The impact of weekly multicourse collective exams on pharmacy student academic behaviors and learning in an integrated biological sciences course

Doctor of Pharmacy (PharmD) degree program curricula are typically comprised of heavy course loads and assessment burden. Typically, students "live" from exam to exam only preparing and studying for the exam directly ahead of them while neglecting concurrent courses. Therefore, the aim of the study was to determine the impact of weekly multicourse collective exams academic behaviors and learning in an integrated biological sciences (BSI) course within a PharmD program. Weekly multicourse exams included questions, four per credit hour, from all first semester courses that traditionally included summative exams. Seven courses contributed questions, which amounted to 15 weekly exams of ∼60 questions. No other graded assessments were given in any of the courses, other than individual course cumulative final exams; the final exams in each course were not collective. After completion of final exams, a Qualtrics survey was emailed to all students and the two professors teaching the course. Course grades, not including the final exam, were compared between two cohorts with or without the collective exams to determine impact on learning. The cumulative final exam was compared between cohorts to determine impact on retention. The majority of students agreed or strongly agreed that the weekly collective exams encouraged them to study BSI more frequently, most days of the week, reduced the likelihood of skipping class, and increased likelihood to pay attention and engage in class. The majority believed that they better learned and retained the BSI material. The majority specified that they liked the collective exams for BSI and preferred it over a traditional exam schedule. Learning also appeared to be improved. However, the impact on retention is less clear and requires further research. In conclusion, the weekly multicourse collective exams improved academic behaviors and learning.

Synthesis as an Expanding Resource in Human Milk Science

Few classes of natural products rival the structural audacity of oligosaccharides. Their complexity, however, has stood as an immense roadblock to translational research, as access to homogeneous material from nature is challenging. Thus, while carbohydrates are critical to the myriad functional and structural aspects of the biological sciences, their behavior is largely descriptive. This challenge presents an attractive opportunity for synthetic chemistry, particularly in the area of human milk science. First, there is an inordinate need for synthesizing homogeneous human milk oligosaccharides (HMOs). Superimposed on this goal is the mission of conducting syntheses at scale to enable animal studies. Herein, we present a personalized rumination of our involvement, and that of our colleagues, which has led to the synthesis and characterization of HMOs and mechanistic probes. Along the way, we highlight chemical, chemoenzymatic, and synthetic biology based approaches. We close with a discussion on emergent challenges and opportunities for synthesis, broadly defined, in human milk science.

Modeling individual development plans, mentoring support, and career preparedness relationships among Doctor of Philosophy (Ph.D.) trainees in the life sciences

Background: As greater career development support for doctoral students and postdoctoral researchers has been emphasized, the individual development plan (IDP) has become a recommended mentoring tool. However, little is known about the effect of IDPs on mentoring and career development. This study proposed two conceptual models to examine the interrelationships among the use of IDPs, mentoring support, and career preparedness with a diverse sample of doctoral students and postdoctoral researchers in the life sciences. Methods: The data leveraged for this study was collected over a three-month period, March 2016 to June 2016, as part of a cross-sectional, online survey. The survey was distributed through social media and direct email to participants enrolled in life/biological/medical or physical/applied doctoral programs at U.S. institutions. To test the proposed conceptual models, this study employed the design-based multilevel structural equation modeling. Results: The analytic sample comprised 660 doctoral students and postdoctoral researchers in the life sciences from 91 institutions. The results suggested that 1) using the IDP could enhance mentoring support and career preparedness of doctoral students and postdoctoral researchers; 2) greater mentoring support and career preparedness would motivate mentees to continue utilizing the IDP with their principal investigator (PI) or advisor; and 3) females, postdoctoral researchers, and international scholars might need more support throughout the mentoring and career development process. Conclusions: This research offered empirical evidence for how an IDP, mentorship, and career preparedness interact. Findings revealed the IDP enhances mentoring support and career preparedness, as well as mentoring support and career preparedness predict IDP use. We conclude the IDP is an important mentorship tool that enhances trainees' overall career preparation.

Modeling individual development plans, mentoring support, and career preparedness relationships among Doctor of Philosophy (Ph.D.) trainees in the life sciences

Background: As greater career development support for doctoral students and postdoctoral researchers has been emphasized, the individual development plan (IDP) has become a recommended mentoring tool. However, little is known about the effect of IDPs on mentoring and career development. This study proposed two conceptual models to examine the interrelationships among the use of IDPs, mentoring support, and career preparedness with a diverse sample of doctoral students and postdoctoral researchers in the life sciences. Methods: The data leveraged for this study was collected over a three-month period, March 2016 to June 2016, as part of a cross-sectional, online survey. The survey was distributed through social media and direct email to participants enrolled in life/biological/medical or physical/applied doctoral programs at U.S. institutions. To test the proposed conceptual models, this study employed the design-based multilevel structural equation modeling. Results: The analytic sample comprised 660 doctoral students and postdoctoral researchers in the life sciences from 91 institutions. The results suggested that 1) using the IDP could enhance mentoring support and career preparedness of doctoral students and postdoctoral researchers; 2) greater mentoring support and career preparedness would motivate mentees to continue utilizing the IDP with their principal investigator (PI) or advisor; and 3) females, postdoctoral researchers, and international scholars might need more support throughout the mentoring and career development process. Conclusions: This research demonstrated the empirical evidence an IDP has within mentorship and career preparedness, and that an IDP is an important career development tool that enhances trainees' overall career preparation.

Quantum computing at the frontiers of biological sciences

Computing plays a critical role in the biological sciences but faces increasing challenges of scale and complexity. Quantum computing, a computational paradigm exploiting the unique properties of quantum mechanical analogs of classical bits, seeks to address many of these challenges. We discuss the potential for quantum computing to aid in the merging of insights across different areas of biological sciences.

Seeing clearly through COVID-19: current and future questions for the history and philosophy of the life sciences

The role of a journal like HPLS during the novel coronavirus pandemic should serve as a means for scholars in different fields and professions to consider historically and critically what is happening as it unfolds. Surely it cannot tackle all the possible issues related to the pandemic, in particular to the COVID-19 pandemic, but it does have a responsibility to foster the best possible dialogue about the various issues related to the history and philosophy of the life sciences, and thus to solicit contributions from potential authors working in different parts of the world and belonging to different cultural traditions. Only a real plurality of perspectives should allow for a better, large-scale comprehension of what the COVID-19 pandemic is.

Animal development in the secondary classroom: linking basic science to livestock production

The field of life sciences encompasses a myriad of disciplines that collectively provide insight toward the intrinsic framework of life. Developmental physiology is one of these disciplines that can describe the origins of life at the molecular, cellular, tissue, and organismal level. However, organismal development is a continual process that transcends conception and progresses throughout the lifetime of an organism. In this Illumination, we discuss opportunities that secondary-level life science educators have when teaching developmental physiology through an agricultural lens. Specifically, we propose teaching about the origins of meat and milk, as a nontraditional approach for introducing developmental physiology to students. To justify this notion, we explore how novel research in livestock production focuses on meeting food demands imposed by our growing global population. In addition, we link these concepts to commonly employed standards in secondary-level science classrooms across the United States. In conclusion, the science of livestock production provides a window of opportunity for secondary-level physiology instructors to teach developmental physiology in a form that can readily adhere to institutionally employed standards.

Innovations strategy for moving from created regional clusters to co-creation in life sciences for health care and well-being ecosystems

Over the last decades, the demographic changes have all altered the population structure and influenced the social, economic, and political characteristics of countries over the world. Therefore, the creation of novel ecosystems, new clusters and systems which involved technology and industry, business, education, science, and innovation are increased rapidly. However, in order to solve the future global challenges, the created various types of clusters, public and private sector systems should cooperate and work together as a unit. Therefore, one of the proposed solutions is unified regional ecosystems' building. The Interreg European Life Science Ecosystems (ELISE) project addresses the societal challenge which is common to the European regions: to promote better health for all. This covers the need to improve health and well-being outcomes, to promote market growth, job creation, and EU competitiveness. Based on the project, three different regions of the European countries-Poland, Italy, and Germany-are selected in order to perform the analysis of drivers directly influencing the move from the existing clusters to unified regional ecosystem. The performed analysis showed that the government of a country and regional public authorities have the direct influence and play the central role in shaping unified regional ecosystems. The common economic, social, and political situation in a country is dependent on the government and it is influenced by the regional public authorities. Therefore, the collaboration and conversation among such institutions is the important factor defining how quickly different countries will create unified ecosystems and will solve the future problems.

From intent to implementation: Factors affecting public involvement in life science research

Public involvement is key to closing the gap between research production and research use, and the only way to achieving ultimate transparency in science. The majority of life science research is not public-facing, but is funded by the public and impacts communities. We undertook an exploratory survey of researchers within the life sciences to better understand their views and perceived challenges to involving the public in their research. As survey response rate could not be determined, interpretation of the results must be cautious. We had a valid response cohort of n = 110 researchers, of whom 90% were primarily laboratory based. Using a mixed methods approach, we demonstrate that a top-down approach is key to motivate progression of life scientists from feeling positive towards public involvement to actually engaging in it. Researchers who viewed public involvement as beneficial to their research were more likely to have direct experience of doing it. We demonstrate that the systemic flaws in the way life sciences research enterprise is organised, including the promotion system, hyper-competition, and time pressures are major barriers to involving the public in the scientific process. Scientists are also apprehensive of being involuntarily involved in the current politicized climate; misinformation and publicity hype surrounding science nowadays makes them hesitant to share their early and in-progress research. The time required to deliberate study design and relevance, plan and build relationships for sustained involvement, provide and undertake training, and improve communication in the current research environment is often considered nonpragmatic, particularly for early career researchers. In conclusion, a top-down approach involving institutional incentives and infrastructure appears most effective at transitioning researchers from feeling positive towards public involvement to actually implementing it.

Recent Advances in the Fabrication and Functionalization of Flexible Optical Biosensors: Toward Smart Life-Sciences Applications

Over the last 30 years, optical biosensors based on nanostructured materials have obtained increasing interest since they allow the screening of a wide variety of biomolecules with high specificity, low limits of detection, and great sensitivity. Among them, flexible optical platforms have the advantage of adapting to non-planar surfaces, suitable for in vivo and real-time monitoring of diseases and assessment of food safety. In this review, we summarize the newest and most advanced platforms coupling optically active materials (noble metal nanoparticles) and flexible substrates giving rise to hybrid nanomaterials and/or nanocomposites, whose performances are comparable to the ones obtained with hard substrates (e.g., glass and semiconductors). We focus on localized surface plasmon resonance (LSPR)-based and surface-enhanced Raman spectroscopy (SERS)-based biosensors. We show that large-scale, cost-effective plasmonic platforms can be realized with the currently available techniques and we emphasize the open issues associated with this topic.

The roles of code in biology

The way in which computer code is perceived and used in biological research has been a source of some controversy and confusion, and has resulted in sub-optimal outcomes related to reproducibility, scalability and productivity. We suggest that the confusion is due in part to a misunderstanding of the function of code when applied to the life sciences. Code has many roles, and in this paper we present a three-dimensional taxonomy to classify those roles and map them specifically to the life sciences. We identify a "sweet spot" in the taxonomy-a convergence where bioinformaticians should concentrate their efforts in order to derive the most value from the time they spend using code. We suggest the use of the "inverse Conway maneuver" to shape a research team so as to allow dedicated software engineers to interface with researchers working in this "sweet spot." We conclude that in order to address current issues in the use of software in life science research such as reproducibility and scalability, the field must reevaluate its relationship with software engineering, and adapt its research structures to overcome current issues in bioinformatics such as reproducibility, scalability and productivity.

Wide Input Dynamic Range Fully Integrated Capacitive Sensor for Life Science Applications

This paper presents a new fully integrated CMOS capacitance sensor chip with a wider input dynamic range (IDR) compared to the state-of-the-art, suitable for a variety of life science applications. With the novel differential capacitance to current conversion topology, it achieves an IDR of about seven times higher compared to the previous charge based capacitive measurement (CBCM) circuits and about three times higher compared to the CBCM with cascode current mirrors. It also features a calibration circuitry consisting of an array of switched capacitors, interdigitated electrodes (IDEs) realized on the topmost metal layer, a current-controlled 300 MHz oscillator, and a counter-serializer to create digital output. The proposed sensor, fabricated in AMS 0.35 μm CMOS technology, enables a high-resolution measurement, equal to 416 aF, of physiochemical changes in the IDE with up to 1.27 pF input offset adjustment range (IOAR). With a measurement speed of 15 μs, this sensor is among the fast CMOS capacitive sensors in the literature. In this paper, we demonstrate its functionality and applicability and present the experimental results for monitoring 2 μL evaporating droplets of chemical solvents. By using samples of solvents with different conductivity and relative permittivity, a wide range of capacitance and resistance variations in the sample-IDE interface electric equivalent model can be created. In addition, the evaporating droplet test has inherently fast dynamic changes. Based on the results, our proposed device addresses the challenge of detecting small capacitance changes despite large parasitic elements caused by the ions in the solution or by remnants deposited on the electrode.

From Reductionism to Reintegration: Solving society's most pressing problems requires building bridges between data types across the life sciences

Decades of reductionist approaches in biology have achieved spectacular progress, but the proliferation of subdisciplines, each with its own technical and social practices regarding data, impedes the growth of the multidisciplinary and interdisciplinary approaches now needed to address pressing societal challenges. Data integration is key to a reintegrated biology able to address global issues such as climate change, biodiversity loss, and sustainable ecosystem management. We identify major challenges to data integration and present a vision for a "Data as a Service"-oriented architecture to promote reuse of data for discovery. The proposed architecture includes standards development, new tools and services, and strategies for career-development and sustainability.

Covid-19 and the need for more history and philosophy of RNA

RNA is central to the COVID-19 pandemic-it shapes how the SARS Coronavirus 2 (SARS-CoV-2) behaves, and how researchers investigate and fight it. However, RNA has received relatively little attention in the history and philosophy of the life sciences. By analysing RNA biology in more detail, philosophers and historians of science could gain new and powerful tools to assess the current pandemic, and the biological sciences more generally.

Point estimates, Simpson's paradox, and nonergodicity in biological sciences

Modern biomedical, behavioral and psychological inference about cause-effect relationships respects an ergodic assumption, that is, that mean response of representative samples allow predictions about individual members of those samples. Recent empirical evidence in all of the same fields indicates systematic violations of the ergodic assumption. Indeed, violation of ergodicity in biomedical, behavioral and psychological causes is precisely the inspiration behind our research inquiry. Here, we review the long term costs to scientific progress in these domains and a practical way forward. Specifically, we advocate using statistical measures that can themselves encode the degree and type of nonergodicity in measurements. Taking such steps will lead to a paradigm shift, allowing researchers to investigate the nonstationary, far-from-equilibrium processes that characterize the creativity and emergence of biological and psychological behavior.

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The face-to-face between the world of law and the life sciences is heavy with implicit: fear that it will open the way to liberticidal confrontations or hope that it will be able to allay the social fears born of human intervention in living things. We therefore expect the law to organize a legal order capable of governing activities relating to the life sciences. However, this demand for legal protection and security appears to be excessive in relation to the capacities of the law. In fact, it expresses a social anxiety commensurate with the crisis that our civilization is going through.

biotoolsSchema: a formalized schema for bioinformatics software description

BACKGROUND

Life scientists routinely face massive and heterogeneous data analysis tasks and must find and access the most suitable databases or software in a jungle of web-accessible resources. The diversity of information used to describe life-scientific digital resources presents an obstacle to their utilization. Although several standardization efforts are emerging, no information schema has been sufficiently detailed to enable uniform semantic and syntactic description-and cataloguing-of bioinformatics resources.

FINDINGS

Here we describe biotoolsSchema, a formalized information model that balances the needs of conciseness for rapid adoption against the provision of rich technical information and scientific context. biotoolsSchema results from a series of community-driven workshops and is deployed in the bio.tools registry, providing the scientific community with >17,000 machine-readable and human-understandable descriptions of software and other digital life-science resources. We compare our approach to related initiatives and provide alignments to foster interoperability and reusability.

CONCLUSIONS

biotoolsSchema supports the formalized, rigorous, and consistent specification of the syntax and semantics of bioinformatics resources, and enables cataloguing efforts such as bio.tools that help scientists to find, comprehend, and compare resources. The use of biotoolsSchema in bio.tools promotes the FAIRness of research software, a key element of open and reproducible developments for data-intensive sciences.

An empirical meta-analysis of the life sciences linked open data on the web

While the biomedical community has published several "open data" sources in the last decade, most researchers still endure severe logistical and technical challenges to discover, query, and integrate heterogeneous data and knowledge from multiple sources. To tackle these challenges, the community has experimented with Semantic Web and linked data technologies to create the Life Sciences Linked Open Data (LSLOD) cloud. In this paper, we extract schemas from more than 80 biomedical linked open data sources into an LSLOD schema graph and conduct an empirical meta-analysis to evaluate the extent of semantic heterogeneity across the LSLOD cloud. We observe that several LSLOD sources exist as stand-alone data sources that are not inter-linked with other sources, use unpublished schemas with minimal reuse or mappings, and have elements that are not useful for data integration from a biomedical perspective. We envision that the LSLOD schema graph and the findings from this research will aid researchers who wish to query and integrate data and knowledge from multiple biomedical sources simultaneously on the Web.

Degree requirements of physiology undergraduate programs in the Physiology Majors Interest Group

Physiology undergraduate degree programs operate in isolation relative to other biological science programs, with little to no understanding of how other institutions structure their course requirements and other degree requirements. The purpose of this report is to preliminarily describe the collective curriculum of physiology programs represented at the Physiology Majors Interest Group (P-MIG) annual meetings from 2018 to 2019. A short preconference survey was sent to attendees that inquired about degree requirements of their respective physiology programs. The requirement for Physiology I (69.2%) with laboratory (66.7%) and Anatomy I (57.1%) with laboratory (42.9%), or combined Anatomy and Physiology I (16.7%) and laboratory (18.2%), were common requirements, but many programs did not require Physiology II (27.3%) or Anatomy II (11.1%). There was nearly consensus on required prerequisites such as Biology (2 semesters with laboratories, 85.7%), Chemistry (2 semesters with laboratory, 88.9%), Physics (2 semesters with laboratory, 75%), Calculus I (61.1%), and Statistics (Biostatistics 42.9%; General Statistics 13.3%). There was less agreement among programs in regards to Calculus II (20.0%), Organic Chemistry (2 semesters, 55.6%), and Biochemistry I (47%), which may be reflective of individual department focus. There was considerable heterogeneity among physiology program course requirements for disciplinary core courses and upper division electives. This report is meant to generate discussion on physiology program curricula in efforts to improve physiology education for majors and assist P-MIG in determining minimal points of consensus as they write the first set of national curricular guidelines for degree programs.

Could early tweet counts predict later citation counts? A gender study in Life Sciences and Biomedicine (2014-2016)

In this study, it was investigated whether early tweets counts could differentially benefit female and male (first, last) authors in terms of the later citation counts received. The data for this study comprised 47,961 articles in the research area of Life Sciences & Biomedicine from 2014-2016, retrieved from Web of Science's Medline. For each article, the number of received citations per year was downloaded from WOS, while the number of received tweets per year was obtained from PlumX. Using the hurdle regression model, I compared the number of received citations by female and male (first, last) authored papers and then I investigated whether early tweet counts could predict the later citation counts received by female and male (first, last) authored papers. In the regression models, I controlled for several important factors that were investigated in previous research in relation to citation counts, gender or Altmetrics. These included journal impact (SNIP), number of authors, open access, research funding, topic of an article, international collaboration, lay summary, F1000 Score and mega journal. The findings showed that the percentage of papers with male authors in first or last authorship positions was higher than that for female authors. However, female first and last-authored papers had a small but significant citation advantage of 4.7% and 5.5% compared to male-authored papers. The findings also showed that irrespective of whether the factors were included in regression models or not, early tweet counts had a weak positive and significant association with the later citations counts (3.3%) and the probability of a paper being cited (21.1%). Regarding gender, the findings showed that when all variables were controlled, female (first, last) authored papers had a small citation advantage of 3.7% and 4.2% in comparison to the male authored papers for the same number of tweets.

The effects of microgravity on the digestive system and the new insights it brings to the life sciences

BACKGROUND

Weightlessness is a component of the complex space environment. It exerts adverse effects on the human body, and may pose unknown challenges to the implementation of space missions. The regular function of the digestive system is an important checkpoint for astronauts to conduct missions. Simulated microgravity can recreate the changes experienced by the human body in a weightless environment in space to a certain extent, providing technical support for the exploration of its mechanism and a practical method for other scientific research.

METHODS AND MATERIALS

In the present study, we reviewed and discussed the latest research on the effects of weightlessness or simulated microgravity on the digestive system, as well as the current challenges and future expectations for progress in medical science and further space exploration.

RESULTS

A series of studies have investigated the effects of weightlessness on the human digestive system. On one hand, weightlessness and the changing space environment may exert certain adverse effects on the human body. Studies based on cells or animals have demonstrated the complex effects on the human digestive system in response to weightlessness. On the other hand, a microgravity environment also facilitates the ideation of novel concepts for research in the domain of life science.

CONCLUSION

The effects of weightlessness on the digestive system are considerably complicated. The emergence of methods that help simulate a weightless environment provides a more convenient alternative for assessing the impact and the mechanism underlying the effect of weightlessness on the human body. In addition, the simulated microgravity environment facilitates the ideation of novel concepts for application in regenerative medicine and other fields of life science.

Prevalence and Prevention of Reproducibility Deficiencies in Life Sciences Research: Large-Scale Meta-Analyses

BACKGROUND Studies have found that many published life sciences research results are irreproducible. Our goal was to provide comprehensive risk estimates of familiar reproducibility deficiencies to support quality improvement in research. MATERIAL AND METHODS Reports included were peer-reviewed, published between 1980 and 2016, and presented frequency data of basic biomedical research deficiencies. Manual and electronic literature searches were performed in seven bibliographic databases. For deficiency concepts with at least four frequency studies and with a sample size of at least 15 units in each, a meta-analysis was performed. RESULTS Overall, 68 publications met our inclusion criteria. The study identified several major groups of research quality defects: study design, cell lines, statistical analysis, and reporting. In the study design group of 3 deficiencies, missing power calculation was the most frequent (82.3% [95% Confidence Interval (CI): 69.9-94.6]). Among the 6 cell line deficiencies, mixed contamination was the most frequent (22.4% [95% CI: 10.4-34.3]). Among the 3 statistical analysis deficiencies, the use of chi-square test when expected cells frequency was <5 was the most prevalent (15.7% [95% CI: -3.2-34.7]). In the reporting group of 12 deficiencies, failure to state the number of tails was the most frequent (65% [95% CI: 39.3-90.8]). CONCLUSIONS The results of this study could serve as a general reference when consistently measurable sources of deficiencies need to be identified in research quality improvement.

Silencing trust: confidence and familiarity in re-engineering knowledge infrastructures

In this paper, we tell the story of efforts currently underway, on diverse fronts, to build digital knowledge repositories ('knowledge-bases') to support research in the life sciences. If successful, knowledge bases will be part of a new knowledge infrastructure-capable of facilitating ever-more comprehensive, computational models of biological systems. Such an infrastructure would, however, represent a sea-change in the technological management and manipulation of complex data, inducing a generational shift in how questions are asked and answered and results published and circulated. Integrating such knowledge bases into the daily workflow of the lab thus destabilizes a number of well-established habits which biologists rely on to ensure the quality of the knowledge they produce, evaluate, communicate and exploit. As the story we tell here shows, such destabilization introduces a situation of unfamiliarity, one that carries with it epistemic risks. It should elicit-to use Niklas Luhmann's terms-the question of trust: a shared recognition that the reliability of research practices is being risked, but that such a risk is worth taking in view of what may be gained. And yet, the problem of trust is being unexpectedly silenced. How that silencing has come about, why it matters, and what might yet be done forms the heart of this paper.

Female In-Class Participation and Performance Increase with More Female Peers and/or a Female Instructor in Life Sciences Courses

As we strive to make science education more inclusive, more research is needed to fully understand gender gaps in academic performance and in-class participation in the life sciences. Studies suggest that male voices dominate introductory biology courses, but no studies have been done on upper-level courses. Results on achievement gender gaps in biology vary and often conflict, and no studies have been done on the correlation between participation and academic performance gaps. We observed 34 life sciences courses at all levels at a large private university. Overall, males were more likely to participate than their female peers, but these gender gaps varied from class to class. Females participated more in classes in which the instructor called on most hands that were raised or in classes with more females in attendance. Performance gender gaps also varied by classroom, but female final course grades were as much as 0.2 SD higher in classes with a female instructor and/or a female student majority. Gender gaps in participation and final course grades were positively correlated, but this could be solely because female students are more likely to both participate more and earn higher grades in classes with many females in attendance.

Using COVID-19 as a teaching tool in a time of remote learning: A workflow for bioinformatic approaches to identifying candidates for therapeutic and vaccine development

The COVID-19 pandemic has led to an urgent need for engaging computational alternatives to traditional laboratory exercises. Here we introduce a customizable and flexible workflow, designed with the SARS CoV-2 virus that causes COVID-19 in mind, as a means of reinforcing fundamental biology concepts using bioinformatics approaches. This workflow is accessible to a wide range of students in life science majors regardless of their prior bioinformatics knowledge, and all software is freely available, thus eliminating potential cost barriers. Using the workflow can thus provide a diverse group of students the opportunity to conduct inquiry-driven research. Here we demonstrate the utility of this workflow and outline the logical steps involved in the identification of therapeutic or vaccine targets against SARS CoV-2. We also provide an example of how the workflow may be adapted to other infectious microbes. Overall, our workflow anchors student understanding of viral biology and genomics and allows students to develop valuable bioinformatics expertise as well as to hone critical thinking and problem-solving skills, while also creating an opportunity to better understand emerging information surrounding the COVID-19 pandemic.

Critical Review: digital resolution biomolecular sensing for diagnostics and life science research

One of the frontiers in the field of biosensors is the ability to quantify specific target molecules with enough precision to count individual units in a test sample, and to observe the characteristics of individual biomolecular interactions. Technologies that enable observation of molecules with "digital precision" have applications for in vitro diagnostics with ultra-sensitive limits of detection, characterization of biomolecular binding kinetics with a greater degree of precision, and gaining deeper insights into biological processes through quantification of molecules in complex specimens that would otherwise be unobservable. In this review, we seek to capture the current state-of-the-art in the field of digital resolution biosensing. We describe the capabilities of commercially available technology platforms, as well as capabilities that have been described in published literature. We highlight approaches that utilize enzymatic amplification, nanoparticle tags, chemical tags, as well as label-free biosensing methods.

Unwarranted assumptions: Claude Bernard and the growth of the vera causa standard

The physiologist Claude Bernard was an important nineteenth-century methodologist of the life sciences. Here I place his thought in the context of the history of the vera causa standard, arguably the dominant epistemology of science in the eighteenth and early nineteenth centuries. Its proponents held that in order for a cause to be legitimately invoked in a scientific explanation, the cause must be shown by direct evidence to exist and to be competent to produce the effects ascribed to it. Historians of scientific method have argued that in the course of the nineteenth century the vera causa standard was superseded by a more powerful consequentialist epistemology, which also admitted indirect evidence for the existence and competence of causes. The prime example of this is the luminiferous ether, which was widely accepted, in the absence of direct evidence, because it entailed verified observational consequences and, in particular, successful novel predictions. According to the received view, the vera causa standard's demand for direct evidence of existence and competence came to be seen as an impracticable and needless restriction on the scope of legitimate inquiry into the fine structure of nature. The Mill-Whewell debate has been taken to exemplify this shift in scientific epistemology, with Whewell's consequentialism prevailing over Mill's defense of the older standard. However, Bernard's reflections on biological practice challenge the received view. His methodology marked a significant extension of the vera causa standard that made it both powerful and practicable. In particular, Bernard emphasized the importance of detection procedures in establishing the existence of unobservable entities. Moreover, his sophisticated notion of controlled experimentation permitted inferences about competence even in complex biological systems. In the life sciences, the vera causa standard began to flourish precisely around the time of its alleged abandonment.

"I am Primarily Paid for Publishing…": The Narrative Framing of Societal Responsibilities in Academic Life Science Research

Building on group discussions and interviews with life science researchers in Austria, this paper analyses the narratives that researchers use in describing what they feel responsible for, with a particular focus on how they perceive the societal responsibilities of their research. Our analysis shows that the core narratives used by the life scientists participating in this study continue to be informed by the linear model of innovation. This makes it challenging for more complex innovation models [such as responsible research and innovation (RRI)] to gain ground in how researchers make sense of and conduct their research. Furthermore, the paper shows that the life scientists were not easily able to imagine specific practices that would address broader societal concerns and thus found it hard to integrate the latter into their core responsibilities. Linked to this, researchers saw institutional reward structures (e.g. evaluations, contractual commitments) as strongly focused on scientific excellence ("I am primarily paid for publishing…"). Thus, they saw reward structures as competing with-rather than incentivising-broader notions of societal responsibility. This narrative framing of societal responsibilities is indicative of a structural marginalisation of responsibility practices and explains the claim, made by many researchers in our sample, that they cannot afford to spend time on such practices. The paper thus concludes that the core ideas of RRI stand in tension with predominant narrative and institutional infrastructures that researchers draw on to attribute meaning to their research practices. This suggests that scientific institutions (like universities, professional communities or funding institutions) still have a core role to play in providing new and context-specific narratives as well as new forms of valuing responsibility practices.

The Academic Career Readiness Assessment: Clarifying Hiring and Training Expectations for Future Biomedical Life Sciences Faculty

We describe here the development and validation of the Academic Career Readiness Assessment (ACRA) rubric, an instrument that was designed to provide more equity in mentoring, transparency in hiring, and accountability in training of aspiring faculty in the biomedical life sciences. We report here the results of interviews with faculty at 20 U.S. institutions that resulted in the identification of 14 qualifications and levels of achievement required for obtaining a faculty position at three groups of institutions: research intensive (R), teaching only (T), and research and teaching focused (RT). T institutions hire candidates based on teaching experience and pedagogical practices and ability to serve diverse student populations. RT institutions hire faculty on both research- and teaching-related qualifications, as well as on the ability to support students in the laboratory. R institutions hire candidates mainly on their research achievements and potential. We discuss how these hiring practices may limit the diversification of the life science academic pathway.

Construction, comparison and evolution of networks in life sciences and other disciplines

Network approaches have become pervasive in many research fields. They allow for a more comprehensive understanding of complex relationships between entities as well as their group-level properties and dynamics. Many networks change over time, be it within seconds or millions of years, depending on the nature of the network. Our focus will be on comparative network analyses in life sciences, where deciphering temporal network changes is a core interest of molecular, ecological, neuropsychological and evolutionary biologists. Further, we will take a journey through different disciplines, such as social sciences, finance and computational gastronomy, to present commonalities and differences in how networks change and can be analysed. Finally, we envision how borrowing ideas from these disciplines could enrich the future of life science research.

General theory of topological explanations and explanatory asymmetry

In this paper, I present a general theory of topological explanations, and illustrate its fruitfulness by showing how it accounts for explanatory asymmetry. My argument is developed in three steps. In the first step, I show what it is for some topological property A to explain some physical or dynamical property B. Based on that, I derive three key criteria of successful topological explanations: a criterion concerning the facticity of topological explanations, i.e. what makes it true of a particular system; a criterion for describing counterfactual dependencies in two explanatory modes, i.e. the vertical and the horizontal and, finally, a third perspectival one that tells us when to use the vertical and when to use the horizontal mode. In the second step, I show how this general theory of topological explanations accounts for explanatory asymmetry in both the vertical and horizontal explanatory modes. Finally, in the third step, I argue that this theory is universally applicable across biological sciences, which helps in unifying essential concepts of biological networks. This article is part of the theme issue 'Unifying the essential concepts of biological networks: biological insights and philosophical foundations'.

Editorial: Mathematical Modeling to Solve the Problems in Life Sciences

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Wikidata as a knowledge graph for the life sciences

Wikidata is a community-maintained knowledge base that has been assembled from repositories in the fields of genomics, proteomics, genetic variants, pathways, chemical compounds, and diseases, and that adheres to the FAIR principles of findability, accessibility, interoperability and reusability. Here we describe the breadth and depth of the biomedical knowledge contained within Wikidata, and discuss the open-source tools we have built to add information to Wikidata and to synchronize it with source databases. We also demonstrate several use cases for Wikidata, including the crowdsourced curation of biomedical ontologies, phenotype-based diagnosis of disease, and drug repurposing.

BioHackathon 2015: Semantics of data for life sciences and reproducible research

We report on the activities of the 2015 edition of the BioHackathon, an annual event that brings together researchers and developers from around the world to develop tools and technologies that promote the reusability of biological data. We discuss issues surrounding the representation, publication, integration, mining and reuse of biological data and metadata across a wide range of biomedical data types of relevance for the life sciences, including chemistry, genotypes and phenotypes, orthology and phylogeny, proteomics, genomics, glycomics, and metabolomics. We describe our progress to address ongoing challenges to the reusability and reproducibility of research results, and identify outstanding issues that continue to impede the progress of bioinformatics research. We share our perspective on the state of the art, continued challenges, and goals for future research and development for the life sciences Semantic Web.

Rethinking enzyme kinetics: Designing and developing a biomolecular interactive tutorial (BIOMINT) learning tool for undergraduate students

Enzyme kinetics is the study of enzymatic catalytic rates in biochemical reactions. This topic is commonly taught to life science students in introductory biochemistry courses during their undergraduate education. Unlike most other biochemistry topics, which focus on visual structures of biomolecules and their processes, enzyme kinetics is explained primarily through abstract mathematical and two-dimensional graphical plots. However, these abstract/symbolic representations often make it difficult for students to relate the kinetic parameters to the underlying molecular system that is being described. In this article, we present the design and development of a web-based multimedia interactive learning tool, biomolecular interactive tutorials (BIOMINT) to help students better bridge the relationships between these abstract mathematical models and the molecular behaviors, interactions, and dynamics that produce kinetic phenomena. This learning tool can be accessed at https://bit.ly/biomint. © 2019 International Union of Biochemistry and Molecular Biology, 48(1):74-79, 2020.

What Should Health Science Journalists Do in Epidemic Responses?

Journalists have long covered outbreaks of infectious disease. In the history of global health journalism-from the 1721 Boston smallpox epidemic to the 2002-2003 SARS outbreak in China and Singapore and to recent outbreaks of Ebola in West Africa and the Democratic Republic of the Congo-newsrooms have wielded their power both responsibly and irresponsibly. This article examines journalism practice during the 2013-2016 Ebola epidemic and recommends strategies for improving epidemic reporting.

FINDUS: An Open-Source 3D Printable Liquid-Handling Workstation for Laboratory Automation in Life Sciences

3D-printed laboratory devices can enable ambitious research purposes even at a low-budget level. To follow this trend, here we describe the construction, calibration, and usage of the FINDUS (Fully Integrable Noncommercial Dispensing Utility System). We report the successful 3D printing and assembly of a liquid-handling workstation for less than $400. Using this setup, we achieve reliable and flexible liquid-dispensing automation with relative pipetting errors of less than 0.3%. We show our system is well suited for several showcase applications from both the biology and chemistry fields. In support of the open-source spirit, we make all 3D models, assembly instructions, and source code available for free download, rebuild, and modification.

Bourdieu, networks, and movements: Using the concepts of habitus, field and capital to understand a network analysis of gender differences in undergraduate physics

Current trends suggest that significant gender disparities exist within Science, Technology, Engineering, and Mathematics (STEM) education at university, with female students being underrepresented in physics, but more equally represented in life sciences (e.g., biology, medicine). To understand these trends, it is important to consider the context in which students make decisions about which university courses to enrol in. The current study seeks to investigate gender differences in STEM through a unique approach that combines network analysis of student enrollment data with an interpretive lens based on the sociological theory of Pierre Bourdieu. We generate a network of courses taken by around 9000 undergraduate physics students (from 2009 to 2014) to quantify Bourdieu's concept of field. We identify the fields in which physics students participate by constructing a weighted co-enrollment network and finding communities within it. We then use odds ratios to report gender differences in transverse movements between different academic fields, and non-parametric tests to assess gender differences in vertical movements (changes in students' achievement rankings within a field). Odds ratios comparing the likelihood of progression from one field to another indicate that female students were more likely to make transverse movements into life science fields. We also found that university physics did a poor job in attracting high achieving students, and especially high achieving female students. Of the students who did choose to study physics at university, low and middle achieving female high school students were more likely to decrease their relative rank in their first year compared to their male counterparts. Low achieving female students were also less likely to continue with physics after their first year compared to their male counterparts. Results and implications are discussed in the context of Bourdieu's theory, and previous research. We argue that in order to remove constraints on female students' study choices, the field of physics needs to provide a culture in which all students feel like they belong.

Establishing a distributed national research infrastructure providing bioinformatics support to life science researchers in Australia

EMBL Australia Bioinformatics Resource (EMBL-ABR) is a developing national research infrastructure, providing bioinformatics resources and support to life science and biomedical researchers in Australia. EMBL-ABR comprises 10 geographically distributed national nodes with one coordinating hub, with current funding provided through Bioplatforms Australia and the University of Melbourne for its initial 2-year development phase. The EMBL-ABR mission is to: (1) increase Australia’s capacity in bioinformatics and data sciences; (2) contribute to the development of training in bioinformatics skills; (3) showcase Australian data sets at an international level and (4) enable engagement in international programs. The activities of EMBL-ABR are focussed in six key areas, aligning with comparable international initiatives such as ELIXIR, CyVerse and NIH Commons. These key areas—Tools, Data, Standards, Platforms, Compute and Training—are described in this article.

The bio.tools registry of software tools and data resources for the life sciences

Bioinformaticians and biologists rely increasingly upon workflows for the flexible utilization of the many life science tools that are needed to optimally convert data into knowledge. We outline a pan-European enterprise to provide a catalogue ( https://bio.tools ) of tools and databases that can be used in these workflows. bio.tools not only lists where to find resources, but also provides a wide variety of practical information.

Microfluidic Chips for Life Sciences-A Comparison of Low Entry Manufacturing Technologies

Microfluidic water-in-oil droplets are a versatile tool for biological and biochemical applications due to the advantages of extremely small monodisperse reaction vessels in the pL-nL range. A key factor for the successful dissemination of this technology to life science laboratory users is the ability to produce microfluidic droplet generators and related accessories by low-entry barrier methods, which enable rapid prototyping and manufacturing of devices with low instrument and material costs. The direct, experimental side-by-side comparison of three commonly used additive manufacturing (AM) methods, namely fused deposition modeling (FDM), inkjet printing (InkJ), and stereolithography (SLA), is reported. As a benchmark, micromilling (MM) is used as an established method. To demonstrate which of these methods can be easily applied by the non-expert to realize applications in topical fields of biochemistry and microbiology, the methods are evaluated with regard to their limits for the minimum structure resolution in all three spatial directions. The suitability of functional SLA and MM chips to replace classic SU-8 prototypes is demonstrated on the basis of representative application cases.

The conservative bias of life scientists

Life scientists may think of themselves as liberal, but they seem to have a strong conservative bias that negatively impacts diversity in research. The bias can be revealed with a Google Scholar search; the phrase "conserved from [species X] to humans" occurs over 90,000 times, yet the reverse, "conserved from humans to [species X]" is found fewer than 1000 times (Figure 1A). I will explore why this conservative bias in direction exists in the literature and the implications that it has on our thinking and choices for research.

Cells in ExperimentaL Life Sciences (CELLS-2018): capturing the knowledge of normal and diseased cells with ontologies

Cell cultures and cell lines are widely used in life science experiments. In conjunction with the 2018 International Conference on Biomedical Ontology (ICBO-2018), the 2nd International Workshop on Cells in ExperimentaL Life Science (CELLS-2018) focused on two themes of knowledge representation, for newly-discovered cell types and for cells in disease states. This workshop included five oral presentations and a general discussion session. Two new ontologies, including the Cancer Cell Ontology (CCL) and the Ontology for Stem Cell Investigations (OSCI), were reported in the workshop. In another representation, the Cell Line Ontology (CLO) framework was applied and extended to represent cell line cells used in China and their Chinese representation. Other presentations included a report on the application of ontologies to cross-compare cell types and marker patterns used in flow cytometry studies, and a presentation on new experimental findings about novel cell types based on single cell RNA sequencing assay and their corresponding ontological representation. The general discussion session focused on the ontology design patterns in representing newly-discovered cell types and cells in disease states.

Harmonizing semantic annotations for computational models in biology

Life science researchers use computational models to articulate and test hypotheses about the behavior of biological systems. Semantic annotation is a critical component for enhancing the interoperability and reusability of such models as well as for the integration of the data needed for model parameterization and validation. Encoded as machine-readable links to knowledge resource terms, semantic annotations describe the computational or biological meaning of what models and data represent. These annotations help researchers find and repurpose models, accelerate model composition and enable knowledge integration across model repositories and experimental data stores. However, realizing the potential benefits of semantic annotation requires the development of model annotation standards that adhere to a community-based annotation protocol. Without such standards, tool developers must account for a variety of annotation formats and approaches, a situation that can become prohibitively cumbersome and which can defeat the purpose of linking model elements to controlled knowledge resource terms. Currently, no consensus protocol for semantic annotation exists among the larger biological modeling community. Here, we report on the landscape of current annotation practices among the COmputational Modeling in BIology NEtwork community and provide a set of recommendations for building a consensus approach to semantic annotation.

Learning to successfully search the scientific and medical literature

Searching the literature is often overlooked and receives inadequate attention. In this article, we seek to address this issue by presenting several strategies. Here, five steps are outlined and discussed to facilitate effective literature searching.

Honoring eight senior distinguished plant biologists from India

We summarize here research contributions of eight stalwarts in photosynthesis research from India. These distinguished scientists (Shree Kumar Apte, Basanti Biswal, Udaya C. Biswal, Agepati S. Raghavendra, Attipalli Ramachandra Reddy, Prafullachandra Vishnu (Raj) Sane, Baishnab Charan Tripathy, and Dinesh C. Uprety) were honored on November 2, 2017, at the School of Life Sciences, University of Hyderabad. We include here two group photographs of this special event, which was organized by the Department of Plant Sciences, during the 8th International Conference on Photosynthesis and Hydrogen Energy Research for Sustainability-2017 ( https://prs.science/wp-content/uploads/2017/10/Photosynthesis-Research-for-Sustainability-2017.pdf , also available at: http://www.life.illinois.edu/govindjee/world-historical.html ). The main conference had honored three international scientists: William Cramer (Purdue University. West Lafayette, Indiana, USA), Govindjee (University of Illinois at Urbana-Champaign, Illinois, USA, one of the authors here); and Agepati S. Raghavendra (University of Hyderabad, India, one of those honored here as well); see papers in this Special Issue, edited by Suleyman Allakhverdiev, one of the authors here.

Putting post-decision wagering to the test: a measure of self-perceived knowledge in basic sciences?

INTRODUCTION

Students learn more effectively when they know what they do not know. Gaining insight into students' metacognitive awareness is needed as misalignment between actual and self-perceived knowledge impedes their learning process. The optimal method of measuring self-perceived knowledge is still under debate. In this study, we evaluate the use of psychology-derived post-decision wagering for mapping students self-perceived knowledge.

METHODS

Students (n = 71) performed a pre-test on medical physiology, followed by a teacher-moderated discussion and a post-test with isomorph questions. Half of the students rated their self-perceived knowledge on each question using post-decision wagering, i. e. betting 1-5 points on the correctness of their answer, whereas the other half used a 5-point Likert scale to rate their confidence.

RESULTS

Self-perceived knowledge scores were higher for post-decision wagering (pre: 3.75 ± 0.14, post: 4.60 ± 0.07) compared with Likert scales (pre: 3.13 ± 0.08, post: 3.92 ± 0.08) despite similar actual knowledge scores. Furthermore, Likert ratings showed a near-normal distribution, whereas wagers were placed preferentially using the outer ends of the scale. Correlations between mean actual and self-perceived knowledge scores were low in both groups. On average, 8.5% of responses were classified as misconceptions, defined as highly confident incorrect answers.

DISCUSSION

Despite the presumed reliability of post-decision wagering, our findings suggest that we should adhere to the use of Likert scales as a balanced measure for self-perceived knowledge in medical education. Moreover, the prevalence of misconceptions did not alter after instruction, indicating a need for instructional designs that enhance students' conceptual understanding in basic sciences.