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Stepping in the same river twice : replication in biological research
An international team of biologists, philosophers, and historians of science explores the critically important process of replication in biological and biomedical research. Without replication, the trustworthiness of scientific research remains in doubt. Although replication is increasingly recognized as a central problem in many scientific disciplines, repeating the same scientific observations of experiments or reproducing the same set of analyses from existing data is remarkably difficult. In this important volume, an international team of biologists, philosophers, and historians of science addresses challenges and solutions for valid replication of research in medicine, ecology, natural history, agriculture, physiology, and computer science. After the introduction to important concepts and historical background, the book offers paired chapters that provide theoretical overviews followed by detailed case studies. These studies range widely in topics, from infectious-diseases and environmental monitoring to museum collections, meta-analysis, bioinformatics, and more. The closing chapters explicate and quantify problems in the case studies, and the volume concludes with important recommendations for best practices. -- Provided by publisher.
Book
Responsible research with biological select agents and toxins
The effort to understand and combat infectious diseases has, during the centuries, produced many key advances in science and medicine-including the development of vaccines, drugs, and other treatments. A subset of this research is conducted with agents that, like anthrax, not only pose a severe threat to the health of humans, plants, and animals but can also be used for ill-intended purposes. Such agents have been listed by the government as biological select agents and toxins. The 2001 anthrax letter attacks prompted the creation of new regulations aimed at increasing security for research with dangerous pathogens. The outcome of the anthrax letter investigation has raised concern about whether these measures are adequate.
Responsible Research with Biological Select Agents and Toxins evaluates both the physical security of select agent laboratories and personnel reliability measures designed to ensure the trustworthiness of those with access to biological select agents and toxins. The book offers a set of guiding principles and recommended changes to minimize security risk and facilitate the productivity of research. The book recommends fostering a culture of trust and responsibility in the laboratory, engaging the community in oversight of the Select Agent Program, and enhancing the operation of the Select Agent Program.
eBook
Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension
The CONSORT 2010 statement provides minimum guidelines for reporting randomized trials. Its widespread use has been instrumental in ensuring transparency in the evaluation of new interventions. More recently, there has been a growing recognition that interventions involving artificial intelligence (AI) need to undergo rigorous, prospective evaluation to demonstrate impact on health outcomes. The CONSORT-AI (Consolidated Standards of Reporting Trials–Artificial Intelligence) extension is a new reporting guideline for clinical trials evaluating interventions with an AI component. It was developed in parallel with its companion statement for clinical trial protocols: SPIRIT-AI (Standard Protocol Items: Recommendations for Interventional Trials–Artificial Intelligence). Both guidelines were developed through a staged consensus process involving literature review and expert consultation to generate 29 candidate items, which were assessed by an international multi-stakeholder group in a two-stage Delphi survey (103 stakeholders), agreed upon in a two-day consensus meeting (31 stakeholders) and refined through a checklist pilot (34 participants). The CONSORT-AI extension includes 14 new items that were considered sufficiently important for AI interventions that they should be routinely reported in addition to the core CONSORT 2010 items. CONSORT-AI recommends that investigators provide clear descriptions of the AI intervention, including instructions and skills required for use, the setting in which the AI intervention is integrated, the handling of inputs and outputs of the AI intervention, the human–AI interaction and provision of an analysis of error cases. CONSORT-AI will help promote transparency and completeness in reporting clinical trials for AI interventions. It will assist editors and peer reviewers, as well as the general readership, to understand, interpret and critically appraise the quality of clinical trial design and risk of bias in the reported outcomes.
The CONSORT-AI and SPIRIT-AI extensions improve the transparency of clinical trial design and trial protocol reporting for artificial intelligence interventions.
Journal Article
Avoiding a replication crisis in deep-learning-based bioimage analysis
Deep learning algorithms are powerful tools for analyzing, restoring and transforming bioimaging data. One promise of deep learning is parameter-free one-click image analysis with expert-level performance in a fraction of the time previously required. However, as with most emerging technologies, the potential for inappropriate use is raising concerns among the research community. In this Comment, we discuss key concepts that we believe are important for researchers to consider when using deep learning for their microscopy studies. We describe how results obtained using deep learning can be validated and propose what should, in our view, be considered when choosing a suitable tool. We also suggest what aspects of a deep learning analysis should be reported in publications to ensure reproducibility. We hope this perspective will foster further discussion among developers, image analysis specialists, users and journal editors to define adequate guidelines and ensure the appropriate use of this transformative technology.
Journal Article
Guidelines and definitions for research on epithelial–mesenchymal transition
Epithelial–mesenchymal transition (EMT) encompasses dynamic changes in cellular organization from epithelial to mesenchymal phenotypes, which leads to functional changes in cell migration and invasion. EMT occurs in a diverse range of physiological and pathological conditions and is driven by a conserved set of inducing signals, transcriptional regulators and downstream effectors. With over 5,700 publications indexed by Web of Science in 2019 alone, research on EMT is expanding rapidly. This growing interest warrants the need for a consensus among researchers when referring to and undertaking research on EMT. This Consensus Statement, mediated by ‘the EMT International Association’ (TEMTIA), is the outcome of a 2-year-long discussion among EMT researchers and aims to both clarify the nomenclature and provide definitions and guidelines for EMT research in future publications. We trust that these guidelines will help to reduce misunderstanding and misinterpretation of research data generated in various experimental models and to promote cross-disciplinary collaboration to identify and address key open questions in this research field. While recognizing the importance of maintaining diversity in experimental approaches and conceptual frameworks, we emphasize that lasting contributions of EMT research to increasing our understanding of developmental processes and combatting cancer and other diseases depend on the adoption of a unified terminology to describe EMT.In this Consensus Statement, the authors (on behalf of the EMT International Association) propose guidelines to define epithelial–mesenchymal transition, its phenotypic plasticity and the associated multiple intermediate epithelial–mesenchymal cell states. Clarification of nomenclature and definitions will help reduce misinterpretation of research data generated in different experimental model systems and promote cross-disciplinary collaboration.
Journal Article
Multi-omics approaches to disease
High-throughput technologies have revolutionized medical research. The advent of genotyping arrays enabled large-scale genome-wide association studies and methods for examining global transcript levels, which gave rise to the field of “integrative genetics”. Other omics technologies, such as proteomics and metabolomics, are now often incorporated into the everyday methodology of biological researchers. In this review, we provide an overview of such omics technologies and focus on methods for their integration across multiple omics layers. As compared to studies of a single omics type, multi-omics offers the opportunity to understand the flow of information that underlies disease.
Journal Article
Survey of laboratory-acquired infections around the world in biosafety level 3 and 4 laboratories
Laboratory-acquired infections due to a variety of bacteria, viruses, parasites, and fungi have been described over the last century, and laboratory workers are at risk of exposure to these infectious agents. However, reporting laboratory-associated infections has been largely voluntary, and there is no way to determine the real number of people involved or to know the precise risks for workers. In this study, an international survey based on volunteering was conducted in biosafety level 3 and 4 laboratories to determine the number of laboratory-acquired infections and the possible underlying causes of these contaminations. The analysis of the survey reveals that laboratory-acquired infections have been infrequent and even rare in recent years, and human errors represent a very high percentage of the cases. Today, most risks from biological hazards can be reduced through the use of appropriate procedures and techniques, containment devices and facilities, and the training of personnel.
Journal Article
A Catalog of Reference Genomes from the Human Microbiome
The human microbiome refers to the community of microorganisms, including prokaryotes, viruses, and microbial eukaryotes, that populate the human body. The National Institutes of Health launched an initiative that focuses on describing the diversity of microbial species that are associated with health and disease. The first phase of this initiative includes the sequencing of hundreds of microbial reference genomes, coupled to metagenomic sequencing from multiple body sites. Here we present results from an initial reference genome sequencing of 178 microbial genomes. From 547,968 predicted polypeptides that correspond to the gene complement of these strains, previously unidentified (\"novel\") polypeptides that had both unmasked sequence length greater than 100 amino acids and no BLASTP match to any nonreference entry in the nonredundant subset were defined. This analysis resulted in a set of 30,867 polypeptides, of which 29,987 (̃97%) were unique. In addition, this set of microbial genomes allows for ̃40% of random sequences from the microbiome of the gastrointestinal tract to be associated with organisms based on the match criteria used. Insights into pan-genome analysis suggest that we are still far from saturating microbial species genetic data sets. In addition, the associated metrics and standards used by our group for quality assurance are presented.
Journal Article
Promoting transparency and reproducibility in enhanced molecular simulations
The PLUMED consortium unifies developers and contributors to PLUMED, an open-source library for enhanced-sampling, free-energy calculations and the analysis of molecular dynamics simulations. Here, we outline our efforts to promote transparency and reproducibility by disseminating protocols for enhanced-sampling molecular simulations.
Journal Article