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\"Scientists specializing in the in-depth analysis of the published scientific literature have to the conclusion that a large part of the scientific literature covers results that cannot be replicated in other independent laboratories. Scientists take this to mean that the results are unreliable or untrue. In this book, biomedical researcher Csaba Szabo summarizes the causes and consequences of this so-called \"reproducibility crisis\" in biomedical research. The range of causes is wide, from the specificities of the methods used, through various pitfalls in the design of experiments and analysis of experimental data (e.g., confirmation bias), plagiarism and deliberate data falsification, to the systematic publication of fictitious experiments that have never been performed. Through a few blatant examples - e.g. Anil Potti (Duke University); Piero Anversa (Harvard University) - Szabo describes the damaging impact that blatant fraud can have on the development of an entire field of science, and introduces some of the maverick \"science investigators\" - often working in anonymity - who devote their lives to tracking down and exposing scientific fraudsters. The book also answers the questions (a) what individual and systemic factors are involved in allowing these phenomena to occur, (b) why the appropriate steps have not been taken to control them, and (c) what the implications of the crisis are for the future of medicine and, within it, for the development of new drugs\"-- Provided by publisher.

\"This book critically examines the historical and philosophical foundations of construct validity theory (CVT), and how these have and continue to inform and constrain the conceptualization of validity and its application in research. CVT has had an immense impact on how researchers in the behavioural sciences conceptualize and approach their subject matter. Yet, there is equivocation regarding the foundations of the CVT framework as well as ambiguities concerning the nature of the 'constructs' that are its raison d'etre. The book is organized in terms of three major parts that speak, respectively, to the historical, philosophical, and pragmatic dimensions of CVT. The primary objective is to provide researchers and students with a critical lens through which a deeper understanding may be gained of both the utility and limitations of CVT and the validation practices to which it has given rise.\"-- Back cover.

Heat shock protein 90 (Hsp90) is an ATP-dependent molecular chaperone which is essential in eukaryotes. It is required for the activation and stabilization of a wide variety of client proteins and many of them are involved in important cellular pathways. Since Hsp90 affects numerous physiological processes such as signal transduction, intracellular transport, and protein degradation, it became an interesting target for cancer therapy. Structurally, Hsp90 is a flexible dimeric protein composed of three different domains which adopt structurally distinct conformations. ATP binding triggers directionality in these conformational changes and leads to a more compact state. To achieve its function, Hsp90 works together with a large group of cofactors, termed co-chaperones. Co-chaperones form defined binary or ternary complexes with Hsp90, which facilitate the maturation of client proteins. In addition, posttranslational modifications of Hsp90, such as phosphorylation and acetylation, provide another level of regulation. They influence the conformational cycle, co-chaperone interaction, and inter-domain communications. In this review, we discuss the recent progress made in understanding the Hsp90 machinery.

In 2014 the National Science Foundation (NSF) provided support to the National Academies of Sciences, Engineering, and Medicine for a series of Forums on Open Science in response to a government-wide directive to support increased public access to the results of research funded by the federal government. However, the breadth of the work resulting from the series precluded a focus on any specific topic or discussion about how to improve public access. Thus, the main goal of the Workshop on Transparency and Reproducibility in Federal Statistics was to develop some understanding of what principles and practices are, or would be, supportive of making federal statistics more understandable and reviewable, both by agency staff and the public. This publication summarizes the presentations and discussions from the workshop.

•Most studies do not present all results of their analysis, hiding subthreshold ones.•Hiding results negatively affects the interpretation and understanding of the study.•Neuroimagers should present all results of their study, highlighting key ones.•Using the public NARPS data, we show several benefits of the \"highlighting\" approach.•The highlighting approach improves individual studies and meta-analyses. Most neuroimaging studies display results that represent only a tiny fraction of the collected data. While it is conventional to present \"only the significant results\" to the reader, here we suggest that this practice has several negative consequences for both reproducibility and understanding. This practice hides away most of the results of the dataset and leads to problems of selection bias and irreproducibility, both of which have been recognized as major issues in neuroimaging studies recently. Opaque, all-or-nothing thresholding, even if well-intentioned, places undue influence on arbitrary filter values, hinders clear communication of scientific results, wastes data, is antithetical to good scientific practice, and leads to conceptual inconsistencies. It is also inconsistent with the properties of the acquired data and the underlying biology being studied. Instead of presenting only a few statistically significant locations and hiding away the remaining results, studies should \"highlight\" the former while also showing as much as possible of the rest. This is distinct from but complementary to utilizing data sharing repositories: the initial presentation of results has an enormous impact on the interpretation of a study. We present practical examples and extensions of this approach for voxelwise, regionwise and cross-study analyses using publicly available data that was analyzed previously by 70 teams (NARPS; Botvinik-Nezer, et al., 2020), showing that it is possible to balance the goals of displaying a full set of results with providing the reader reasonably concise and \"digestible\" findings. In particular, the highlighting approach sheds useful light on the kind of variability present among the NARPS teams' results, which is primarily a varied strength of agreement rather than disagreement. Using a meta-analysis built on the informative \"highlighting\" approach shows this relative agreement, while one using the standard \"hiding\" approach does not. We describe how this simple but powerful change in practice—focusing on highlighting results, rather than hiding all but the strongest ones—can help address many large concerns within the field, or at least to provide more complete information about them. We include a list of practical suggestions for results reporting to improve reproducibility, cross-study comparisons and meta-analyses.

Unpublished code and sensitivity to training conditions make many claims hard to verify. The booming field of artificial intelligence (AI) is grappling with a replication crisis, much like the ones that have afflicted psychology, medicine, and other fields over the past decade. Just because algorithms are based on code doesn't mean experiments are easily replicated. Far from it. Unpublished codes and a sensitivity to training conditions have made it difficult for AI researchers to reproduce many key results. That is leading to a new conscientiousness about research methods and publication protocols. Last week, at a meeting of the Association for the Advancement of Artificial Intelligence in New Orleans, Louisiana, reproducibility was on the agenda, with some teams diagnosing the problem—and one laying out tools to mitigate it.

Preregistration has gained traction as one of the most promising solutions to improve the replicability of scientific effects. In this project, we compared 193 psychology studies that earned a Preregistration Challenge prize or preregistration badge to 193 related studies that were not preregistered. In contrast to our theoretical expectations and prior research, we did not find that preregistered studies had a lower proportion of positive results (Hypothesis 1), smaller effect sizes (Hypothesis 2), or fewer statistical errors (Hypothesis 3) than non-preregistered studies. Supporting our Hypotheses 4 and 5, we found that preregistered studies more often contained power analyses and typically had larger sample sizes than non-preregistered studies. Finally, concerns about the publishability and impact of preregistered studies seem unwarranted, as preregistered studies did not take longer to publish and scored better on several impact measures. Overall, our data indicate that preregistration has beneficial effects in the realm of statistical power and impact, but we did not find robust evidence that preregistration prevents p -hacking and HARKing (Hypothesizing After the Results are Known).

The goal of clinical laboratories is to produce accurate information for clinical decision making in medicine. More than half of the medical decisions made depend on clinical laboratory tests. Patient safety represents an important and critical problem for laboratories. They need to assure that the information they deliver to physicians is accurate, and therefore safe for clinicians to use. Endogenous compounds can interfere with laboratory tests, decreasing accuracy and threatening patient safety. Elevated bilirubin (bilirubinemia) and elevated lipids (lipemia) are common conditions that cause significant interferences with laboratory results. Clinicians depend on laboratories to detect these endogenous interferences. Laboratories must have a means to detect these endogenous interferences, make decisions about reporting results, and evaluate their impact. Most clinical pathology books provide only an abbreviated introduction to the subject, or provide a long list of references, without the necessary foundation for evaluating their significance. Package inserts typically provide scant information. This book provides the empirical and theoretical foundation for these interferences, describes the clinical settings where they occur, and explains their evaluation and detection, allowing the laboratory to interpret the available data on interferences and make the appropriate decision to effectively report test results while protecting patient safety.

In a companion paper by Cohen-Adad et al . we introduce the spine generic quantitative MRI protocol that provides valuable metrics for assessing spinal cord macrostructural and microstructural integrity. This protocol was used to acquire a single subject dataset across 19 centers and a multi-subject dataset across 42 centers (for a total of 260 participants), spanning the three main MRI manufacturers: GE, Philips and Siemens. Both datasets are publicly available via git-annex. Data were analysed using the Spinal Cord Toolbox to produce normative values as well as inter/intra-site and inter/intra-manufacturer statistics. Reproducibility for the spine generic protocol was high across sites and manufacturers, with an average inter-site coefficient of variation of less than 5% for all the metrics. Full documentation and results can be found at https://spine-generic.rtfd.io/ . The datasets and analysis pipeline will help pave the way towards accessible and reproducible quantitative MRI in the spinal cord. Measurement(s) spinal cord Technology Type(s) magnetic resonance imaging Factor Type(s) manufacturer • site Sample Characteristic - Organism Homo sapiens Sample Characteristic - Location Canada • Switzerland • Australia • United States of America • United Kingdom • Germany • French Republic • Czech Republic • Italy • Japan • Kingdom of Spain • China Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.14052269