Category Archives: Medicine in general

Marshall McLuhan rides again

Marshall McLuhan famously said “the medium is the message”. Who knew he was talking about molecular biology?  But he was, if you think of the process of transcription of DNA into various forms of RNA as the medium and the products of transcription as the message.  That’s exactly what this paper [ Cell vol. 171 pp. 103 – 119 ’17 ] says.

T cells are a type of immune cell formed in the thymus.  One of the important transcription factors which turns on expression of the genes which make a T cell a Tell is called Bcl11b.  Early in T cell development it is sequestered away near the nuclear membrane in highly compacted DNA. Remember that you must compress your 1 meter of DNA down by 100,000fold to have it fit in the nucleus which is 1/100,000th of a meter (10 microns).

What turns it on?  Transcription of nonCoding (for protein) RNA calledThymoD.  From my reading of the paper, ThymoD doesn’t do anything, but just the act of opening up compacted DNA near the nuclear membrane produced by transcribing ThymoD is enough to cause this part of the genome to move into the center of the nucleus where the gene for Bcl11b can be transcribed into RNA.

There’s a lot more to the paper,  but that’s the message if you will.  It’s the act of transcription rather than what is being transcribed which is important.

Here’s more about McLuhan —

If some of the terms used here are unfamiliar — look at the following post and follow the links as far as you need to.

Well that was an old post.  Here’s another example [ Cell vol. 173 pp. 1318 – 1319, 1398 – 1412 ’18 ] It concerns a gene called PVT1 (Plasmacytoma Variant Translocation 1) found 25 years ago.  It was the first gene coding for a long nonCoding (for proteins RNA (lncRNA) found as a recurrent breakpoint in Burkitt’s lymphoma, which sadly took a friend (Nick Cozzarelli) far too young as (he edited PNAS for 10 years).

So PVT1 is involved in cancer.  The translocation turns on expression of the myc oncogene, something that has been studied out the gazoo and we’re still not sure of how it causes cancer. I’ve got 60,000 characters of notes on the damn thing, but as someone said 6 years ago “Whatever the latest trend in cancer biology — cell cycle, cell growth, apoptosis, metabolism, cancer stem cells, microRNAs, angiogenesis, inflammation — Myc is there regulating most of the key genes”

We do know that the lncRNA coded by PVT1 in some way stabilizes the myc protein [ Nature vol. 512 pp. 82 – 87 ’14 ].  However the cell experiments knocked out the lncRNA of PVT1 and myc expression was still turned on.

PVT1 resides 53 kiloBases away from myc on chromosome #8.  That’s about 17% of the diameter of the average nucleus (10 microns) if the DNA is stretched out into the B-DNA form seen in all the textbooks.  Since each base is 3.3 Angstroms thick that’s 175,000 Angstroms 17,500 nanoMeters 1.7 microns.  You can get an idea of how compacted DNA is in the nucleus when you realize that there are 3,200,000,000/53,000 = 60,000 such segments in the genome all packed into a sphere 10 microns in diameter.

To cut to the chase, within the PVT1 gene there are at least 4 enhancers (use the link above to find what all the terms to be used actually mean).  Briefly enhancers are what promoters bind to to help turn on the transcription of the genes in DNA into RNA (messenger and otherwise).  This means that the promoter of PVT1 binds one or more of the enhancers, preventing the promoter of the myc oncogene from binding.

Just how they know that there are 4 enhancers in PVT1 is a story in itself.  They cut various parts of the PVT1 gene (which itself has 306,721 basepairs) out, and place it in front of a reporter gene and see if transcription increases.

The actual repressor of myc is the promoter of PVT1 according to the paper (it binds to the enhancers present in the gene body preventing the myc promoter from doing so).  Things may be a bit more complicated as the PVT1 gene also codes for a cluster of 7 microRNAs and what they do isn’t explained in the paper.

So it’s as if the sardonic sense of humor of ‘nature’, ‘evolution’, ‘God’, (call it what you will) has set molecular biologists off on a wild goose chase, looking at the structure of the gene product (the lncRNA) to determine the function of the gene, when actually it’s the promoter in front of the gene and the enhancers within which are performing the function.

The mechanism may be more widespread, as 4/36 lncRNA promoters silenced by CRISPR techniques subsequently activated genes in a 1 megaBase window (possibly by the same mechanism as PVT1 and myc).

Where does McLuhan come in?  The cell paper also notes that lncRNA gene promoters are more evolutionarily conserved than their gene bodies.  So it’s the medium (promoter, enhancer) is the message once again (rather than what we thought the message was).



The other uses of amyloid (not all bad)

Neurologists and drug chemists pretty much view amyloid as a bad thing.  It is the major component of the senile plaque of Alzheimer’s disease, and when deposited in nerve causes amyloidotic polyneuropathy.  A recent paper and editorial casts amyloid in a different light [ Cell vol. 173 pp. 1068 – 1070, 1244 – 2253 ’18 ].  However if amyloid is so bad why do cytomegalovirus, herpes simplex viruses and E. Coli make proteins to prevent a type of amyloid from forming.

Cell death isn’t what it used to be.  Back in the day, they just died when things didn’t go well.  Now we know there are a variety of ways that cells die, and all of them have rather specific mechanisms.  Apoptosis (aka programmed cell death) is a mechanism of cell death used widely during embryonic development.  It allows the cell to die very quietly without causing inflammation.  Necroptosis is entirely different, it is another type of programmed cell death, designed to cause inflammation — bringing the immune system in to attack invading pathogens.

Two proteins (Receptor Interacting Protein Kinase 1 — RIPK1, and RIPK3) bind to each other forming amyloid, that looks for all the world like typical amyloid –it binds Congo Red, shows crossBeta diffraction and has a filamentous appearance.  Fascinating chemistry aside, the amyloid formed is crucial for necroptosis to occur, which is why various bugs try to prevent it.

The paper above describes the structure of the amyloid formed — unusual in itself, because until now amyloid was thought to involve the aggregation of a single protein.

The proteins are large: RIPK1 contains 671 amino acids, and RIPK3 contains 518.  They  both contain RHIMs (Receptor interacting protein Homotypic Interaction Motifs) which are fairly large themselves (amino acids 496 – 583 of RIPK1 and 388 – 518 of RIPK3).  Yet the amyloid the two proteins form use a very small stretches (amino acids 532 – 543 from RIPK1 and 451 – 462 from RIPK3).  How the rest of these large proteins pack around the beta strands of the 11 amino acid stretches isn’t discussed in the paper.  Even within these stretches, it is two consensus tetrapeptides (IQIG from RIPK1, and VQVG from RIPK3) that do most of the binding.

Even if you assume that I (Isoleucine) Q (glutamine) G (glycine) V (valine) occur at a frequency of 5%, in our proteome of 20,000 proteins assuming a length of amino acids IQIG and VQVG should occur 10 times each.  This may explain why 300/20,000 of our proteins contain a 100 amino acid  segment called BRICHOS which acts as a chaperone preventing amyloid formation. For details see —

Just another reason to take up the research idea in the link and find out just what other things amyloid is doing within our cells in the course of their normal functioning.


How Badly are Thy Genomes, Oh Humanity — take II

With apologies to Numbers 24:5, “How goodly are thy tents, Oh Jacob” —  a recent paper shows how shockingly error ridden our genomes actually are [ Science vol. 360 pp. 327 – 331  ’18 ].  I’d written about this in 2012 (see the end), but technology has marched on.  Back then only the parts of the genome coding for protein (the exome) were sequenced.  The present work did whole genome sequencing (WGS) to a mean coverage of 40+ (e.g. they sequenced the other 98 percent of the genome).

The authors were studying families in which one or more children had autism spectrum disorder to find genome abnormalities which might have caused the ASD. They were looking for structural variants (SVs) by which they mean ” biallelic deletion, tandem duplications, inversions, four classes of complex SV, and four families of mobile element insertions”

Why?  Because studying proteins alone doesn’t tell you how they are controlled.  That’s in the DNA surrounding them.  Structural variants are more likely to affect control elements than the proteins themselves.

Showing how technology has marched on they determined the whole genomes of 9274 subjects from 2600 families affected by ASD.

The absolutely mindboggling point in the article is the following direct quote “An average of 3746 SVs were detected per individual”.  That’s simply incredible (assuming the above isn’t a misprint).

Here’s the older post

How Badly Are Thy Genomes, Oh Humanity

With apologies to Numbers 24:5, “How goodly are thy tents, Oh Jacob” —  a recent paper shows how shockingly error ridden our genomes actually are [ Science vol. 337 pp. 64 – 69 ’12 ].  The authors sequenced roughly three quarters of the genes coding for proteins in some 2,439 people — e.g. 15,585 protein coding genes.  This left 98% of the genome untouched, primarily because we really don’t know what it does or how it does it, despite the fact that it controls, when, where and how much of each protein is made.  So they basically looked at the bricks from which we are built (the proteins) and not the plans (the 98%).

The news is not very good.  The subjects came from two groups: 1,351 Europeans and 1,088 Africans (the latter, because genetic diversity is far higher among Africans as that’s where humanity arose, and where mutations have had the longest time to accumulate).

The news is not very good. First, some background.

Recall that each nucleotide is one of four possibilities (A, T, G, C), and that each 3 nucleotides therefore has 4^3 = 64 possibilities.  61/64 combinations code for amino acids which, since we have only 20 gives a certain redundancy of the famed genetic code.   The other 3 combinations code for no amino acid (usually) and tell the machinery making proteins to stop.  Although crucial to our existence, these are called nonsense codons.

The genetic code is therefore 3fold degenerate (on average).  However, some amino acids are coded for by just 1 combination of 3 nucleotides while others are coded by as many as 6.  So some single nucleotide variants (SNVs) leave the amino acid coded for the same (these are the synonymous SNVs), while others change the amino acid (nonSynonymous SNVs), and possibly protein function.

Ask some one with sickle cell anemia how much trouble just one nonSynonymous SNV can cause — it’s only 1 amino acid out of 147.  Even worse, ask someone with cystic fibrosis where just one of 1,480 amino acids is missing.

Here’s the bad news.  In the population as a whole, they found 500,000 single nucleotide variants (SNVs).  If you’re still not sure what is meant by this, the 5 articles in should be all the background you need.

More than 400,000 of the variants were previously unknown.  Also more than 400,000 of them were found either in Africans or Europeans but not both.  If you divide 500,000 by 2,439 you get 205 variants per person.  However, SNVs are far more common than that, and each individual contains an average of 14,000.

Well, how many of the 500,000 or so SNVs they found are nonSynonymous? One would think about 1/3 statistically.  However, They found more than half 292,125/500,000 — nearly 60% — were nonSynonymous.

It get’s worse: 6,165 of the nonSynonymous variants are nonSense codons.  This means that the protein coded for by such a gene, terminates prematurely, meaning that it can terminate anywhere.  On average one would expect that half of these nonsense codons result in a protein of less than half the normal length.   This would very likely obliterate whatever function the protein had.

Obviously, they couldn’t test all 500,000 SNVs to see how they affected protein function (and we really only have a decent idea of what half our 20,000 or so proteins are doing).  They had to guess.  They came up with a figure of 2 – 4% of the 14,000 SNVs being functionally significant — That’s 280 – 560 significant mutations per individual.

Clearly, despite the horrible examples of cystic fibrosis and sickle cell anemia above, most of these can’t be doing very much, because these were normal people being studied.

There are all sorts of implications of this work.  One is the subject of a future post — how hard this diversity makes drug discovery.  Another reiterates the Tolstoy theme mentioned earlier about the genetic defects causing schizophrenia and autism — ““Happy families are all alike; every unhappy family is unhappy in its own way”.  Thus beginneth Anna Karenina.

For details please see  and

A third is that this shows that the 1000 fold expansion of the human population has pretty much obviated much natural selection eliminating these variants.  I’ll leave it to the geneticists to figure out what this means for the eventual survival of the species, as these mutants continue to accumulate.

The paper is fascinating, and sure to change our conception of what a ‘normal’ genome actually is.  Nonetheless, all they did was follow Yogi Berra’s dictum — “You can observe a lot by watching.”   It certainly wasn’t creative or ingenious in any sense.  Sometimes grunt work like this wins the day.

A research idea yours for the taking

Why would the gene for a protein contain a part which could form amyloid (the major component of the senile plaque of Alzheimer’s disease) and another part to prevent its formation. Therein lies a research idea, requiring no grant money, and free for you to pursue since I’ll be 80 this month and have no academic affiliation.

Bri2 (aka Integral TransMembrane protein 2B — ITM2B) is such a protein.  It is described in [ Proc. Natl. Acad. Sci. vol. 115 pp. E2752 – E2761 ’18 ]

As a former neurologist I was interested in the paper because two different mutations in the stop codon for Bri2 cause 2 familial forms of Alzheimer’s disease  Familial British Dementia (FBD) and Familial Danish Dementia (FDD).   So the mutated protein is longer at the carboxy terminal end.  And it is the extra amino acids which form the amyloid.

Lots of our proteins form amyloid when mutated, mutations in transthyretin cause familial amyloidotic polyneuropathy.  Amylin (Islet Amyloid Polypeptide — IAPP) is one of the most proficient amyloid formers.  Yet amylin is a protein found in the beta cell of the pancreas which releases insulin (actually in the same secretory granule containing insulin).

This is where Bri2 is thought to come in. It is also found in the pancreas.   Bri2 contains a 100 amino acid motif called BRICHOS  in its 266 amino acids which acts as a chaperone to prevent IAPP from forming amyloid (as it does in the pancreas of 90% of type II diabetics).

Even more interesting is the fact that the BRICHOS domain is found in 300 human genes, grouped into 12 distinct protein families.

Do these proteins also have segments which can form amyloid?  Are they like the amyloid in Bri2, in segments of the gene which can only be expressed if a stop codon is read through.  Nothing in the cell is perfect and how often readthrough occurs at stop codons isn’t known completely, but work is being done — Nucleic Acids Res. 2014 Aug 18; 42(14): 8928–8938.

I find it remarkable that the cause and the cure of a disease is found in the same protein.

Here’s the research proposal for you.  Look at the other 300 human genes containing the BRICHOS motif (itself just a beta sheet with alpha helices on either side) and see how many have sequences which can form amyloid.  There should be programs which predict the likelihood of an amino acid sequence forming amyloid.

It’s very hard to avoid teleology when thinking about cellular biochemistry and physiology.  It’s back to Aristotle where everything has a purpose and a design.  Clearly BRICHOS is being used for something or evolution/nature/natural selection/the creator would have long ago gotten rid of it.  Things that aren’t used tend to disappear in evolutionary time — witness the blind fish living in caves in Mexico that have essentially lost their eyes. The BRICHOS domain clearly hasn’t disappeared being present in over 1% of our proteins.

Suppose that many of the BRICHOS containing proteins have potential amyloid segments.  That would imply (to me at least) that the amyloid isn’t just junk that causes disease, but something with a cellular function. Finding out just what the function is would occupy several research groups for a long time.   This is also where you come in.  It may not pan out, but pathbreaking research is always a gamble when it isn’t stamp collecting.


Amyloid again, again . . .

Big pharma has spent (and lost) several fortunes trying to attack the amyloid deposits of Alzheimer’s.  But like my late med school classmate’s book — “Why God Won’t Go Away” ==, amyloid won’t go away either.   It’s a bit oblique but some 300 of our proteins contain a 100 amino acid stretch called BRICHOS.  Why? Because it acts as a chaperone protein preventing proteins with a tendency to form amyloid from aggregating into fibrils.   The amino acids form a beta sheet surrounded front and back by a single alpha helix.

[ Proc. Natl. Acad. Sci. vol. 115 pp. E2752 – E2761 ’18 ] Discusses Bri2 (aka Integral Transmembrane protein 2B (ITM2B), a 266 amino acid type II transmembrane protein. Bri2 contains a carboxy terminal domain Bri23 released by proteolytic processing between amino acids #243 #244 by furinlike proteases. Different missense mutations at the stop codon of Bri2 cause extended carboxy terminal peptides called  Abri or Adan to be released by the proteases. Abri produces Familial British Dementia (FBD) and Adan produces Familial Danish Dementia (FDD). Both are associated with amyloid deposition in blood vessels, and amyloid plaques throughout the brain along with neurofibrillary tangles.

What is fascinating (to me) is that the cause and cure are both present in the same molecule Bri2 also contains a BRICHOS domain.  This implies (to me) that possibly the segment possibly forming amyloid is being used by the cell in some other fashion.

Bri2 is found in the beta cell of the pancreas (produces insulin).  The beta cell also produces Islet Amyloid PolyPeptide (IAPP  aka amylin ) one of the most potent amyloid forming proteins known.  Nonetheless the pancreas makes tons of it, and like insulin, is secreted by the beta cell in response to elevated blood glucose.  The present work shows that Bri2 is what keeps IAPP from forming amyloid.  The BRICHOS segment (amino acids #130 – #231) is released from Bri2 by ADAM10 (you don’t want to know what the acronym stands for).

How many of the 300 or so human proteins containing the BRICHOS domain also have amyloid forming segments.  If they do, this implies that the amyloid forming segments are doing something physiologically useful.



Old paradigms die hard

A statement in a recent Nature editorial [ vol. 554 pp. 308 – 309 ’18 ] had me thinking that a real paradigm shift in our understanding of cancer was under way, but in fact it was an out of date paradigm that tripped up the editorialist.  Since breast cancer is likely to affect us individually or someone we know, it’s worth looking at this paper.

Ductal Carcinoma In Situ (DCIS) of the breast, is breast cancer confined to one of the ducts in the breast bringing milk to the nipple.  If it stayed there forever it would be harmless, like a benign mole on the skin. Unfortunately ‘up to’ 40% of DCIS invades the lining of the duct and the soft tissue of the breast becoming Invasive Ductal Carcinoma (IDC) where it is not harmless at all.  There is currently no way to tell which DCIS will stay quiet so everyone gets treated.

A heroic paper in cell (vol. 172 pp, 205 – 217 ’18 ) used the highest of high technology to study the question.  First they used Laser Capture Microdissection to separate a selected cell from its neighbors by tracing a laser beam around the cell.  Then they used laser catapulting in which energy from an ultraviolet laser propels the microdissected cell into a collection tube.  Then they performed exon sequencing on the collected cells (e.g. they sequenced the parts of the gene coding for protein), comparing cells which were DCIS from IDCs.  Some 1,293 cells from 10 patients were studied.

There was an average of 23 mutations/patient.  “The transition from DCIS to IDC was not associated with a notable increase in the number of mutations.”  “The authors’ main finding is the remarkable genetic similarity of a patient’s tumor cells in these two distinct states”


I thought mutations caused cancer and that the more you had the worse the cancer.  Not so in this paper. A paradigm shift indeed.

What’s wrong with this thinking?  Think a bit before reading further.

If you are old enough, you may remember statements that we were 98% chimps based on our genome (or at least what was known of it at the time).  This is because the sequence of the amino acids in our 20,000 or so proteins varies only by 2% from that of the chimp.

That proves it.  Except that it doesn’t.  Amazingly enough, the amount of all 3,200,000,000 positions of our genome coding for protein is under 2%.  So 98% of or genome does NOT code for protein.  It contains the code to determine when, for how long, and where each gene is made into messenger RNA which is then made into protein.

An analogy may help.

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.

On this point it would be very worthwhile to look beyond the genes mutated in both sets of tumors, sequencing their promotors and enhancers.  I think it would likely show profound differences.

No further posts for a while.  We’re going to visit a new grandson, 3 days old, whose parents apparently lack the creativity to name him.


Cytocapsular tubes

“Extraordinary claims require extraordinary evidence”  Carl Sagan.  That goes in spades for a recent PNAS article vol. 115 pp. E1137 – E1146 2018 —

Start by looking at the following 3 videos




Unfortunately, to get to them, it appears that you must be a PNAS subscriber, so I’ll tell you what they show.

First, some background. Cell culture usually involves putting them into a Petri dish, something inherently two dimensional, but most cells in our body live in a 3 dimensional environment. So this work implanted Human Mammary Epithelial Cells (HMECs) into a 3 dimensional matrix of Matrigel (an extracellular matrix surrogate secreted by mouse sarcoma cells, containing, laminin, nidogen, collagen and heparan sulfate proteoglycans) Matrigel also contains the growth factors Transforming Growth Factor Beta (TGFbeta) and Epidermal Growth Factor (EGF), both of which prevent differentiation and promote proliferation. The 3d Matrigel matrix is softer and spongier than the hard surface of a Petri dish.

The behavior of these cells in the Matrigel is completely different than that usually seen. In fact no one has ever seen anything like it before, which is why, if possible you must look at the 3 movies the paper supplies in the supplementary material (referenced above).

The cells move around, but nowhere to be seen are the lamellipodia or the filopodia seen in 2 dimensional cell culture.

In the first movie a small cell repeatedly generates and retracts multiple membranous protrusions called cytocapsues (some larger than the cell itself) which the cell sometimes enters.

The second has multiple cells within the tubes formed by the cytocapsules (cytocapsular tubes) migrating within them. The cells drag the tubes through the matrix, without breaking the tube or allowing another tube to merge with it.

If replicated, this work has bearing on embryology, normal organ function and cancer metastasis.

No one has ever seen anything like this. Why not? The authors say that ‘only when the polymerization, density and viscoelasticity of the Matrigel is tightly controlled are the tubes seen. Unlike secreted extracellular vesicles, cells get inside the cytocapsular tubes. The tubes themselves interconnect and form networks. The tubes degrade and decompose without cells inside them.

They note that polymerized actin (microfilaments) are present under the tube membranes.

Even though the membranes are mostly lipids, proteins are required, and eIF4E levels are elevated. Inhibiting it suppresses cytocapsular tube generation.

It’s worth repeating Sagan – “Extraordinary claims require extraordinary evidence” Stay tuned

It’s probably too good to be true

SR9009 and SR9011 are drugs which selectively kill cancer cells by an entirely new mechanism.  They mess with DNA but don’t mutate it. [ Nature vol. 553 pp. 351 – 355 ’18 ] has the details.

First a bit of background.  How do the classic hormones (estrogen, androgen, thyroid, adrenal steroids) do what they do?  Clearly they change the expression of many many genes as any post-pubertal woman will attest.  They bind to proteins called nuclear hormone receptors, changing their shape so they can bind to DNA and change gene expression.   We have 48 of them in our genome.  For a long time we didn’t know what the natural ligands of many actually were.  These were called orphan nuclear hormone receptors.  I’m not sure how many orphans are left.


SR9009 and SR9011 bind to REV-ERBalpha and REV-ERBbeta which are nuclear hormone receptors. They are agonists (e.g. they cause SR9009 and 11 to do what they do)  Their natural ligand is heme (which isn’t a hormone) and they are involved in the circadian clock.   However they also act as repressors of processes involved in tumorigenesis, including metabolism, proliferation and inflammation.

So the authors threw the agonists at a variety of tumor cells (brain cancer, leukaemia, breast cancer, colon cancer and melanoma) and watched them commit suicide (apoptosis).  They had no effect on normal cells !

How do they work?  There is only speculation at this point.  It is known that SR90xx’s inhibit autophagy, something cancer cells depend on for nourishment.  Normal cells only use autophagy under starvation conditions. They also repress several lipogenic enzymes (fatty acid synthase etc. etc) and cancer cells are said to be dependent on de novo lipogenesis (if they want to proliferate, they got to make a lot of membrane).

It’s almost too good to be true.  Stay tuned.

So much work, so little progress

Two years ago, I found going to a memorial service for a friend and classmate who died of Alzheimer’s curiously uplifting  (see the link at the end). The disease is far from ignored. A monster review in Neuron vol. 97 pp. 32 – 58 ’18 —  contained references to over 400 research articles half of them published since January 2013.

Still I found it quite depressing.  Tons of work and tons findings, and yet no coherent path to the cause (or causes); something absolutely necessary for a rational treatment, unless we somehow stumble into a therapy.

In a way it’s like cancer.  The cancer genome atlas intensively studied the genome of various cancers, looking for ‘the’ or ‘the set of’ causative mutations.  They found way too much.  The average colon and breast cancer had an average of 93 mutated genes, of which 11 were thought to be cancer promoting.  Not only that, but the same 11 were not consistent from tumor to tumor.

So it is with this epic review.  Which of the myriad findings described are causative of the disease and which are responses of the nervous system to the ’cause’ (or causes).

In the review the authors posit that Alzheimer’s disease is due to failure of ‘homeostatic systems’ that maintain a ‘set point’ of neuronal firing.  Unfortunately what is measured to determine the set point isn’t known. This seems to be an example of redefining a question into an answer.  Clearly if you juice up neuronal firing rates by stimulation they come back down, or if you inhibit them, they come back up.  So you can operationally define set point without defining it mechanistically.   It must be due to some sort of feedback on whatever it is that is sensing ‘the set point’ , but what is it that is being sensed?

The following is from an earlier post but is quite relevant to homeostasis and set points.

The whole notion of control in the presence of feedback is far from clear cut.  Here’s the story of the first inklings of feedback in endocrinology.  I watched it happen.

Endocrinology was pretty simple in med school back in the 60s. All the target endocrine glands (ovary, adrenal, thyroid, etc.) were controlled by the pituitary; a gland about the size of a marble sitting an inch or so directly behind the bridge of your nose. The pituitary released a variety of hormones into the blood (one or more for each target gland) telling the target glands to secrete, and secrete they did. That’s why the pituitary was called the master gland back then.  The master gland ruled.

Things became a bit more complicated when it was found that a small (4 grams or so out of 1500) part of the brain called the hypothalamus sitting just above the pituitary was really in control, telling the pituitary what and when to secrete. Subsequently it was found that the hormones secreted by the target glands (thyroid, ovary, etc.) were getting into the hypothalamus and altering its effects on the pituitary. Estrogen is one example. Any notion of simple control vanished into an ambiguous miasma of setpoints, influences and equilibria. Goodbye linearity and simple notions of causation.

As soon as feedback (or simultaneous influence) enters the picture it becomes like the three body problem in physics, where 3 objects influence each other’s motion at the same time by the gravitational force. As John Gribbin (former science writer at Natureand now prolific author) said in his book ‘Deep Simplicity’, “It’s important to appreciate, though, that the lack of solutions to the three-body problem is not caused by our human deficiencies as mathematicians; it is built into the laws of mathematics.” The physics problem is actually much easier than endocrinology, because we know the exact strength and form of the gravitational force.

Body Mass Index (BMI): mine, yours, and Trump’s

The ‘investigative press’ is quite concerned about President Trump’s height.  If he is 6 foot 3 and 239 pounds, he is overweight but not obese, if he is 6 foot 2 he is obese.  All this is a matter of definition by a single number — the body mass index (BMI).

So let’s all calm down and find out what ours actually is.  There is a website which will do it for you. Here’s the link — — have at it. You can use pounds feet and inches as well as kilograms and meters.

The current definition of obese is a BMI over 30, overweight between 25 and 30, and normal weight under 25.

Who cares?  Well, you should if BMI’s correlate with mortality and they do.

A great paper 5 years ago by Katherine Flegal analyzed nearly 3 million people with 270, 000 deaths reported in a variety of studies —

The problem is that the lowest mortality didn’t occur in those with normal weight (BMI < 25) but was lowest in the overweight group — not by much (6%), and second lowest in the mildly obese (BMI 30 – 35), over 35 it was 20% higher.

Naturally this did not sit well people who'd staked their research careers on telling people to lose weight.  There is a truly hilarious article describing a meeting at Harvard discussing the paper.  Here's a link   It's worth reading in its entirety, particularly for a graph it contains.

One study by a Harvard guy removed 900,000 people from the study leading to the following great comment — “It's hard to argue with data,” says Robert Eckel, an endocrinologist at University of Colorado in Denver. “We're scientists. We pay attention to data, we don't try to un-explain them.”

The Nature paper contains a terrific graph from the following paper — Source: Childers, D.K. & Allison, D.B. Int. J. obesity 34, 1231–1238 (2010).

Look at it carefully.  Mortality vs. BMI is plotted in several curves one for people between 20 – 30, one for 30 – 40, etc. etc.  Under 50 the best BMI to have in terms of mortality is under 25, but over 50 it rises, so that at 70 the low point is around 27 (in the overweight range) and not far from Trump at 6' 3" (29.9) or even at 6' 2" (30.7).

In a way this data fits with the fact that for a long time Americans were getting fatter and fatter, yet living longer and longer.  For details see —

Why should the best BMI for you to have rise after age 50?  I've not seen this explanation anywhere else.

The BMI is far from perfect, but to calculate it all you need are two simple measurements that anyone can make — height and weight. It doesn't rely on what people remember.  However the calculation is not a simple ratio of weight divided by height but weight divided by height squared.

People lose height as they age, so the BMI is quite sensitive to it (remember the denominator has height squared).  Well as a high school basketball player my height was 6′ 1”+, now (at age 75) its 6’0″ (God knows what it is several years later). So even with constant weight my BMI goes up.

Well it’s time to do the calculation to see what a fairly common shrinkage from 73.5 inches to 72 would to to the BMI (at a constant weight). Surprisingly it is not trivial — (72/73.5) * (72/73.5) = .9596. So the divisor is 4% less meaning the BMI is 4% more, which is almost exactly what the low point on the curve does with each passing decade after 50 ! ! ! This might even be an original observation, and it would explain a lot.

As long as I’m on the subject of the ‘investigative press’  here is how they glossed over Hillary’s fainting spell during the presidential campaign, calling it a stumble.  Remarkable discipline that they all used the same word.  So take their worries about Trump’s weight with a grain of salt.

“Like the Michigan poll I started out with, most of the latest campaign surveys were carried out during last weekend and earlier this week, when the news was dominated by Clinton’s stumble outside Ground Zero, which prompted the campaign to reveal that she had pneumonia.” John Cassiday New Yorker

“For Orient—and the many media organizations that have recently been circulating her work—Clinton’s stumble looked like proof that they were right.” Wired —

The Boston Globe had a similar echo of the meme that all Hillary did when leaving the 9/11 ceremony was stumble.

As Richard Pryor famously said when his wife caught him with another woman. He denies anything is going on, and asks his wife, “Who you gonna believe, me or your lying eyes?”

See for yourself —