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The science behind Cassava Sciences (SAVA) — the latest as of 23 April ’23

It’s time for an update on the science  behind Cassava Sciences’ anti-Alzheimer drug, Simufilam.  It is  based on an older post of mine and a review of the published literature and my decades of experience as a clinical neurologist.

Disclaimer:  My wife and I have known Lindsay Burns, one of the Cassava Sciences principals since she was a teenager and we were friendly with her parents when I practiced neurology in Montana.

But as H. L. Mencken said, “A Professor must have a theory as a dog must have fleas”, and the reason I’m excited about Simufilam has nothing to do with the theory of the science behind it.  Simply put, the results of Cassava’s open label trial have never  been seen with Alzheimer’s patients.  10% improved by nearly 50% at 1 year, and over half did not deteriorate.  As a clinical neurologist with decades of experience seeing hundreds of demented people, I never saw anything like this, especially significant improvement after a year).  For more detail please see

Here is the science behind the drug.  We’ll start with the protein the drug is supposed to affect — filamin A, a very large protein (2,603 amino acids to be exact).  I’ve known about it for years because it crosslinks actin in muscle, and I read everything I could about it, starting back in the day when I ran a muscular dystrophy clinic in Montana.

Filamin binds actin by its amino terminal domain.  It forms a dimerization domain at its carboxy terminal end.  In between are 23 repeats of 96 amino acids which resemble immunoglobulin — forming a rod 800 Angstroms long.  The dimer forms a V with the actin binding domain at the two tips of the V, making it clear how it could link actin filaments together.

Immunoglobulins are good at binding things and 90 different proteins are known to which filamin A binds.  This is an enormous potential source of trouble.

As one might imagine, filamin A could have a lot of conformations in addition to the V, and the pictures shown in

One such altered (from the V) conformation binds to the alpha7 nicotinic cholinergic receptor on the surface of neurons and Toll-Like Receptor 4 (TLR4) inside the cell.

Abeta42, the toxic peptide, has been known for years to bind tightly to the alpha7 nicotinic receptor — they say in the femtoMolar (10^-15 Molar) range, although I have my doubts as to whether such tiny concentration values are meaningful.  Let’s just say the binding is tight and that femtoMolar binding is tighter than picoMolar is tighter than nanoMolar is tighter than microMolar  binding etc., etc.

When aBeta42 binds to alpha7 on the outside of the neuronal plasma membrane  filamin A binds to alpha 7 on the inside making  aBeta42 binding even tighter.

The tight binding causes signaling inside the cell  to hyperphosphorylate the tau protein forming the neurofibrillary tangle, which is more directly correlated with dementia in Alzheimer’s disease than the number of senile plaques.

In more detail, the high affinity aBeta42-alpha7 nicotinic cholinergic receptor binding activates the MAPK cascade (Mitogen Activated Protein Kinase cascade), ending in activation of the protein kinases ERK2, and JNK1.  Activated protein kinases catalyze the addition of phosphate to proteins forming an ester with the free hydroxyl groups of serine and/or threonine.  Activating ERK2 and JNK1 allows them to phosphorylate the tau protein leading to the neurofibrillary tangle of  Alzheimer’s disease (which is just a mess of hyperphosphorylated tau protein).

But there is still more about the mechanism which isn’t clear.  Recall that MAPK stands for Mitogen Activated Protein Kinase where a mitogen binds to a receptor on the cell surface, and a mitogen is nowhere in sight here, so there are still a few missing steps between aBeta42 binding to the alpha7 nicotinic cholinergic receptor and MAPK activation.  The references do show that MAPK signaling, ERK2 and JNK1 are activated when aBeta42 binds to the alpha7 nicotinic acetyl choline receptor.

Also the mechanism is radical in the extreme. The nicotinic acetyl choline receptor is a receptor all right but for acetyl choline. It is an ion channel and   looks nothing like the receptors that proteins and peptides bind to which are usually G Protein Coupled Receptors (GPCRs) or Receptors with Tyrosine Kinase activity (RTKs).  Also aBeta42 is not a mitogen.

So what does Sumifilam actually do — it changes the ‘altered’ conformation of filamin A getting it away from the alpha7 acetyl choline receptor and “indirectly reducing the high femtoMolar binding affinity of aBeta42 for alpha7” (and however this binding triggers tau hyperphosphorylation)  How do they know the conformation of filamin A has changed?  They haven’t done cryoEM or Xray crystallography on the protein.  The only evidence for a change in conformation, is a change in the electrophoretic mobility (which is pretty good evidence, but I’d like to know what conformation is changed to what).

So there you have it, after a fairly deep dive into protein chemistry, cellular physiology and biochemistry, the current thinking of how Simufilam works.

But even if the theory is completely wrong, the data in the link above must be regarded with respect.  Clinical blinded studies are ongoing, and the soon to be released Cognition Maintenance Study should  give us more information –

An incredibly clever experiment

Every now and then an experiment comes along that is so clever and definitive that all you can do is admire it and tell your friends.

The question to be answered is do bees have a cognitive map of their surroundings?  E.g. do they know where other objects are in relation to the hive and, more importantly to each other?

How in the world would you ever figure out a way to answer the question?

Anyone who has ever taken a college biology course has probably heard of the waggle dance.   The dance is performed by bees not strippers.  It tells other members of the hive where the dancer has found food (by the direction the bee moves during the dance) and how far away it is (by the length of the dance).

Well you don’t need a cognitive map of everything in your surroundings to do that.  Just a given direction and a given distance is enough to find the food.

The clever part (and a technical tour de force) was putting something on the bee allowing its flight pattern to be detected, and then (after the bee had performed its dance), taking it and moving it to a position away from the hive and watching what it did (incredibly clever to think of that).  The bee (most of the time) made a beeline for the original target, even though the flight was in a different distance and of a different length.  Clearly the bee had to know where the target was in relation to the bee’s new position.  The only reasonable explanation is that the bee possessed a map of where things were in relation to arbitrary locations in its environment (not just the hive).

Here’s an article about the experiment — Proc. Natl. Acad. Sci. vol. 120 e2303202120 ’23 — and a link to it —  — hopefully not behind a pay wall.


Mine eyes have seen the scupting of the brain

With apologies to the Battle Hymn of the Republic

Mine eyes have seen the sculpting of the brain

He is trampling out the variants where the memes of thought are stored

He hath loosed the fateful errors of his terrible swift sword

Our genes are marching on

Well not quite but we know quite a bit more about the genetic changes that have given us our much larger and much more complex brain than the chimpanzee.

Many thanks to Pierre Vanderhaeghen one of the authors of [ Neuron vol. 111 pp. 65 – 80 ’23 ] discussed in a recent post — for sending me the PDF of his review “Cellular and Molecular Mechanisms Linking Cortical Development and Evolution” in Annu. Rev. Genet. vol. 55 pp. 24.1 – 24.27 ’21 in response to my request for more information about the genetic changes which make our brains what they are today.

It will be very difficult to separate the significant changes in our genomes which are specific to humans and not found in the chimp and gorilla.  Some 20,000,000 to be exact.  (This figure comes from the notes I took on Cell vol. 149 pp. 737 –  739, 912 – 922, 923 – 935 ’12** or Nature vol. 486 pp. 481 – 482 ’12** years ago.  Unfortunately when I tried to pull up these papers on the net to check the figure, I couldn’t do it — there will be more of this in this post, and when I can’t I’ll put a ** after the year).

The previous paper talked about CROCCP2, a duplicated gene unique to man which is expressed only in the human developing cerebral cortex.   Our genome contains 10 families of protein coding genes the duplications of which are only found in man.  Our genome contains over 50 families of duplicated protein coding genes (obviously not all unique to man), but 30 duplicated genes are expressed in the fetal developing brain.  The CROCCP2 variant leads a larger brain — for details please see

Well 30 duplicated genes isn’t much.  What about where the real action is — the control of when and where these genes are expressed.

The following is from a post of 2015

It ain’t the bricks, it’s the plan

Nothing better shows the utility (and the futility) of chemistry in biology than using it to explain the difference between man and chimpanzee. You’ve all heard that our proteins are only 2% different than the chimp, so we are 98% chimpanzee. The facts are correct, the interpretation wrong. We are far more than the protein ‘bricks’ that make us up, and two current papers in Cell [ vol. 163 pp. 24 – 26, 66 – 83 ’15 ] essentially prove this.

This is like saying Monticello and Independence Hall are just the same because they’re both made out of bricks. One could chemically identify Monticello bricks as coming from the Virginia piedmont, and Independence Hall bricks coming from the red clay of New Jersey, but the real difference between the buildings is the plan.

It’s not the proteins, but where and when and how much of them are made. The control for this (plan if you will) lies outside the genes for the proteins themselves, in the rest of the genome (remember only 2% of the genome codes for the amino acids making up our 20,000 or so protein genes). The control elements have as much right to be called genes, as the parts of the genome coding for amino acids. Granted, it’s easier to study genes coding for proteins, because we’ve identified them and know so much about them. It’s like the drunk looking for his keys under the lamppost because that’s where the light is.”

One of the things  determining when and where proteins are expressed are the enhancers.  These are stretches of DNA which enhance the transcription of a protein coding gene into mRNA which is translated by the ribosome into protein.  They consist of hundreds of basepairs of DNA and are bound by transcription factors. Each cell type is estimated to contain 70,000 -100,000 enhancers [ Cell vol. 183 p. 40 ’20 ]**

Here’s where the evolutionary rubber hits the road.  Human Gained Enhancers (HGEs) are enhancers active only in man and thousands of them are active in cerebral cortex formation [ Annu. Rev. Genet. vol. 55 pp. 24.1 – 24.27 ’21 ].

Human Accelerated Regions (HARs) are regions of our genome which are thought to show accelerated mutation changes in an otherwise evolutionarily ultraconserved sequence.  These sequences are unique to the human genome and there are 2,772 of them [ Neuron vol. 109 pp. 3231 – 3233, 3239 – 3251 ’21 ]**.  As you might expect, they are in the 98% of our genomes which are not coding for the amino acids of proteins.  They are enriched for transcription binding motifs.  So some might be in enhancers, some might be in promoters, but they’re all about ‘the plan’ and not the bricks.

Control elements can also be lost, and some 510 locations are known where DNA sequences have been lost in the human genome.  These sequences are highly conserved between chimp and other mammals, and most of them are in enhancers [ Nature vol. 471 pp. 216 – 219 ‘ 11 ]**.

And then there is repurposing of an existing gene.  Osteocrinin (aka Musclin) is an exercise induced protein which acts in muscle to increase exercise capcity.  It is turned on by MEF2 (Myocyte Enhancer Factor 2) a transcription factor. t of  But only in man, is osteocrinin found in the brain why.  Because another MEF binding site has been put in front of the gene, so that (in some unspecified manner, neural activity turns it on). [ Nature vol. 539 pp. 171 – 172, 242 – 247 ’16 ]**

So we have myriads of genome changes involved in building our brains (enhancer gain and loss), human accelerated regions, duplicated genes with new functions and repurposed genes.

Mine eyes have seen the sculpting of the brain (but only dimly presently). Stay tuned.

The origin of runner’s high

There is a great moment (for the neuropharmacologist) in “Postcards from the Edge” with Meryl Streep.  She’s walking along with the bimbo who she just found out seduced the guy who seduced her, when the bimbo blurts out that she feels great because of her endolphins.

Well exercise may raise endorphins in the blood which many regarded as an explanation of the runner’s high.   But almost as soon as the endorphins were discovered, it was found that they don’t get into the brain when injected into the blood.   (If you’re wondering how we can know this, it is based on a synthetic endorphin containing a radioactive atom — injecting it into the blood stream shows it doesn’t get into the brain.

This shouldn’t be surprising, the brain is quite selective about what it lets in.  Consider the first useful treatment of Parkinson’s disease, L-DOPA (L DihydrOxy PhenylAlanine) which does get into the brain, which then breaks it down to dopamine losing two oxygens in the process, which doesn’t get into the brain (even though dopamine is a smaller and less complicated molecule).   Functionally, this is known as the blood brain barrier (BBB).

So maybe exercise raises endorphrins in the brain, but a better explanation for the runner’s high is now at hand [ Nature vol. 612 pp. 633 – 634, 739 – 747 ’22 ].  You won’t believe the answer, which involves the organisms in your gut, but the evidence is quite good, as you are about to read.

First, the composition of the gut microbiome predicts how much mice voluntarily run on exercise wheels or treatmills.  Treatment with antibiotics which diminishes the amount of microbiota diminishes exercise endurance.  Adding the gut microbiome from high exercise mice to germ free mice (gnotobiotic mice) raises running capacity to that of the donor.

Increased levels of dopamine are considered rewarding or pleasurable.  Cocaine prevents it from being taken up after neurons release it, an antidepressant (Monamine Oxidase — MAO) prevents it from being destroyed. etc. etc.

It is known that exercise increases the levels of dopamine in an area of the brain called the striatum.  Dopamine gets to the striatum by the axons of neurons in the ventral tegmental area (VTA).  Inhibition of neurons in the VTA decreases dopamine in the striatum and decreases the amount of exercise a mouse will do.

What does the gut microbiota have to do with this?

Well, germfree (gnotobiotic) mice didn’t change MAO levels in the striatum on exercise, and the dopamine surge and striatal neural activity were blunted.  And germfree mice don’t run as much.

Well, clearly the little bugs down there are producing some sort of signal which IS getting to the brain, not an easy feat getting past the blood brain barrier given the example of L-DOPA above.

We know the bugs produce all sorts of metabolites, the body uses.  One example is vitamin K, which is crucial in the biochemical maturation of coagulation factors, deficiencies of which produce hemorrhagic disease of the newborn. This may explain why the ritual circumcision of Jewish males occurs 8 days after birth, after the gut bacteria have had a chance to make it.

The work cited above shows that the bugs produce fatty acid amides (FAAs) which bind to the type I cannabinoid receptor (CB1) which binds marihuana.

Like just about everything else in the body, there are sensory nerves from the gut going to the spinal cord.  The FAAs activate some of these nerves by binding to CB1.   Giving FAAs to germfree mice increases physical activity.

Gut sensory nerves containing CB1 also have another protein called TRPV1.  Stimulating these nerves with a TRPV1 ligand increases physical activity.  This is true even in germfree mice.

Well we know marihuana has no trouble getting pCast the BBB, so why couldn’t the FAAs produced by the bugs do the same and increase exercise.   Well, it could but it doesn’t.  Severing the sensory nerve before it gets to the spinal cord abolishes the effects of the microbiome (which is still there) on exercise.

So, clearly the continuity of the nerve is crucial for the effect of gut bacteria on exercise, as are FAAs and the CB1 receptor found on the nerve.

Well the sensory nerve from the gut gets into the spinal cord, but there is a lot more work to be done, to determine the pathway by which stimulation of the nerve changes MAO levels in the striatum (as the striatum is a long way from the spinal cord).   So like all great experiments, it suggests further questions and work required to resolve them.

A  beautiful series of experiments.  Could brain ‘endolphins’ still play a role in exercise.  Sure,  but whether they do or not, doesn’t detract from the work here.

One could study the effect of exercise on brain (not blood) endorphins and the effect of cutting the sensory nerve from the gut on their brain levels.




A visual proof of the the theorem egregium of Gauss

Nothing better illustrates the difference between the intuitive understanding that something is true and being convinced by logic that something is true  than the visual proof of the theorem egregium of Gauss found in “Visual Differential Geometry and Forms” by Tristan Needham and  the 9 step algebraic proof in  “The Geometry of Spacetime” by Jim Callahan.

Mathematicians attempt to tie down the Gulliver of our powerful appreciation of space with Lilliputian strands of logic.

First: some background on the neurology of vision and our perception of space and why it is so compelling to us.

In the old days, we neurologists figured out what the brain was doing by studying what was lost when parts of the brain were destroyed (usually by strokes, but sometimes by tumors or trauma).  This wasn’t terribly logical, as pulling the plug on a lamp plunges you in darkness, but the plug has nothing to do with how the lightbulb or LED produces light.  Even so,  it was clear that the occipital lobe was important — destroy it on both sides and you are blind — but the occipital lobe accounts for only 10% of the gray matter of the cerebral cortex.

The information flowing into your brain from your eyes is enormous.  The optic nerve connecting the eyeball to the brain has a million fibers, and they can fire ‘up to 500 times a second.  If each firing (nerve impulse) is a bit, then that’s an information flow into your brain of a gigaBit/second.   This information is highly processed by the neurons and receptors in the 10 layers of the retina. Over 30 retinal cell types in our retinas are known, each responding to a different aspect of the visual stimulus.  For instance, there are cells responding to color, to movement in one direction, to a light stimulus turning on, to a light stimulus turning off, etc. etc.

So how does the relatively small occipital lobe deal with this? It doesn’t.  At least half of your the brain responds to visual stimuli.  How do we know?   It’s complicated, but something called functional Magnetic Resonance Imaging (fMRI) is able to show us increased neuronal activity primarily by the increase in blood flow it causes.

Given that half of your brain is processing what you see, it makes sense to use it to ‘see’ what’s going on in Mathematics involving space.  This is where Tristan Needham’s books come in.

I’ve written several posts about them.

and Here —



OK, so what is the theorem egregium?  Look at any object (say a banana). You can see how curved it is by just looking at its surface (e.g. how it looks in the 3 dimensional space of our existence).  Gauss showed that you don’t
have to even look at an object in 3 space,  just perform local measurements (using the distance between surface points, e.g. the metric e.g.  the metric tensor) .  Curvature is intrinsic to the surface itself, and you don’t have to get outside of the surface (as we are) to find it.



The idea (and mathematical machinery) has been extended to the 3 dimensional space we live in (something we can’t get outside of).  Is our  universe curved or not? To study the question is to determine its intrinsic curvature by extrapolating the tools Gauss gave us to higher dimensions and comparing the mathematical results with experimental observation. The elephant in the room is general relativity which would be impossible without this (which is why I’m studying the theorem egregium in the first place).


So how does Callahan phrase and prove the theorem egregium? He defines curvature as the ratio of the area on a (small) patch on the surface to the area of another patch on the unit sphere. If you took some vector calculus, you’ll know that the area spanned by two nonCollinear vectors is the numeric value of their cross product.



The vectors Callahan needs for the cross product are the normal vectors to the surface.  Herein beginneth the algebra. Callahan parameterizes the surface in 3 space from a region in the plane, uses the metric of the surface to determine a formula for the normal vector to the surface  at a point (which has 3 components  x , y and z,  each of which is the sum of 4 elements, each of which is the product of a second order derivative with a first order derivative of the metric). Forming the cross product of the normal vectors and writing it out is an algebraic nightmare.  At this point you know you are describing something called curvature, but you have no clear conception of what curvature is.  But you have a clear definition in terms of the ratio of areas, which soon disappears in a massive (but necessary) algebraic fandango.



On pages 258 – 262 Callahan breaks down the proof into 9 steps involving various mathematical functions of the metric and its derivatives such as  Christoffel symbols,  the Riemann curvature tensors etc. etc.  It is logically complete, logically convincing, and shows that all this mathematical machinery arises from the metric (intrinsic to the surface) and its derivatives (some as high as third order).



For this we all owe Callahan a great debt.  But unfortunately, although I believe it,  I don’t see it.  This certainly isn’t to denigrate Callahan, who has helped me through his book, and a guy who I consider a friend as I’ve drunk beer with him and his wife while  listening to Irish music in a dive bar north of Amherst.



Callahan’s proof is the way Gauss himself did it and Callahan told me that Gauss didn’t have the notational tools we have today making the theorem even more outstanding (egregious).


Well now,  onto Needham’s geometrical proof.  Disabuse yourself of the notion that it won’t involve much intellectual work on your part even though it uses the geometric intuition you were born with (the green glasses of Immanuel Kant —


Needham’s definition of curvature uses angular excess of a triangle.  Angles are measured in radians, which is the ratio of the arc subtended by the angle to the radius of the circle (not the circumference as I thought I remembered).  Since the circumference of a circle is 2*pi*radius, radian measure varies from 0 to 2*pi.   So a right angle is pi/2 radians.


Here is a triangle with angular excess.  Start with a sphere of radius R.  Go to the north pol and drop a longitude down to the equator.  It meets the equator at a right angle (pi/2).  Go back to the north pole, form an angle of pi/2 with the first longitude, and drop another longitude at that angle which meets the equator at an angle of pi/2.   The two points on the equator and the north pole form a triangle, with total internal angles of 3*(pi/2).  In plane geometry we know that the total angles of a triangle is 2 (pi/2).  (Interestingly this depends on the parallel postulate. See if you can figure out why).  So the angular excess of our triangle is pi/2.  Nothing complicated to understand (or visualize) here.


Needham defines the curvature of the triangle (and any closed area) as the ratio between the angular excess of the triangle to its area



What is the area of the triangle?  Well, the volume of a sphere is (4/3) pi * r^3, and its area is the integral (4 pi * r^2).  The area of the north hemisphere, is 2 pi *r^2, and the area of the triangle just made is 1/2 * Pi * r^2.



So the curvature of the triangle is (pi/2) / (1/2 * pi * r^2) = 1 / r^2.   More to the point, this is the curvature of a sphere of radius r.



At this point you should have a geometric intuition of just what curvature is, and how to find it.  So when you are embroiled in the algebra in higher dimensions trying to describe curvature there, you will have a mental image of what the algebra is attempting to describe, rather than just the symbols and machinations of the algebra itself (the Lilliputian strands of logic tying down the Gulliver of curvature).


The road from here to the Einstein gravitational field equations (p. 326 of Needham) and one I haven’t so far traversed,  presently is about 50 pages.Just to get to this point however,  you have been exposed to comprehensible geometrical expositions, of geodesics, holonomy,  parallel transport and vector fields, and you should have mental images of them all.Interested?  Be prepared to work, and to reorient how you think about these things if you’ve met them before.  The 3 links mentioned about will give you a glimpse of Needham’s style.  You probably should read them next.

New light on protein folding

Henry Eyring would have loved this paper [ Proc. Natl. Acad. Sci. vol. 119 e2112372118 ’22  —  ] He developed transition state theory.  You can read about it and what Eyring was actually like here —

The paper also gives an excellent history of the intellectual twists and turns of the protein folding problem.  It starts with Anfinsen’s work on Ribonuclease (RNAase), which is a rather simple protein.  He noted that even when unfolded (denatured), RNAase would spontaneously fold to its native structure.  Thus was born the thermodynamic hypothesis of protein structure.  Because the native form occurred spontaneously it had to have the lowest free energy of all the possible conformations.   This was long before we knew about protein chaperones,.

This was followed by the molten globule idea.  It was modeled on solid formation from a gas in which a metastable liquid phase precedes solid formation during gas deposition.  The molten globule has a high degree of secondary structure (alpha helices, beta sheets), but no fixed arrangement of them relative to each other (e.g. no tertiary structure).  To be considered a molten globule, the protein must have an expanded structure relative to the native fully folded protein.

This was followed by the energy landscape theory of protein folding, something I never liked because I never saw a way to calculate the surface of the landscape.  Proteins fold by following the landscape to a lower potential energy, the way a skier follows the mountain down hill. It seems like a high falutin’ way of saying proteins fold, the same way docs say you have idiopathic something or other instead of saying we don’t know what caused what you have.  In the energy landscape theory molten globule intermediates are not necessary.

Then there is the foldon hypothesis — proteins fold following a unique pathway by the cooperative and sequential formation of native structure domains (e.g. the foldons).  Folding amounts to the productive tinkering of amino acids and foldons rather than the diffusion of a protein in a funnel-like energy landscape.

The paper studied Barnase, a 110 amino acid protein which degrades RNA (so much like the original protein Anfinsen studied years ago).  Barnase is highly soluble and very stable making it one of the E. Coli’s of protein folding studies.

The new wrinkle of the paper is that they were able to study the folding and unfolding and the transition state of single molecules of Barnase at different temperatures (an experiment which would have been unlikely for Eyring to even think about doing in 1935 when he developed transition state theory, and yet this is exactly the sort of thing what he was thinking about but not about proteins whose structure was unknown back then).

The work alluded to in the link to another post above, did something similar except that they used DNA instead of a protein.  Here is the relevant part of it.

A polyNucleotide hairpin of DNA  was connected to double stranded DNA handles in optical traps where it could fluctuate between folded (hairpin) and unfolded (no hairpin) states.  They could measure just how far apart the handles were and in the hairpin state the length appears to be 100 Angstroms (10 nanoMeters) shorter than the unfolded state.

So they could follow the length vs. time and measure the 50 microSeconds or so it took to make the journey across the free energy maximum (e.g. the transition state). A mere 323,495 different transition paths were studied.

This allowed them to determine not just the change in free energy (deltaG)  between the unfolded (U) and the transition state (TS) and the native state (N) of Barnase, but also the changes in enthalpy (delta H) and entropy (delta S) between U and TS and between N and TS.

Remember delta G = Delta H – T delta S.  A process will occur if deltaG is negative, which is why an increase in entropy is favorable, and why the decrease in entropy between U and TS is unfavorable.

Almost all of the entropy decrease  between U and N occurs between U and TS.  Which makes sense as the transition state is a lot more ordered than than the unfolded state.  Most of the change in enthalpy occur on the TS –> N transition.

The results are most consistent with both the energy landscape of Wolynes and the molten globule  They describe the transition state as like a golf course, where there are many positions for the ball (the molten globule), but only one place to go down to the native state.  Once the hole is found the protein zooms down to the native state through the potential energy funnel.

Fascinating stuff.

Are the antiVaxers already relatively immune?

As delta, omicron and god knows what other Greek letter variant of the pandemic virus marches through our population, it is time to find out how many of the unvaccinated have actually been infected asymptomatically.  It could well be most of them.  Studies done July 2020, a year and a half ago in New York State (before we even had vaccines) showed high levels of antibodies to the virus.

Do distinguish what an antibody to the virus means from a positive PCR or antigen test.  A positive antibody test means you’ve been infected with the virus at some point — almost certainly it’s long gone (the footprint of the bear is not the actual bear — sounds like Zen).  A positive antigen or PCR test means that the virus is within you now.

At a clinic in Corona, a working-class neighborhood in Queens, more than 68 percent of people tested positive for antibodies to the new coronavirus. At another clinic in Jackson Heights, Queens, that number was 56 percent. But at a clinic in Cobble Hill, a mostly white and wealthy neighborhood in Brooklyn, only 13 percent of people tested positive for antibodies.

Note the date — July of 2020.   Clearly most of these people did not require hospitalization.

So it’s time to look for antibodies in the never vaccinateds (there is no point in looking at the already vaccinated as they should have them).  If the never vaccinated antibody rate is as high as I think it is (>80%), it’s time to stop the lockdowns, the maskings, and the school closures.  Why — because they’ve already been infected and fought off the virus.

It is clear that vaccination will not keep you out of the hospital.

At the end of 25 January the state of Massachusetts had 2,617 people in the hospital with COVID19, 405 in the ICU and 248 intubated.  Half of them are described by the department of Health are described as ‘fully vaccinated’  (which just means 2 shots as of their definition of September 2021 — clearly this should be updated).   Probably almost all of these are with omicron.

Although this is bad, it represents a drop from 3,192, 466 and 290 just a week ago.

I doubt that such a study will be done, but it would be useful.

Addendum  Science 28 January 2022  p. 387.  Well how wrong could I be . “A serosurvey he led in Gauteng province, home to one-quarter of South Africa’s population, showed close to 70% of unvaccinated people carried SARS-CoV-2 antibodies at the start of the Omicron wave. In the next survey, he expects that number to have gone up to at least 85%, a level that should prepare South Africa for a post-Omicron future.”

Second Addendum 28 January 2022 — Here’s a link to (and a bit more about)  the paper on which the proceeding paragraph was based — It’s not peer-reviewed yet, but it’s from the S. African Medical Research Council, so it is likely to be valid.

The serosurvey was recent (22 October – 9 December 2021) and just before omicron hit the country.   Only 1,319 of the 7,010 people in the study were vaccinated.  An amazing 70% of the unvaccinated were seropositive (had antibodies to the pandemic virus).  As (not quite expected) the vaccinated had a higher seropositive rate (93%) but I thought it would be higher.

This is exactly the sort of study carried out in New York, where the testers went out and grabbed people to get a sample of what was actually going on in the population at large which makes it highly likely to be valid.  We should do a similar study in the USA.

What would really be terrific (but I don’t think it exists yet) would be a test for antibodies to omicron which distinguishes them from antibodies to older SARS-CoV-2 variants.

There is some evidence that vaccination protects against severe infections with omicron, so leave that to the unvaccinated, and leave the rest of us alone.

A premature book review and a 60 year history with complex variables in 4 acts

“Visual Differential Geometry and Forms” (VDGF) by Tristan Needham is an incredible book.  Here is a premature review having only been through the first 82 pages of 464 pages of text.

Here’s why.

While mathematicians may try to tie down the visual Gulliver with Lilliputian strands of logic, there is always far more information in visual stimuli than logic can appreciate.  There is no such a thing as a pure visual percept (a la Bertrand Russell), as visual processing begins within the 10 layers of the retina and continues on from there.  Remember: half your brain is involved in processing visual information.  Which is a long winded way of saying that Needham’s visual approach to curvature and other visual constructs is an excellent idea.
Needham loves complex variables and geometry and his book is full of pictures (probably on 50% of the pages).

My history with complex variables goes back over 60 years and occurs in 4 acts.


Act I:  Complex variable course as an undergraduate. Time late 50s.  Instructor Raymond Smullyan a man who, while in this world, was definitely not of it.  He really wasn’t a bad instructor but he appeared to be thinking about something else most of the time.


Act II: Complex variable course at Rocky Mountain College, Billings Montana.  Time early 80s.  The instructor and MIT PhD was excellent.  Unfortunately I can’t remember his name.  I took complex variables again, because I’d been knocked out for probably 30 minutes the previous year and wanted to see if I could still think about the hard stuff.


Act III: 1999 The publication of Needham’s first book — Visual Complex Analysis.  Absolutely unique at the time, full of pictures with a glowing recommendation from Roger Penrose, Needham’s PhD advisor.  I read parts of it, but really didn’t appreciate it.


Act IV 2021 the publication of Needham’s second book, and the subject of this partial review.  Just what I wanted after studying differential geometry with a view to really understanding general relativity, so I could read a classmate’s book on the subject.  Just like VCA, and I got through 82 pages or so, before I realized I should go back and go through the relevant parts (several hundred pages) of VCA again, which is where I am now.  Euclid is all you need for the geometry of VCA, but any extra math you know won’t hurt.


I can’t recommend both strongly enough, particularly if you’ve been studying differential geometry and physics.  There really is a reason for saying “I see it” when you understand something.


Both books are engagingly and informally written, and I can’t recommend them enough (well at least the first 82 pages of VDGF).


An intentional social and epidemiological experiment

Back in the day, mutations causing disease were called experiments of nature, something I thought cruel because as a budding chemist I regarded experiments as something intentional, and mutations occuring outside the lab are anything but intentional.

Massachusetts entered an intentional social and epidemiological experiment today. I hope it turns out well, but I seriously doubt it.

Unvaccinated people are ‘urged’ to wear masks. The state “advises all unvaccinated residents to continue to wear masks in indoor settings and when they can’t socially distance.” Lots of luck with that.

So I went to the working class cafe where I get coffee every day. A place where irony is unknown. In a 25 – 25 foot space (my guess) were 50 people in 6 booths and about 6 tables, none wearing masks. I doubt that all were vaccinated. Fortunately the cafe staff has all been vaccinated.

The cafe is in an old building with at most a 9 foot ceiling. Service was likely slow because of the crowd. So they’d likely spend 30 – 60 minutes breathing each other’s air, a perfect way to transmit the virus if any of the 50 would be infected. For details please see

The clientele is not a healthy lot, and I’d estimate that 40% of those present had BMIs over 30.

For some reason the classic editor won’t let me put in links. So I’m publishing this as is.

Minorities on course to win the Darwin awards

While the plural of anecdote is not data, two episodes this week have me very depressed about the spread of the pandemic virus in the minority community (particularly in Blacks). The first occurred with a very intelligent Black woman who worked in tech support at Comcast and helped us when our internet connection went down. You do not get a job like that unless you’re smart. She’s heard a lot about vaccine side effects and isn’t going to get it. The next was a National Guard woman working for AAA, who won’t get the vaccine unless its a military requirement.

At 3 visits to our vaccination site in a town 45% of the population is Puerto Rican we saw nary a one (except for the guy disinfecting the chairs). I talked to one of the nurses, who said that our experience is typical of what she sees day after day.

One way to make a dent in this, is force hospitals when reporting COVID19 deaths, to state whether the patient was vaccinated or not. Granted most COVID19 will not be vaccinated at out current levels of vaccination, but as this doesn’t change with increasing vaccination levels, perhaps they will be convinced (but unfortunately after a lot of unnecessary deaths.

This is not written with the old WordPress Editor, but with the new one which I hate. It doesn’t seem to let you put in tabs.

You now have to pay up to get Premium edition to install the classic editor. Although initially angered, I’ve been using it for a decade absolutely free, and it’s time to pay up