Can small institutes address some problems facing biomedical researchers?

At a time of historically low National Institutes of Health funding rates and many problems with the conduct of research (unfunded mandates, disgruntled reviewers, and rampant paranoia), there is a concern that biomedical research as a profession is waning in the United States (see ”Rescuing US biomedical research from its systemic flaws” by Alberts and colleagues in the Proceedings of the National Academy of Sciences). However, it is wonderful to discover something new and to tackle tough puzzles. If we could focus more of our effort on discussing scientific problems and doing research, then we could be more productive and perhaps happier. One potential solution is to focus efforts on small thematic institutes in the university structure that can provide a stimulating and supportive environment for innovation and exploration. With an open-lab concept, there are economies of scale that can diminish paperwork and costs, while providing greater access to state-of-the-art equipment. Merging multiple disciplines around a common theme can catalyze innovation, and this enables individuals to develop new concepts without giving up the credit they deserve, because it is usually clear who did the work. Small institutes do not solve larger systemic problems but rather enable collective efforts to address the noisome aspects of the system and foster an innovative community effort to address scientific problems.     

An open science pathway for drug marketing authorization—Registered drug approval

Florian Naudet and co-authors propose a pathway involving registered criteria for evaluation and approval of new drugs.

Publisher’s note: This Perspective is one of the two winning Essays of the “Reimagine biomedical research for a healthier future” Essay challenge, launched by the Health Research Alliance in partnership with PLOS. This publication is coordinated with that of the other winning Essay in PLOS Biology. The competition was intended to spark a discussion around the future of biomedical research; publication does not imply endorsement from HRA or PLOS.

     

A view from the NIH bridge: perspectives of a program officer

This essay is written from my perspective as a program officer for research and training activities at the National Institute of General Medical Sciences (NIGMS) for almost 27 yr. It gives a bird's-eye view of the job of a program officer, which includes providing advice to applicants and grantees, making funding recommendations, overseeing grantees' progress, facilitating scientific opportunities in specific areas of program responsibility, and shaping NIGMS and National Institutes of Health (NIH) policy. I have highlighted the numerous rewards of serving as a program officer, as well as some of the difficulties. For those who may be considering a position as an NIH program officer now or in the future, I've also described the qualities and qualifications that are important for such a career choice. Finally, this essay addresses some of the challenges for the NIH and the research community in the years ahead as we simultaneously face exciting scientific opportunities and tighter budgets.     

Survey of Academic Field Experiences (SAFE): Trainees Report Harassment and Assault

Little is known about the climate of the scientific fieldwork setting as it relates to gendered experiences, sexual harassment, and sexual assault. We conducted an internet-based survey of field scientists (N = 666) to characterize these experiences. Codes of conduct and sexual harassment policies were not regularly encountered by respondents, while harassment and assault were commonly experienced by respondents during trainee career stages. Women trainees were the primary targets; their perpetrators were predominantly senior to them professionally within the research team. Male trainees were more often targeted by their peers at the research site. Few respondents were aware of mechanisms to report incidents; most who did report were unsatisfied with the outcome. These findings suggest that policies emphasizing safety, inclusivity, and collegiality have the potential to improve field experiences of a diversity of researchers, especially during early career stages. These include better awareness of mechanisms for direct and oblique reporting of harassment and assault and, the implementation of productive response mechanisms when such behaviors are reported. Principal investigators are particularly well positioned to influence workplace culture at their field sites.     

Scientific approaches to science policy

The development of robust science policy depends on use of the best available data, rigorous analysis, and inclusion of a wide range of input. While director of the National Institute of General Medical Sciences (NIGMS), I took advantage of available data and emerging tools to analyze training time distribution by new NIGMS grantees, the distribution of the number of publications as a function of total annual National Institutes of Health support per investigator, and the predictive value of peer-review scores on subsequent scientific productivity. Rigorous data analysis should be used to develop new reforms and initiatives that will help build a more sustainable American biomedical research enterprise.Good scientists almost invariably insist on obtaining the best data potentially available and fostering open and direct communication and criticism to address scientific problems. Remarkably, this same approach is only sometimes used in the context of the development of science policy. In my opinion, several factors underlie the reluctance to apply scientific methods rigorously to inform science policy questions. First, obtaining the relevant data can be challenging and time-consuming. Tools relatively unfamiliar to many scientists may be required, and the data collected may have inherent limitations that make their use challenging. Second, reliance on data may require the abandonment of preconceived notions and a willingness to face potentially unwanted political consequences, depending on where the data analysis leads.One of my first experiences witnessing the application of a rigorous approach to a policy question involved previous American Society for Cell Biology Public Service awardee Tom Pollard when he and I were both at Johns Hopkins School of Medicine. Tom was leading an effort to reorganize the first-year medical school curriculum, trying to move toward an integrated plan and away from an entrenched departmentally based system (DeAngelis, 2000 ). He insisted that every lecture in the old curriculum be on the table for discussion, requiring frank discussions and defusing one of the most powerful arguments in academia: “But, we''ve always done it that way.” As the curriculum was being implemented, he recruited a set of a dozen or so students who were tasked with filling out questionnaires immediately after every lecture; this enabled evaluation and refinement of the curriculum and yielded a data set that changed the character of future discussions.After 13 years as a department director at Johns Hopkins (including a number of years as course director for the Molecules and Cells course in the first-year medical school curriculum), I had the opportunity to become director of the National Institute of General Medical Sciences (NIGMS) at the National Institutes of Health (NIH). NIH supports large data systems, as these are essential for NIH staff to perform their work in receiving, reviewing, funding, and monitoring research grants. While these rich data sources were available, the resources for analysis were not as sophisticated as they could have been. This became apparent when we tried to understand how long successful young scientists spent at various early-career stages (in graduate school, doing postdoctoral fellowships, and in faculty positions before funding). This was a relatively simple question to formulate, but it took considerable effort to collect the data because the relevant data were in free-text form. An intrepid staff member took on the challenge, and went through three years’ worth of biosketches by hand to find 360 individuals who had received their first R01 awards from NIGMS and then compiled data on the years those individuals had graduated from college, completed graduate school, started their faculty positions, and received their R01 awards. Analysis of these data revealed that the median time from BS/BA to R01 award was ∼15 years, including a median of 3.6 years between starting a faculty position and receiving the grant. These results were presented to the NIGMS Advisory Council but were not shared more widely, because of the absence of a good medium at the time for reporting such results. I did provide them subsequently through a blog in the context of a discussion of similar issues (DrugMonkey, 2012 ). To address the communications need, we had developed the NIGMS Feedback Loop, first as an electronic newsletter (NIGMS, 2005 ) and subsequently as a blog (NIGMS, 2009 ). This vehicle has been of great utility for bidirectional communication, particularly under unusual circumstances. For example, during the period prior to the implementation of the American Recovery and Reinvestment Act, that is, the “stimulus bill,” I shared our thoughts and solicited input from the community. I subsequently received and answered hundreds of emails that offered reactions and suggestions. Having these admittedly nonscientific survey data in hand was useful in subsequent NIH-wide policy-development discussions.At this point, staff members at several NIH institutes, including NIGMS, were developing tools for data analysis, including the ability to link results from different data systems. Many of the questions I was most eager to address involved the relationship between scientific productivity and other parameters, including the level of grant support and the results of peer review that led to funding in the first place. With an initial system that was capable of linking NIH-funded investigators to publications, I performed an analysis of the number of publications from 2007 to mid-2010 attributed to NIH funding as a function of the total amount of annual NIH direct-cost support for 2938 NIGMS-funded investigators from fiscal year 2006 (Berg, 2010 ). The results revealed that the number of publications did not increase monotonically but rather reached a plateau near an annual funding level near $700,000. This observation received considerable attention (Wadman, 2010 ) and provided support for a long-standing NIGMS policy of imposing an extra level of oversight for well-funded investigators. It is important to note that, not surprisingly, there was considerable variation in the number of publications at all funding levels and, in my opinion, this observation is as important as the plateau in moving policies away from automatic caps and toward case-by-case analysis by staff armed with the data.This analysis provoked considerable discussion on the Feedback Loop blog and elsewhere regarding whether the number of publications was an appropriate measure of productivity. With better tools, it was possible to extend such analyses to other measures, including the number of citations, the number of citations relative to other publications, and many other factors. This extended set of metrics was applied to an analysis of the ability of peer-review scores to predict subsequent productivity (Berg, 2012a , b ). Three conclusions were supported by this analysis. First, the various metrics were sufficiently correlated with one another that the choice of metric did not affect any major conclusions (although metrics such as number of citations performed slightly better than number of publications). Second, peer-review scores could predict subsequent productivity to some extent (compared with randomly assigned scores), but the level of prediction was modest. Importantly, this provided some of the first direct evidence that peer review is capable of identifying applications that are more likely to be productive. Finally, the results revealed no noticeable drop-off in productivity, even near the 20th percentile, supporting the view that a substantial amount of productive science is being left unfunded with pay lines below the 20th percentile, let alone the 10th percentile.In 2011, I moved to the University of Pittsburgh and also became president-elect of the American Society for Biochemistry and Molecular Biology (ASBMB). In my new positions, I have been able to gain a more direct perspective on the current state of the academic biomedical research enterprise. It is exciting to be back in the trenches again. On the other hand, my observations support a conclusion I had drawn while I was at NIH: the biomedical research enterprise is not sustainable in its present form due not only to the level of federal support, but also to the duration of training periods, the number of individuals being trained to support the research effort, the lack of appropriate pathways for individuals interested in careers as bench scientists, challenges in the interactions between the academic and private sectors, and other factors. Working with the Public Affair Advisory Committee at ASBMB, we have produced a white paper (ASBMB, 2013 ) that we hope will help initiate conversations about imagining and then moving toward more sustainable models for biomedical research. We can expect to arrive at effective policy changes and initiatives only through data-driven and thorough self-examination and candid discussions between different stakeholders. We look forward to working with leaders and members from other scientific societies as we tackle this crucial set of issues.Open in a separate windowJeremy M. Berg     

A call for transparency in tracking student and postdoc career outcomes

There is a common misconception that the United States is suffering from a “STEM shortage,” a dearth of graduates with scientific, technological, engineering, and mathematical backgrounds. In biomedical science, however, we are likely suffering from the opposite problem and could certainly better tailor training to actual career outcomes. At the Future of Research Symposium, various workshops identified this as a key issue in a pipeline traditionally geared toward academia. Proposals for reform all ultimately come up against the same problem: there is a shocking lack of data at institutional and national levels on the size, shape, and successful careers of participants in the research workforce. In this paper, we call for improved institutional reporting of the number of graduate students and postdocs and their training and career outcomes.We and our fellow postdocs across the Boston area (from institutions including Tufts, Harvard Medical School, MIT, Brandeis, and Boston University) organized the Future of Research Symposium (http://futureofresearch.org). In so doing, we sought to give young scientists in Boston a voice in discussions of fundamental challenges facing the research enterprise, such as hypercompetition, skewed incentives, and an unsustainable workforce model (Alberts et al., 2014 ). During the symposium, attendees (largely postdocs and graduate students) participated in workshops designed to identify the most pressing concerns for trainees and to solicit their thoughts on possible solutions. While the complete outcomes of those sessions are listed in our meeting report (McDowell et al., 2015 ) and the supporting data (McDowell et al., 2015 , Data set 1), the organizing committee identified three principles crucial to building a more sustainable scientific enterprise, among them transparency in collecting and sharing information on the research workforce.Our culture is affected by a deeply ingrained notion that there is a “STEM shortage”—a dearth of graduates with scientific, technological, engineering, and mathematical backgrounds— an assertion that has been repeated too many times to count (Teitelbaum, 2014 ). For example, the President''s Council of Advisors on Science and Technology called for an additional one million science, technology, engineering, and mathematics (STEM) trainees in 2012 (PCAST, 2012 ). Yet a recent report by the Center for Immigration Studies using U.S. census data is one of a chorus of recent publications asserting that STEM graduates are actually struggling to get relevant jobs (Camarota and Zeigler, 2014 ). For example, only 11% of those who hold a bachelor''s degree in science actually work in a science field (table 2 in Camarota and Zeigler, 2014 ). This rhetoric is also blatantly misleading for PhD holders in biomedical science and probably lulls students interested in this path into a false sense of job security. The number of graduate students has roughly doubled from 1990 to 2012 along with a comparable increase in the number of postdocs (figures 1 and 5 in National Institutes of Health [NIH], 2012 ). Yet there is little evidence to suggest that permanent research positions, whether in academia or industry, have increased concomitantly. The problem has been eloquently summed up by Henry Bourne, referring to the swelling postdoc pool (Bourne, 2013a ) that becomes a “holding tank” (Bourne, 2013b ) from which PhD holders find great difficulty transitioning into permanent positions. Tellingly, in the National Science Foundation''s (NSF) Science and Engineering Indicators 2014 report, the most rapidly growing reason cited for starting a postdoc is “other employment not available” (table 5-19 in National Science Board, 2014, p. 5-34 ). Recent efforts to make PhD programs broadly applicable outside academia (through the NIH BEST grants and other efforts) have bolstered the argument that a PhD in biomedical sciences is broadly applicable for many careers, but a culture still exists in academia that graduate students should be training only for academic tracks. While there may be some argument for maintaining current levels of graduate student numbers, on the condition that they receive training relevant to their own career goals, the benefits of a large postdoctoral workforce are still being called sharply into question.Despite this, many leading officials have yet to take a position on the issue of the size of the workforce. For example, Sally Rockey and Francis Collins have written that “there is no definitive evidence that PhD production exceeds current employment opportunities” (Rockey and Collins, 2013 ).Technically, this is correct, but only because there are no definitive data at all. Take, for example, a very basic metric: How many postdocs are there in the U.S. research system? This is clearly a statistic that the NIH should have on hand to make the bold assertion that PhD numbers do not exceed employment opportunities: after all, many PhDs simply transition into becoming postdoctoral researchers. Except, the NIH does not know how many postdocs there are. The Boston Globe recently reported that, “The National Institutes of Health estimates there are somewhere between 37,000 and 68,000 postdocs in the country,” a tolerance of 15,500 (Johnson, 2014 ). The NIH''s Biomedical Research Workforce Working Group Report gives no concrete numbers, and it qualifies data it does show with “the number of postdoctoral researchers … may be underestimated by as much as a factor of 2” (National Institutes of Health, 2012, p. 2 ) One estimate puts the number at a little more than 50,000 (National Research Council, 2011 ), while the NSF, using data from the Survey of Graduate Students and Postdoctorates in Science and Engineering, estimates 63,000 postdocs, 44,000 of whom are in science and engineering (National Science Board, 2014 ). From data from Boston-area postdoctoral offices, we are certain the number of postdocs in the Boston area alone approaches 9000, and so we agree with the National Postdoctoral Association that all these estimates are too low and that the number of postdoctoral researchers in the United States is close to 90,000 (www.nationalpostdoc.org/policy-22/what-is-a-postdoc). But the fact that this number is up for debate at all speaks to a need for better accounting practices, especially since alarms have sounded at the pyramidal nature of the workforce for more than a decade (National Research Council, 1998 ; Kennedy et al., 2004 ).While data on the biomedical research workforce are still incomplete, anecdotal evidence suggests graduate students are finally becoming savvier about their professional futures. We conducted an informal poll of a dozen students from across the United States, asking them what they thought of the job market for PhDs at the time they accepted the offer to go to graduate school (Figure 1). Those who entered graduate school earlier reported not considering the job market before starting their PhD; by contrast, those who matriculated more recently reported low expectations, especially for academic careers. While our extremely small survey would suggest that some students are entering graduate school with no expectation of staying in academia whatsoever, their choices are by necessity based on hearsay rather than concrete information.Open in a separate windowFIGURE 1:Excerpted quotes from survey respondents. The question posed was “What did you think of the job market for PhDs at the time you accepted the offer to go to graduate school?” The year of matriculation is listed below each quote. Full responses are listed in Supplemental Table 1.Therefore we believe that graduate programs and postdoc offices have a moral imperative to inform students and fellows of what they are getting into. We call for increased efforts in collecting and sharing data on student and fellow demographics and career outcomes, such as by conducting thorough exit and alumni surveys. We also encourage our recently graduated peers to cooperate fully with such requests from our alma maters. In biomedical science, some institutions are leading the way on this front, with the University of California–San Francisco and Duke University''s Program in Cell and Molecular Biology posting some statistics online (UCSF Graduate Division, 2013 ; Duke University, 2015 ). We believe that there is an obligation for other institutions to follow their lead. In addition, we believe that a culture supporting transparency will ultimately strengthen the scientific enterprise.First, clear communication of career information may increase student and postdoc productivity down the road. While research shows that postdocs are able to accurately estimate their chances of attaining a faculty position (Sauermann, 2013 ), our experience suggests that many current graduate students do not gain this awareness until later in their careers. When rosy illusions are shattered only after an investment of many years, the ensuing disgruntlement can negatively impact trainees themselves, others in the lab, and even entire communities at particular institutions. Instead, making student outcomes more readily available is likely to select for students with realistic expectations of their training. Much like Orion Weiner''s finding that students with prior research experience subjectively perform better in graduate school, trainees who “know what they are getting into” may be more likely to display sustained motivation (Weiner, 2014 ).Second, disclosure of these data will act as a catalyst for change. Increased transparency of program outcomes will help hold institutions and programs accountable for the quality of training they provide. Also, increased awareness of the actual career paths chosen by trainees will encourage programs to offer training in skills apart from those required to conduct academic research. Increased instruction in writing, management, and leadership will benefit all trainees, including those who do stay in academic research.Students'' motivations for entering graduate school are already changing; academic institutions must now discard old rhetoric about the purpose of graduate school and confront this new landscape. It can no longer be acceptable to drive graduate programs purely toward academic career paths. While critics may worry that honesty could discourage some trainees from applying, it will also encourage those whose goals are better in line with their likely outcome. While the research enterprise is changing shape, students and postdocs deserve to enter it with their eyes open.     

The NIDDK Information Network: A Community Portal for Finding Data,Materials, and Tools for Researchers Studying Diabetes,Digestive, and Kidney Diseases

The NIDDK Information Network (dkNET; http://dknet.org) was launched to serve the needs of basic and clinical investigators in metabolic, digestive and kidney disease by facilitating access to research resources that advance the mission of the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK). By research resources, we mean the multitude of data, software tools, materials, services, projects and organizations available to researchers in the public domain. Most of these are accessed via web-accessible databases or web portals, each developed, designed and maintained by numerous different projects, organizations and individuals. While many of the large government funded databases, maintained by agencies such as European Bioinformatics Institute and the National Center for Biotechnology Information, are well known to researchers, many more that have been developed by and for the biomedical research community are unknown or underutilized. At least part of the problem is the nature of dynamic databases, which are considered part of the “hidden” web, that is, content that is not easily accessed by search engines. dkNET was created specifically to address the challenge of connecting researchers to research resources via these types of community databases and web portals. dkNET functions as a “search engine for data”, searching across millions of database records contained in hundreds of biomedical databases developed and maintained by independent projects around the world. A primary focus of dkNET are centers and projects specifically created to provide high quality data and resources to NIDDK researchers. Through the novel data ingest process used in dkNET, additional data sources can easily be incorporated, allowing it to scale with the growth of digital data and the needs of the dkNET community. Here, we provide an overview of the dkNET portal and its functions. We show how dkNET can be used to address a variety of use cases that involve searching for research resources.     

Abuse of residents: it's time to take action.

The scientific study of the sexual dynamics that come into play during residency training seems to both fascinate and repel trainees and their supervisors. One of the more provocative and shameful dimensions of this area of inquiry, the abuse of residents, causes a good deal of distress. How do we respond to findings of significant psychological abuse, discrimination on the basis of sex or sexual orientation and sexual harassment in medical settings? How can we ignore over a decade of research? How can we not heed the experience of so many young physicians? Given the uncertain times in Canadian medicine and the insecurity in our professional and personal lives, we must work together to improve the culture of our teaching institutions and implement measures nationally and locally to close this dark chapter.     

An Innovative Lab-Based Training Program to Help Patient Groups Understand Their Disease and the Research Process

Genuine partnership between patient groups and medical experts is important but challenging. Our training program meets this challenge by organizing hands-on, lab-based training sessions for members of patient groups. These sessions allow “trainees” to better understand their disease and the biomedical research process, and strengthen links between patients and local researchers. Over the past decade, we and our partner institutes have received more than 900 French patients, with the participation of over 60 researchers and clinicians.

This Community Page is part of the "Public Engagement in Science" Series.

     

Bio-Logic Builder: A Non-Technical Tool for Building Dynamical,Qualitative Models

Computational modeling of biological processes is a promising tool in biomedical research. While a large part of its potential lies in the ability to integrate it with laboratory research, modeling currently generally requires a high degree of training in mathematics and/or computer science. To help address this issue, we have developed a web-based tool, Bio-Logic Builder, that enables laboratory scientists to define mathematical representations (based on a discrete formalism) of biological regulatory mechanisms in a modular and non-technical fashion. As part of the user interface, generalized “bio-logic” modules have been defined to provide users with the building blocks for many biological processes. To build/modify computational models, experimentalists provide purely qualitative information about a particular regulatory mechanisms as is generally found in the laboratory. The Bio-Logic Builder subsequently converts the provided information into a mathematical representation described with Boolean expressions/rules. We used this tool to build a number of dynamical models, including a 130-protein large-scale model of signal transduction with over 800 interactions, influenza A replication cycle with 127 species and 200+ interactions, and mammalian and budding yeast cell cycles. We also show that any and all qualitative regulatory mechanisms can be built using this tool.     

Reciprocity on the Hardwood: Passing Patterns among Professional Basketball Players

Past theory and research view reciprocal resource sharing as a fundamental building block of human societies. Most studies of reciprocity dynamics have focused on trading among individuals in laboratory settings. But if motivations to engage in these patterns of resource sharing are powerful, then we should observe forms of reciprocity even in highly structured group environments in which reciprocity does not clearly serve individual or group interests. To this end, we investigated whether patterns of reciprocity might emerge among teammates in professional basketball games. Using data from logs of National Basketball Association (NBA) games of the 2008–9 season, we estimated a series of conditional logistic regression models to test the impact of different factors on the probability that a given player would assist another player in scoring a basket. Our analysis found evidence for a direct reciprocity effect in which players who had “received” assists in the past tended to subsequently reciprocate their benefactors. Further, this tendency was time-dependent, with the probability of repayment highest soon after receiving an assist and declining as game time passed. We found no evidence for generalized reciprocity – a tendency to “pay forward” assists – and only very limited evidence for indirect reciprocity – a tendency to reward players who had sent others many assists. These findings highlight the power of reciprocity to shape human behavior, even in a setting characterized by extensive planning, division of labor, quick decision-making, and a focus on inter-group competition.     

Mice in Bion-M 1 Space Mission: Training and Selection

After a 16-year hiatus, Russia has resumed its program of biomedical research in space, with the successful 30-day flight of the Bion-M 1 biosatellite (April 19–May 19, 2013). The principal species for biomedical research in this project was the mouse. This paper presents an overview of the scientific goals, the experimental design and the mouse training/selection program. The aim of mice experiments in the Bion-M 1 project was to elucidate cellular and molecular mechanisms, underlying the adaptation of key physiological systems to long-term exposure in microgravity. The studies with mice combined in vivo measurements, both in flight and post-flight (including continuous blood pressure measurement), with extensive in vitro studies carried out shortly after return of the mice and in the end of recovery study. Male C57/BL6 mice group housed in space habitats were flown aboard the Bion-M 1 biosatellite, or remained on ground in the control experiment that replicated environmental and housing conditions in the spacecraft. Vivarium control groups were used to account for housing effects and possible seasonal differences. Mice training included the co-adaptation in housing groups and mice adaptation to paste food diet. The measures taken to co-adapt aggressive male mice in housing groups and the peculiarities of “space” paste food are described. The training program for mice designated for in vivo studies was broader and included behavioral/functional test battery and continuous behavioral measurements in the home-cage. The results of the preliminary tests were used for the selection of homogenous groups. After the flight, mice were in good condition for biomedical studies and displayed signs of pronounced disadaptation to Earth''s gravity. The outcomes of the training program for the mice welfare are discussed. We conclude that our training program was effective and that male mice can be successfully employed in space biomedical research.     

Surprise Realistic Mock Disasters—The Most Effective Means of Disaster Training

Realism introduced in several large scale surprise mock-disaster tests proved to be a real challenge to a disaster-conscious hospital staff that had previously undergone fairly extensive disaster training and testing, utilizing conventional methods.Serious weaknesses, flaws, omissions and deficiencies in disaster capability were dramatically and conclusively revealed by use of what appeared to be a “live” disaster setting with smoke, fire, explosions; adverse weather and light conditions; realistically-simulated “casualites” especially prepared not only to look but to act the part; selected harassment incidents from well-documented disasters, such as utility failures, automobile accident on the main access route, overload of telephone switchboard, and invasion of hospital and disaster site by distraught relatives and the morbidly curious.     

Roles of leader and follower cells in collective cell migration

Collective cell migration is a widely observed phenomenon during animal development, tissue repair, and cancer metastasis. Considering its broad involvement in biological processes, it is essential to understand the basics behind the collective movement. Based on the topology of migrating populations, tissue-scale kinetics, called the “leader–follower” model, has been proposed for persistent directional collective movement. Extensive in vivo and in vitro studies reveal the characteristics of leader cells, as well as the special mechanisms leader cells employ for maintaining their positions in collective migration. However, follower cells have attracted increasing attention recently due to their important contributions to collective movement. In this Perspective, the current understanding of the molecular mechanisms behind the “leader–follower” model is reviewed with a special focus on the force transmission and diverse roles of leaders and followers during collective cell movement.     

Creating opportunities for science PhDs to pursue careers in high school education

The United States is confronting important challenges at both the early and late stages of science education. At the level of K–12 education, a recent National Research Council report (Successful K–12 STEM Education) proposed a bold restructuring of how science is taught, moving away from memorizing facts and emphasizing hands-on, inquiry-based learning and a deeper understanding of the process of science. At higher levels of training, limited funding for science is leading PhDs to seek training and careers in areas other than research. Might science PhDs play a bigger role in the future of K–12 education, particularly at the high school level? We explore this question by discussing the roles that PhDs can play in high school education and the current and rather extensive barriers to PhDs entering the teaching profession and finally suggest ways to ease the entrance of qualified PhDs into high school education.In many K–12 classrooms, science is presented as a series of textbook facts; students are not exposed to scientific methods of inquiry and lose interest in science. At the very opposite end of the science training pipeline, life science PhDs and postdocs in the United States are experiencing difficulties in finding university jobs, a situation that will likely persist in the coming decade if research funding fails to grow; we cannot expect all PhD graduates to become principal investigators (PIs) at academic institutions.Might these two problems add up to a solution (or at least a partial solution)? Is there a place for graduates of PhD training programs in teaching K–12 science, particularly at the high school (HS) level (the focus of this article)? We argue that the answer is “yes” and that more PhDs, even if their numbers are small compared with the entire teaching pool, could have a catalytic effect on reinvigorating precollege science education. This topic is not new; the National Research Council (NRC) issued two thoughtful reports on attracting science and math PhDs to secondary school education more than a decade ago (Committee on Attracting Science and Mathematics Ph.D.s to Secondary School Teaching, National Research Council, 2000 ; Committee on Attracting Science and Mathematics PhDs to K-12 Education: From Analysis to Implementation, Division of Policy and Global Affairs, National Research Council, 2002 ). Their recommendations were not implemented, however, and the reports have largely been forgotten. Little has changed since then; the roadblocks, both in perception and logistics, that discouraged a PhD from becoming a HS teacher in the year 2000 still exist. Since the NRC reports were released, the topic of a HS teaching career option for a PhD has rarely been discussed or debated in our scientific community. We feel that it is time to reopen this discussion. The focus of this article is on PhDs entering the high school system, but much of this discussion also pertains to graduates of science master degree programs and to individuals with scientific training becoming involved in all levels of K–12 education. Our goal is to make students, postdocs, and senior scientists aware of the value of high school teaching for certain individuals as well as for our nation''s educational system. We also consider how changes at the local level (including the perception of K–12 teaching within research universities), as well as at the policy level of teacher accreditation, might facilitate this career path.     

Leveraging vibration of effects analysis for robust discovery in observational biomedical data science

Hypothesis generation in observational, biomedical data science often starts with computing an association or identifying the statistical relationship between a dependent and an independent variable. However, the outcome of this process depends fundamentally on modeling strategy, with differing strategies generating what can be called “vibration of effects” (VoE). VoE is defined by variation in associations that often lead to contradictory results. Here, we present a computational tool capable of modeling VoE in biomedical data by fitting millions of different models and comparing their output. We execute a VoE analysis on a series of widely reported associations (e.g., carrot intake associated with eyesight) with an extended additional focus on lifestyle exposures (e.g., physical activity) and components of the Framingham Risk Score for cardiovascular health (e.g., blood pressure). We leveraged our tool for potential confounder identification, investigating what adjusting variables are responsible for conflicting models. We propose modeling VoE as a critical step in navigating discovery in observational data, discerning robust associations, and cataloging adjusting variables that impact model output.

COVID positivity and vitamin D intake, red meat and heart disease; how can we discern when biomedical associations are reliable and when they are susceptible to our own arbitrary choices and assumptions? This study presents “quantvoe,” a software package for exploring the entirety of possible findings due to the multiverse of associations possible.     

"Willing to Pay?" Tax Compliance in Britain and Italy: An Experimental Analysis

As shown by the recent crisis, tax evasion poses a significant problem for countries such as Greece, Spain and Italy. While these societies certainly possess weaker fiscal institutions as compared to other EU members, might broader cultural differences between northern and southern Europe also help to explain citizens’ (un)willingness to pay their taxes? To address this question, we conduct laboratory experiments in the UK and Italy, two countries which straddle this North-South divide. Our design allows us to examine citizens’ willingness to contribute to public goods via taxes while holding institutions constant. We report a surprising result: when faced with identical tax institutions, redistribution rules and audit probabilities, Italian participants are significantly more likely to comply than Britons. Overall, our findings cast doubt upon “culturalist” arguments that would attribute cross-country differences in tax compliance to the lack of morality amongst southern European taxpayers.     

50 years of the Institute for Laboratory Animal Research (ILAR): 1953-2003

The history of the Institute for Laboratory Animal Research (ILAR) begins, as does all of laboratory animal science, with the ancient philosophers, anatomists, and physiologists whose work presaged the use of animals in biomedical research and the institutions that arose due to this use. Modern laboratory animal science and medicine began in the late 1940s and early 1950s as five Chicago-area institutions hired veterinarians to manage their animal facilities. Each of these men became instrumental in the founding of the organizations that collectively make up the laboratory animal science and medicine organizations. Nathan Brewer, one of the "Chicago five," was particularly influential in the founding of ILAR. His boss at the University of Chicago, Dr. Paul Weiss, a member of the National Academy of Sciences (NAS), asked him to help establish a committee with the stated purpose of preparing recommendations to the NAS to develop an office to obtain information on sources of supply for research animals. This office became ILAR, and Brewer was chairman of its first report on the diseases of laboratory animals. He was also a founding diplomat and first president of the American College of Laboratory Animal Medicine. This history recognizes the thoughtful and energetic contributions of scientists and veterinarians to ILAR. It provides a 50-year overview of the programs and reports of ILAR and highlights examples where these reports have been adopted by scientists and federal agencies and incorporated into national laws and policies governing the use of animals in research both in the United States and in other countries.