Open Resources for Biology Education (ORBE): a resource collection

In undergraduate life sciences education, open educational resources (OERs) increase accessibility and retention for students, reduce costs, and save instructors time and effort. Despite increasing awareness and utilization of these resources, OERs are not centrally located, and many undergraduate instructors describe challenges in locating relevant materials for use in their classes. To address this challenge, we have designed a resource collection (referred to as Open Resources for Biology Education, ORBE) with 89 unique resources that are primarily relevant to undergraduate life sciences education. To identify the resources in ORBE, we asked undergraduate life sciences instructors to list what OERs they use in their teaching and curated their responses. Here, we summarize the contents of the ORBE and describe how educators can use this resource as a tool to identify suitable materials to use in their classroom context. By highlighting the breadth of unique resources openly available for undergraduate biology education, we intend for the ORBE to increase instructors' awareness and use of OERs.

Illegal interlocks among life science company boards of directors

Competition between life science companies is critical to ensure innovative therapies are efficiently developed. Anticompetitive behavior may harm scientific progress and, ultimately, patients. One well-established category of anticompetitive behavior is the 'interlocking directorate'. It is illegal for companies' directors to 'interlock' by also serving on the boards of competitors. We evaluated overlaps in the board membership of 2,241 public life science companies since 2000. We show that a robust network of interlocking companies is present among these firms. At any given time, 10-20 percent of board members are interlocked; the number of interlocks has more than doubled in the last two decades. Over half of these interlocked firms report over $5 million in historical revenue, exceeding a legal threshold that makes an interlocking directorate a violation of antitrust law. Those interlocks are only illegal if the companies compete, even in part. Using the disease categories for which companies have sponsored clinical trials, we discover that a few markets are responsible for a large fraction of interlocks. We show that in dozens of cases, companies share directors with the very firms they identify as their biggest competitive threats. We provide a data-driven roadmap for policymakers, regulators, and companies to further investigate the contribution of anticompetitive behavior to increased healthcare costs and to enforce the law against illegal interlocks between firms.

Roses Have Thorns: Understanding the Downside of Oncological Care Delivery Through Visual Analytics and Sequential Rule Mining

Personalized head and neck cancer therapeutics have greatly improved survival rates for patients, but are often leading to understudied long-lasting symptoms which affect quality of life. Sequential rule mining (SRM) is a promising unsupervised machine learning method for predicting longitudinal patterns in temporal data which, however, can output many repetitive patterns that are difficult to interpret without the assistance of visual analytics. We present a data-driven, human-machine analysis visual system developed in collaboration with SRM model builders in cancer symptom research, which facilitates mechanistic knowledge discovery in large scale, multivariate cohort symptom data. Our system supports multivariate predictive modeling of post-treatment symptoms based on during-treatment symptoms. It supports this goal through an SRM, clustering, and aggregation back end, and a custom front end to help develop and tune the predictive models. The system also explains the resulting predictions in the context of therapeutic decisions typical in personalized care delivery. We evaluate the resulting models and system with an interdisciplinary group of modelers and head and neck oncology researchers. The results demonstrate that our system effectively supports clinical and symptom research.

Biotechnology in India: An Analysis of 'Biotechnology Industry Research Assistance Council' (BIRAC)-Supported Projects

A comprehensive analysis of 2165 projects funded by India's Department of Biotechnology since 2005 through private-public partnerships, and as of 2012 through the 'Biotechnology Industry Research Assistance Council (BIRAC)' until BIRAC's tenth anniversary at the end of March 2022 reveals details of the science and technology underpinning past and current biotechnology research and development projects in the country. They are led by human healthcare projects (74.9 % overall), of which medical technology (58.7 %) and therapeutics (24.5 %) are the main drivers, ahead of vaccines (4.3 %), regenerative medicine (3.9 %), public health (3.5 %) and others (5.1 %). Agricultural projects (15.2 % overall) have mainly been driven by plant breeding and cloning (24.6 %), animal biotechnology (20.4 %), agri-informatics (13.4 %), aquaculture (6.1 %), and (bio)fertilizers (4.3 %). The key components of industrial biotechnology (9.9 % overall) have been fine chemicals (44.7 %), environmental projects (23.3 %), clean energy (18.1 %) and industrial enzymes (12.1 %). Analysis of the projects funded pre- versus post-2017, compared to the distribution of equity funding as of early 2022 identifies trends in terms of growth areas and locations of industrial biotechnology projects and activities in India.

Life Sciences undergraduate students' preferences on online learning

Online learning is implemented in response to emergency remote teaching during global pandemic. We conducted a survey on Life Sciences undergraduate students on their preferences on mode of lesson delivery, mode of learning and learning activities. Students across different study years responded in a similar order ranking blended learning delivery as highly favorable. The survey gathered insightful understandings on Life Sciences undergraduates' learning preferences on online learning which inform future purposeful learning design taking student's preferences into consideration.

life sciences

In 2008, the Chinese government created the Thousand Talents Program (TTP) to recruit overseas expertise to build up China's science and technology knowledge and innovation base. Ten years later, in 2018, the Federal Bureau of Investigation (FBI) announced a new "China Initiative" that aimed to counter the transfer by U.S.-based scientists involved in the TTP of knowledge and intellectual property that could support China's military and economic might and pose threats to U.S. national security. This initiative launched a number of investigations into major U.S. federal funding agencies and universities and charged several scientists, many of them life scientists, with failing to accurately report their work and affiliations with Chinese entities and illegally transferring scientific information to China. Although the FBI cases demonstrate a clear problem with disclosure of foreign contracts and research integrity among some TTP recipients, they have failed to demonstrate any harm to U.S. national security interests. At the heart of this controversy are core questions that remain unresolved and need more attention: What is required to transfer and develop knowledge to further a country's science and technology ambitions? And can the knowledge acquired by a visiting scientist be easily used to further a country's ambitions? Drawing on literature from the field of science and technology studies, this article discusses the key issues that should be considered in evaluating this question in the Chinese context and the potential scientific, intelligence, and policy implications of knowledge transfer as it relates to the TTP.

Reflexive expectations in innovation financing: An analysis of venture capital as a mode of valuation

Social studies of expectations are premised on the notion that the future is brought into the present, and thereby expectations about the future come to shape our actions, decisions, and practices in ways that performatively bring about the imagined future. In this article, I examine how social actors themselves understand, construct, and deploy future expectations in innovation financing, focusing specifically on the venture capital industry financing of the life sciences sector. I do so to analyse how these reflexive efforts configure the valuation and investment decisions of these social actors and others. I build on analytical perspectives in STS and adjacent fields such as organization studies and economic sociology that analyse the role of expectations - manifested as stories, narratives, and accounts - in social action. To do so, I unpack how reflexivity comes to configure valuation and investment decisions, and the goals (e.g. exits) they rationalize.

Transformer-based deep learning for predicting protein properties in the life sciences

Recent developments in deep learning, coupled with an increasing number of sequenced proteins, have led to a breakthrough in life science applications, in particular in protein property prediction. There is hope that deep learning can close the gap between the number of sequenced proteins and proteins with known properties based on lab experiments. Language models from the field of natural language processing have gained popularity for protein property predictions and have led to a new computational revolution in biology, where old prediction results are being improved regularly. Such models can learn useful multipurpose representations of proteins from large open repositories of protein sequences and can be used, for instance, to predict protein properties. The field of natural language processing is growing quickly because of developments in a class of models based on a particular model-the Transformer model. We review recent developments and the use of large-scale Transformer models in applications for predicting protein characteristics and how such models can be used to predict, for example, post-translational modifications. We review shortcomings of other deep learning models and explain how the Transformer models have quickly proven to be a very promising way to unravel information hidden in the sequences of amino acids.

How to teach life sciences students about dual-use research-a view from the field

To reduce biological risks, raising awareness for dual-use issues already at the level of university education is essential. Currently, most life sciences education programs do not incorporate biosecurity and dual-use in their regular curricula. Consequently, the responsibility rests with individual lecturers and depends on their initiative to incorporate dual-use topics into teaching activities. Students interested in biosecurity and dual-use topics often only have the option to educate themselves in external or online courses. Here, we provide practical guidance on how to initiate and integrate a dual-use education program within the curriculum and provide a selection of existing teaching materials. In addition, we suggest key learning objectives to guide the planning of dual-use courses. Different course formats like lectures, seminars, or stand-alone events are discussed regarding their advantages, disadvantages, and suitability for conveying the learning objectives to different educational stages and audiences. As a minimum, we recommend the incorporation of dual-use issues into at least one mandatory course. Ideally, students should additionally participate in in-depth seminars, which can be voluntary and offered in cooperation with external organisations.

Challenges related to data protection in clinical research before and during the COVID-19 pandemic: An exploratory study

Background

The COVID-19 pandemic brought global disruption to health, society and economy, including to the conduct of clinical research. In the European Union (EU), the legal and ethical framework for research is complex and divergent. Many challenges exist in relation to the interplay of the various applicable rules, particularly with respect to compliance with the General Data Protection Regulation (GDPR). This study aimed to gain insights into the experience of key clinical research stakeholders [investigators, ethics committees (ECs), and data protection officers (DPOs)/legal experts working with clinical research sponsors] across the EU and the UK on the main challenges related to data protection in clinical research before and during the pandemic.

Materials and methods

The study consisted of an online survey and follow-up semi-structured interviews. Data collection occurred between April and December 2021. Survey data was analyzed descriptively, and the interviews underwent a framework analysis.

Results and conclusion

In total, 191 respondents filled in the survey, of whom fourteen participated in the follow-up interviews. Out of the targeted 28 countries (EU and UK), 25 were represented in the survey. The majority of stakeholders were based in Western Europe. This study empirically elucidated numerous key legal and ethical issues related to GDPR compliance in the context of (cross-border) clinical research. It showed that the lack of legal harmonization remains the biggest challenge in the field, and that it is present not only at the level of the interplay of key EU legislative acts and national implementation of the GDPR, but also when it comes to interpretation at local, regional and institutional levels. Moreover, the role of ECs in data protection was further explored and possible ways forward for its normative delineation were discussed. According to the participants, the pandemic did not bring additional legal challenges. Although practical challenges (for instance, mainly related to the provision of information to patients) were high due to the globally enacted crisis measures, the key problematic issues on (cross-border) health research, interpretations of the legal texts and compliance strategies remained largely the same.

Genetic epidemiology of human neutrophil antigen variants suggests significant global variability

Human neutrophil antigens possess significant clinical implications especially in the fields of transfusion and transplantation medicine. Efforts to estimate the prevalence of genetic variations underpinning the antigenic expression are emerging. However, there lacks a precise capture of the global frequency profiles. Our article emphasizes the potential utility of maintaining an organized online repository of evidence on neutrophil antigen-associated genetic variants from published literature and reports. This, in our opinion, is an emerging area and would significantly benefit from the awareness and understanding of population-level diversities.

Three decades of ethical, legal, and social implications research: Looking back to chart a path forward

More than thirty years ago in the United States, the National Center for Human Genome Research (NCHGR) at the National Institutes of Health (NIH) and its partner in the Human Genome Project (HGP), the Department of Energy (DOE), called for proposals from social scientists, ethicists, lawyers, and others to explore the ethical, legal, and social implications (ELSI) of mapping and sequencing the human genome. Today, nearly twenty years after the completion of the HGP, the ELSI Research Program of the National Human Genome Research Institute (NHGRI) continues this support. It has fostered the growth of ELSI research into a global field of study, uniquely positioned at the nexus of many academic disciplines and in proximity to basic and applied scientific research. We examine the formation of the first ELSI program and consider whether science policy in the public interest can exist within the confines of a set-aside from the NHGRI budget.

Innovative Sensor Technology for Emergency Detection in Life Science Laboratories

Chemical, analytical and biological laboratories use a variety of different solvents and gases. Many of these compounds are harmful or even toxic to laboratory personnel. Permanent monitoring of the air quality is therefore of great importance regarding the greatest possible occupational safety and the detection of dangerous situations in the work process. An increasing need exists for the development and application of small and portable sensor solutions that enable personal monitoring and that can be flexibly adapted to different environments and situations. Different sensor principles are available for the detection of gases and solvent vapors, which differ in terms of their selectivity and sensitivity. Besides simple sensing elements, integrated sensors and smart sensors are increasingly available, which, depending on their scope of functions, require a distinct effort in integration. This chapter gives an overview of available sensors and their integration options, and describes ready-to-use sensor systems for personal monitoring in life science laboratories.

Human-centered explainability for life sciences, healthcare, and medical informatics

Rapid advances in artificial intelligence (AI) and availability of biological, medical, and healthcare data have enabled the development of a wide variety of models. Significant success has been achieved in a wide range of fields, such as genomics, protein folding, disease diagnosis, imaging, and clinical tasks. Although widely used, the inherent opacity of deep AI models has brought criticism from the research field and little adoption in clinical practice. Concurrently, there has been a significant amount of research focused on making such methods more interpretable, reviewed here, but inherent critiques of such explainability in AI (XAI), its requirements, and concerns with fairness/robustness have hampered their real-world adoption. We here discuss how user-driven XAI can be made more useful for different healthcare stakeholders through the definition of three key personas-data scientists, clinical researchers, and clinicians-and present an overview of how different XAI approaches can address their needs. For illustration, we also walk through several research and clinical examples that take advantage of XAI open-source tools, including those that help enhance the explanation of the results through visualization. This perspective thus aims to provide a guidance tool for developing explainability solutions for healthcare by empowering both subject matter experts, providing them with a survey of available tools, and explainability developers, by providing examples of how such methods can influence in practice adoption of solutions.

THALIS: Human-Machine Analysis of Longitudinal Symptoms in Cancer Therapy

Although cancer patients survive years after oncologic therapy, they are plagued with long-lasting or permanent residual symptoms, whose severity, rate of development, and resolution after treatment vary largely between survivors. The analysis and interpretation of symptoms is complicated by their partial co-occurrence, variability across populations and across time, and, in the case of cancers that use radiotherapy, by further symptom dependency on the tumor location and prescribed treatment. We describe THALIS, an environment for visual analysis and knowledge discovery from cancer therapy symptom data, developed in close collaboration with oncology experts. Our approach leverages unsupervised machine learning methodology over cohorts of patients, and, in conjunction with custom visual encodings and interactions, provides context for new patients based on patients with similar diagnostic features and symptom evolution. We evaluate this approach on data collected from a cohort of head and neck cancer patients. Feedback from our clinician collaborators indicates that THALIS supports knowledge discovery beyond the limits of machines or humans alone, and that it serves as a valuable tool in both the clinic and symptom research.

Life sciences and mass spectrometry: some personal reflections

Molecular analysis of biological systems by mass spectrometry was in focus of technological developments in the second half of the 20th century, in which the issues of chemical identification of high molecular diversity by biophysical instrumental methods appeared as a mission impossible. By developing dialogs between researchers dealing with life sciences and medicine on one side and technology developers on the other, new horizons toward deciphering, identifying and quantifying of complex systems became a reality. Contributions toward this goal can be today considered as pioneering efforts delivered by a number of researchers, including generations of motivated students and associates.

Academic Teams and Commercialization in the Life Sciences

We review the literature on entrepreneurial team formation with a focus on data to study academic teams and summarize our empirical work on the life sciences industry. We consider how academics form teams to start new companies and the implications of various configurations on firm behavior with regards to patenting, survival and firm growth. We present several empirical challenges facing research on academic teams and conclude with suggestions for future research.

Perspectives on automated composition of workflows in the life sciences

Scientific data analyses often combine several computational tools in automated pipelines, or workflows. Thousands of such workflows have been used in the life sciences, though their composition has remained a cumbersome manual process due to a lack of standards for annotation, assembly, and implementation. Recent technological advances have returned the long-standing vision of automated workflow composition into focus. This article summarizes a recent Lorentz Center workshop dedicated to automated composition of workflows in the life sciences. We survey previous initiatives to automate the composition process, and discuss the current state of the art and future perspectives. We start by drawing the "big picture" of the scientific workflow development life cycle, before surveying and discussing current methods, technologies and practices for semantic domain modelling, automation in workflow development, and workflow assessment. Finally, we derive a roadmap of individual and community-based actions to work toward the vision of automated workflow development in the forthcoming years. A central outcome of the workshop is a general description of the workflow life cycle in six stages: 1) scientific question or hypothesis, 2) conceptual workflow, 3) abstract workflow, 4) concrete workflow, 5) production workflow, and 6) scientific results. The transitions between stages are facilitated by diverse tools and methods, usually incorporating domain knowledge in some form. Formal semantic domain modelling is hard and often a bottleneck for the application of semantic technologies. However, life science communities have made considerable progress here in recent years and are continuously improving, renewing interest in the application of semantic technologies for workflow exploration, composition and instantiation. Combined with systematic benchmarking with reference data and large-scale deployment of production-stage workflows, such technologies enable a more systematic process of workflow development than we know today. We believe that this can lead to more robust, reusable, and sustainable workflows in the future.

[Development of practical liberal courses for students with non-biology majors under the "Double First-class" background]

Life sciences are the disciplines most closely related with human beings. As experimental disciplines, life sciences develop rapidly and highly intersect in many scientific fields. Under the "double first-class" initiative, the comprehensive development-oriented talent training system has put forward an urgent need for life sciences literacy and comprehensive ability training of college students. Taking the reform of liberal education curriculum system as an opportunity, we developed a series of eight life sciences practical liberal courses for students with non-biology majors. The courses cover all sub-disciplines or directions of life sciences, and aim to foster interdisciplinary talents with life sciences knowledge and literacy, as well as practical and innovative abilities. These courses could serve as references for experimental teaching centers in colleges and universities to set up practical liberal and experimental courses.

[Application of micro-teaching in life sciences courses based on the "National Universities Micro-teaching Competition of Life Sciences" analysis]

With improvements in information technology and expansion in education reforms, more innovative teaching reform programs have also been launched. Information technology has increased interest in the use of the flipped classroom innovative teaching model. In order to explore new ideas for the improvement of teaching, this paper focuses on the flipped classroom teaching approach with the integration of information technology. Micro-teaching is an important innovative flipped classroom teaching approach with a number of advantages as it is short, concise, and interesting, which therefore helps improve students' self-learning ability. Designing and preparing micro-teaching would become a prerequisite skill for college teachers. Based on the analysis of the entries in the "National Universities Micro-teaching Competition of Life Science", this paper explores the application of micro-teaching in life sciences teaching from the perspective of curriculum introduction, mode of presentation, teaching design, and other aspects of teaching. This information could serve as a guide to frontline college teachers to help them understand and master the skills of designing micro-teaching, so as to generate interest and improve learning efficiency among college students.

The Potential Role of School Citizen Science Programs in Infectious Disease Surveillance: A Critical Review

Public involvement in science has allowed researchers to collect large-scale and real-time data and also engage citizens, so researchers are adopting citizen science (CS) in many areas. One promising appeal is student participation in CS school programs. In this literature review, we aimed to investigate which school CS programs exist in the areas of (applied) life sciences and if any projects target infectious disease surveillance. This review’s objectives are to determine success factors in terms of data quality and student engagement. After a comprehensive search in biomedical and social databases, we found 23 projects. None of the projects found focused on infectious disease surveillance, and the majority centered around species biodiversity. While a few projects had issues with data quality, simplifying the protocol or allowing students to resubmit data made the data collected more usable. Overall, students at different educational levels and disciplines were able to collect usable data that was comparable to expert data and had positive learning experiences. In this review, we have identified limitations and gaps in reported CS school projects and provided recommendations for establishing future programs. This review shows the value of using CS in collaboration with traditional research techniques to advance future science and increasingly engage communities.

De novo genome assemblies of butterflies

BACKGROUND

The availability of thousands of genomes has enabled new advancements in biology. However, many genomes have not been investigated for their quality. Here we examine quality trends in a taxonomically diverse and well-known group, butterflies (Papilionoidea), and provide draft, de novo assemblies for all available butterfly genomes. Owing to massive genome sequencing investment and taxonomic curation, this is an excellent group to explore genome quality.

FINDINGS

We provide de novo assemblies for all 822 available butterfly genomes and interpret their quality in terms of completeness and continuity. We identify the 50 highest quality genomes across butterflies and conclude that the ringlet, Aphantopus hyperantus, has the highest quality genome. Our post-processing of draft genome assemblies identified 118 butterfly genomes that should not be reused owing to contamination or extremely low quality. However, many draft genomes are of high utility, especially because permissibility of low-quality genomes is dependent on the objective of the study. Our assemblies will serve as a key resource for papilionid genomics, especially for researchers without computational resources.

CONCLUSIONS

Quality metrics and assemblies are typically presented with annotated genome accessions but rarely with de novo genomes. We recommend that studies presenting genome sequences provide the assembly and some metrics of quality because quality will significantly affect downstream results. Transparency in quality metrics is needed to improve the field of genome science and encourage data reuse.

Where Do We Stand in Regularization for Life Science Studies?

More and more biologists and bioinformaticians turn to machine learning to analyze large amounts of data. In this context, it is crucial to understand which is the most suitable data analysis pipeline for achieving reliable results. This process may be challenging, due to a variety of factors, the most crucial ones being the data type and the general goal of the analysis (e.g., explorative or predictive). Life science data sets require further consideration as they often contain measures with a low signal-to-noise ratio, high-dimensional observations, and relatively few samples. In this complex setting, regularization, which can be defined as the introduction of additional information to solve an ill-posed problem, is the tool of choice to obtain robust models. Different regularization practices may be used depending both on characteristics of the data and of the question asked, and different choices may lead to different results. In this article, we provide a comprehensive description of the impact and importance of regularization techniques in life science studies. In particular, we provide an intuition of what regularization is and of the different ways it can be implemented and exploited. We propose four general life sciences problems in which regularization is fundamental and should be exploited for robustness. For each of these large families of problems, we enumerate different techniques as well as examples and case studies. Lastly, we provide a unified view of how to approach each data type with various regularization techniques.

[Exploration and practice of blended teaching in "Introduction to Life Sciences" for non-biology students]

In the era of Internet +, teaching models in universities are undergoing changes due to the rapid development of information technology. Blended teaching, combining online with offline teaching, is being implemented and developed in universities. In order to reform teaching mode and improve teaching effect, the curriculum team carried out the exploration of blended teaching reform for the "Introduction to Life Sciences" for non-biology students. The course combined high-level MOOC (Massive Open Online Course), small class teaching, diversified platform and multi-dimensional teaching mode, built a multi-disciplinary collaborative teaching team, formed a multi-dimensional evaluation system focusing on process and ability, practiced the education concept of combining knowledge teaching and value leading, gained valuable practical experience, and achieved the expected teaching results. It can provide reference for the reform and construction of similar courses in other colleges and universities. The development of blended teaching expands the breadth and depth of teaching, stimulates students' interest and potential for learning, opens up students' thinking and perspective, cultivates students' scientific literacy and comprehensive ability, and plays a positive role in the cultivation of innovative and inter-disciplinary talents.

A Semi-Automated Workflow for FAIR Maturity Indicators in the Life Sciences

Data sharing and reuse are crucial to enhance scientific progress and maximize return of investments in science. Although attitudes are increasingly favorable, data reuse remains difficult due to lack of infrastructures, standards, and policies. The FAIR (findable, accessible, interoperable, reusable) principles aim to provide recommendations to increase data reuse. Because of the broad interpretation of the FAIR principles, maturity indicators are necessary to determine the FAIRness of a dataset. In this work, we propose a reproducible computational workflow to assess data FAIRness in the life sciences. Our implementation follows principles and guidelines recommended by the maturity indicator authoring group and integrates concepts from the literature. In addition, we propose a FAIR balloon plot to summarize and compare dataset FAIRness. We evaluated the feasibility of our method on three real use cases where researchers looked for six datasets to answer their scientific questions. We retrieved information from repositories (ArrayExpress, Gene Expression Omnibus, eNanoMapper, caNanoLab, NanoCommons and ChEMBL), a registry of repositories, and a searchable resource (Google Dataset Search) via application program interfaces (API) wherever possible. With our analysis, we found that the six datasets met the majority of the criteria defined by the maturity indicators, and we showed areas where improvements can easily be reached. We suggest that use of standard schema for metadata and the presence of specific attributes in registries of repositories could increase FAIRness of datasets.

Cryo-FIB preparation of whole cells and tissue for cryo-TEM: use of high-pressure frozen specimens in tubes and planchets

The desire to study macromolecular complexes within their cellular context requires the ability to produce thin samples suitable for cryo‐TEM (cryo‐transmission electron microscope) investigations. In this paper, we discuss two similar approaches, which were developed independently in Utrecht (the Netherlands) and Albany (USA). The methods are particularly suitable for both tissue samples and cell suspensions prepared by a high‐pressure freezer (HPF). The workflows are explained with particular attention to potential pitfalls, while underlying principles are highlighted (‘why to do so’). Although both workflows function with a high success rate, full execution requires considerable experience and remains demanding. In addition, throughput is low. We hope to encourage other research groups worldwide to take on the challenge of improving the HPF– cryo‐FIB‐SEM – cryo‐TEM workflow. We discuss a number of suggestions to this end.

Lay Description

Life is ultimately dictated by the interaction of molecules in our bodies. Highly complex equipment is being used and further developed to study these interactions. The present paper describes methods to prepare small, very thin lamellae (area of 5×5 µm², thickness 50–300 nm) of a cell to be studied in a cryo‐transmission electron microscope (cryo‐TEM). Special care must be taken to preserve the natural state of molecules in their natural environment. In the case of cryo‐TEM, the samples must be frozen and kept frozen to be compatible with the vacuum conditions in the microscope. The frozen condition imposes technical challenges which are addressed. Two approaches to obtain the thin lamellae are described. Both make use of a focused ion beam (FIB) microscope. The FIB allows removal of material with nanometre precision by focusing a beam of ionised atoms (gallium ions) onto the sample. Careful control of the FIB allows cutting out of the required thin lamellae. In both strategies, the thin lamellae remain attached to the original sample, and the ensemble of sample with section and sample holder is transported from the FIB microscope to the TEM while being kept frozen.

[Reform of experimental course of large-scale life science equipment in universities]

The opening and sharing of large-scale life science equipment in universities is expanding. We must find ways to improve the role of large-scale equipment in cultivating students' practical and innovative abilities, to tap the potential of equipment, then to support scientific research and speed up scientific research output. We established a set of large-scale equipment training and practice teaching system including 15 topics and covering a wide range of technologies. In practice, we constantly innovated personalized courses. According to the differences of students' major and scientific research needs, we classified teaching content and set up parallel classes. Each class had the individualized teaching content and students could select from a menu of courses. In addition, we built up a cloud classroom teaching platform, online and offline teaching method supplemented each other. The teaching system have produced certain effect.

Physiology and philhellenism in the late nineteenth century: The self-fashioning of Emil du Bois-Reymond

Nineteenth-century Prussia was deeply entrenched in philhellenism, which affected the ideological framework of its public institutions. At Berlin's Friedrich Wilhelm University, philhellenism provided the rationale for a persistent elevation of the humanities over the burgeoning experimental life sciences. Despite this outspoken hierarchy, professor of physiology Emil du Bois-Reymond eventually managed to increase the prestige of his discipline considerably. We argue that du Bois-Reymond's use of philhellenic repertoires in his expositions on physiology for the educated German public contributed to the rise of physiology as a renowned scientific discipline. Du Bois-Reymond's rhetorical strategies helped to disassociate experimental physiology from clinical medicine, legitimize experimental practices, and associate the emerging discipline with the more esteemed humanities and theoretical sciences. His appropriation of philhellenic rhetoric thus spurred the late nineteenth-century change in disciplinary hierarchies and helped to pave the way for the current hegemonic position of the life sciences.

Optical Micromachines for Biological Studies

Optical tweezers have been used for biological studies since shortly after their inception. However, over the years research has suggested that the intense laser light used to create optical traps may damage the specimens being studied. This review aims to provide a brief overview of optical tweezers and the possible mechanisms for damage, and more importantly examines the role of optical micromachines as tools for biological studies. This review covers the achievements to date in the field of optical micromachines: improvements in the ability to produce micromachines, including multi-body microrobots; and design considerations for both optical microrobots and the optical trapping set-up used for controlling them are all discussed. The review focuses especially on the role of micromachines in biological research, and explores some of the potential that the technology has in this area.

Introduction to Genomic Analysis Workshop: A catalyst for engaging life-science researchers in high throughput analysis

Researchers in the life sciences are increasingly faced with the task of obtaining compute resources and training to analyze large, high-throughput technology generated datasets. As demand for compute resources has grown, high performance computing (HPC) systems have been implemented by research organizations and international consortiums to support academic researchers. However, life science researchers lack effective time-of-need training resources for utilization of these systems. Current training options have drawbacks that inhibit the effective training of researchers without experience in computational analysis. We identified the need for flexible, centrally-organized, easily accessible, interactive, and compute resource specific training for academic HPC use.  In our delivery of a modular workshop series, we provided foundational training to a group of researchers in a coordinated manner, allowing them to further pursue additional training and analysis on compute resources available to them. Efficacy measures indicate that the material was effectively delivered to a broad audience in a short time period, including both virtual and on-site students. The practical approach to catalyze academic HPC use is amenable to diverse systems worldwide.

KIR specificity and avidity of standard and unusual C1, C2, Bw4, Bw6 and A3/11 amino acid motifs at entire HLA:KIR interface between NK and target cells, the functional and evolutionary classification of HLA class I molecules

Natural killer (NK) cells make vital contributions to the immune system and the reproductive system. Notably, NK cells of donor origin can recognize and kill residual leukaemic cells and cure malignant patients in hematopoietic stem cell (HSC) transplant setting. NK cell function is regulated by KIRs that recognize cognate HLA class I molecules on target cells, depending on their amino acid residues. In review, we addressed the question of binding capacity and avidity of HLA class I molecules to different killer cell immunoglobulin-like receptors (KIRs) depending on all interacting amino acid residues both on HLA and KIR side. We searched PubMed database and analysed available HLA:KIR crystallographic data for amino acid residues in HLA molecules, those physically involved in binding KIRs (termed here the "entire KIR interface"). Within entire KIR interface, we selected five functional sequence motifs (14-19, 66-76, 77-84, 88-92 and 142-151) and classified them according to the conservation of their amino acid sequences among 8,942 HLA class I molecules. Although some conserved amino acid motifs were shared by different groups of KIR ligands, the HLA motif combinations were exclusive for the ligand groups. In 135 common HLA class I molecules with known HLA:KIR recognition, we found 54 combinations of five motifs in each of the KIR-binding interfaces (C1, C2, Bw4, A3/11) and conserved non-KIR-binding interfaces. Based on the entire KIR interface, this analysis allowed to classify 8,942 HLA class I molecules into KIR specificity groups. This functional and evolutionary classification of entire KIR interfaces provides a tool for unambiguously predicting HLA:KIR interactions for common and those HLA molecules that have not yet been functionally tested. Considering the entire KIR interface in HLA class I molecules, functional interactions of HLA and KIR can be predicted in immune responses, reproduction and allotransplantation. Further functional studies are needed on the HLA:KIR interaction variations caused by the repertoires of peptides presented by HLA molecules and KIR polymorphisms at allelic level.

Cyberbiosecurity: A Call for Cooperation in a New Threat Landscape

The life sciences now interface broadly with information technology (IT) and cybersecurity. This convergence is a key driver in the explosion of biotechnology research and its industrial applications in health care, agriculture, manufacturing, automation, artificial intelligence, and synthetic biology. As the information and handling mechanisms for biological materials have become increasingly digitized, many market sectors are now vulnerable to threats at the digital interface. This growing landscape will be addressed by cyberbiosecurity, the emerging field at the convergence of both the life sciences and IT disciplines. This manuscript summarizes the current cyberbiosecurity landscape, identifies existing vulnerabilities, and calls for formalized collaboration across a swath of disciplines to develop frameworks for early response systems to anticipate, identify, and mitigate threats in this emerging domain.

New indicators and indexes for benchmarking university-industry-government innovation in medical and life science clusters: results from the European FP7 Regions of Knowledge HealthTIES project

Background

While the European Union is striving to become the ‘Innovation Union’, there remains a lack of quantifiable indicators to compare and benchmark regional innovation clusters. To address this issue, a HealthTIES (Healthcare, Technology and Innovation for Economic Success) consortium was funded by the European Union’s Regions of Knowledge initiative, research and innovation funding programme FP7. HealthTIES examined whether the health technology innovation cycle was functioning differently in five European regional innovation clusters and proposed regional and joint actions to improve their performance. The clusters included BioCat (Barcelona, Catalonia, Spain), Medical Delta (Leiden, Rotterdam and Delft, South Holland, Netherlands), Oxford and Thames Valley (United Kingdom), Life Science Zürich (Switzerland), and Innova Észak-Alföld (Debrecen, Hungary).

Methods

Appreciation of the ‘triple helix’ of university–industry–government innovation provided the impetus for the development of two quantifiable innovation indexes and related indicators. The HealthTIES H-index is calculated for disease and technology platforms based on the h-index proposed by Hirsch. The HealthTIES Innovation Index is calculated for regions based on 32 relevant quantitative and discriminative indicators grouped into 12 categories and 3 innovation phases, namely ‘Input’ (n = 12), ‘Innovation System’ (n = 9) and ‘Output’ (n = 11).

Results

The HealthTIES regions had developed relatively similar disease and technology platform profiles, yet with distinctive strengths and weaknesses. The regional profiles of the innovation cycle in each of the three phases were surprisingly divergent. Comparative assessments based on the indicators and indexes helped identify and share best practice and inform regional and joint action plans to strengthen the competitiveness of the HealthTIES regions.

Conclusion

The HealthTIES indicators and indexes provide useful practical tools for the measurement and benchmarking of university–industry–government innovation in European medical and life science clusters. They are validated internally within the HealthTIES consortium and appear to have a degree of external prima facie validity. Potentially, the tools and accompanying analyses can be used beyond the HealthTIES consortium to inform other regional governments, researchers and, possibly, large companies searching for their next location, analyse and benchmark ‘triple helix’ dynamics within their own networks over time, and to develop integrated public–private and cross-regional research and innovation strategies in Europe and beyond.

Electronic supplementary material

The online version of this article (10.1186/s12961-019-0414-5) contains supplementary material, which is available to authorized users.

EU Clinical Trials Regulation 2014: Fetter or facilitator?

European Union (EU) Clinical Trials Regulation 536/2014, expected to come into force in 2019, provides for a streamlined single EU application for cross-border clinical trials and enhanced transparency of results. The status of the Regulation in post-Brexit UK is uncertain. Matters of regulatory alignment will be covered by agreements on the future EU-UK relationship. In the short term, implementation of the Regulation in the United Kingdom depends on the Brexit model and timing of the Regulation’s implementation. The EU (Withdrawal) Act will convert EU law into UK law, including the vast array of EU life sciences regulation. However, the Regulation is likely to be implemented after the United Kingdom leaves the EU, but within the transition period. If the United Kingdom is not part of the legal framework governing clinical trials in the EU, then the United Kingdom will still need to comply with the global framework set out in the International Council on Harmonisation if it wants to be part of trials of medicinal products for which marketing authorization will be sought for licensing in the European Economic Area. This article extols the virtues of harmonization with the EU and attempts to counter some of the media focus on the advantages of a deregulated bespoke approach.

Recent developments in scholarly publishing to improve research practices in the life sciences

We outline recent developments in scholarly publishing that we think will improve the working environment and career prospects for life scientists. Most prominently, we discuss two key developments. (1) Life scientists are now embracing a preprint culture leading to rapid dissemination of research findings. (2) We outline steps to overcome the reproducibility crisis. We also briefly describe other innovations in scholarly publishing, along with changes to open access mandates from funding agencies.

Hidden concerns of sharing research data by low/middle-income country scientists

There has considerable interest in bringing low/middle-income countries (LMIC) scientists into discussions on Open Data - both as contributors and users. The establishment of in situ data sharing practices within LMIC research institutions is vital for the development of an Open Data landscape in the Global South. Nonetheless, many LMICs have significant challenges - resource provision, research support and extra-laboratory infrastructures. These low-resourced environments shape data sharing activities, but are rarely examined within Open Data discourse. In particular, little attention is given to how these research environments shape scientists' perceptions of data sharing (dis)incentives. This paper expands on these issues of incentivizing data sharing, using data from a quantitative survey disseminated to life scientists in 13 countries in sub-Saharan Africa. This interrogated not only perceptions of data sharing amongst LMIC scientists, but also how these are connected to the research environments and daily challenges experienced by them. The paper offers a series of analysis around commonly cited (dis)incentives such as data sharing as a means of improving research visibility; sharing and funding; and online connectivity. It identifies key areas that the Open Data community need to consider if true openness in research is to be established in the Global South.

Deuterium- and Tritium-Labelled Compounds: Applications in the Life Sciences

Hydrogen isotopes are unique tools for identifying and understanding biological and chemical processes. Hydrogen isotope labelling allows for the traceless and direct incorporation of an additional mass or radioactive tag into an organic molecule with almost no changes in its chemical structure, physical properties, or biological activity. Using deuterium-labelled isotopologues to study the unique mass-spectrometric patterns generated from mixtures of biologically relevant molecules drastically simplifies analysis. Such methods are now providing unprecedented levels of insight in a wide and continuously growing range of applications in the life sciences and beyond. Tritium (³ H), in particular, has seen an increase in utilization, especially in pharmaceutical drug discovery. The efforts and costs associated with the synthesis of labelled compounds are more than compensated for by the enhanced molecular sensitivity during analysis and the high reliability of the data obtained. In this Review, advances in the application of hydrogen isotopes in the life sciences are described.

Implementing a web-based introductory bioinformatics course for non-bioinformaticians that incorporates practical exercises

A recent scientific discipline, bioinformatics, defined as using informatics for the study of biological problems, is now a requirement for the study of biological sciences. Bioinformatics has become such a powerful and popular discipline that several academic institutions have created programs in this field, allowing students to become specialized. However, biology students who are not involved in a bioinformatics program also need a solid toolbox of bioinformatics software and skills. Therefore, we have developed a completely online bioinformatics course for non-bioinformaticians, entitled "BIF-1901 Introduction à la bio-informatique et à ses outils (Introduction to bioinformatics and bioinformatics tools)," given by the Department of Biochemistry, Microbiology, and Bioinformatics of Université Laval (Quebec City, Canada). This course requires neither a bioinformatics background nor specific skills in informatics. The underlying main goal was to produce a completely online up-to-date bioinformatics course, including practical exercises, with an intuitive pedagogical framework. The course, BIF-1901, was conceived to cover the three fundamental aspects of bioinformatics: (1) informatics, (2) biological sequence analysis, and (3) structural bioinformatics. This article discusses the content of the modules, the evaluations, the pedagogical framework, and the challenges inherent to a multidisciplinary, fully online course. © 2017 by The International Union of Biochemistry and Molecular Biology, 46(1):31-38, 2018.

Homo Politicus meets Homo Ludens: Public participation in serious life science games

Public participation in science and gamification of science are two strong contemporary trends, especially in the area of emerging techno-sciences. Involvement of the public in research-related activities is an integral part of public engagement with science and technologies, which can be successfully achieved through a participatory game design. Focusing on the participatory dimension of educational games, we have reviewed a number of existing participation heuristics in light of their suitability to characterize available mobile and browser science games. We analyzed 87 games with respect to their participatory and motivational elements and demonstrated that the majority of mobile games have only basic participative features. This review of the landscape of participative science games in the domain of life sciences highlights a number of major challenges present in the design of such applications. At the same time, it reveals a number of opportunities to enhance public engagement using science games.

[Big Biology : Supersizing Wissenschaft zu Beginn des 21. Jahrhunderts]

Ist Biologie das jüngste Mitglied in der Familie von Big Science? Die vermehrte Zusammenarbeit in der biologischen Forschung wurde in der Folge des Human Genome Project zwar zum Gegenstand hitziger Diskussionen, aber Debatten und Reflexionen blieben meist im Polemischen verhaftet und zeigten eine begrenzte Wertschätzung für die Vielfalt und Erklärungskraft des Konzepts von Big Science. Zur gleichen Zeit haben Wissenschafts- und Technikforscher/innen in ihren Beschreibungen des Wandels der Forschungslandschaft die Verwendung des Begriffs Big Science gemieden. Dieser interdisziplinäre Artikel kombiniert eine begriffliche Analyse des Konzepts von Big Science mit unterschiedlichen Daten und Ideen aus einer Multimethodenuntersuchung mehrerer großer Forschungsprojekte in der Biologie. Ziel ist es, ein empirisch fundiertes, nuanciertes und analytisch nützliches Verständnis von Big Biology zu entwickeln und die normativen Debatten mit ihren einfachen Dichotomien und rhetorischen Positionen hinter sich zu lassen. Zwar kann das Konzept von Big Science als eine Mode in der Wissenschaftspolitik gesehen werden – inzwischen vielleicht sogar als ein altmodisches Konzept –, doch lautet meine innovative Argumentation, dass dessen analytische Verwendung unsere Aufmerksamkeit auf die Ausweitung der Zusammenarbeit in den Biowissenschaften lenkt. Die Analyse von Big Biology zeigt Unterschiede zu Big Physics und anderen Formen von Big Science, namentlich in den Mustern der Forschungsorganisation, der verwendeten Technologien und der gesellschaftlichen Zusammenhänge, in denen sie tätig ist. So können Reflexionen über Big Science, Big Biology und ihre Beziehungen zur Wissensproduktion die jüngsten Behauptungen über grundlegende Veränderungen in der Life Science-Forschung in einen historischen Kontext stellen.

How Do Scientists Define Openness? Exploring the Relationship Between Open Science Policies and Research Practice

This article documents how biomedical researchers in the United Kingdom understand and enact the idea of "openness." This is of particular interest to researchers and science policy worldwide in view of the recent adoption of pioneering policies on Open Science and Open Access by the U.K. government-policies whose impact on and implications for research practice are in need of urgent evaluation, so as to decide on their eventual implementation elsewhere. This study is based on 22 in-depth interviews with U.K. researchers in systems biology, synthetic biology, and bioinformatics, which were conducted between September 2013 and February 2014. Through an analysis of the interview transcripts, we identify seven core themes that characterize researchers' understanding of openness in science and nine factors that shape the practice of openness in research. Our findings highlight the implications that Open Science policies can have for research processes and outcomes and provide recommendations for enhancing their content, effectiveness, and implementation.

A Model For Teaching Advanced Neuroscience Methods: A Student-Run Seminar to Increase Practical Understanding and Confidence

Neuroscience doctoral students must master specific laboratory techniques and approaches to complete their thesis work (hands-on learning). Due to the highly interdisciplinary nature of the field, learning about a diverse range of methodologies through literature surveys and coursework is also necessary for student success (hands-off learning). Traditional neuroscience coursework stresses what is known about the nervous system with relatively little emphasis on the details of the methods used to obtain this knowledge. Furthermore, hands-off learning is made difficult by a lack of detail in methods sections of primary articles, subfield-specific jargon and vague experimental rationales. We designed a student-taught course to enable first-year neuroscience doctoral students to overcome difficulties in hands-off learning by introducing a new approach to reading and presenting primary research articles that focuses on methodology. In our literature-based course students were encouraged to present a method with which they had no previous experience. To facilitate weekly discussions, "experts" were invited to class sessions. Experts were advanced graduate students who had hands-on experience with the method being covered and served as discussion co-leaders. Self-evaluation worksheets were administered on the first and last days of the 10-week course and used to assess students' confidence in discussing research and methods outside of their primary research expertise. These evaluations revealed that the course significantly increased the students' confidence in reading, presenting and discussing a wide range of advanced neuroscience methods.

Towards an open science publishing platform

The way science and research is done is rapidly becoming more open and collaborative. The traditional way of publishing new findings in journals is becoming increasingly outdated and no longer serves the needs of much of science. Whilst preprints can bring significant benefits of removing delay and selection, they do not go far enough if simply implemented alongside the existing journal system. We propose that we need a new approach, an Open Science Platform, that takes the benefits of preprints but adds formal, invited, and transparent post-publication peer review. This bypasses the problems of the current journal system and, in doing so, moves the evaluation of research and researchers away from the journal-based Impact Factor and towards a fairer system of article-based qualitative and quantitative indicators. In the long term, it should be irrelevant where a researcher publishes their findings. What is important is that research is shared and made available without delay within a framework that encourages quality standards and requires all players in the research community to work as collaborators.

Pharmaceutical Market Access: current state of affairs and key challenges - results of the Market Access Launch Excellence Inventory (MALEI)

OBJECTIVES

To take inventory of the current state of affairs of Market Access Launch Excellence in the life sciences industry. To identify key gaps and challenges for Market Access (MA) and discuss how they can be addressed. To generate a baseline for benchmarking MA launch excellence.

METHODOLOGY

An online survey was conducted with pharmaceutical executives primarily working in MA, marketing, or general management. The survey aimed to evaluate MA excellence prerequisites across the product life cycle (rated by importance and level of implementation) and to describe MA activity models in the respective companies. Composite scores were calculated from respondents' ratings and answers.

RESULTS

Implementation levels of MA excellence prerequisites generally lagged behind their perceived importance. Item importance and the respective level of implementation correlated well, which can be interpreted as proof of the validity of the questionnaire. The following areas were shown to be particularly underimplemented: 1) early integration of MA and health economic considerations in research and development decision making, 2) developing true partnerships with payers, including the development of services 'beyond the pill', and 3) consideration of human resource and talent management. The concept of importance-adjusted implementation levels as a hybrid parameter was introduced and shown to be a viable tool for benchmarking purposes. More than 70% of respondents indicated that their companies will invest broadly in MA in terms of capital and headcount within the next 3 years.

CONCLUSIONS

MA (launch) excellence needs to be further developed in order to close implementation gaps across the entire product life cycle. As MA is a comparatively young pharmaceutical discipline in a complex and dynamic environment, this effort will require strategic focus and dedication. The Market Access Launch Excellence Inventory benchmarking tool may help guide decision makers to prioritize their endeavors.

Future opportunities and trends for e-infrastructures and life sciences: going beyond the grid to enable life science data analysis

With the increasingly rapid growth of data in life sciences we are witnessing a major transition in the way research is conducted, from hypothesis-driven studies to data-driven simulations of whole systems. Such approaches necessitate the use of large-scale computational resources and e-infrastructures, such as the European Grid Infrastructure (EGI). EGI, one of key the enablers of the digital European Research Area, is a federation of resource providers set up to deliver sustainable, integrated and secure computing services to European researchers and their international partners. Here we aim to provide the state of the art of Grid/Cloud computing in EU research as viewed from within the field of life sciences, focusing on key infrastructures and projects within the life sciences community. Rather than focusing purely on the technical aspects underlying the currently provided solutions, we outline the design aspects and key characteristics that can be identified across major research approaches. Overall, we aim to provide significant insights into the road ahead by establishing ever-strengthening connections between EGI as a whole and the life sciences community.

Moving life science ethics debates beyond national borders: some empirical observations

The life sciences are increasingly being called on to produce "socially robust" knowledge that honors the social contract between science and society. This has resulted in the emergence of a number of "broad social issues" that reflect the ethical tensions in these social contracts. These issues are framed in a variety of ways around the world, evidenced by differences in regulations addressing them. It is important to question whether these variations are simply regulatory variations or in fact reflect a contextual approach to ethics that brings into question the existence of a system of "global scientific ethics". Nonetheless, within ethics education for scientists these broad social issues are often presented using this scheme of global ethics due to legacies of science ethics pedagogy. This paper suggests this may present barriers to fostering international discourse between communities of scientists, and may cause difficulties in harmonizing (and transporting) national regulations for the governance of these issues. Reinterpreting these variations according to how the content of ethical principles is attributed by communities is proposed as crucial for developing a robust international discourse. To illustrate this, the paper offers some empirical fieldwork data that considers how the concept of dual-use (as a broad social issue) was discussed within African and UK laboratories. Demonstrating that African scientists reshaped the concept of dual-use according to their own research environmental pressures and ascribed alternative content to the principles that underpin it, suggests that the limitations of a "global scientific ethics" system for these issues cannot be ignored.

Roughness statistical influence on cell adhesion using profilometry and multiscale analysis

In this study, two series of 11 samples of TiAl6V4 titanium alloy and 316L stainless steel have been polished in an isotropic manner at different levels in order to quantify the influence of biomaterial roughness on cell behavior. Topography was measured by a tactile profilometer and a multiscale analysis has been carried out. Human osteoblasts have been cultured on those samples. It appears that roughness has no reproducible effect on the cell behavior except an influence on cell orientation on the wider grooves. As a conclusion, biomaterial surface damage, in the roughness range between Ra = 0.01 and 0.1 μm, has no influence on cell-adhesion mechanisms when roughness is isotropic and groove width is inferior to a critical value.

Report of a Royal College of Physicians and National Institute for Health Research workshop - developing research capacity to ensure successful study development and delivery

The landscape and opportunities for clinical research have changed significantly following the creation of the National Institute for Health Research (NIHR) in 2006. This article describes the scale and impact of the NIHR network infrastructure for clinical research and identifies areas for future development in partnership with the National Health Service (NHS), clinicians and research funders.

Establishing a liquid-covered culture of polarized human airway epithelial Calu-3 cells to study host cell response to respiratory pathogens in vitro

The apical and basolateral surfaces of airway epithelial cells demonstrate directional responses to pathogen exposure in vivo. Thus, ideal in vitro models for examining cellular responses to respiratory pathogens polarize, forming apical and basolateral surfaces. One such model is differentiated normal human bronchial epithelial cells (NHBE). However, this system requires lung tissue samples, expertise isolating and culturing epithelial cells from tissue, and time to generate an air-liquid interface culture. Calu-3 cells, derived from a human bronchial adenocarcinoma, are an alternative model for examining the response of proximal airway epithelial cells to respiratory insult, pharmacological compounds, and bacterial and viral pathogens, including influenza virus, rhinovirus and severe acute respiratory syndrome-associated coronavirus. Recently, we demonstrated that Calu-3 cells are susceptible to respiratory syncytial virus (RSV) infection in a manner consistent with NHBE. Here, we detail the establishment of a polarized, liquid-covered culture (LCC) of Calu-3 cells, focusing on the technical details of growing and culturing Calu-3 cells, maintaining cells that have been cultured into LCC, and we present the method for performing respiratory virus infection of polarized Calu-3 cells. To consistently obtain polarized Calu-3 LCC, Calu-3 cells must be carefully subcultured before culturing in Transwell inserts. Calu-3 monolayer cultures should remain below 90% confluence, should be subcultured fewer than 10 times from frozen stock, and should regularly be supplied with fresh medium. Once cultured in Transwells, Calu-3 LCC must be handled with care. Irregular media changes and mechanical or physical disruption of the cell layers or plates negatively impact polarization for several hours or days. Polarization is monitored by evaluating trans-epithelial electrical resistance (TEER) and is verified by evaluating the passive equilibration of sodium fluorescein between the apical and basolateral compartments . Once TEER plateaus at or above 1,000 Ω×cm(2), Calu-3 LCC are ready to use to examine cellular responses to respiratory pathogens.