Reporting and misreporting of sex differences in the biological sciences.

As part of an initiative to improve rigor and reproducibility in biomedical research, the U.S. National Institutes of Health now requires the consideration of sex as a biological variable in preclinical studies. This new policy has been interpreted by some as a call to compare males and females with each other. Researchers testing for sex differences may not be trained to do so, however, increasing risk for misinterpretation of results. Using a list of recently published articles curated by Woitowich et al. (eLife, 2020; 9:e56344), we examined reports of sex differences and non-differences across nine biological disciplines. Sex differences were claimed in the majority of the 147 articles we analyzed; however, statistical evidence supporting those differences was often missing. For example, when a sex-specific effect of a manipulation was claimed, authors usually had not tested statistically whether females and males responded differently. Thus, sex-specific effects may be over-reported. In contrast, we also encountered practices that could mask sex differences, such as pooling the sexes without first testing for a difference. Our findings support the need for continuing efforts to train researchers how to test for and report sex differences in order to promote rigor and reproducibility in biomedical research.

Biomedical research has a long history of including only men or male laboratory animals in studies. To address this disparity, the United States National Institutes of Health (NIH) rolled out a policy in 2016 called Sex as a Biological Variable (or SABV). The policy requires researchers funded by the NIH to include males and females in every experiment unless there is a strong justification not to, such as studies of ovarian cancer. Since then, the number of research papers including both sexes has continued to grow. Although the NIH does not require investigators to compare males and females, many researchers have interpreted the SABV policy as a call to do so. This has led to reports of sex differences that would otherwise have been unrecognized or ignored. However, researchers may not be trained on how best to test for sex differences in their data, and if the data are not analyzed appropriately this may lead to misleading interpretations. Here, Garcia-Sifuentes and Maney have examined the methods of 147 papers published in 2019 that included both males and females. They discovered that more than half of these studies had reported sex differences, but these claims were not always backed by statistical evidence. Indeed, in a large majority (more than 70%) of the papers describing differences in how males and females responded to a treatment, the impact of the treatment was not actually statistically compared between the sexes. This suggests that sex-specific effects may be over-reported. In contrast, Garcia-Sifuentes and Maney also encountered instances where an effect may have been masked due to data from males and females being pooled together without testing for a difference first. These findings reveal how easy it is to draw misleading conclusions from sex-based data. Garcia-Sifuentes and Maney hope their work raises awareness of this issue and encourages the development of more training materials for researchers.

Europe PMC in 2020.

Europe PMC (https://europepmc.org) is a database of research articles, including peer reviewed full text articles and abstracts, and preprints - all freely available for use via website, APIs and bulk download. This article outlines new developments since 2017 where work has focussed on three key areas: (i) Europe PMC has added to its core content to include life science preprint abstracts and a special collection of full text of COVID-19-related preprints. Europe PMC is unique as an aggregator of biomedical preprints alongside peer-reviewed articles, with over 180 000 preprints available to search. (ii) Europe PMC has significantly expanded its links to content related to the publications, such as links to Unpaywall, providing wider access to full text, preprint peer-review platforms, all major curated data resources in the life sciences, and experimental protocols. The redesigned Europe PMC website features the PubMed abstract and corresponding PMC full text merged into one article page; there is more evident and user-friendly navigation within articles and to related content, plus a figure browse feature. (iii) The expanded annotations platform offers ∼1.3 billion text mined biological terms and concepts sourced from 10 providers and over 40 global data resources.

An institutional analysis of graduate outcomes reveals a contemporary workforce footprint for biomedical master's degrees.

There is continued growth in the number of master's degrees awarded in the life sciences to address the evolving needs of the biomedical workforce. Academic medical centers leverage the expertise of their faculty and industry partners to develop one to two year intensive and multidisciplinary master's programs that equip students with advanced scientific skills and practical training experiences. However, there is little data published on the outcomes of these graduates to evaluate the effectiveness of these programs and to inform the return on investment of students. Here, the authors show the first five-year career outlook for master of science graduates from programs housed at an academic medical center. Georgetown University Biomedical Graduate Education researchers analyzed the placement outcomes of 1,204 graduates from 2014-2018, and the two-year outcomes of 412 graduates from 2016 and 2017. From the 15 M.S. programs analyzed, they found that 69% of graduates entered the workforce, while 28% entered an advanced degree program such as a Ph.D., allopathic or osteopathic medicine (M.D. or D.O.), or health professions degree. International students who pursue advanced degrees largely pursued Ph.D. degrees, while domestic students represent the majority of students entering into medical programs. Researchers found that a majority of the alumni that entered the workforce pursue research-based work, with 59% of graduates conducting research-based job functions across industries. Forty-nine percent of employed graduates analyzed from 2016 and 2017 changed employment positions, while 15% entered advanced degree programs. Alumni that changed positions changed companies in the same job function, changed to a position of increasing responsibility in the same or different organization, or changed to a different job function in the same or different company. Overall, standalone master's programs equip graduates with research skills, analytical prowess, and content expertise, strengthening the talent pipeline of the biomedical workforce.

The COVID-19 response illustrates that traditional academic reward structures and metrics do not reflect crucial contributions to modern science.

The COVID-19 pandemic has motivated many open and collaborative analytical research projects with real-world impact. However, despite their value, such activities are generally overlooked by traditional academic metrics. Science is ultimately improved by analytical work, whether ensuring reproducible and well-documented code to accompany papers, developing and maintaining flexible tools, sharing and curating data, or disseminating analysis to wider audiences. To increase the impact and sustainability of modern science, it will be crucial to ensure these analytical activities-and the people who do them-are valued in academia.

SCALEUS-FD: A FAIR Data Tool for Biomedical Applications.

The Semantic Web and Linked Data concepts and technologies have empowered the scientific community with solutions to take full advantage of the increasingly available distributed and heterogeneous data in distinct silos. Additionally, FAIR Data principles established guidelines for data to be Findable, Accessible, Interoperable, and Reusable, and they are gaining traction in data stewardship. However, to explore their full potential, we must be able to transform legacy solutions smoothly into the FAIR Data ecosystem. In this paper, we introduce SCALEUS-FD, a FAIR Data extension of a legacy semantic web tool successfully used for data integration and semantic annotation and enrichment. The core functionalities of the solution follow the Semantic Web and Linked Data principles, offering a FAIR REST API for machine-to-machine operations. We applied a set of metrics to evaluate its "FAIRness" and created an application scenario in the rare diseases domain.

The motivation for citizens' involvement in life sciences research is predicted by age and gender.

Open Science is an umbrella term encompassing multiple concepts as open access to publications, open data, open education and citizen science that aim to make science more open and transparent. Citizen science, an important facet of Open Science, actively involves non-scientists in the research process, and can potentially be beneficial for multiple actors, such as scientists, citizens, policymakers and society in general. However, the reasons that motivate different segments of the public to participate in research are still understudied. Therefore, based on data gathered from a survey conducted in Czechia, Germany, Italy, Spain, Sweden, and the UK (N = 5,870), this study explores five types of incentives that can motivate individuals to become involved in life sciences research. The results demonstrate that men and younger individuals are more persuaded by extrinsic motives (external benefits or rewards), as compared with women and older people, who are driven by intrinsic motives (that originates from within an individual). This paper shows that specific strata of the population are differentially motivated to engage in research, thereby providing relevant knowledge for effectively designing public involvement activities that target various groups of the public in research projects.

[Determinants of patents in the life sciences and health sciences at federal universities in Minas Gerais State, Brazil: an analysis of panel data for 1995-2016]. / Determinantes das patentes em ciências da vida e da saúde nas universidades federais de Minas Gerais, Brasil: uma análise de dados em painel para o período 1995-2016.

In the 1990s, the development of microelectronics and communication technologies spawned the information technology paradigm, characterized by an intensity of information which, transformed into knowledge and innovation, plays a crucial role for development. In order for this to occur, countries need to build appropriate institutional arrangements. This led to the Triple Helix model for systems innovation, which views innovation and technical progress in a Knowledge Economy as the result of a complex set of relations between universities, companies, and government. In this context, the current study aims to identify the impact of knowledge production and public policies for the production of patent applications by life sciences and health sciences researchers affiliated with federal universities in the State of Minas Gerais, Brazil. The analysis covered the years 1995 to 2016 and used econometric techniques in panel data. According to the findings, educational factors (thesis supervision), economic factors (technological products and the provision of technological services), and political factors (legal framework, financial resources, and incentive policies) impact the production of patent applications by the selected researchers. The results reveal efforts by government, although incipient, in the attempt to promote a technological leap.

Na década de 1990, com o desenvolvimento da microeletrônica e das tecnologias de comunicações, emergiu o paradigma da tecnologia da informação, caracterizado pela intensidade de informação que, transformada em conhecimento e inovação, desempenha um papel crucial para o desenvolvimento. Entretanto, para que isso ocorra, é necessário que os países construam arranjos institucionais apropriados. Com isso, surge o modelo de sistemas de inovação da Tríplice Hélice, que compreende a inovação e o progresso técnico, em uma Economia do Conhecimento, como o resultado de um conjunto complexo de relações entre universidade, empresa e governo. Nesse contexto, o presente estudo tem o objetivo de identificar o impacto da produção de conhecimento e das políticas públicas para a produção de depósitos de patentes dos pesquisadores pertencentes ao domínio científico Ciências da Vida e da Saúde, no âmbito das universidades federais de Minas Gerais, Brasil. A análise considerou o período de 1995 a 2016, e utilizou técnicas de econometria em painel de dados. Os resultados mostram que fatores educacionais (orientações em pós-graduação), econômicos (produtos tecnológicos e prestação de serviços tecnológicos) e políticos (arcabouço legal, recursos financeiros e políticas de estímulo) impactam a produção de depósitos de patentes dos pesquisadores selecionados. Por meio da análise dos resultados, podem-se perceber os esforços do governo, mesmo que ainda incipientes, na tentativa de promover o salto tecnológico.

Durante la década de 1990, con el desarrollo de la microelectrónica y las tecnologías de la comunicación, surgió el paradigma de la tecnología de la información, caracterizado por la intensidad de información que, transformada en conocimiento e innovación, desempeña un papel crucial para el desarrollo. No obstante, para que esto ocurra, es necesario que los países construyan marcos institucionales apropiados. Por ello, surge el modelo de sistemas de innovación de Triple Hélice, que abarca innovación y progreso técnico en una Economía del Conocimiento, como resultado de un conjunto complejo de relaciones entre universidad, empresa y gobierno. En este contexto, el presente estudio tiene como objetivo de identificar el impacto de la producción de conocimiento y de las políticas públicas, con el fin de producir depósitos para patentes de investigadores, pertenecientes al campo científico de las Ciencias de la Vida y la Salud, en el ámbito de las universidades federales de Minas Gerais, Brasil. El análisis consideró el período de 1995 a 2016, y utilizó técnicas de econometría de panel de datos. Los resultados muestran que los factores educacionales (orientación durante el posgrado), económicos (productos tecnológicos y prestación de servicios tecnológicos) y políticos (marco legal, recursos financieros y políticas de estímulo) impactan en la producción de depósitos para patentes de los investigadores seleccionados. Mediante el análisis de los resultados, se pueden percibir los esfuerzos del gobierno, aunque sean incipientes, en la tentativa de promover el salto tecnológico.

Detecting the contagion effect in mass killings; a constructive example of the statistical advantages of unbinned likelihood methods.

BACKGROUND: When attempting to statistically distinguish between a null and an alternative hypothesis, many researchers in the life and social sciences turn to binned statistical analysis methods, or methods that are simply based on the moments of a distribution (such as the mean, and variance). These methods have the advantage of simplicity of implementation, and simplicity of explanation. However, when null and alternative hypotheses manifest themselves in subtle differences in patterns in the data, binned analysis methods may be insensitive to these differences, and researchers may erroneously fail to reject the null hypothesis when in fact more sensitive statistical analysis methods might produce a different result when the null hypothesis is actually false. Here, with a focus on two recent conflicting studies of contagion in mass killings as instructive examples, we discuss how the use of unbinned likelihood methods makes optimal use of the information in the data; a fact that has been long known in statistical theory, but perhaps is not as widely appreciated amongst general researchers in the life and social sciences. METHODS: In 2015, Towers et al published a paper that quantified the long-suspected contagion effect in mass killings. However, in 2017, Lankford & Tomek subsequently published a paper, based upon the same data, that claimed to contradict the results of the earlier study. The former used unbinned likelihood methods, and the latter used binned methods, and comparison of distribution moments. Using these analyses, we also discuss how visualization of the data can aid in determination of the most appropriate statistical analysis methods to distinguish between a null and alternate hypothesis. We also discuss the importance of assessment of the robustness of analysis results to methodological assumptions made (for example, arbitrary choices of number of bins and bin widths when using binned methods); an issue that is widely overlooked in the literature, but is critical to analysis reproducibility and robustness. CONCLUSIONS: When an analysis cannot distinguish between a null and alternate hypothesis, care must be taken to ensure that the analysis methodology itself maximizes the use of information in the data that can distinguish between the two hypotheses. The use of binned methods by Lankford & Tomek (2017), that examined how many mass killings fell within a 14 day window from a previous mass killing, substantially reduced the sensitivity of their analysis to contagion effects. The unbinned likelihood methods used by Towers et al (2015) did not suffer from this problem. While a binned analysis might be favorable for simplicity and clarity of presentation, unbinned likelihood methods are preferable when effects might be somewhat subtle.

How do physicians become medical experts? A test of three competing theories: distinct domains, independent influence and encapsulation models.

The distinction between basic sciences and clinical knowledge which has led to a theoretical debate on how medical expertise is developed has implications for medical school and lifelong medical education. This longitudinal, population based observational study was conducted to test the fit of three theories-knowledge encapsulation, independent influence, distinct domains-of the development of medical expertise employing structural equation modelling. Data were collected from 548 physicians (292 men-53.3%; 256 women-46.7%; mean age = 24.2 years on admission) who had graduated from medical school 2009-2014. They included (1) Admissions data of undergraduate grade point average and Medical College Admission Test sub-test scores, (2) Course performance data from years 1, 2, and 3 of medical school, and (3) Performance on the NBME exams (i.e., Step 1, Step 2 CK, and Step 3). Statistical fit indices (Goodness of Fit Index-GFI; standardized root mean squared residual-SRMR; root mean squared error of approximation-RSMEA) and comparative fit [Formula: see text] of three theories of cognitive development of medical expertise were used to assess model fit. There is support for the knowledge encapsulation three factor model of clinical competency (GFI = 0.973, SRMR = 0.043, RSMEA = 0.063) which had superior fit indices to both the independent influence and distinct domains theories ([Formula: see text] vs [Formula: see text] [[Formula: see text]] vs [Formula: see text] [[Formula: see text]], respectively). The findings support a theory where basic sciences and medical aptitude are direct, correlated influences on clinical competency that encapsulates basic knowledge.

Determinantes das patentes em ciências da vida e da saúde nas universidades federais de Minas Gerais, Brasil: uma análise de dados em painel para o período 1995-2016 / Determinants of patents in the life sciences and health sciences at federal universities in Minas Gerais State, Brazil: an analysis of panel data for 1995-2016 / Determinantes de las patentes en el ámbito de las ciencias de la vida y la salud en universidades federales de Minas Gerais, Brasil: un análisis de datos de panel durante el período 1995-2016

Na década de 1990, com o desenvolvimento da microeletrônica e das tecnologias de comunicações, emergiu o paradigma da tecnologia da informação, caracterizado pela intensidade de informação que, transformada em conhecimento e inovação, desempenha um papel crucial para o desenvolvimento. Entretanto, para que isso ocorra, é necessário que os países construam arranjos institucionais apropriados. Com isso, surge o modelo de sistemas de inovação da Tríplice Hélice, que compreende a inovação e o progresso técnico, em uma Economia do Conhecimento, como o resultado de um conjunto complexo de relações entre universidade, empresa e governo. Nesse contexto, o presente estudo tem o objetivo de identificar o impacto da produção de conhecimento e das políticas públicas para a produção de depósitos de patentes dos pesquisadores pertencentes ao domínio científico Ciências da Vida e da Saúde, no âmbito das universidades federais de Minas Gerais, Brasil. A análise considerou o período de 1995 a 2016, e utilizou técnicas de econometria em painel de dados. Os resultados mostram que fatores educacionais (orientações em pós-graduação), econômicos (produtos tecnológicos e prestação de serviços tecnológicos) e políticos (arcabouço legal, recursos financeiros e políticas de estímulo) impactam a produção de depósitos de patentes dos pesquisadores selecionados. Por meio da análise dos resultados, podem-se perceber os esforços do governo, mesmo que ainda incipientes, na tentativa de promover o salto tecnológico.

In the 1990s, the development of microelectronics and communication technologies spawned the information technology paradigm, characterized by an intensity of information which, transformed into knowledge and innovation, plays a crucial role for development. In order for this to occur, countries need to build appropriate institutional arrangements. This led to the Triple Helix model for systems innovation, which views innovation and technical progress in a Knowledge Economy as the result of a complex set of relations between universities, companies, and government. In this context, the current study aims to identify the impact of knowledge production and public policies for the production of patent applications by life sciences and health sciences researchers affiliated with federal universities in the State of Minas Gerais, Brazil. The analysis covered the years 1995 to 2016 and used econometric techniques in panel data. According to the findings, educational factors (thesis supervision), economic factors (technological products and the provision of technological services), and political factors (legal framework, financial resources, and incentive policies) impact the production of patent applications by the selected researchers. The results reveal efforts by government, although incipient, in the attempt to promote a technological leap.

Durante la década de 1990, con el desarrollo de la microelectrónica y las tecnologías de la comunicación, surgió el paradigma de la tecnología de la información, caracterizado por la intensidad de información que, transformada en conocimiento e innovación, desempeña un papel crucial para el desarrollo. No obstante, para que esto ocurra, es necesario que los países construyan marcos institucionales apropiados. Por ello, surge el modelo de sistemas de innovación de Triple Hélice, que abarca innovación y progreso técnico en una Economía del Conocimiento, como resultado de un conjunto complejo de relaciones entre universidad, empresa y gobierno. En este contexto, el presente estudio tiene como objetivo de identificar el impacto de la producción de conocimiento y de las políticas públicas, con el fin de producir depósitos para patentes de investigadores, pertenecientes al campo científico de las Ciencias de la Vida y la Salud, en el ámbito de las universidades federales de Minas Gerais, Brasil. El análisis consideró el período de 1995 a 2016, y utilizó técnicas de econometría de panel de datos. Los resultados muestran que los factores educacionales (orientación durante el posgrado), económicos (productos tecnológicos y prestación de servicios tecnológicos) y políticos (marco legal, recursos financieros y políticas de estímulo) impactan en la producción de depósitos para patentes de los investigadores seleccionados. Mediante el análisis de los resultados, se pueden percibir los esfuerzos del gobierno, aunque sean incipientes, en la tentativa de promover el salto tecnológico.

MAGPIE: Simplifying access and execution of computational models in the life sciences.

Over the past decades, quantitative methods linking theory and observation became increasingly important in many areas of life science. Subsequently, a large number of mathematical and computational models has been developed. The BioModels database alone lists more than 140,000 Systems Biology Markup Language (SBML) models. However, while the exchange within specific model classes has been supported by standardisation and database efforts, the generic application and especially the re-use of models is still limited by practical issues such as easy and straight forward model execution. MAGPIE, a Modeling and Analysis Generic Platform with Integrated Evaluation, closes this gap by providing a software platform for both, publishing and executing computational models without restrictions on the programming language, thereby combining a maximum on flexibility for programmers with easy handling for non-technical users. MAGPIE goes beyond classical SBML platforms by including all models, independent of the underlying programming language, ranging from simple script models to complex data integration and computations. We demonstrate the versatility of MAGPIE using four prototypic example cases. We also outline the potential of MAGPIE to improve transparency and reproducibility of computational models in life sciences. A demo server is available at magpie.imb.medizin.tu-dresden.de.

Using egocentric analysis to investigate professional networks and productivity of graduate students and faculty in life sciences in Japan, Singapore, and Taiwan.

Prior studies showed that scientists' professional networks contribute to research productivity, but little work has examined what factors predict the formation of professional networks. This study sought to 1) examine what factors predict the formation of international ties between faculty and graduate students and 2) identify how these international ties would affect publication productivity in three East Asian countries. Face-to-face surveys and in-depth semi-structured interviews were conducted with a sample of faculty and doctoral students in life sciences at 10 research institutions in Japan, Singapore, and Taiwan. Our final sample consisted of 290 respondents (84 faculty and 206 doctoral students) and 1,435 network members. We used egocentric social network analysis to examine the structure of international ties and how they relate to research productivity. Our findings suggest that overseas graduate training can be a key factor in graduate students' development of international ties in these countries. Those with a higher proportion of international ties in their professional networks were likely to have published more papers and written more manuscripts. For faculty, international ties did not affect the number of manuscripts written or of papers published, but did correlate with an increase in publishing in top journals. The networks we examined were identified by asking study participants with whom they discuss their research. Because the relationships may not appear in explicit co-authorship networks, these networks were not officially recorded elsewhere. This study sheds light on the relationships of these invisible support networks to researcher productivity.

Identifiers for the 21st century: How to design, provision, and reuse persistent identifiers to maximize utility and impact of life science data.

In many disciplines, data are highly decentralized across thousands of online databases (repositories, registries, and knowledgebases). Wringing value from such databases depends on the discipline of data science and on the humble bricks and mortar that make integration possible; identifiers are a core component of this integration infrastructure. Drawing on our experience and on work by other groups, we outline 10 lessons we have learned about the identifier qualities and best practices that facilitate large-scale data integration. Specifically, we propose actions that identifier practitioners (database providers) should take in the design, provision and reuse of identifiers. We also outline the important considerations for those referencing identifiers in various circumstances, including by authors and data generators. While the importance and relevance of each lesson will vary by context, there is a need for increased awareness about how to avoid and manage common identifier problems, especially those related to persistence and web-accessibility/resolvability. We focus strongly on web-based identifiers in the life sciences; however, the principles are broadly relevant to other disciplines.

Open data and digital morphology.

Over the past two decades, the development of methods for visualizing and analysing specimens digitally, in three and even four dimensions, has transformed the study of living and fossil organisms. However, the initial promise that the widespread application of such methods would facilitate access to the underlying digital data has not been fully achieved. The underlying datasets for many published studies are not readily or freely available, introducing a barrier to verification and reproducibility, and the reuse of data. There is no current agreement or policy on the amount and type of data that should be made available alongside studies that use, and in some cases are wholly reliant on, digital morphology. Here, we propose a set of recommendations for minimum standards and additional best practice for three-dimensional digital data publication, and review the issues around data storage, management and accessibility.