Gender differences, academic patenting, and tenure-track reform in China: Evidence from life sciences at elite universities.

This study is the first to examine the gender gap in academic patenting among faculty members in Chinese universities, a critical issue for the sustainable development of scientific research and innovation. Using a unique dataset that includes the patenting activities and professional status of 1,836 faculty members in life science-related departments at 36 top Chinese universities, this research reveals an evolving landscape of patenting dynamics. The trend of male faculty members leading in the annual number of patent applications and patents granted has shifted among newly graduated faculty members. Female faculty submit and receive their first patent applications significantly earlier than male faculty. However, male faculty are more likely to be lead inventors, and this gender gap remains difficult to close, with female faculty more likely to be supporting inventors. This research is contextualized within the broader framework of China's university tenure reform and the growing presence of women in the life sciences. While progress is evident, the study uncovers persistent systemic barriers that prevent women from fully translating their research into patentable innovations. By identifying these social and institutional barriers, our study not only sheds light on the gender gap, but also suggests policy measures to promote gender equity in scientific innovation, making it a critical read for policymakers and academic leaders.

Internet-enabled lab-on-a-chip technology for education.

Despite many interventions, science education remains highly inequitable throughout the world. Internet-enabled experimental learning has the potential to reach underserved communities and increase the diversity of the scientific workforce. Here, we demonstrate the use of lab-on-a-chip (LoC) technologies to expose Latinx life science undergraduate students to introductory concepts of computer programming by taking advantage of open-loop cloud-integrated LoCs. We developed a context-aware curriculum to train students at over 8000 km from the experimental site. Through this curriculum, the students completed an assignment testing bacteria contamination in water using LoCs. We showed that this approach was sufficient to reduce the students' fear of programming and increase their interest in continuing careers with a computer science component. Altogether, we conclude that LoC-based internet-enabled learning can become a powerful tool to train Latinx students and increase the diversity in STEM.

Sharing sensitive data in life sciences: an overview of centralized and federated approaches.

Biomedical data are generated and collected from various sources, including medical imaging, laboratory tests and genome sequencing. Sharing these data for research can help address unmet health needs, contribute to scientific breakthroughs, accelerate the development of more effective treatments and inform public health policy. Due to the potential sensitivity of such data, however, privacy concerns have led to policies that restrict data sharing. In addition, sharing sensitive data requires a secure and robust infrastructure with appropriate storage solutions. Here, we examine and compare the centralized and federated data sharing models through the prism of five large-scale and real-world use cases of strategic significance within the European data sharing landscape: the French Health Data Hub, the BBMRI-ERIC Colorectal Cancer Cohort, the federated European Genome-phenome Archive, the Observational Medical Outcomes Partnership/OHDSI network and the EBRAINS Medical Informatics Platform. Our analysis indicates that centralized models facilitate data linkage, harmonization and interoperability, while federated models facilitate scaling up and legal compliance, as the data typically reside on the data generator's premises, allowing for better control of how data are shared. This comparative study thus offers guidance on the selection of the most appropriate sharing strategy for sensitive datasets and provides key insights for informed decision-making in data sharing efforts.

Mentoring practices that predict doctoral student outcomes in a biological sciences cohort.

Despite the importance of a diversity of backgrounds and perspectives in biological research, women, racial and ethnic minorities, and students from non-traditional academic backgrounds remain underrepresented in the composition of university faculty. Through a study on doctoral students at a research-intensive university, we pinpoint advising from faculty as a critical component of graduate student experiences and productivity. Graduate students from minority backgrounds reported lower levels of support from their advisors and research groups. However, working with an advisor from a similar demographic background substantially improved productivity and well-being of these students. Several other aspects of mentoring practices positively predicted student success and belonging, including frequent one-on-one meetings, empathetic and constructive feedback, and relationships with other peer or faculty mentors. Our study highlights the need to renovate graduate education with a focus on retention-not just recruitment-to best prepare students for success in scientific careers.

Diversifying laboratory assessment modes broadens engagement with practical competencies in life science students.

Laboratory practicals in life science subjects are traditionally assessed by written reports that reflect disciplinary norms for documenting experimental activities. However, the exclusive application of this assessment has the potential to engage only a narrow range of competencies. In this study, we explored how multiple modes of laboratory assessment might affect student perceptions of learned skills in a life science module. We hypothesized that while a mixture of assessments may not impact student summative performance, it might positively influence student perceptions of different skills that varied assessments allowed them to practice. This was informed by universal design for learning and teaching for understanding frameworks. In our study, in a third-year Bioscience program, written reports were complemented with group presentations and online quizzes via Moodle. Anonymous surveys evaluated whether this expanded portfolio of assessments promoted awareness of, and engagement with, a broader range of practical competencies. Aspects that influenced student preferences in assessment mode included time limitations, time investment, ability to practice new skills, links with lecture material, and experience of assessment anxiety. In particular, presentations were highlighted as promoting collaboration and communication and the quiz as an effective means of diversifying assessment schedules. A key takeaway from students was that while reports were important, an overreliance on them was detrimental. This study suggests that undergraduate life science students can benefit significantly from a holistic assessment strategy that complements reports with performance-based approaches that incorporate broader competencies and allow for greater student engagement and expression in undergraduate modules.NEW & NOTEWORTHY This study suggests that undergraduate life science students can benefit significantly from a holistic assessment strategy that complements reports with performance-based approaches that incorporate broader competencies and allow for greater student engagement and expression in undergraduate modules.

An identity-based learning community intervention enhances the lived experience and success of first-generation college students in the biological sciences.

Working-class first-generation (FG) college students are underrepresented in higher education and STEM. Using a longitudinal quasi-experiment, we tested the impacts of a living learning community (LLC) in the biological sciences on FG students in their first year of college (Semester 1: N = 243; Semester 2: N = 199), across three cohorts (2018-2019, 2019-2020 and 2020-2021). Participation in the LLC enhanced FG students' belonging, confidence, motivation, grades, knowledge of the social relevance of biology, and reduced STEM anxiety compared to a control group of FG students not in an LLC. LLC participation also increased retention in biological science majors one-year post-intervention compared to the control FG group. Moreover, LLC participation closed the academic gap between FG students in the LLC and honors students from college-educated families in a separate honors LLC. Benefits of the LLC intervention remained stable despite the COVID-19 pandemic, when living together became impossible, producing positive effects across cohorts from pre-pandemic to in-pandemic. Our results suggest that affinity-based learning communities-with or without shared housing-in the transition to college enhance academic thriving, persistence, and reduce social class driven achievement gaps in STEM.

[Contribution to the world of 3D cell products created by bio 3D printing technology and to the life science field].

We have been making 3D tissues consist of cells only, based on the corporate philosophy of "contributing to dramatic advances in medical care through the practical application of innovative 3D cell stacking technology." Currently, in the field of regenerative medicine, we are working toward obtaining approval from the Ministry of Health, Labor and Welfare and commercializing large artificial organs that are made from patients' own cells and have functions such as nerve regeneration, osteochondral regeneration, and blood vessels. On the other hand, this three-dimensional cell stacking technology can be extended to technology for culturing cells in an environment similar to the human body, and is expected to serve as a new methodology for evaluating the effects of new products in various fields on living organisms. Therefore, we are planning a business to provide developers of pharmaceuticals, foods, cosmetics, etc. with a small device called "Functional Cell Device (FCD)" that reproduces some of the functions of human organs outside the body. As the first step, we have developed a three-dimensional liver construct (3D mini-liver). The in vitro human liver model has a wide range of usage, such as evaluation of hepatotoxicity of drugs, elucidation of drug metabolism mechanism, and model of liver disease. In this report, we will outline it together with actual examples in regenerative medicine.

Terminología anatómica: un camino difíci / Anatomical terminology: a difficult pat

En el presente artículo se hace una revisión sistemática o evaluativa de carácter descriptivo-exploratorio donde se buscaron los estudios más relevantes de forma sistematizada en relación a la terminología anatómica, se abordó su historia, su evolución hasta el presente y las dificultades existentes para su correcta aplicación y difusión(AU)

In the present article a systematic or evaluative review of descriptive-exploration nature is made, where the most relevant studies searched in a systematic way in relation to the anatomic terminology, its history, its evolution to the present and the existing difficulties for its correct application and dissemination were addresse(AU)

KDGene: knowledge graph completion for disease gene prediction using interactional tensor decomposition.

The accurate identification of disease-associated genes is crucial for understanding the molecular mechanisms underlying various diseases. Most current methods focus on constructing biological networks and utilizing machine learning, particularly deep learning, to identify disease genes. However, these methods overlook complex relations among entities in biological knowledge graphs. Such information has been successfully applied in other areas of life science research, demonstrating their effectiveness. Knowledge graph embedding methods can learn the semantic information of different relations within the knowledge graphs. Nonetheless, the performance of existing representation learning techniques, when applied to domain-specific biological data, remains suboptimal. To solve these problems, we construct a biological knowledge graph centered on diseases and genes, and develop an end-to-end knowledge graph completion framework for disease gene prediction using interactional tensor decomposition named KDGene. KDGene incorporates an interaction module that bridges entity and relation embeddings within tensor decomposition, aiming to improve the representation of semantically similar concepts in specific domains and enhance the ability to accurately predict disease genes. Experimental results show that KDGene significantly outperforms state-of-the-art algorithms, whether existing disease gene prediction methods or knowledge graph embedding methods for general domains. Moreover, the comprehensive biological analysis of the predicted results further validates KDGene's capability to accurately identify new candidate genes. This work proposes a scalable knowledge graph completion framework to identify disease candidate genes, from which the results are promising to provide valuable references for further wet experiments. Data and source codes are available at https://github.com/2020MEAI/KDGene.

Perspectives from Undergraduate Life Sciences Faculty: Are We Equipped to Effectively Accommodate Students With Disabilities in Our Classrooms?

Higher education has evolved in ways that may increase the challenges life science faculty face in providing accommodations for students with disabilities. Guided by Expectancy-Value Theory, we interviewed 34 life sciences faculty instructors from institutions nationwide to explore faculty motivation to create disability-inclusive educational experiences. We found that faculty in our sample perceive that providing most standard accommodations is a manageable but often challenging task. Further, faculty in our sample feel that improving accommodations necessitates additional support from their institutions. Most faculty had high attainment value for providing accommodations, in that they strongly believed that supporting students with disabilities is the fair and right thing to do. However, faculty did not perceive much utility value or intrinsic value in their task of providing accommodations, and most reported that providing accommodations can be a substantial burden on faculty. These findings imply that current approaches to providing inclusive educational experiences for students with disabilities rely primarily on the personal belief that providing accommodations is the right thing to do, which likely results in a flawed and inequitable system given that not all faculty equally share this conviction.

Advice to a Young Mathematical Biologist.

This paper offers advice to early-mid career researchers in Mathematical Biology from ten past and current Presidents of the Society for Mathematical Biology. The topics covered include deciding if a career in academia is right for you; finding and working with a mentor; building collaborations and working with those from other disciplines; formulating a research question; writing a paper; reviewing papers; networking; writing fellowship or grant proposals; applying for faculty positions; and preparing and giving lectures. While written with mathematical biologists in mind, it is hoped that this paper will be of use to early and mid career researchers across the mathematical, physical and life sciences, as they embark on careers in these disciplines.

Staying on track - Keeping things running in a high-end scientific imaging core facility.

Modern life science research is a collaborative effort. Few research groups can single-handedly support the necessary equipment, expertise and personnel needed for the ever-expanding portfolio of technologies that are required across multiple disciplines in today's life science endeavours. Thus, research institutes are increasingly setting up scientific core facilities to provide access and specialised support for cutting-edge technologies. Maintaining the momentum needed to carry out leading research while ensuring high-quality daily operations is an ongoing challenge, regardless of the resources allocated to establish such facilities. Here, we outline and discuss the range of activities required to keep things running once a scientific imaging core facility has been established. These include managing a wide range of equipment and users, handling repairs and service contracts, planning for equipment upgrades, renewals, or decommissioning, and continuously upskilling while balancing innovation and consolidation.

An open source knowledge graph ecosystem for the life sciences.

Translational research requires data at multiple scales of biological organization. Advancements in sequencing and multi-omics technologies have increased the availability of these data, but researchers face significant integration challenges. Knowledge graphs (KGs) are used to model complex phenomena, and methods exist to construct them automatically. However, tackling complex biomedical integration problems requires flexibility in the way knowledge is modeled. Moreover, existing KG construction methods provide robust tooling at the cost of fixed or limited choices among knowledge representation models. PheKnowLator (Phenotype Knowledge Translator) is a semantic ecosystem for automating the FAIR (Findable, Accessible, Interoperable, and Reusable) construction of ontologically grounded KGs with fully customizable knowledge representation. The ecosystem includes KG construction resources (e.g., data preparation APIs), analysis tools (e.g., SPARQL endpoint resources and abstraction algorithms), and benchmarks (e.g., prebuilt KGs). We evaluated the ecosystem by systematically comparing it to existing open-source KG construction methods and by analyzing its computational performance when used to construct 12 different large-scale KGs. With flexible knowledge representation, PheKnowLator enables fully customizable KGs without compromising performance or usability.

Growing value of data standardization: Allotrope Foundation Connect Workshop Proceedings.

Recent Allotrope Foundation (AF) Connect Workshops (2021-2023) showcased some of the latest advancements in data standardization for analytical data in the pharmaceutical industry. These workshops demonstrated the adaption of two key technologies, the Allotrope Data Format (ADF) and the Allotrope Simple Model (ASM), which streamline instrument data representation and terminology to enhance interoperability across systems. Notably, ASM has facilitated broader adoption of the standard. The increasing significance of data-driven decision-making in the life sciences is underscored by the evolving landscape of open-source solutions and commercial implementations, as demonstrated by industry leaders adopting these standards. Here, we highlight selected examples that illustrate the collective efforts of the community in advancing data standards and data management in the life sciences.

An open-source, high-resolution, automated fluorescence microscope.

Fluorescence microscopy is a fundamental tool in the life sciences, but the availability of sophisticated equipment required to yield high-quality, quantitative data is a major bottleneck in data production in many laboratories worldwide. This problem has long been recognized and the abundancy of low-cost electronics and the simplification of fabrication through 3D-printing have led to the emergence of open-source scientific hardware as a research field. Cost effective fluorescence microscopes can be assembled from cheaply mass-produced components, but lag behind commercial solutions in image quality. On the other hand, blueprints of sophisticated microscopes such as light-sheet or super-resolution systems, custom-assembled from high quality parts, are available, but require a high level of expertise from the user. Here, we combine the UC2 microscopy toolbox with high-quality components and integrated electronics and software to assemble an automated high-resolution fluorescence microscope. Using this microscope, we demonstrate high resolution fluorescence imaging for fixed and live samples. When operated inside an incubator, long-term live-cell imaging over several days was possible. Our microscope reaches single molecule sensitivity, and we performed single particle tracking and SMLM super-resolution microscopy experiments in cells. Our setup costs a fraction of its commercially available counterparts but still provides a maximum of capabilities and image quality. We thus provide a proof of concept that high quality scientific data can be generated by lay users with a low-budget system and open-source software. Our system can be used for routine imaging in laboratories that do not have the means to acquire commercial systems and through its affordability can serve as teaching material to students.

Overcoming the Barriers to Teaching Teamwork to Undergraduates in STEM.

There is widespread recognition that undergraduate students in the life sciences must learn how to work in teams. However, instructors who wish to incorporate teamwork into their classrooms rarely have formal training in how to teach teamwork. This is further complicated by the application of synonymous and often ambiguous terminology regarding teamwork that is found in literature spread among many different disciplines. There are significant barriers for instructors wishing to identify and implement best practices. We synthesize key concepts in teamwork by considering the knowledge, skills, and attitudes (KSAs) necessary for success, the pedagogies and curricula for teaching those KSAs, and the instruments available for evaluating and assessing success. There are only a limited number of studies on teamwork in higher education that present an intervention with a control group and a formal evaluation or assessment. Moreover, these studies are almost exclusively outside STEM disciplines, raising questions about their extensibility. We conclude by considering how to build an evidence base for instruction that will empower students with the KSAs necessary for participating in a lifetime of equitable and inclusive teamwork.

The discovery of archaea: from observed anomaly to consequential restructuring of the phylogenetic tree.

Observational and experimental discoveries of new factual entities such as objects, systems, or processes, are major contributors to some advances in the life sciences. Yet, whereas discovery of theories was extensively deliberated by philosophers of science, very little philosophical attention was paid to the discovery of factual entities. This paper examines historical and philosophical aspects of the experimental discovery by Carl Woese of archaea, prokaryotes that comprise one of the three principal domains of the phylogenetic tree. Borrowing Kuhn's terminology, this discovery of a major biological entity was made during a 'normal science' project of building molecular taxonomy for prokaryotes. Unexpectedly, however, an observed anomaly instigated the discovery of archaea. Substantiation of the existence of the new archaeal entity and consequent reconstruction of the phylogenetic tree prompted replacement of a long-held model of a prokarya and eukarya bipartite tree of life by a new model of a tripartite tree comprising of bacteria, archaea, and eukarya. This paper explores the history and philosophical implications of the progression of Woese's project from normal science to anomaly-instigated model-changing discovery. It is also shown that the consequential discoveries of RNA splicing and of ribozymes were similarly prompted by unexpected irregularities during normal science activities. It is thus submitted that some discoveries of factual biological entities are triggered by unforeseen observational or experimental anomalies.

Controlled experiment finds no detectable citation bump from Twitter promotion.

Multiple studies across a variety of scientific disciplines have shown that the number of times that a paper is shared on Twitter (now called X) is correlated with the number of citations that paper receives. However, these studies were not designed to answer whether tweeting about scientific papers causes an increase in citations, or whether they were simply highlighting that some papers have higher relevance, importance or quality and are therefore both tweeted about more and cited more. The authors of this study are leading science communicators on Twitter from several life science disciplines, with substantially higher follower counts than the average scientist, making us uniquely placed to address this question. We conducted a three-year-long controlled experiment, randomly selecting five articles published in the same month and journal, and randomly tweeting one while retaining the others as controls. This process was repeated for 10 articles from each of 11 journals, recording Altmetric scores, number of tweets, and citation counts before and after tweeting. Randomization tests revealed that tweeted articles were downloaded 2.6-3.9 times more often than controls immediately after tweeting, and retained significantly higher Altmetric scores (+81%) and number of tweets (+105%) three years after tweeting. However, while some tweeted papers were cited more than their respective control papers published in the same journal and month, the overall increase in citation counts after three years (+7% for Web of Science and +12% for Google Scholar) was not statistically significant (p > 0.15). Therefore while discussing science on social media has many professional and societal benefits (and has been a lot of fun), increasing the citation rate of a scientist's papers is likely not among them.