from the world's big
We Are Training Too Many Scientists
James Watson is an American molecular biologist best known for his discovery of the structure of DNA with Francis Crick in 1953. He was born in Chicago in 1928 and attended the University of Chicago for his undergraduate degree in zoology. While pursuing his Ph.D at Indiana University, Watson became interested in molecular biology, which led him to the University of Cambridge's Cavendish Laboratory for postdoctoral research. There he met Crick, the two recognized a common interest in discovering the structure of DNA. Watson, Crick, and another researcher Maurice Wilkins would later share the 1962 Nobel Prize in Physiology or Medicine for their work in this field.
In 1956, Watson became a junior member of Harvard University's Biological Laboratories, where he quickly advanced to the position of full professor. Then in 1968 he became director of Cold Spring Harbor Laboratory (CSHL) on Long Island, New York, where he shifted his research emphasis to the study of cancer. Between 1988 and 1992, Watson was also associated with the National Institutes of Health, spearheading the Human Genome Project. In 2007 he became the second person, after molecular biologist Craig Venter, to have his entire genome sequenced. Watson remained involved with CSHL, as president and later as chancellor, until 2007, when he retired following a controversy over comments he made claiming blacks are less intelligent than whites.
Watson has written many books, including the seminal textbook "The Molecular Biology of the Gene" (1965), his bestseller "The Double Helix" (1968) about his discovery of the DNA structure, and his memoir "Avoid Boring People" (2007).
Question: Do you spend much time reading scientific journals?
James Watson: Well I think I have to... if I want to... I’d like to say three hours per day, but that you know, probably in a day when I’m on my desk and not in New York City or something. But I think I would read more than most people, even those younger than me who are so busy doing things. So I have the leisure time actually to read. And I think that’s what we’ve lost now in sort of science today is leisure.
Now Crick and I had plenty of leisure because nothing was happening when we were trying to find the DNA structure. There was, you know, there weren’t hundreds of new facts appearing almost every week that we might learn about. And now people lead, defensively, want to be sure that they’re... you know, people will think they are experts, so they’ve become more and more narrow experts and not very broad. And I still can’t get over when I was at a pharmaceutical company, they half-jokingly but I’m sure the reality was true. They had 1000 PhD technicians. As you got your PhD, you were just a technician. No one was... you were hiring you for a very narrow thing and not to show any big thoughts at all. So, with so many facts, what I miss now are thinkers. The [...] were smart.
Now when I was a boy, you know, smart people were respected, now it’s, you know, people do things, who do it. And also you find that there hasn’t been one person doing it; there are 50 names on the paper. And our famous paper for instance, mine, could have included Morris Wilkins’ name on it because he was really part of it. He didn’t make the discovery, but he was you know, part of the stuff just before it. So we asked him to put his name on the paper, and he said, no. That would have been a three-person paper.
But, the... I worry about people really thinking big. I don’t find many people who do so now. When I was a student at the University of Chicago, Robert Hutchens in his speech, said “The function of the College of the University of the Chicago was to prepare you for greatness.” He used those words because our education was largely reading the great books. And you were reading the great books, not to be a teacher, but to let you go beyond the great books and produce another great book. So, that was how he saw it. Of course, he would know that that would happen very often, but it was still there that... And it’s certainly in dreams of people, you know, that they do something big. Most of the time they keep it secret because you know, it’s more realistic and often then you get braggarts who tell you, you know, they’re doing something great and you don’t believe them. But nonetheless, you know, in some sort of quiet way, you should have big dreams.
Question: How can we encourage this in our education system?
James Watson: I think stop having 50 names on a paper. Just you know, accept the fact that the rest really didn’t think at all about it. And you should really, you know, were just technicians, you know, in a real sense—and reserve authorship for people who put together the sentences. I mean, now, you know, put together the answer. Whereas, I feel it very unsatisfactory to be the mother of a scientist now. And after son handed in a paper where there were 20 other people on the paper. And she’d wonder, "Is he going anywhere?"
So, and another problem may be, though it is against everything we now say, we may be training too many scientists. That is, we’re training people who really don’t want to think, they just want to have jobs. And they consume money. And so you’d lose some, you know, if you cut out people who didn’t have real dreams. But if you go into science, I think you better go in with a dream that maybe you too will get a Nobel Prize. It’s not that I went in and I thought I was very bright and I was going to get one, but I’ll confess, you know, I knew what it was. And Crick’s thinking was otherwise, but the moment I saw that structure I thought: “We’re gonna get a Nobel Prize.” I knew it in five minutes, it was so obvious.
Recorded on September 28, 2010
Interviewed by Paul Hoffman
If you go into science, you should do so in order to win the Nobel Prize, not to earn a decent paycheck.
Duke University researchers might have solved a half-century old problem.
- Duke University researchers created a hydrogel that appears to be as strong and flexible as human cartilage.
- The blend of three polymers provides enough flexibility and durability to mimic the knee.
- The next step is to test this hydrogel in sheep; human use can take at least three years.
Duke researchers have developed the first gel-based synthetic cartilage with the strength of the real thing. A quarter-sized disc of the material can withstand the weight of a 100-pound kettlebell without tearing or losing its shape.
Photo: Feichen Yang.<p>That's the word from a team in the Department of Chemistry and Department of Mechanical Engineering and Materials Science at Duke University. Their <a href="https://onlinelibrary.wiley.com/doi/abs/10.1002/adfm.202003451" target="_blank">new paper</a>, published in the journal,<em> Advanced Functional Materials</em>, details this exciting evolution of this frustrating joint.<br></p><p>Researchers have sought materials strong and versatile enough to repair a knee since at least the seventies. This new hydrogel, comprised of three polymers, might be it. When two of the polymers are stretched, a third keeps the entire structure intact. When pulled 100,000 times, the cartilage held up as well as materials used in bone implants. The team also rubbed the hydrogel against natural cartilage a million times and found it to be as wear-resistant as the real thing. </p><p>The hydrogel has the appearance of Jell-O and is comprised of 60 percent water. Co-author, Feichen Yang, <a href="https://today.duke.edu/2020/06/lab-first-cartilage-mimicking-gel-strong-enough-knees" target="_blank">says</a> this network of polymers is particularly durable: "Only this combination of all three components is both flexible and stiff and therefore strong." </p><p> As with any new material, a lot of testing must be conducted. They don't foresee this hydrogel being implanted into human bodies for at least three years. The next step is to test it out in sheep. </p><p>Still, this is an exciting step forward in the rehabilitation of one of our trickiest joints. Given the potential reward, the wait is worth it. </p><p><span></span>--</p><p><em>Stay in touch with Derek on <a href="http://www.twitter.com/derekberes" target="_blank">Twitter</a>, <a href="https://www.facebook.com/DerekBeresdotcom" target="_blank">Facebook</a> and <a href="https://derekberes.substack.com/" target="_blank">Substack</a>. His next book is</em> "<em>Hero's Dose: The Case For Psychedelics in Ritual and Therapy."</em></p>
An algorithm may allow doctors to assess PTSD candidates for early intervention after traumatic ER visits.
- 10-15% of people visiting emergency rooms eventually develop symptoms of long-lasting PTSD.
- Early treatment is available but there's been no way to tell who needs it.
- Using clinical data already being collected, machine learning can identify who's at risk.
The psychological scars a traumatic experience can leave behind may have a more profound effect on a person than the original traumatic experience. Long after an acute emergency is resolved, victims of post-traumatic stress disorder (PTSD) continue to suffer its consequences.
In the U.S. some 30 million patients are annually treated in emergency departments (EDs) for a range of traumatic injuries. Add to that urgent admissions to the ED with the onset of COVID-19 symptoms. Health experts predict that some 10 percent to 15 percent of these people will develop long-lasting PTSD within a year of the initial incident. While there are interventions that can help individuals avoid PTSD, there's been no reliable way to identify those most likely to need it.
That may now have changed. A multi-disciplinary team of researchers has developed a method for predicting who is most likely to develop PTSD after a traumatic emergency-room experience. Their study is published in the journal Nature Medicine.
70 data points and machine learning
Image source: Creators Collective/Unsplash
Study lead author Katharina Schultebraucks of Columbia University's Department Vagelos College of Physicians and Surgeons says:
"For many trauma patients, the ED visit is often their sole contact with the health care system. The time immediately after a traumatic injury is a critical window for identifying people at risk for PTSD and arranging appropriate follow-up treatment. The earlier we can treat those at risk, the better the likely outcomes."
The new PTSD test uses machine learning and 70 clinical data points plus a clinical stress-level assessment to develop a PTSD score for an individual that identifies their risk of acquiring the condition.
Among the 70 data points are stress hormone levels, inflammatory signals, high blood pressure, and an anxiety-level assessment. Says Schultebraucks, "We selected measures that are routinely collected in the ED and logged in the electronic medical record, plus answers to a few short questions about the psychological stress response. The idea was to create a tool that would be universally available and would add little burden to ED personnel."
Researchers used data from adult trauma survivors in Atlanta, Georgia (377 individuals) and New York City (221 individuals) to test their system.
Of this cohort, 90 percent of those predicted to be at high risk developed long-lasting PTSD symptoms within a year of the initial traumatic event — just 5 percent of people who never developed PTSD symptoms had been erroneously identified as being at risk.
On the other side of the coin, 29 percent of individuals were 'false negatives," tagged by the algorithm as not being at risk of PTSD, but then developing symptoms.
Image source: Külli Kittus/Unsplash
Schultebraucks looks forward to more testing as the researchers continue to refine their algorithm and to instill confidence in the approach among ED clinicians: "Because previous models for predicting PTSD risk have not been validated in independent samples like our model, they haven't been adopted in clinical practice." She expects that, "Testing and validation of our model in larger samples will be necessary for the algorithm to be ready-to-use in the general population."
"Currently only 7% of level-1 trauma centers routinely screen for PTSD," notes Schultebraucks. "We hope that the algorithm will provide ED clinicians with a rapid, automatic readout that they could use for discharge planning and the prevention of PTSD." She envisions the algorithm being implemented in the future as a feature of electronic medical records.
The researchers also plan to test their algorithm at predicting PTSD in people whose traumatic experiences come in the form of health events such as heart attacks and strokes, as opposed to visits to the emergency department.
What would it be like to experience the 4th dimension?
Physicists have understood at least theoretically, that there may be higher dimensions, besides our normal three. The first clue came in 1905 when Einstein developed his theory of special relativity. Of course, by dimensions we’re talking about length, width, and height. Generally speaking, when we talk about a fourth dimension, it’s considered space-time. But here, physicists mean a spatial dimension beyond the normal three, not a parallel universe, as such dimensions are mistaken for in popular sci-fi shows.
Vaccines find more success in development than any other kind of drug, but have been relatively neglected in recent decades.
Vaccines are more likely to get through clinical trials than any other type of drug — but have been given relatively little pharmaceutical industry support during the last two decades, according to a new study by MIT scholars.