I think one of the things that tends to lead us astray when we try to understand complex phenomena like evolution, disease, or the economy, is that we have this idea that they must have a single explanation. For example, recently two papers have been published in high profile journals trying to explain mammal monogamy. Although monogamy is quite common in birds it only occurs in 5% of mammals. Here is Carl Zimmer’s summary. The study in Science, which surveyed 2545 mammal species, argued that monogamy arises when females are solitary and sparse. Males must then commit to one since dates are so hard to find. The study in PNAS examined 230 primate species, for which monogamy occurs at the higher rate of 27%, and used Bayesian inference to argue that monogamy arises to prevent male infanticide. It’s better to help out at home rather than go around killing other men’s babies. Although both of these arguments are plausible, there need not be a single universal explanation. Each species could have its own set of circumstances that led to monogamy involving these two explanations and others. However, while we should not be biased towards a single explanation, we shouldn’t also throw up our hands like Hayek and argue that no complex phenomenon can be understood. Some phenomena will have simpler explanations than others but since the Kolmogorov complexity is undecidable there is no algorithm that can tell you which is which. We will just have to struggle with each problem as it comes.
I’m currently in Mt. Snow, Vermont to give a talk at the Gordon Research Conference on Computer Aided Drug Design. Yes, I know nothing about drug design. I am here because the organizer, Anthony Nicholls, asked me to give a pedagogical talk on Bayesian Inference. My slides are here. I only arrived yesterday but the few talks I’ve seen have been quite interesting. One interesting aspect of this conference is that many of the participants are from industry. The evening sessions are meant to be of more general interest. Last night were two talks about how to make science more reproducible. As I’ve posted before, many published results are simply wrong. The very enterprising Elizabeth Iorns has started something called the Reproducibility Initiative. I am not completely clear about how it works but it is part of another entity she started called Science Exchange, which helps to facilitate collaborations with a fee-for-service model. The Reproducibility Initiative piggy backs on Science Exchange by providing a service (for a fee) to validate any particular result. Papers that pass approval get a stamp of approval. It is expected that pharma would be interested in using this service so they can inexpensively check if possible drug targets actually hold up. Many drugs fail at phase three of clinical trials because they’ve been shown to be ineffective and this may be due to the target being wrong to start with.
On a final note, I flew to Albany and drove here. Unlike in the past when I would have printed out a map, I simply assumed that I could use Google Maps on my smart phone to get here. However, Google Maps doesn’t really know where Mt. Snow is. It tried to take me up a dirt road to the back of the ski resort. Also, just after I turned up the road, the phone signal disappeared so I was blind and had no paper backup. I was suspicious that this was the right way to go so I turned back to the main highway in hopes of finding a signal or a gas station to ask for directions. A few miles down Route 9, I finally did get a signal and also found a sign that led me the way. Google Maps still tried to take me the wrong way. I should have followed what I always tell my daughter – Always have a backup plan.
A Coulon, CC Chow, RH Singer, DR Larson Eukaryotic transcriptional dynamics: from single molecules to cell populations. Nat Gen Reviews (2013).
Abstract | Transcriptional regulation is achieved through combinatorial interactions between regulatory elements in the human genome and a vast range of factors that modulate the recruitment and activity of RNA polymerase. Experimental approaches for studying transcription in vivo now extend from single-molecule techniques to genome-wide measurements. Parallel to these developments is the need for testable quantitative and predictive models for understanding gene regulation. These conceptual models must also provide insight into the dynamics of transcription and the variability that is observed at the single-cell level. In this Review, we discuss recent results on transcriptional regulation and also the models those results engender. We show how a non-equilibrium description informs our view of transcription by explicitly considering time- and energy-dependence at the molecular level.
This paper started many years ago when Steve Wank, of the Digestive Diseases Branch of NIDDK, had this idea to use this new wireless PH detecting SmartPill that you could swallow to determine how much acid your stomach was producing. There really was no noninvasive way to monitor how well medications would work for certain reflux diseases. What he wanted was a model of gastric acid secretion output based on the dynamics of PH when a buffer was added to design a protocol for the experiment. I came up with a simple mass-action model of acid buffering and made some graphs for him. We then tested the model out in a beaker. He thought the model worked better than I did but it was somewhat useful to him in designing the experiment.
BACKGROUND:Gastro-oesophageal reflux disease (GERD) and gastric acid hypersecretion respond well to suppression of gastric acid secretion. However, clinical management and research in diseases of acid secretion have been hindered by the lack of a non-invasive, accurate and reproducible tool to measure gastric acid output (GAO). Thus, symptoms or, in refractory cases, invasive testing may guide acid suppression therapy.
AIM:To present and validate a novel, non-invasive method of GAO analysis in healthy subjects using a wireless pH sensor, SmartPill (SP) (SmartPill Corporation, Buffalo, NY, USA).
METHODS:Twenty healthy subjects underwent conventional GAO studies with a nasogastric tube. Variables impacting liquid meal-stimulated GAO analysis were assessed by modelling and in vitro verification. Buffering capacity of Ensure Plus was empirically determined. SP GAO was calculated using the rate of acidification of the Ensure Plus meal. Gastric emptying scintigraphy and GAO studies with radiolabelled Ensure Plus and SP assessed emptying time, acidification rate and mixing. Twelve subjects had a second SP GAO study to assess reproducibility.
RESULTS:Meal-stimulated SP GAO analysis was dependent on acid secretion rate and meal-buffering capacity, but not on gastric emptying time. On repeated studies, SP GAO strongly correlated with conventional basal acid output (BAO) (r = 0.51, P = 0.02), maximal acid output (MAO) (r = 0.72, P = 0.0004) and peak acid output (PAO) (r = 0.60, P = 0.006). The SP sampled the stomach well during meal acidification.
CONCLUSIONS:SP GAO analysis is a non-invasive, accurate and reproducible method for the quantitative measurement of GAO in healthy subjects. SP GAO analysis could facilitate research and clinical management of GERD and other disorders of gastric acid secretion.
I recently wrote about Michael Houghton declining the prestigious Gairdner prize because it left out two critical contributors to the discovery of the Hepatitis C virus. Houghton has now written an opinion piece in Nature Medicine arguing that prizes relax the restriction to three awardees, an arbitrary number I’ve never understood. After all, one could argue that Freeman Dyson had a reasonable claim on the Nobel Prize awarded to Feynman, Schwinger, and Tomonaga for QED. I’ve quoted the entire piece below.
Nature Medicine: Earlier this year, I was greatly honored with the offer of a 2013 Canada Gairdner International Award for my contributions to the discovery of the hepatitis C virus (HCV). I was selected along with Harvey Alter, chief of clinical studies in the Department of Transfusion Medicine at the US National Institutes of Health’s Clinical Center in Bethesda, Maryland, and Daniel Bradley, a consultant at the US Centers for Disease Control and Prevention in Atlanta, both of whom had a vital role in the research that eventually led to the identification and characterization of the virus.
My colleagues accepted their awards. However, I declined my C$100,000 ($98,000) prize because it excluded two other key contributors who worked with me closely to successfully isolate the viral genome for the first time. I felt that given their crucial inputs, it would be wrong of me to keep accepting major prizes just ‘on their behalf’, a situation that has developed because major award foundations and committees around the world insist that prizes be limited to no more than three recipients per topic.
HCV was identified in 1989 in my laboratory at the Chiron Corporation, a California biotechnology firm since purchased by the Swiss drug company Novartis. The discovery was the result of seven years of research in which I worked closely, both intellectually and experimentally, with Qui-Lim Choo, a member of my own laboratory, and George Kuo, who had his own laboratory next door to mine at Chiron. We finally identified the virus using a technically risky DNA-expression screening technique through which we isolated a single small nucleic acid clone from among many millions of such clones from different recombinant libraries. This was achieved without the aid of the still-evolving PCR technology to amplify the miniscule amounts of viral nucleic acid present in blood. We ultimately proved that this clone derived from a positive-stranded viral RNA genome intimately associated with hepatitis, but one not linked to either the hepatitis A or B viruses1, 2. The finding represented the first time any virus had been identified without either prior visualization of the virus itself, characterization of its antigens or viral propagation in cell culture.
The high-titer infectious chimpanzee plasma used for our molecular analyses at Chiron was provided in 1985 by Bradley, an expert in chimpanzee transmission of HCV and in the virus’s basic properties and cellular responses, with whom I had an active collaboration since 1982. The proposed aim of the collaboration was for my laboratory to apply contemporary molecular cloning methodologies to a problem that had proven intractable since the mid-1970s, when Alter and his colleagues first demonstrated the existence of non-A, non-B hepatitis (NANBH), as it was then known. Alter’s team went on to define the high incidence and medical importance of NANBH, including the virus’s propensity to cause liver fibrosis, cirrhosis and cancer. They also identified high-titer infectious human plasma in 1980 and were instrumental in promoting the adoption of surrogate tests for NANBH by blood banks to reduce the incidence of post-transfusion infection.
With regrets to the Gairdner Foundation—a generous and altruistic organization—I felt compelled to decline the International Gairdner Award without the addition of Kuo and Choo to the trio of scientists offered the award. In 1992, all five of us received the Karl Landsteiner Memorial Award from the American Association of Blood Banks. But subsequent accolades given in honor of HCV’s discovery have omitted key members of the group: only Bradley and I received the 1993 Robert Koch Prize, and only Alter and I won the 2000 Albert Lasker Award for Clinical Medical Research—in both cases, despite my repeated requests that the other scientists involved in the discovery be recognized. With the exclusion once more of Kuo and Choo from this year’s Gairdner Award, I decided that I should not continue to accept major awards without them. In doing so, I became the first person since the Gairdner’s inception in 1959 to turn down the prize.
I hope that my decision helps bring attention to a fundamental problem with many scientific prizes today. Although some awards, such as the Landsteiner, are inclusionary and emphasize outstanding team accomplishments, the majority of the world’s prestigious scientific awards—including the Gairdner, Lasker and Shaw prizes, which all seem to be modeled on the Nobel Prize and indeed are sometimes known as the ‘baby Nobels’—are usually restricted to at most three individuals per discovery. Unsurprisingly, this limitation often leads to controversy, when one or more worthy recipients are omitted from the winners list.
Perhaps what may help this situation is for awards committees to solicit, and then be responsive to, input from potential recipients themselves prior to making their final decisions. Some of the recipients are best placed to know the full and often intricate history of the discovery and collaborative efforts, and such input should help committees better understand the size of the contributing team from which they can then choose recipients according to each award’s particular policy.
With this information in hand, award organizers should be willing to award more than three researchers. As knowledge and technology grows exponentially around the world and with an increasing need for multidisciplinary collaborations to address complex questions and problems, there is a case to be made for award committees adjusting to this changing paradigm. Moreover, it is inherently unfair to exclude individuals who played a key part in the discovery. Why should they and their families suffer such great disappointment after contributing such crucial input? Some award restructuring could also be inspirational to young scientists, encouraging them to be highly interactive and collaborative in the knowledge that when a novel, long-shot idea or approach actually translates to scientific success, all key parties will be acknowledged appropriately.
In this vein, I am happy to note that the inaugural Queen Elizabeth Prize for Engineering, a new £1 million ($1.6 million) prize from the UK government, was awarded at a formal ceremony last month to five individuals who helped create the internet and the World Wide Web, even though the original guidelines stipulated a maximum of three recipients. If the Queen of England—the very emblem of tradition—can cast protocol aside, clearly other institutions can too. I hope more awards committees will follow Her Majesty’s lead.
The Obama administration has decided to delay by one year the implementation of the employer health care mandate for businesses with more than 50 employees. The fear was that companies with slightly more than 50 employees would simply lay off or convert to part-time the workers above the threshold to avoid the penalties. I think in general thresholds are a bad idea for economic and tax policy as they provide an incentive to game the system. They should be replaced by smooth scales. US federal income taxes have a small number of rigid brackets for which income above a certain amount is taxed at a higher rate. This should be replaced by a smooth function so the tax rate for an extra dollar earned will only be slightly higher than the previous dollar. The shape of the function can be debated but a smooth one would certainly work better than the current discontinuous one. In terms of the employer mandate for providing health care, a smooth phased-in penalty would avoid the incentives for companies to manipulate the number of employees they have.