, when you get angina we find the blockage and we fix it and your angina’s better, but the lesions that were gonna cause next week’s heart attack often are not the lesion we fixed, but there’s 25 other moderate plaques in the coronary tree and one of them is heating up and it’s vulnerable. […] ACS, the whole thing here is the idea of a vulnerable plaque rupture. And it’s often not a severe narrowing.” (3-5 minutes in)

[One of the plaque rupture triggers of relevance is inflammatory cytokines…] “What’s a good example of that? Influenza. Right, influenza releases things like, IL-6 and other cytokines. What do they do? Well, they make you shake and shiver and feel like your muscles are dying. They also dissolve plaques. […] If you take a town like Ann Arbor and vaccinate everybody for influenza, we reduce heart attacks by a lot … 20-30 % during flu season.” (~11-12 minutes in)

“What happens to your systolic function as you get older? Any ideas? I’m happy to tell you it stays strong. […] What happens to diastole? […] As your myocardial cells die, a few die every day, […] those cells get replaced by fibrous tissue. So an aging heart becomes gradually stiffer [*this is apparently termed ‘presbycardia’*]. It beats well because the cells that are alive can overcome the fibrosis and squeeze, but it doesn’t relax as well. So left ventricular and diastolic pressure goes up. Older patients are much more likely to develop heart failure [in the ACS setting] because they already have impaired diastole from […] presbycardia.” (~1.14-1.15)

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Some links to coverage of topics covered during the lecture:

Acute Coronary Syndrome.

Unstable angina.

Pathology of Acute Myocardial Infarction.

Acute Coronary Syndrome Workup.

Acute Coronary Syndrome Treatment & Management.

The GRACE risk score.

Complications of Myocardial Infarction.

Early versus Delayed Invasive Intervention in Acute Coronary Syndromes (*Mehta et al.* 2009).

## National EM Board Review Course: Toxicology

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Some links:

Flumazenil.

Naloxone.

Alcoholic Ketoacidosis.

Gastrointestinal decontamination in the acutely poisoned patient.

Chelation in Metal Intoxication.

Mudpiles – causes of high anion-gap metabolic acidosis.

Toxidromes.

Whole-bowel irrigation: Background, indications, contraindications…

Organophosphate toxicity.

Withdrawal syndromes.

Acetaminophen toxicity.

Alcohol withdrawal.

Wernicke syndrome.

Methanol toxicity.

Ethylene glycol toxicity.

Sympathomimetic toxicity.

Disulfiram toxicity.

Arsenic toxicity.

Barbiturate toxicity.

Beta-blocker toxicity.

Calcium channel blocker toxicity.

Carbon monoxide toxicity.

Caustic ingestions.

Clonidine toxicity.

Cyanide toxicity.

Digitalis toxicity.

Gamma-hydroxybutyrate toxicity.

Hydrocarbon toxicity.

CDC Facts About Hydrogen Fluoride (Hydrofluoric Acid).

Hydrogen Sulfide Toxicity.

Isoniazid toxicity.

Iron toxicity.

Lead toxicity.

Lithium toxicity.

Mercury toxicity.

Methemoglobinemia.

Mushroom toxicity.

Argyria.

Gyromitra mushroom toxicity.

Neuroleptic agent toxicity.

Neuroleptic malignant syndrome.

Oral hypoglycemic agent toxicity.

PCP toxicity.

Phenytoin toxicity.

Rodenticide toxicity.

Salicylate toxicity.

Serotonin syndrome.

TCA toxicity.