Correctly taken to task by two readers and some breaking news

I should have amended the previous post to say I mistrust unverified models.  Here are two comments

#1 Andyextance

• “Leaving aside the questions of the reliability of models in different subjects, and whether all of your six reasons truly relate to models, I have one core question: Without models, how can we have any idea about what the future might hold? Models may not always be right – but as long as they have some level of predictive skill they can often at least be a guide.”

  Absolutely correct — it’s all about prediction, not plausibility.

#2 Former Bell Labs denizen

“And yet you board a commercial airliner without hesitation, freely trusting your life to the models of aerodynamics, materials science, control system theory, electronics, etc. that were used in designing the aircraft. Similar comments apply to entering a modern skyscraper, or even pushing the brake pedal on your automobile.

Perhaps what you are really saying is that you don’t trust models until their correctness is demonstrated by experience; after that, you trust them. Hey, nothing to disagree with there.”

Correct again

Breaking news

This just in — too late for yesterday’s post — the climate models have overestimated the amount of warming to be expected this century — the source  is an article  in

Nature Geoscience (2017) doi:10.1038/ngeo2973 — behind a paywall — but here’s the abstract

In the early twenty-first century, satellite-derived tropospheric warming trends were generally smaller than trends estimated from a large multi-model ensemble. Because observations and coupled model simulations do not have the same phasing of natural internal variability, such decadal differences in simulated and observed warming rates invariably occur. Here we analyse global-mean tropospheric temperatures from satellites and climate model simulations to examine whether warming rate differences over the satellite era can be explained by internal climate variability alone. We find that in the last two decades of the twentieth century, differences between modelled and observed tropospheric temperature trends are broadly consistent with internal variability. Over most of the early twenty-first century, however, model tropospheric warming is substantially larger than observed; warming rate differences are generally outside the range of trends arising from internal variability. The probability that multi-decadal internal variability fully explains the asymmetry between the late twentieth and early twenty-first century results is low (between zero and about 9%). It is also unlikely that this asymmetry is due to the combined effects of internal variability and a model error in climate sensitivity. We conclude that model overestimation of tropospheric warming in the early twenty-first century is partly due to systematic deficiencies in some of the post-2000 external forcings used in the model simulations.

 

Unfortunately the abstract doesn’t quantify generally smaller.

 

Models whose predictions are falsified by data are not to be trusted.

 

Yet another reason Trump was correct to get the US out of the Paris accords— in addition to the reasons he used — no method of verification, no penalties for failure to reduce CO2 etc. etc.  The US would tie itself in economic knots trying to live up to it, while other countries would emit pious goals for reduction and do very little. 

In addition, \ I find it rather intriguing that the article was not published in Nature Climate Change   –,http://www.nature.com/nclimate/index.html — which would seem to be the appropriate place.  Perhaps it’s just too painful for them.

I mistrust models.

I have no special mistrust of climate models, I mistrust all models of complex systems.  Here are six reasons why.

Reason #1:  My cousin runs an advisory service for institutional investors (hedge funds, retirement funds, stock market funds etc. etc.)  Here is the beginning of his latest post 16 June ’17

”

There were 3 great reads yesterday. First was Neil Irwin’s article in the NY Times “Janet Yellen, the Fed and the Case of the Missing Inflation.”  He points out that Yellen is a labor market scholar who anticipated the sharp decline in the unemployment rate. However the models on which the Fed has relied anticipate higher levels of inflation. Yet every inflation measure that the Fed uses has fallen well short of the Fed’s 2% stability rate. If they continue raising short-term rates in the face of low inflation, then “real” rates could restrain future economic growth. Second was Greg Ip’s article “Lousy Raise? It Might Not Get Better.” Greg makes the point that tight labor markets are a global phenomenon in many industrialized countries, yet wage inflation remains muted. Writes Greg “If a labor market this tight can’t generate better pay, quite possibly it never will in Germany & Japan.” Third was an article by Glenn Hubbard (Dean of Columbia Business School & former chairman of the Council of Economic Advisors under George W. Bush). His Wall Street Journal op-ed was titled “How to Keep the Fed from Following its Models off a Cliff.”  Hubbard suggests that Fed officials should interact more with market participants and business people. And Fed governors should be selected because of their varied life experiences, and they should encourage a healthy skepticism of prevailing economic models.

Serious money was spent developing these models.  Do you think that climate is in some way simpler than the US economy, so that they are more likely to be accurate?  I do not.

Reason #2: Americans are getting fatter yet living longer, contradicting the model that being mildly overweight is bad for you.  It is far too long to go into so here’s the link — https://luysii.wordpress.com/2013/05/30/something-is-wrong-with-the-model-take-2/.

The first part is particularly fascinating, in that data showed that overweight (not obese) people tended to live longer.  The article describes how people who had spent their research careers telling the public that being overweight was bad, tried to discount the data. The best quote in the article is the following ““We’re scientists. We pay attention to data, we don’t try to un-explain them.”,

Reason #3: The economic predictions of the Congressional Budget Office on just about anything –inflation, gross national product, economic growth, the deficit — are consistently wrong — http://www.ncpa.org/sub/dpd/?Article_ID=21516.

Reason #4:  Animal models of stroke:  There were at least 60, in which some therapy or other was of benefit.  None of them worked in people. It got so bad I stopped reading the literature about it.  We still have no useful treatment for garden variety strokes

Reason #5:  The Club of Rome,  — dire prediction based on a computer model which got a lot of play in the 70s.  For details see — https://luysii.wordpress.com/2017/06/01/a-bit-of-history/.  The post also has a lot about “The Population Bomb” and its failed predictions and also a review of a book about “The Bet” between Paul Ehrlich and Simon

Reason #6: Live by the model, die by the model. A fascinating book “Shattered” about the Hillary Clinton campaign, explains why the campaign did no polling in the final 3 weeks of the campaign. The man running the ‘data analytics’ (translation: model) Robby Mook, thought the analytics were better and more accurate (p. 367).

 

The best laid plans of mice and men

I sent a copy of the previous post (reprinted below) about an idea to diagnose and treat chronic fatigue syndrome to Dr. Norman Sharpless, the author of the Cell review on cellular senescence.  He thought the idea was “great”; and, even better, he ran the lab which did the test I wanted to try.  I also sent a copy to a patient group.  “Solve ME/CFS Initiative”, and they want to use the post on their website.

Sharpless noted that the problem with ideas like this is accumulating patients, something the patient group could probably provide.  So all went well until 8 days ago when Dr. Sharpless was named to be the head of the National Cancer Institute, with its 4.5 billion dollar  budget by President Trump.  Being a full prof at the University of North Carolina Medical School, he would have been the ideal individual to run the study (or find someone to do it), but he now has far bigger fish to fry.

After I wrote to congratulate him, he wrote back reiterating that the idea was good, but he said he had to sever all connections with the lab he founded due to conflict of interest considerations.  He did give me the name of someone to contact there, which is where the matter stands presently.

Since the idea is based on the correlation between the amount of fatigue after chemotherapy with the level of a white cell protein (p16^INK4a), he would have had no problem accumulating chemotherapy patients as head of NCI, but again the spectre of conflict of interest rears its ugly head.  Repeating the chemotherapy study to make sure the results are in fact real is the first order of business.

So there you have a research idea, endorsed by the new head of the NCI.  I am a retired neurologist, who no longer has a license to practice medicine (but who doesn’t need a license to think).

If you’re an academic out there, looking for something to do, write up a grant proposal.  The current treatments do help people live with chronic fatigue syndrome, but they are in no sense treatments of the underlying problem.

Here is the original post

How to (possibly) diagnose and treat chronic fatigue syndrome (myalgic encephalomyelitis)

As a neurologist I saw a lot of people who were chronically tired and fatigued, because neurologists deal with muscle weakness and diseases like myasthenia gravis which are associated with fatigue.  Once I ruled out neuromuscular disease as a cause, I had nothing to offer then (nor did medicine).  Some were undoubtedly neurotic, but there was little question in my mind that some of them had something wrong that medicine just hadn’t figured out.  Not it hasn’t been trying.

Infections of almost any sort are associated with fatigue, probably because components of the inflammatory response cause it.  Anyone who’s gone through mononucleosis knows this.    The long search for an infectious cause of chronic fatigue syndrome (CFS) has had its ups and downs — particularly downs — see https://luysii.wordpress.com/2011/03/25/evil-scientists-create-virus-causing-chronic-fatigue-syndrome-in-lab/

At worst many people with these symptoms are written off as crazy; at best, depressed  and given antidepressants.  The fact that many of those given antidepressants feel better is far from conclusive, since most patients with chronic illnesses are somewhat depressed.

Even if we didn’t have a treatment, just having a test which separated sufferers from normal people would at least be of some psychological help, by telling them that they weren’t nuts.

Two recent papers may actually have the answer. Although neither paper dealt with chronic fatigue syndrome directly, and I can find no studies in the literature linking what I’m about to describe to CFS they at least imply that there could be a diagnostic test for CFS, and a possible treatment as well.

Because I expect that many people with minimal biological background will be reading this, I’ll start by describing the basic biology of cellular senescence and death

Background:  Most cells in our bodies are destined to die long before we do. Neurons are the longest lasting (essentially as long as we do).  The lining of the intestines is renewed weekly.  No circulating blood cell lasts more than half a year.

Cells die in a variety of ways.  Some are killed (by infections, heat, toxins).  This is called necrosis. Others voluntarily commit suicide (this is called apoptosis).   Sometimes a cell under stress undergoes cellular senescence, a state in which it doesn’t die, but doesn’t reproduce either.  Such cells have a variety of biochemical characteristics — they are resistant to apoptosis, they express molecules which prevent them from proliferating and most importantly, they secrete proinflammatory molecules (this is called the Senescence Associated Secretory Phenotype — SASP).

At first the very existence of the senescent state was questioned, but exist it does.  What is it good for?  Theories abound, one being that mutation is one cause of stress, and stopping mutated cells from proliferating prevents cancer. However, senescent cells are found during fetal life; and they are almost certainly important in wound healing.  They are known to accumulate the older you get and some think they cause aging.

Many stresses induce cellular senescence.  The one of interest to us is chemotherapy for cancer, something obviously good as a cancer cell turned senescent has stopped proliferating.   If you know anyone who has undergone chemotherapy, you know that fatigue is almost invariable.

One biochemical characteristic of the senescent cell is increased levels of a protein called p16^INK4a, which helps stop cellular proliferation.  While p16^INK4a can easily be measured in tissue biopsies, tissue biopsies are inherently not easy. Fortunately it can also be measured in circulating blood cells.

The following study — Cancer Discov. vol. 7 pp. 165 – 176 ’17 looked at 89 women with breast cancer undergoing chemotherapy. They correlated the amount of fatigue experienced with the levels of p16^INK4a in a type of circulating white blood cell (T lymphocyte).  There was a 44% incidence of fatigue in the highest quartile of  p16^INK4a levels, vs. a 5% incidence of fatigue in the lowest. The cited paper didn’t mention CFS nor did the highly technical but excellent review on which much of the above is based [ Cell vol. 169 pp. 1000 -1011 ’17 ]

But it is definitely time to measure p16^INK4a levels in patients with chronic fatigue and compare them to people without it.  This may be the definitive diagnostic test, if people with CFS show higher levels of p16^INK4a.

If this turns out to be the case, then there is a logical therapy for chronic fatigue syndrome.  As mentioned above, senescent cells are resistant to apoptosis (voluntary suicide).  What stops these cells from suicide? Naturally occurring cellular suicide inhibitors (with names like BCL2, BCL-XL, BCL-W) do so .  Drugs called sensolytics already exist to target the inhibitors causing senescent cells to commit suicide.

So if excessive senescent cells are the cause of CFS, then killing them should make things better. Sensolytics do exist but there are problems; one couldn’t be used because of side effects.  Others do exist (one such is Venetoclax) and have been approved by the FDA for leukemia — but it isn’t as potent .

So there is a potentially both a diagnostic test and a treatment for CFS.

The initial experiment should be fairly easy for research to do — just corral some CSF patients and controls and run a test for p16^INK4a levels in their blood cells. Also easy on the patients as only a blood draw is involved.

This, in itself, would be great, but there is far more to think about.

If CFS patients have too many senescent cells, getting rid of them — although (hopefully) symptomatically beneficial — will not get rid of what caused the senescent cells to accumulate in the first place. In addition, getting rid of all of them at once would probably cause huge problems causing something similar to the tumor lysis syndrome – https://en.wikipedia.org/wiki/Tumor_lysis_syndrome.

But these are problems CFS patients and

How to (possibly) diagnose and treat chronic fatigue syndrome (myalgic encephalomyelitis)

As a neurologist I saw a lot of people who were chronically tired and fatigued, because neurologists deal with muscle weakness and diseases like myasthenia gravis which are associated with fatigue.  Once I ruled out neuromuscular disease as a cause, I had nothing to offer then (nor did medicine).  Some were undoubtedly neurotic, but there was little question in my mind that some of them had something wrong that medicine just hadn’t figured out.  Not it hasn’t been trying.

Infections of almost any sort are associated with fatigue, probably because components of the inflammatory response cause it.  Anyone who’s gone through mononucleosis knows this.    The long search for an infectious cause of chronic fatigue syndrome (CFS) has had its ups and downs — particularly downs — see https://luysii.wordpress.com/2011/03/25/evil-scientists-create-virus-causing-chronic-fatigue-syndrome-in-lab/

At worst many people with these symptoms are written off as crazy; at best, depressed  and given antidepressants.  The fact that many of those given antidepressants feel better is far from conclusive, since most patients with chronic illnesses are somewhat depressed.

Even if we didn’t have a treatment, just having a test which separated sufferers from normal people would at least be of some psychological help, by telling them that they weren’t nuts.

Two recent papers may actually have the answer. Although neither paper dealt with chronic fatigue syndrome directly, and I can find no studies in the literature linking what I’m about to describe to CFS they at least imply that there could be a diagnostic test for CFS, and a possible treatment as well.

Because I expect that many people with minimal biological background will be reading this, I’ll start by describing the basic biology of cellular senescence and death

Background:  Most cells in our bodies are destined to die long before we do. Neurons are the longest lasting (essentially as long as we do).  The lining of the intestines is renewed weekly.  No circulating blood cell lasts more than half a year.

Cells die in a variety of ways.  Some are killed (by infections, heat, toxins).  This is called necrosis. Others voluntarily commit suicide (this is called apoptosis).   Sometimes a cell under stress undergoes cellular senescence, a state in which it doesn’t die, but doesn’t reproduce either.  Such cells have a variety of biochemical characteristics — they are resistant to apoptosis, they express molecules which prevent them from proliferating and most importantly, they secrete proinflammatory molecules (this is called the Senescence Associated Secretory Phenotype — SASP).

At first the very existence of the senescent state was questioned, but exist it does.  What is it good for?  Theories abound, one being that mutation is one cause of stress, and stopping mutated cells from proliferating prevents cancer. However, senescent cells are found during fetal life; and they are almost certainly important in wound healing.  They are known to accumulate the older you get and some think they cause aging.

Many stresses induce cellular senescence.  The one of interest to us is chemotherapy for cancer, something obviously good as a cancer cell turned senescent has stopped proliferating.   If you know anyone who has undergone chemotherapy, you know that fatigue is almost invariable.

One biochemical characteristic of the senescent cell is increased levels of a protein called p16^INK4a, which helps stop cellular proliferation.  While p16^INK4a can easily be measured in tissue biopsies, tissue biopsies are inherently not easy. Fortunately it can also be measured in circulating blood cells.

The following study — Cancer Discov. vol. 7 pp. 165 – 176 ’17 looked at 89 women with breast cancer undergoing chemotherapy. They correlated the amount of fatigue experienced with the levels of p16^INK4a in a type of circulating white blood cell (T lymphocyte).  There was a 44% incidence of fatigue in the highest quartile of  p16^INK4a levels, vs. a 5% incidence of fatigue in the lowest. The cited paper didn’t mention CFS nor did the highly technical but excellent review on which much of the above is based [ Cell vol. 169 pp. 1000 -1011 ’17 ]

But it is definitely time to measure p16^INK4a levels in patients with chronic fatigue and compare them to people without it.  This may be the definitive diagnostic test, if people with CFS show higher levels of p16^INK4a.

If this turns out to be the case, then there is a logical therapy for chronic fatigue syndrome.  As mentioned above, senescent cells are resistant to apoptosis (voluntary suicide).  What stops these cells from suicide? Naturally occurring cellular suicide inhibitors (with names like BCL2, BCL-XL, BCL-W) do so .  Drugs called sensolytics already exist to target the inhibitors causing senescent cells to commit suicide.

So if excessive senescent cells are the cause of CFS, then killing them should make things better. Sensolytics do exist but there are problems; one couldn’t be used because of side effects.  Others do exist (one such is Venetoclax) and have been approved by the FDA for leukemia — but it isn’t as potent .

So there is a potentially both a diagnostic test and a treatment for CFS.

The initial experiment should be fairly easy for research to do — just corral some CSF patients and controls and run a test for p16^INK4a levels in their blood cells. Also easy on the patients as only a blood draw is involved.

This, in itself, would be great, but there is far more to think about. 

If CFS patients have too many senescent cells, getting rid of them — although (hopefully) symptomatically beneficial — will not get rid of what caused the senescent cells to accumulate in the first place. In addition, getting rid of all of them at once would probably cause huge problems causing something similar to the tumor lysis syndrome – https://en.wikipedia.org/wiki/Tumor_lysis_syndrome.

But these are problems CFS patients and their physicians would love to have.

They want to be left alone with their own kind

From the statement of Hon. Thomas G. Abernethy, First District of Mississippi House of Representatitves on H. R. 140 before the House Committee of the Judiciary 1957 concerning HR 140 and other Civil Rights Legislation.

“Negroes naturally prefer the association and society of their own kind. .. They know the purpose of this legislation is not just to give them the vote, nor to give them better schools. They know that the ultimate and longtime objective of its sponsors is to force the Negroes and white people to mix in all the affairs of life. . . This the respectable negroes do not want. They want to be left alone with their own kind. . . Even in the small towns and villages they segretate themselves because they like it that way. It is the natural way of life; everything after its own kind.. . ”

Well, silly me. In 1960, there I was as a Princeton undergraduate picketing the local Woolworth’s on Nassau street because of their segregated southern lunch counters https://books.google.com/books?id=nxJbAAAAYAAJ&pg=RA6-PA9&lpg=RA6-PA9&dq=princeton+undergraduates+picket+woolworth&source=bl&ots=Q0s9mKDNqS&sig=r97hAklMbv0QwjwXssVzl2EwgQY&hl=en&sa=X&ved=0ahUKEwjn4ubhy6TUAhVC6YMKHV5nAdEQ6AEIODAD#v=onepage&q=princeton%20undergraduates%20picket%20woolworth&f=false

Little did I know that advanced sociological thinking by blacks 57 years later would confirm Abernethy’s thoughts — https://www.bostonglobe.com/metro/2017/05/08/black-grad-students-harvard-hold-own-commencement-ceremony/6tGHbUjyz8vLvDNVZwzidL/story.html.

Rumor has it that the appropriately named Harvard Board of Overseers — http://www.harvard.edu/about-harvard/harvards-leadership/board-overseers — will further accommodate them by planting cotton and watermelons in Harvard yard so they can feel more at home ‘among their own kind’.

If you are concerned that I’m a bigot or anti-black in any way I suggest that you look at the following earlier post — https://luysii.wordpress.com/2012/05/22/warren-harvard-and-penn-sanctimony-hypocrisy-and-fraud/

A bit of history

I’ve been reading Nature since I’ve been able to afford a subscription, e.g. since about 1972. To put their undoubted coming hysteria about Trump’s withdrawal from the Paris agreement into perspective, consider the fact that they bought the arguments of the Club of Rome, hook line and sinker. The Wikipedia article is quite sanitized, but here’s a direct quote from the jacket flap of the club’s book “The Limits to Growth” which came out in 1972.

“Will this be the world that your grandchildren with thank you for? A world where industrial production has sunk to zero. Where population has suffered a catastrophic decline. Where the air, sea and land are polluted beyond redemption. Where civilization is a distant memory. This is the world that the computer forecasts. What is even more alarming, the collapse will not come gradually, but with awsome suddenness, with no way of stopping it”

Well, it’s 45 years later and their grandchildren have seen no such thing. Nature’s online available archives go back to 1975, but I’ve been unable to find a link to one of their articles. If anyone out there has found one, post a comment.

When we were down in New Haven, I picked up a book by a Yale Prof, Paul Sabin called “The Bet” concerning the intellectual conflict between Paul Ehrlich — he of the population bomb and Julian Simon. Ehrlich said we’d run out of just about everything shortly (presumably because of too many people), so economist Simon bet him that we wouldn’t. The intellectual war began in earnest in the 80’s and dragged on for a decade or so.

I recommend the book. In it you will find John Holdren, Obama’s ‘science’ advisor, also a devout malthusian, although with a degree in physics.

Perhaps Nature has it right this time, and that the models of warming which failed to predict the climate stasis of 17 years duration (the term pause gives away the game implying that temperature will continue to increase) are a reliable guide to the future.

Even if Nature is right, the Paris Agreement was terrible, no verification, no penalties for missing targets etc. etc. A massive expansion of governmental control and clamps on economic expansion, for minimal benefit.

So relax. Protest if you wish, it’s a cheap display of virtue which costs you nothing, even though you’re quite willing to fight global warming down to the last coal miner.

Logically correct operationally horrible

A med school classmate who graduated from the University of Chicago was fond of saying — that’s how it works in practice, but how does it work in theory?

Exactly the opposite happened when I had to do some programming. It shows the exact difference between computer science and mathematics.

Basically I had to read a large textEdit file (minimum 2 megaBytes, Maximum 8) into a Filemaker Table and do something similar 15 times. The files ranged in size from 20,000 to 70,000 lines (each delimited by a carriage return). They needed to be broken up into 1000 records.

Each record began with “Begin Card Xnnnn” and ended with “End Card Xnnn” so it was easy to see where each of the 1000 cards began and ended. So a program was written to
l. look for “Begin Card Xnnn”
2. count the number of lines until “End Card Xnnn” was found
3. Open a new record in Filemaker
4. Put the data from Card Xnnnn into a field of the record
5. Repeat 1000 times.

Before I started, I checked the program out with smaller sized Files with 1, 5, 10, 50, 100, 200, 500 Cards.

The first program used a variable called “lineCounter” which just pointed to the line being processed. As each line was read, the pointer was advanced.

It was clear that the runTime was seriously nonLinear 10 cards took more than twice the time that 5 cards did. Even worse the more cards in the file the worse things got, so that 1000 cards took over an hour.

Although the logic of using an advancing pointer to select and retrieve lines was impeccable, the implementation was not.

You’ve really not been given enough information to figure out what went wrong but give it a shot before reading further.

I was thinking of the LineCounter variable as a memory pointer (which it was), similar to memory pointers in C.

But it wasn’t — to get to line 25,342, the high level command in Filemaker — MiddleValues (Text; Starting_Line ; Number_of_Lines_to_get) had to start at the beginning of the file, examine each character for a character return, keep a running count of character returns, and stop after 25,342 lines had been counted.

So what happened to run time?

Assume the LinePointer had to read each line (not exactly true, but close enough).

Given n lines in the file — that’s the sum of 1 to n — which turns out to be n^2 + n. (Derivation at the end)

So when there were 2*n lines in the file, the runtime went up by over 4 times (exactly 2^2 * n^2 + 2n)

So run times scaled in a polynomial fashion k * n lines would scale as k^2 * n^2 + k * n

At least it wasn’t exponential time which would have scaled as 2^k

How to solve the problem ?

Think about it before reading further

The trick was to start at the first lines in the file, get one card and then throw those lines away, starting over at the top each time. The speed up was impressive.

It really shows the difference between math and computer science. Both use logic, but computer science uses more

Derivation of sum of 1 to n.

Consider a square n little squares on a side. The total number of squares is n^2. Throw away the diagonal giving n^2 – n. The number of squares left is twice the sum of 1 to n – 1. So divide n^2 – n by 2, and add back n giving you n^2 + n

Entangled points

The terms Limit point, Cluster point, Accumulation point don’t really match the concept point set topology is trying to capture.

As usual, the motivation for any topological concept (including this one) lies in the real numbers.

1 is a limit point of the open interval (0, 1) of real numbers. Any open interval containing 1 also contains elements of (0, 1). 1 is entangled with the set (0, 1) given the usual topology of the real line.

What is the usual topology of the real line? (E.g. how are its open sets defined) It’s the set of open intervals) and their infinite unions and their finite intersection.

In this topology no open set can separate 1 from the set ( 0, 1) — e.g. they are entangled.

So call 1 an entangled point.This way of thinking allows you to think of open sets as separators of points from sets.

Hausdorff thought this way, when he described the separation axioms (TrennungsAxioms) describing points and sets that open sets could and could not separate.

The most useful collection of open sets satisfy Trennungsaxiom #2 — giving a Hausdorff topological space. There are enough of them so that every two distinct points are contained in two distinct disjoint open sets.

Thinking of limit points as entangled points gives you a more coherent way to think of continuous functions between topological spaces. They never separate a set and any of its entangled points in the domain when they map them to the target space. At least to me, this is far more satisfactory (and actually equivalent) to continuity than the usual definition; the inverse of an open set in the target space is an open set in the domain.

Clarity of thought and ease of implementation are two very different things. It is much easier to prove/disprove that a function is continuous using the usual definition than using the preservation of entangled points.

Organic chemistry could certainly use some better nomenclature. Why not call an SN1 reaction (Substitution Nucleophilic 1) SN-pancake — as the 4 carbons left after the bond is broken form a plane. Even better SN2 should be called SN-umbrella, as it is exactly like an umbrella turning inside out in the wind.

The Leakathon

My late father-in-law did financial forensics for the SEC and on loan to Treasury. His work involved high-profile cases and he put many people in jail. He never, ever, discussed a case he was working on with his wife, my wife and me. He retired in 1972 just Watergate broke. Sam Dash chief counsel for the Senate Watergate Committee asked him to come out of retirement and trace the Watergate money, saying it would only be a few weeks work, but he wisely refused.

This brings us to “The law enforcement investigation into possible coordination between Russia and the Trump campaign has identified a current White House Official as a signifiant person of interest, showing that the probe is reaching into the highest levels of government, according to people familiar with the matter.” as reported in the Washington Post 20 May.

This sort of thing is probably criminal and certainly disgusting. Presumably someone in the FBI is doing the leaking. Hopefully Mueller will put a stop to this.

What do you think the odds are, that collusion between Trump (or is campaign) and the Russians will actually be found? My guess is that they are quite low because, despite 7 months of leaks absolutely nothing substantive has been emitted. If the leakers had anything serious, we’d have heard of it by now.

I’ve never bought the idea that second hand smoke was very dangerous, yet we have breathless reports of second hand hearsay — Someone reading Comey’s notes (presumably not the man himself) about something he interpreted Trump to say. I don’t think hearsay evidence is admissible in a court of law.

I never really believed in the Deep State before, but it seems to be in full cry now — https://en.wikipedia.org/wiki/Deep_state_in_the_United_States

What is docosahexenoic acid and why should you care?

Why should drug chemists care about docosahexenoic acid — it’s a fairly trivial organic structure as these things go – a 22 carbon straight chain carboxylic acid with 6 double bonds — https://en.wikipedia.org/wiki/Docosahexaenoic_acid. However the structure is decidedly non-random (see later)

Docosahexenoic acid turns out to be crucial for the function of the blood brain barrier (BBB), something that makes it very difficult to get drugs into the brain. Years of work have shown that the only drugs able to get through the BBB are small lipid soluble molecules of mass under 400 kiloDaltons with fewer than 9 hydrogen bonds. Certainly not a large group of drugs. The more we know about the BBB, the more likely we’ll be able to figure out something to circumvent it.

The BBB was known to exist more than 100 years ago. Ehrlich found that dyes injected into the circulation were rapidly taken up by all organs except the brain. His student E. Goldmann found that dye injected into the CSF stained the brain but not other organs.

The barrier has at least two components — (1) a very tight seal between the cells lining brain blood vessels (e.g. the endothelium) — see the end of the post — (2)very low transfer across the endothelial cell from the vessel lumen. The latter is called transcytosis and involves formation of small vesicles at the lumenal surface of the endothelium, migration across the endothelial cell with release of vesicle content on the other side.

In general there are two mechanisms of transcytosis — clathrin coated pits, and caveolae. Brain endothelium shows very low rates of transcytosis. There aren’t any coated pits (no explanation I can find) and the rate of caveolar transcytosis is very low.

Dococsahexaenoic acid is the reason for the low rate of caveolar transcytosis. Here is why.

[ Nature vol. 509 pp. 432 – 433, 503 – 506, 507 – 511 ’14 Neuron vol. 82 pp. 728 – 730 ’14 ] An orphan transporter, MFSD2a (Major Facilitator Superfamily Domain containing 2a) is selectively expressed in the BBB endothelium. It is REQUIRED for formation and maintenance of BBB integrity. Animals lacking MFSD2a show uninhibited bulk transcytosis across the endothelium. The animals show no obvious defects in the junctions between the endothelial cells. Pericytes (cells in the brain layer after the endothelium) are important in keeping the levels of MFSD2a at normal levels as animals lacking them show the same defects in the BBB as those lacking MFSD2a. Even though knockouts don’t have much of a BBB, they have normal patterning of vascular networks.

MFSD2a is the major transporter of docohexaenoic acid (DHA), an omega3 fatty acid (more later). DHA isn’t made in the brain and must be transported into it. Knockouts have reduced levels of DHA in the brain accompanied by neuronal loss in the hippocampus and cerebellum and microcephaly. Human cases due to mutation are now known (11/15). Transport of DHA and fatty acids into the brain across the BBB occurs only in the form of esters with lysophosphatidylcholines (LPCs) but not as free fatty acids in a sodium dependent manner. The phospho-zwitterionic headgroup of of LPC is essential for transport. MFSD2a ‘prefers’ long chain fatty acids (oleic, palmitic), failing to transport fatty acids with chain lengths under 14.

So MFSD2a inhibits transcytosis at the same time it promotes fatty acid transport into the brain. Major Facilitator Superfamily (MFS) proteins use the electrochemical potential of the cell to transport substrates. The best known MFSs are the glucose transporters (GLUT1 – 4).

So the blood brain barrier is due in part to the lipid transport activity of MFSD2a which gives BBB endothelium a different lipid composition (with lots of docosahexenoic acid) ) than others, inhibiting caveolar transport. Increased DHA levels are associated with membrane cholesterol depletion, as well as displacement of caveolin1 (the major protein involved in this form of transcytosis) from caveolae.

It is likely that MFSD2A acts as a lipid flippase, transporting phospholipids, including DHA containing species from the outer to the inner plasma membrane leaflet (where caveolin1 binds).

What is so hot about docosahexenoic acid — 22 carbons all in a row, a carboxyl group and 6 double bonds. We’re not talking fused ring systems, alkaloids, bizarre functional groups etc. etc.

Half the answer is that the double bonds are NOT randomly arranged. The 6 occur all in a row (but with methylene groups between them). This tells the chemist that they are not conjugated, hence the chain is probably not straight. Think how unlikely the arrangement is considering the way 6 double bonds and 9 methylenes COULD be arranged in a chain (2^15). Answer 5 ways depending on where the arrangement starts relative to the end of the chain.

The other half is that all the double bonds are cis, making it very unlikely that the 21 carbon chain can straighten out and cross the membrane. Lots of DHA means a very disordered membrane, which may be impossible to caveolin1 (and clathrin) to bind to.

So even though it’s years and years since I left organic chemistry, it permits the enjoying of the biochemical esthetics of the blood brain barrier.

The tight junctions between endothelial cells are primarily responsible for barrier function. These tight junctions are found only in the capillaries and postcapillary venules of the brain. Endothelial cells of the brain have few pinocytotic vesicles and fenestriae. [ Neuron vol. 71 p. 408 ’11 ] The brain vasculature has the thinnest endothelial cells, with the tightest junction and a higher degree of pericyte coverage coverage (‘up to’ 30%). [ Neuron vol. 78 pp. 214 – 232 ’13 ] The tight junctions are made from occludin, claudins and junctional adhesion molecules, and are closer to the lumen than the adherens junctions (which also link endothelial cells to each other) made by the cadherins (E, P and N). (ibid p. 219) TLR2/6 specific stimuli.