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.

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.

[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.

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.

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)

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.

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.

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.

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.

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.

Investigation of the dynamical structures of double-chain deoxyribonucleic acid model in biological sciences.

The present research investigates the double-chain deoxyribonucleic acid model, which is important for the transfer and retention of genetic material in biological domains. This model is composed of two lengthy uniformly elastic filaments, that stand in for a pair of polynucleotide chains of the deoxyribonucleic acid molecule joined by hydrogen bonds among the bottom combination, demonstrating the hydrogen bonds formed within the chain's base pairs. The modified extended Fan sub equation method effectively used to explain the exact travelling wave solutions for the double-chain deoxyribonucleic acid model. Compared to the earlier, now in use methods, the previously described modified extended Fan sub equation method provide more innovative, comprehensive solutions and are relatively straightforward to implement. This method transforms a non-linear partial differential equation into an ODE by using a travelling wave transformation. Additionally, the study yields both single and mixed non-degenerate Jacobi elliptic function type solutions. The complexiton, kink wave, dark or anti-bell, V, anti-Z and singular wave shapes soliton solutions are a few of the creative solutions that have been constructed utilizing modified extended Fan sub equation method that can offer details on the transversal and longitudinal moves inside the DNA helix by freely chosen parameters. Solitons propagate at a consistent rate and retain their original shape. They are widely used in nonlinear models and can be found everywhere in nature. To help in understanding the physical significance of the double-chain deoxyribonucleic acid model, several solutions are shown with graphics in the form of contour, 2D and 3D graphs using computer software Mathematica 13.2. All of the requisite constraint factors that are required for the completed solutions to exist appear to be met. Therefore, our method of strengthening symbolic computations offers a powerful and effective mathematical tool for resolving various moderate nonlinear wave problems. The findings demonstrate the system's potentially very rich precise wave forms with biological significance. The fundamentals of double-chain deoxyribonucleic acid model diffusion and processing are demonstrated by this work, which marks a substantial development in our knowledge of double-chain deoxyribonucleic acid model movements.

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.

EU-LIFE charter of independent life science research institutes.

The diverse range of organizations contributing to the global research ecosystem is believed to enhance the overall quality and resilience of its output. Mid-sized autonomous research institutes, distinct from universities, play a crucial role in this landscape. They often lead the way in new research fields and experimental methods, including those in social and organizational domains, which are vital for driving innovation. The EU-LIFE alliance was established with the goal of fostering excellence by developing and disseminating best practices among European biomedical research institutes. As directors of the 15 EU-LIFE institutes, we have spent a decade comparing and refining our processes. Now, we are eager to share the insights we've gained. To this end, we have crafted this Charter, outlining 10 principles we deem essential for research institutes to flourish and achieve ground-breaking discoveries. These principles, detailed in the Charter, encompass excellence, independence, training, internationality and inclusivity, mission focus, technological advancement, administrative innovation, cooperation, societal impact, and public engagement. Our aim is to inspire the establishment of new institutes that adhere to these principles and to raise awareness about their significance. We are convinced that they should be viewed a crucial component of any national and international innovation strategies.

Past, present, and future of CRISPR genome editing technologies.

Genome editing has been a transformative force in the life sciences and human medicine, offering unprecedented opportunities to dissect complex biological processes and treat the underlying causes of many genetic diseases. CRISPR-based technologies, with their remarkable efficiency and easy programmability, stand at the forefront of this revolution. In this Review, we discuss the current state of CRISPR gene editing technologies in both research and therapy, highlighting limitations that constrain them and the technological innovations that have been developed in recent years to address them. Additionally, we examine and summarize the current landscape of gene editing applications in the context of human health and therapeutics. Finally, we outline potential future developments that could shape gene editing technologies and their applications in the coming years.

Molecular World Today and Tomorrow: Recent Trends in Biological Sciences 2.0.

Molecular techniques have become influential instruments in biological study, transforming our comprehension of life at the cellular and genetic levels [...].