In a 1963 letter to molecular biologist Max Perutz, he wrote, “It is now widely realized that nearly all the ‘classical’ problems of molecular biology have either been solved or will be solved in the next decade…The future of molecular biology lies in the extension of research to other fields of biology, notably development and the nervous system.”
Sydney observed, and predicted, the flow of science: “Progress depends on the interplay of techniques, discoveries, and ideas, probably in that order of decreasing importance,” he said.
Man, the toolmaker. In this particularly case, a very special one.
Sydney Brenner (1927–2019) | Science [Obit of Sydney Brenner]
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Scope for recognizing and accommodating exceptional individuals has been diminishing in British universities ever since. Hamilton published relatively few papers, in generally low status journals, and gained only a handful of grants much later in life. Bureaucratic measures of performance are increasingly important and judge the impact of an article only by the journal it is published in. This seriously undervalues radical originality, which although extremely rare is utterly vital to science. It is disturbing that a young Bill Hamilton today would probably find an academic career even more difficult to pursue.
Alan Grafen, in his obituary of Bill Hamilton (Biogr. Mems Fell. R. Soc. Lond. 50, 109–132 (2004)).
I post this excerpt following a discussion with somebody who had never heard of him. Hamilton’s enormous contributions to biology are not well known. You also have to wonder if the lack of a Nobel for biology diminishes medicine in the long run. Some things do indeed get worse.
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Sydney Brenner has died. Not quite the last of the handful of scientists who made one of the two scientific revolutions of the 20th century. The first half belonged to physics, the second to the biology that he co-created.
A precocious boy—a student at the University of the Witwatersrand by the time he was 15—and bullied for it, reading was his connection to the wider world. Courses, he said, never taught him anything. The way to learn was to get a book that told you how to do things, and then to start doing them, whether it was making dyes or, later in life, programming computers. If he thought more deeply than the other great biologists of his age, which he did, it was surely because he read further, too.
Reading Brenner was a staccato of insights. I hadn’t come across the ‘courses’ quote before, but no surprises there.
James Williams worked at Google in a senior role for ten years, but has moved into philosophy at Oxford (for the money obviously….). He has written a wonderful short book, with the title “Stand out of our Light”. The name comes from a humorous account of a meeting between Diogenes and Alexander the Great (no spoilers, here).
His book is a critique of much digital technology that — to use his analogy — does not act as an honest GPS, but instead entices you along paths that make your journay longer. All in the name of capturing your attention, such that you are deflected from your intentions.
He starts chapter 3, with something comical and at the same time profound.
When I told my mother I was moving to the other side of the planet to study technology ethics at a school that’s almost three times as old as my country, she asked, “Why would you go somewhere so old to study something so new? In a way the question contained its own answer.
For me that is the power of the academic ideal.
I like statistics and spent most of my intercalated degree ‘using’ medical stats (essentially, writing programs on an IBM 360 mainframe to handle a large dataset, that I could then interrogate using the GLIM package from the NAG). Yes, the days of batch processing and punchcards. I found — and still find — statistics remarkably hard.
I am always very wary of people who say they understand statistics. Let me rephrase that. I am very suspicious of non-professional statisticians who claim that they find statistics intuitive. I remember that it was said that even the great Paul Erdos got the Monty Hall problem wrong.
The following is from a recent article in Nature:
What will retiring statistical significance look like? We hope that methods sections and data tabulation will be more detailed and nuanced. Authors will emphasize their estimates and the uncertainty in them — for example, by explicitly discussing the lower and upper limits of their intervals. They will not rely on significance tests. When P values are reported, they will be given with sensible precision (for example, P = 0.021 or P = 0.13) — without adornments such as stars or letters to denote statistical significance and not as binary inequalities (P < 0.05 or P > 0.05). Decisions to interpret or to publish results will not be based on statistical thresholds. People will spend less time with statistical software, and more time thinking.
There is lots of blame to go around here. Bad teaching and bad supervision, are easy targets (too easy). I think there are (at least) three more fundamental problems.
Science has been thought of as a form of ‘reliable knowledge’. This form of words always sounded almost too modest to me, especially when you think how powerful science has been shown to be. But in medicine we are increasingly aware that much modern science is not a basis for honest action at all. Blake’s words were to the effect that ‘every honest man is a prophet’. I once miswrote this in an article I wrote as ‘every honest man is for profit’. Many an error….
The quotes below are from an article in the FT (awhile back). They echo one of my rules, a rule that is more of the exception that proves the rule. Just as “no good lab has space” (because the bench space will always be taken up because many will want to work there), so when the grand new building arrives, the quality of work will already be past its peak (because how else would you have justified your future except by looking back). It is all about edge people, and just as social change usually starts at the edge, so do good ideas.
The principle of benign neglect may well operate on a larger scale. Consider Building 20, one of the most celebrated structures at Massachusetts Institute of Technology. The product of wartime urgency, it was designed one afternoon in the spring of 1943, then hurriedly assembled out of plywood, breeze-blocks and asbestos. Fire regulations were waived in exchange for a promise that it would be pulled down within six months of the war’s end; in fact the building endured, dusty and uncomfortable, until 1998.
During that time, it played host not only to the radar researchers of Rad Lab (nine of whom won Nobel Prizes) but one of the first atomic clocks, one of the first particle accelerators, and one of the first anechoic chambers — possibly the one in which composer John Cage conceived 4’33. Noam Chomsky revolutionised linguistics there. Harold Edgerton took his high-speed photographs of bullets hitting apples. The Bose Corporation emerged from Building 20; so did computing powerhouse DEC; so did the hacker movement, via the Tech Model Railroad Club.
Building 20 was a success because it was cheap, ugly and confusing. Researchers and departments with status would be placed in sparkling new buildings or grand old ones — places where people would protest if you nailed something to a door. In Building 20, all the grimy start-ups were thrown in to jostle each other, and they didn’t think twice about nailing something to a door — or, for that matter, for taking out a couple of floors, as Jerrold Zacharias did when installing the atomic clock.
Somewhat reminiscent of Stewart Brand’s ‘How Buildings Learn’
In climate science, you can check out of the lab anytime you like, but you can never leave.
Dave Reay, University of Edinburgh, quoted in Nature this week.
This is from an article by Stephen Senn in Nature. He keeps making this point — for the very good reason that people want to pretend there is no problem. But there is.
Personalized medicine aims to match individuals with the therapy that is best suited to them and their condition. Advocates proclaim the potential of this approach to improve treatment outcomes by pointing to statistics about how most drugs — for conditions ranging from arthritis to heartburn — do not work for most people. That might or might not be true, but the statistics are being misinterpreted. There is no reason to think that a drug that shows itself to be marginally effective in a general population is simply in want of an appropriate subpopulation in which it will perform spectacularly.
When you treat patients with chronic diseases such as psoriasis, it quickly becomes clear that there is considerable within person variation is response to treatments. We do not understand what this variation is due to. What we do know however, is that assuming variation in response between people at single time points may be misleading in that we have no measure of within person variance. This is only one of the problems. But hey, precision, personalised.. whatever: it shifts units (as Frank Zappa once said of Michael Jackson).
Genome-wide study of hair colour in UK Biobank explains most of the SNP heritability.
Michael D. Morgan, Erola Pairo-Castineira, Konrad Rawlik, Oriol Canela-Xandri, Jonathan Rees, David Sims, Albert Tenesa & Ian J. Jackson
[Link to Nature Comm paper] https://doi.org/10.1038/s41467-018-07691-z
My guess is this is likely my last ‘research paper’ (although I now choose to redefine what counts as research). But not my last ‘thinking paper’. I cannot help but contrast the sheer volume of activity with that from our original papers on red hair. Things seemed so much simpler when we were young. But it is a nice coda to a career fugue.
This is from an editorial in the NEJM, discussing the results of a trial of a synthetic peanut antigen to facilitate tolerance. Prevously the ‘raw’ stuff had been shown to be useful. The synethic version will of course cost a lot, and might be considered IPR created through regulatory arbitrage.
AR101 and other, similar products such as CA002, which is being developed by the Cambridge group, would therefore appear to have a role in initial dose escalation. The potential market for these products is believed to be billions of dollars. It is perhaps salutary to consider that in the study conducted by the Cambridge group, children underwent desensitization with a bag of peanut flour costing peanuts.
Costing penauts: I wish I had said that
Leading universities should pledge to actually read the work of applicants for research positions rather than use controversial metrics during the selection process, a Nobel prizewinner has argued.
No, not a spoof, but words from Harold Varmus. Sydney Brenner, a good while back, observed that people tended not to read papers anymore, they just xeroxed them.
Modesty seems to be under negative selection — among modern scientists, at least. So I warmed to this comment on a report of some recent work on the genetics of Africa and hunter-gatherers.
Deepti Gurdasani, a genetic epidemiologist at the Wellcome Sanger Institute in Hinxton, UK. But it’s plausible, she adds. “There is literally nothing in Africa that is not possible since we have no idea what humans were doing on the continent 5,000 years ago.”
This is from an article in Nature.
Under pressure to turn out productive lab members quickly, many PhD programmes in the biomedical sciences have shortened their courses, squeezing out opportunities for putting research into its wider context. Consequently, most PhD curricula are unlikely to nurture the big thinkers and creative problem-solvers that society needs.
That means students are taught every detail of a microbe’s life cycle but little about the life scientific. They need to be taught to recognize how errors can occur. Trainees should evaluate case studies derived from flawed real research, or use interdisciplinary detective games to find logical fallacies in the literature. Above all, students must be shown the scientific process as it is — with its limitations and potential pitfalls as well as its fun side, such as serendipitous discoveries and hilarious blunders.
And from a letter in response
My father designed stellar-inertial guidance systems for reconnaissance aircraft and, after he retired, would often present his work to physics and engineering students. When they asked him what they should study to prepare for such a career, he would reply: “Read the classics,” by which he meant Aristotle, Ralph Waldo Emerson, Jean-Jacques Rousseau and Blaise Pascal.
The best scientific and technical progress does not come out of a box. It is more likely to emerge from trying to fit wild, woolly and tangential ideas into useful societal and economic contexts.
As the historian Norman Davies once said:
“Since no one is judged competent to offer an opinion beyond their own particular mineshaft, beasts of prey have been left to prowl across the prairie unchecked.”
Or as the Economist once put it”
“…professors fixated on crawling alone the frontiers of knowledge with a magnifying glass.”
This is the tragedy of our age: 90% right and 100% wrong. And that is even before we get to medicine.
Yet despite these innovations and those to come, quantitative risk prediction in medicine has been available for several decades, based on more classical statistical learning from more structured data sources. Despite reports that risk models outperform physicians in prognostic accuracy, application in actual clinical practice remains limited.
It seems unlikely that incremental improvements in discriminative performance of the kind typically demonstrated in machine learning research will ultimately drive a major shift in clinical care. In this Viewpoint, we describe 4 major barriers to useful risk prediction that may not be easily overcome by new methods in machine learning and, in some instances, may be more difficult to overcome in the era of big data.
The hype cycle marches on.
How is it that publishers can continue to make profits of 30–40%? How can Elsevier get away with charging, as described in the film, $10,702 for an annual subscription to Biomaterials? It’s partly that if you are a major research university you need access to all journals not just some of them, says Richard Price of Academia.edu, a platform for academics to share research papers. It’s a question of moral hazard, explains Stuart Shieber, a Harvard professor of computer science: the consumers of the research, the academics, are not the people who have to pay. It’s the libraries who pay, and the academics remain insensitive to price…..
In addition, publishers sell bundles of journals. It’s like cable television, you get a few things you do want along with a lot you don’t, explains one librarian. But unlike cable television you don’t know what others are paying—because publishers do secret deals with libraries.
Yes. But it speaks volumes about universities, too.
When working in Africa in the 1980s with my good friend Victor Pretorius, I heard a legend about an important tribe in Central Africa, the Masai. The legend claimed that a genius member of the tribe in the nineteenth century or earlier had the idea that cow’s urine was the safest fluid for washing cooking utensils. Compared with the previous practice of using far from clean river water, it avoided the dangers of dysentery and probably saved many lives. This simple and effective public heath practice was cast out by medical missionaries who had quite different ideas, more religious than medical, about what was clean and what was dirty. Neither the original genius, nor the missionaries, knew anything about the epidemiology of water-borne disease. Whether or not there is any substance to this legend, it has stayed in my mind as a metaphor appropriate for many of our problems today. Inventions such as Newcomen’s steam engine, Faraday’s electrical machines, and the idea that fresh urine is a sterile fluid, all came long before their scientific understanding.
James Lovelock, A Rough Ride to the Future. This is like so much of real discovery in clinical medicine, although the academy gets to write the history of how it is supposed to work.
For a baseline life expectancy of 80 years:
Well these are all taken from John Ioannadis’ article in JAMA. He asks : “Could these results possibly be true?”
The great financial crash led to some (but not enough) soul-searching about the state of academic economics and, in turn, the academy. Whole swathes of the modern research university are geared to the production of unreliable knowledge. There is money in it. Without wishing to understate in any way Ioannadis’ major contributions, we have known that there are fundamental methodological flaws in much of observational epidemiology for a long time (for instance see the late Alvan Feinstein’s article in Science). A must read.
(The Challenge of Reforming Nutritional Epidemiologic Research John P. A. Ioannidis, AMA. Published online August 23, 2018. doi:10.1001/jama.2018.11025)
From an obituary of Paul Boyer.
“Paul Boyer was approaching the finish line of his career when he risked everything with a jaw-dropping proposal. He addressed one of the most important, as-then-unanswered questions in biochemistry”
“We were attending a UCLA seminar in 1972 when I noticed that he wasn’t paying attention to the speaker. Afterwards, Paul approached us in a very excited state. This was surprising because he was known for his calm demeanour. He confessed that he had spent the hour thinking about old unexplained data. He asked: “What would you say if I told you that it doesn’t take energy to make ATP at the catalytic site of ATP synthase,” (as was universally held at the time) “but rather that it takes energy to get ATP off the catalytic site?” This was a eureka moment.
As is often the case with transformational ideas, early reactions were negative. When the Journal of Biological Chemistry rejected our manuscript containing data supporting this concept, Boyer told me without animosity that he could see why they would do that — “It was a very striking claim.”
Well, I have never had an idea to compare with this. But sitting through talks that do not light my fire, I have always found conducive to thinking creatively about something else. Its similar to the way that some writers practice their craft better in a coffee shop than in a silent office. Intellectual white noise.
Remember: the best ideas are not in the literature. If they were…..
Besides, “university league tables are like sausages: the more you know about how they are made, the less you want to [do with] them”.
“Research was structurally unprofitable even if you scored really well in the research excellence framework,” he claims. “It’s being financed by surpluses on taught master’s. I think that’s fine because part of the reason people came on the taught programmes was because the place was very highly ranked in research, and they thought they were going to be sitting at the feet of the best economists around. Academics had to understand the dynamic and deliver the teaching because that was what was paying for the research. Yet because of the history of underfunding [undergraduate] students [before the introduction of £9,000 tuition fees in 2012], a kind of mood gained ground in British universities that [all] students were an unprofitable activity.
Science 21 June 2013: 1394-1399.
For most alumni, university fundraising may seem to be uncoordinated and lacking in focus—an assortment of phone calls, solicitous letters, and invitations to a class reunion. But for Steven Rum, it’s a science. And the goal is to carry out more research.
Rum is senior vice president for development and chief fundraiser for Johns Hopkins Medicine in Baltimore, Maryland. Last year, his team had a banner year, raising $318 million. Their approach places the physician scientists at Hopkins on the donor front lines. The goal is to turn the positive feelings of “grateful patients” into support for new research, faculty chairs, academic scholarships, bricks and mortar, or simply defraying the cost of running a multibillion-dollar medical center.
Rum has 65 full-time fundraisers on a staff of 165. Each one is responsible for meeting weekly with physicians—their “caseloads” range from a dozen to more than 30 docs—to discuss which of their patients might be potential donors. The conversation is designed to help them identify what Rum calls a donor’s “qualifying interest” and connect it to their “capacity,” that is, the ability to make a donation.
More often than not, Rum’s team finds that sweet spot…..
”Ideally, I’d like to have one gift officer manage no more than six doctors,” he says.
Article in Nature. I largely agree, although my views are as much based on the hype-upon-hype that characterises so much of medical research, especially cancer. I do not have a reference, but whatever one’s views about the late David Horrobin, his Lancet article about cancer trials — written when he was dying from lymphoma — is worth a read. What a mess!
Key quotes from this article:
In 2017, my colleagues and I completed a study of all 48 cancer drugs approved by the European Medicines Agency between 2009 and 2013 (C. Davis et al. Br. Med. J. 359, j4530; 2017). Of the 68 clinical indications for these drugs (reasons to use a particular drug on a patient), only 24 (35%) demonstrated evidence of a survival benefit at the time of approval. Even fewer provided evidence of an improved quality of life for symptoms such as pain, tiredness and loss of appetite (7 trials; 10%). Most indications (36 of 68) still lacked such evidence three or more years after approval. Other groups in other regions have observed similar trends. For example, a 2015 study demonstrated that only a small proportion of cancer drugs approved by the FDA improved survival or quality of life (C. Kim and V. Prasad JAMA Intern. Med. 175, 1992–1994; 2015).
But the key point he makes is:
I believe that the low bar also undermines innovation and wastes money.
When assessments — whether in medicine or education — are flawed the loss in value is not in short term financial costs, but in what might have happened 10 years down the road.
There are periodic evaluations, but a poor result means losing only a fraction of your funding, says Schuman, who previously held one of the plum positions in U.S. science: as an investigator funded by the Howard Hughes Medical Institute on a 5-year contract. “I did not realize how the renewal clock of 5 years dissuaded me from going for risky ideas until I became a Max Planck director,” she says.
Cue, David Bowie:
The following is an excerpt from a review in press with Acta. You can see the full article with DOI 10.2340/00015555-2916 here
From the solar constant to thong bikinis and all stops in between.
A review of: “Sun Protection: A risk management approach.” Brian Diffey. IOP Publishing, Bristol, UK. ISBN 978-0-7503-1377-3 (ebook) ISBN 978-0-7503-1378-0 (print) ISBN 978-0-7503-1379-7 (mobi)
Leo Szilard was one of half a dozen or so physical scientists who, having attended the same Budapest gymnasium, revolutionised twentieth century physics. In 1934, whilst working in London, he realised that if one neutron hit an atom which then released two further neutrons, a chain reaction might ensue. Fearing of the consequences, he tried to keep the discovery secret by assigning the patent to the British Admiralty. In 1939, he authored the letter, that Einstein signed, warning the then US President of the coming impact of nuclear weapons.
After the war, in revulsion at the uses to which his physics had been applied, he swapped physics for biology. There was a drawback, however. Szilard liked to think in a hot bath, and he liked to think a lot. Once his interests had turned to biology he remarked that he could no longer enjoy a long uninterrupted bath — he was forever having to leave his bath, to check some factual detail (before returning to think some more). Biology seemed to lack the deep simplifying foundations of the Queen of Sciences.
But all of that media can’t really replace the socializing, networking, and simply fun that happened as part of (or sometimes despite) the conference formula.
I don’t know how to fix conferences, but the first place I’d start on that whiteboard is by getting rid of all of the talks, then trying to find different ways to bring people together — and far more of them than before.
I no longer go to many conferences, and that is a good thing. But fixing them is a problem, not least because many academic conferences are businesses that collect money that supports other activities. This is not always bad, but is often not good. ‘Getting rid of the talks’ is of course attractive. Leo Szilard once suggested that you should stand up, briefly report your conclusions, then sit down. Only if the audience were sceptical of your results would you have to speak for longer. As for size, there is no single right size. However the best conferences I have every attended were all small, with less than 40 people. But I wouldn’t t have got to these small ones, unless I had gone to the big ones.
The surge in open-access predatory journals is making it harder for contributors and readers to distinguish these from legitimate publications — a confusion that is fostered by the predatory-journal industry. One solution could be to deploy a variant of a well-established quality-control test. The scientific community could submit replicate test articles several times a year to a wide array of open-access journals, suspect and non-suspect.
From Steven N Goodman who, as ever, is worth reading. Of course, in one sense, it is a question of serial monogamy, or polygamy.
After earning his medical degree in 1951 he trained in hospitals in Montreal. “To my surprise I also found I enjoyed clinical medicine,” he wrote in his Nobel prize biography. Then he quipped, “It took three years of hospital training after graduation, a year of internship and two of residency in neurology, before that interest finally wore off.”
This is from the obituary of Ben Barres [link]
An utterly committed researcher, Professor Barres would regularly work until 2am or 3am. He “slept on the floor of my small office”, recalled Professor Raff. “Every morning when I arrived and opened the door, it would whack him in the head – he eventually learned to sleep facing the opposite direction.”
Somewhere, I cannot remember where, after one of his seminars, his intellectual depth (Ben Barres) was judged more favourably to that of his ‘sister’. His sister was his his former ‘self’, Barbara Barres. Such a neat experimental design to tease apart causality.
I too worked somewhere where people slept overnight in the lab, although I think the deciding factor there was an inability to find or pay for a suitable flat, rather than enthusiasm
David Hubel, on statistics: “We could hardly get excited about an effect so feeble as to require statistics for its demonstration.”
I came across this (below), in my end of year clear out. And even if this was 2016, rather than 2017, it is as good a thought to open 2018 with, as any other. It is from a review of “Life’s Greatest Secret: The Race to Crack the Genetic Code”, by Matthew Cobb. The review is by H Allen Orr. NYRB
Finally, and perhaps most important, Life’s Greatest Secret highlights the power of the beautiful experiment in science. Though Cobb pays less attention to this subject than he might have, the period of scientific history that he surveys was the golden age of the beautiful experiment in biology. Biologists of the time—including Nirenberg with his UUU, Crick and Brenner with their triplet code work, and others including Matthew Meselson, Franklin Stahl, and Joshua Lederberg—were masters of the sort of experiment that, through some breathtakingly simple manipulation, allowed a decisive or nearly decisive solution to what previously seemed a hopelessly complex problem. Such experiments represent a species of intellectual art that is little appreciated outside a narrow circle of scientists……..
But the larger lesson of Life’s Greatest Secret is one that may be worth remembering. When scientists require definitive answers, not merely suggestive patterns, they require experiments that are decisive and, if all goes well, beautiful.
There is something about teaching that makes you a better researcher. I know this is very countercultural wisdom, but I believed it all along. Luria, Magasanik, and Levinthal all believed it. Levinthal and Luria both had a very strong influence on me in this regard.
An (old) interview with David Botstein, in PloS genetics. Link
At least we are spared the ‘research led teaching’ mission statements.