Sources of error in the retracted scientific literature

Implementation of the EQIPD Quality System

The EQIPD Quality System (QS) was conceptualized and established by an international consortium consisting of academic and industrial partners to ensure that non-regulated biomedical research will be conducted according to Good Research Practice expectations. The QS supports researchers to reflect on and improve internal practices by providing a systematic framework and guidance for implementing the EQIPD QS in a time and cost effective manner. This report describes the content of the EQIPD QS with its key features and 18 Core Requirements (CR) in more detail. It gives a short background on each CR and hands on examples on how they were addressed by two different research labs in their respective laboratory environments. Thereby, this article provides examples and direction for other research labs who aim to implement the QS as well. The final paragraphs discuss the potential benefits of the QS in respect to different user groups and stakeholders within the scientific community and summarize the overall governance structure of the EQIPD framework.

ISSCR standards for the use of human stem cells in basic research

The laboratory culture of human stem cells seeks to capture a cellular state as an in vitro surrogate of a biological system. For the results and outputs from this research to be accurate, meaningful, and durable, standards that ensure reproducibility and reliability of the data should be applied. Although such standards have been previously proposed for repositories and distribution centers, no widely accepted best practices exist for laboratory research with human pluripotent and tissue stem cells. To fill that void, the International Society for Stem Cell Research has developed a set of recommendations, including reporting criteria, for scientists in basic research laboratories. These criteria are designed to be technically and financially feasible and, when implemented, enhance the reproducibility and rigor of stem cell research.

Teaching students to R3eason, not merely to solve problem sets: The role of philosophy and visual data communication in accessible data science education

Much guidance on statistical training in STEM fields has been focused largely on the undergraduate cohort, with graduate education often being absent from the equation. Training in quantitative methods and reasoning is critical for graduate students in biomedical and science programs to foster reproducible and responsible research practices. We argue that graduate student education should more center around fundamental reasoning and integration skills rather than mainly on listing 1 statistical test method after the other without conveying the bigger context picture or critical argumentation skills that will enable student to improve research integrity through rigorous practice. Herein, we describe the approach we take in a quantitative reasoning course in the R3 program at the Johns Hopkins Bloomberg School of Public Health, with an error-focused lens, based on visualization and communication competencies. Specifically, we take this perspective stemming from the discussed causes of irreproducibility and apply it specifically to the many aspects of good statistical practice in science, ranging from experimental design to data collection and analysis, and conclusions drawn from the data. We also provide tips and guidelines for the implementation and adaptation of our course material to various graduate biomedical and STEM science programs.

Prediction and Construction of Energetic Materials Based on Machine Learning Methods

Energetic materials (EMs) are the core materials of weapons and equipment. Achieving precise molecular design and efficient green synthesis of EMs has long been one of the primary concerns of researchers around the world. Traditionally, advanced materials were discovered through a trial-and-error processes, which required long research and development (R&D) cycles and high costs. In recent years, the machine learning (ML) method has matured into a tool that compliments and aids experimental studies for predicting and designing advanced EMs. This paper reviews the critical process of ML methods to discover and predict EMs, including data preparation, feature extraction, model construction, and model performance evaluation. The main ideas and basic steps of applying ML methods are analyzed and outlined. The state-of-the-art research about ML applications in property prediction and inverse material design of EMs is further summarized. Finally, the existing challenges and the strategies for coping with challenges in the further applications of the ML methods are proposed.

Good scientific practice in EEG and MEG research: Progress and perspectives

Good scientific practice (GSP) refers to both explicit and implicit rules, recommendations, and guidelines that help scientists to produce work that is of the highest quality at any given time, and to efficiently share that work with the community for further scrutiny or utilization. For experimental research using magneto- and electroencephalography (MEEG), GSP includes specific standards and guidelines for technical competence, which are periodically updated and adapted to new findings. However, GSP also needs to be regularly revisited in a broader light. At the LiveMEEG 2020 conference, a reflection on GSP was fostered that included explicitly documented guidelines and technical advances, but also emphasized intangible GSP: a general awareness of personal, organizational, and societal realities and how they can influence MEEG research. This article provides an extensive report on most of the LiveMEEG contributions and new literature, with the additional aim to synthesize ongoing cultural changes in GSP. It first covers GSP with respect to cognitive biases and logical fallacies, pre-registration as a tool to avoid those and other early pitfalls, and a number of resources to enable collaborative and reproducible research as a general approach to minimize misconceptions. Second, it covers GSP with respect to data acquisition, analysis, reporting, and sharing, including new tools and frameworks to support collaborative work. Finally, GSP is considered in light of ethical implications of MEEG research and the resulting responsibility that scientists have to engage with societal challenges. Considering among other things the benefits of peer review and open access at all stages, the need to coordinate larger international projects, the complexity of MEEG subject matter, and today's prioritization of fairness, privacy, and the environment, we find that current GSP tends to favor collective and cooperative work, for both scientific and for societal reasons.

ANALYSIS OF RETRACTED PUBLICATIONS FROM KAZAKHSTAN

Introduction: Retraction is a mechanism to prevent the dissemination of erroneous, misleading, or biased data and information. Various factors can cause retraction. In this article, we focused on Kazakhstan data and aimed to present an analysis of retracted publications from Kazakhstan. Methods: Data for this descriptive cross-sectional article were obtained from the 'Retraction Watch’ database without time restriction. Among the country selections, 'Kazakhstan,' 'Tajikistan,' 'Uzbekistan,' 'Kyrgyzstan,' and 'Turkmenistan' were chosen, and the number of retracted articles was recorded. For detailed analysis, Kazakhstan data were focused on and further analyses were performed on Kazakhstan data. Article title, authors, time interval (in days) from publication to retraction, date of retraction, source of publication, subject area of publication, publication type, and retraction reason were recorded in an Excel file. Results: The number of retracted publications was detected as 64 from Kazakhstan, 49 from Tajikistan, 17 from Uzbekistan, 12 from Kyrgyzstan, and 1 from Turkmenistan. Kazakhstan data were as follows: The median time interval between publication date and retraction date was 475 (46 - 2074) days. Retraction reasons were listed as: Plagiarism (n = 22), peer review issues (n = 21), duplication (n = 11), author disagreements and conflict (n = 5), error (n = 5), fraud (n = 2), ethical issues ( n = 1), publication issues (n = 1), and unknown (n = 1). The three areas with the most retracted articles were engineering (n = 22), education (n = 21), and technology (n = 12). Conclusion: Kazakhstan was first among the five Central Asian countries in terms of the number of retracted publications. Plagiarism, peer review issues, and duplication were at the forefront of the retraction reasons. There is a need for approaches to increase the knowledge of researchers in Kazakhstan about the retraction reasons and ethical research conditions.

A comprehensive analysis of self-corrected publications in the imaging literature

BACKGROUND

The characteristics of self-corrected publications have not been fully evaluated.

PURPOSE

To evaluate the annual number and characteristics of self-corrected publications in the imaging literature within the last 20 years.

MATERIAL AND METHODS

We searched MEDLINE (via PubMed) using the following keyword: ("Published Erratum" [Publication Type] OR "Corrected and Republished Article" [Publication Type]) in the imaging literature to identify all self-corrected publications in which initial versions of articles were published during 1999-2018. Extracted data included: date of publication of the original version; date of correction notification; the time interval between initial publication and correction; journal name; journal impact factor (IF); type of articles; number of authors; country of origin; and location of errors. Journals were divided into four quartiles (Q1-Q4) based on their IF.

RESULTS

A total of 1071 self-corrected publications were identified, representing 0.30% of all papers published in the imaging literature. Trend analysis showed exponential growth of the number and rate of self-corrected publications during 1999-2018. The median (range) time interval from initial publication to correction was 120 days (0-7755 days). The rate of self-corrected publications in Q4 journals (0.17%) was significantly lower than those in Q1 (0.35%, P<0.0001), Q2 (0.26%, P=0.0007), and Q3 (0.30%, P<0.0001) journals. Additionally, 80.8% of self-corrected publications were original articles, 29.2% were from the USA, and 30.7% were corrected for author information (name, affiliation, and email address).

CONCLUSION

Self-corrected publications in the imaging literature have increased exponentially during 1999-2018 and author information was the most common location of error correction.

Best practices in statistical computing

The world is becoming increasingly complex, both in terms of the rich sources of data we have access to and the statistical and computational methods we can use on data. These factors create an ever-increasing risk for errors in code and the sensitivity of findings to data preparation and the execution of complex statistical and computing methods. The consequences of coding and data mistakes can be substantial. In this paper, we describe the key steps for implementing a code quality assurance (QA) process that researchers can follow to improve their coding practices throughout a project to assure the quality of the final data, code, analyses, and results. These steps include: (i) adherence to principles for code writing and style that follow best practices; (ii) clear written documentation that describes code, workflow, and key analytic decisions; (iii) careful version control; (iv) good data management; and (v) regular testing and review. Following these steps will greatly improve the ability of a study to assure results are accurate and reproducible. The responsibility for code QA falls not only on individual researchers but institutions, journals, and funding agencies as well.

Highly Versatile Cloud-Based Automation Solution for the Remote Design and Execution of Experiment Protocols during the COVID-19 Pandemic

There is an urgent need to accelerate the development and validation of both diagnostics and vaccines for COVID-19. These priorities are challenging both public and private sector research groups around the world and have shone a spotlight on both existing bottlenecks in the research workflows involved as well as on the implications of having to do much of this work remotely because of enforced social distancing and lockdown measures. The ability to respond quickly to rapidly evolving events, coupled with an emerging understanding of the disease and its pathology, as well as different mutations of the virus, necessitates a highly flexible liquid-handling automation solution that is amenable to rapid switching between different assay workflows and processes to be exploited tactically as needed. In addition, the use of cloud-based software imparts a unique benefit in enabling multiple research groups and remote technical staff around the world to have ready access to the same protocols in real-time without delays, down to the required level of detail, sharing methods and data (for example, in faster clinical trials). Informed by a recent use case, this article explores these issues alongside the recent development and deployment of an automation solution, whose unique approach in terms of both its cloud-native software and its highly modular hardware aligns especially well with achieving the challenge set by this new frontier in the bioanalytical laboratory.

Prevalence and Prevention of Reproducibility Deficiencies in Life Sciences Research: Large-Scale Meta-Analyses

BACKGROUND Studies have found that many published life sciences research results are irreproducible. Our goal was to provide comprehensive risk estimates of familiar reproducibility deficiencies to support quality improvement in research. MATERIAL AND METHODS Reports included were peer-reviewed, published between 1980 and 2016, and presented frequency data of basic biomedical research deficiencies. Manual and electronic literature searches were performed in seven bibliographic databases. For deficiency concepts with at least four frequency studies and with a sample size of at least 15 units in each, a meta-analysis was performed. RESULTS Overall, 68 publications met our inclusion criteria. The study identified several major groups of research quality defects: study design, cell lines, statistical analysis, and reporting. In the study design group of 3 deficiencies, missing power calculation was the most frequent (82.3% [95% Confidence Interval (CI): 69.9-94.6]). Among the 6 cell line deficiencies, mixed contamination was the most frequent (22.4% [95% CI: 10.4-34.3]). Among the 3 statistical analysis deficiencies, the use of chi-square test when expected cells frequency was <5 was the most prevalent (15.7% [95% CI: -3.2-34.7]). In the reporting group of 12 deficiencies, failure to state the number of tails was the most frequent (65% [95% CI: 39.3-90.8]). CONCLUSIONS The results of this study could serve as a general reference when consistently measurable sources of deficiencies need to be identified in research quality improvement.

Assessing and Raising Concerns About Duplicate Publication, Authorship Transgressions and Data Errors in a Body of Preclinical Research

Authorship transgressions, duplicate data reporting and reporting/data errors compromise the integrity of biomedical publications. Using a standardized template, we raised concerns with journals about each of these characteristics in 33 pairs of publications originating from 15 preclinical (animal) trials reported by a group of researchers. The outcomes of interest were journal responses, including time to acknowledgement of concerns, time to decision, content of decision letter, and disposition of publications at 1 year. Authorship transgressions affected 27/36 (75%) publications. The median proportion of duplicate data within pairs of publications was 45% (interquartile range 29-57). Data/reporting discrepancies [median 3 (1-5)] were present in 28/33 (85%) pairs. Journals acknowledged receipt of concerns for 53% and 94% of publications by 1 month and 9 months, respectively. After 1 year, journals had communicated decisions for 16/36 (44%) publications. None of the decision letters specifically addressed each of the concerns raised. Decisions were no action, correction and retraction for 9, 3 and 4 publications, respectively: the amounts of duplicate data reporting and data/reporting discrepancies were similar irrespective of journal decision. Authorship transgressions affected 6/9 (67%) publications for which no action was decided. Journal responses to concerns about duplicate publication, authorship transgressions, and data/reporting discrepancies were slow, opaque and inconsistent.

Correctable Myths About Research Misconduct in the Biomedical Sciences

A recent National Academy report on research integrity noted that policies are not evidence-based, with no formal entity responsible to attend to this deficit. Here we describe four areas of research misconduct (RM) regulations governing Public Health Service funded research that are empirically and/or ethically questionable. Policies for human subject protection, RM and conflict of interest are not harmonized, making it extremely difficult to deal with complex cases which often contain allegations in all of these areas. Second, detection of RM has depended entirely on whistleblowers in spite of evidence of significant under-reporting. Third, the scientific record is far from cleansed of the effects of falsified/fabricated work through current mechanisms of retraction. Finally, lack of fairness in the regulations may reflect lack of a Belmont Report-like document to guide ethics of RM policy. These issues are likely common in other countries. RM regulations should be harmonized with related regulations and their effectiveness tracked, open access to data for independent replication and improved statistical tests are an essential supplement to whistleblowers, correction of the scientific record will require a major effort, and further ethical analysis and guidance are as important as is empirical study for the improvement of RM regulations. Further consideration should be given to assigning current regulations for human subjects protection, RM and conflict of interest to a single authority and to the further development of a Belmont-like report of essential principles, for RM.

Women and Men in the History of Western Cardiology: Some Notes on Their Position as Patients, Role as Investigational Study Subjects, and Impact as Professionals

Nowadays, it is generally appreciated that studies in the medical field should not only include sex-related aspects but also consider age. In the past, taking the era of Hippocrates as a starting point for the Western medical sciences, such aspects were less urgent and barely relevant. However, considering such details during daily life became increasingly important as the traditional roles of men and women in society and household converged. In the Western world, this fundamental transition process started recently and is advancing at an accelerated pace. Research about the role of women has also evolved, starting from plain history about the lives of women to a description of the relation between men and women, resulting in the gender concept. The present survey highlights a historical selection of observations referring to the impact of men and women on the medical sciences, as patient, study object, and professional. Whenever relevant, focus will be on the field of cardiovascular investigations as documented in the Western world. Rather than being exhaustive, we focus on a few remarkable icons, including Trota of Salerno, Hildegard von Bingen, and Miguel Serveto.

Graduate Biomedical Science Education Needs a New Philosophy

There is a growing realization that graduate education in the biomedical sciences is successful at teaching students how to conduct research but falls short in preparing them for a diverse job market, communicating with the public, and remaining versatile scientists throughout their careers. Major problems with graduate level education today include overspecialization in a narrow area of science without a proper grounding in essential critical thinking skills. Shortcomings in education may also contribute to some of the problems of the biomedical sciences, such as poor reproducibility, shoddy literature, and the rise in retracted publications. The challenge is to modify graduate programs such that they continue to generate individuals capable of conducting deep research while at the same time producing more broadly trained scientists without lengthening the time to a degree. Here we describe our first experiences at Johns Hopkins and propose a manifesto for reforming graduate science education.

The ghosts of HeLa: How cell line misidentification contaminates the scientific literature

While problems with cell line misidentification have been known for decades, an unknown number of published papers remains in circulation reporting on the wrong cells without warning or correction. Here we attempt to make a conservative estimate of this ‘contaminated’ literature. We found 32,755 articles reporting on research with misidentified cells, in turn cited by an estimated half a million other papers. The contamination of the literature is not decreasing over time and is anything but restricted to countries in the periphery of global science. The decades-old and often contentious attempts to stop misidentification of cell lines have proven to be insufficient. The contamination of the literature calls for a fair and reasonable notification system, warning users and readers to interpret these papers with appropriate care.

Talking the talk, but not walking the walk: RT-qPCR as a paradigm for the lack of reproducibility in molecular research

Poorly executed and inadequately reported molecular measurement methods are amongst the causes underlying the lack of reproducibility of much biomedical research. Although several high impact factor journals have acknowledged their past failure to scrutinise adequately the technical soundness of manuscripts, there is a perplexing reluctance to implement basic corrective measures. The reverse transcription real-time quantitative PCR (RT-qPCR) is probably the most straightforward measurement technique available for RNA quantification and is widely used in research, diagnostic, forensic and biotechnology applications. Despite the impact of the minimum information for the publication of quantitative PCR experiments (MIQE) guidelines, which aim to improve the robustness and the transparency of reporting of RT-qPCR data, we demonstrate that elementary protocol errors, inappropriate data analysis and inadequate reporting continue to be rife and conclude that the majority of published RT-qPCR data are likely to represent technical noise.

The visibility of scientific misconduct: A review of the literature on retracted journal articles

Retractions of scientific articles are becoming the most relevant institution for making sense of scientific misconduct. An increasing number of retracted articles, mainly attributed to misconduct, is currently providing a new empirical basis for research about scientific misconduct. This article reviews the relevant research literature from an interdisciplinary context. Furthermore, the results from these studies are contextualized sociologically by asking how scientific misconduct is made visible through retractions. This study treats retractions as an emerging institution that renders scientific misconduct visible, thus, following up on the sociology of deviance and its focus on visibility. The article shows that retractions, by highlighting individual cases of misconduct and general policies for preventing misconduct while obscuring the actors and processes through which retractions are effected, produce highly fragmented patterns of visibility. These patterns resemble the bifurcation in current justice systems.

A post-publication analysis of the idealized upper reference value of 2.5 mIU/L for TSH: Time to support the thyroid axis with magnesium and iron especially in the setting of reproduction medicine

Laboratory medicine approaches the evaluation of thyroid function mostly through the single determination of the blood level of thyroid stimulating hormone (TSH). Some authors have suggested an upper reference value for TSH of 2.5 mIU/L. This suggestion has not been confirmed by recent clinical studies. These studies have delivered a clinically valid reference range going from 0.3 to 3.5 mIU/L. These values are valid for both for the general population as well as in the setting of fertility and pregnancy. Current biochemical evidence about the elements required to maintain thyroid function shows that these not only include dietary iodine but also magnesium, iron, selenium and coenzyme Q10. Iron is important for the synthesis of thyroid peroxidase; magnesium-ATP contributes to the active process of iodine uptake; iodine has to be sufficiently present in the diet; selenium acts through selenoproteins to protect the thyroid cell during hormone synthesis and in deiodination of thyroxine; coenzyme Q10 influences thyroid vascularity. As a consequence, good clinical practice requires additional biochemical information on the blood levels of magnesium, selenium, coenzyme Q10 as well as iron status. Since these elements are also important for the maintenance of reproductive function, we postulate that they constitute the connecting link between both endocrine systems.

Retractions in cancer research: a systematic survey

Background

The annual number of retracted publications in the scientific literature is rapidly increasing. The objective of this study was to determine the frequency and reason for retraction of cancer publications and to determine how journals in the cancer field handle retracted articles.

Methods

We searched three online databases (MEDLINE, Embase, The Cochrane Library) from database inception until 2015 for retracted journal publications related to cancer research. For each article, the reason for retraction was categorized as plagiarism, duplicate publication, fraud, error, authorship issues, or ethical issues. Accessibility of the retracted article was defined as intact, removed, or available but with a watermark over each page. Descriptive data was collected on each retracted article including number of citations, journal name and impact factor, study design, and time between publication and retraction. The publications were screened in duplicated and two reviewers extracted and categorized data.

Results

Following database search and article screening, we identified 571 retracted cancer publications. The majority (76.4%) of cancer retractions were issued in the most recent decade, with 16.6 and 6.7% of the retractions in the prior two decades respectively. Retractions were issued by journals with impact factors ranging from 0 (discontinued) to 55.8. The average impact factor was 5.4 (median 3.54, IQR 1.8-5.5). On average, a retracted article was cited 45 times (median 18, IQR 6-51), with a range of 0-742. Reasons for retraction include plagiarism (14.4%), fraud (28.4%), duplicate publication (18.2%), error (24.2%), authorship issues (3.9%), and ethical issues (2.1%). The reason for retraction was not stated in 9.8% of cases. Twenty-nine percent of retracted articles remain available online in their original form.

Conclusions

Retractions in cancer research are increasing in frequency at a similar rate to all biomedical research retractions. Cancer retractions are largely due to academic misconduct. Consequences to cancer patients, the public at large, and the research community can be substantial and should be addressed with future research. Despite the implications of this important issue, some cancer journals currently fall short of the current guidelines for clearly stating the reason for retraction and identifying the publication as retracted.

Widespread Use of Misidentified Cell Line KB (HeLa): Incorrect Attribution and Its Impact Revealed through Mining the Scientific Literature

Continuous cell lines are widely used, but can result in invalid, irreproducible research data. Cell line misidentification is a common problem that can be detected by authentication testing; however, misidentified cell lines continue to be used in publications. Here we explore the impact of one misidentified cell line, KB (HeLa), on the scientific literature. We identified 574 articles between 2000 and 2014 that provided an incorrect attribution for KB, in accordance with its false identity as oral epidermoid carcinoma, but only 57 articles that provided a correct attribution for KB, as HeLa or cervical adenocarcinoma. Statistical analysis of 57 correct and 171 incorrect articles showed that the number of citations to these articles increased over time. Content analysis of 200 citing articles showed there was a tendency to describe the cell line in accordance with the description in the cited paper. Analysis of journal impact factor showed no significant difference between correct and incorrect groups. Articles using KB or citing that usage were most frequently published in the subject areas of pharmacology, pharmacy, oncology, and medicinal chemistry. These findings are important for science policy and support the need for journals to require authentication testing as a condition of publication. Cancer Res; 77(11); 2784-8. ©2017 AACR.

Rigorous Science: a How-To Guide

Proposals to improve the reproducibility of biomedical research have emphasized scientific rigor. Although the word "rigor" is widely used, there has been little specific discussion as to what it means and how it can be achieved. We suggest that scientific rigor combines elements of mathematics, logic, philosophy, and ethics. We propose a framework for rigor that includes redundant experimental design, sound statistical analysis, recognition of error, avoidance of logical fallacies, and intellectual honesty. These elements lead to five actionable recommendations for research education.

A Framework for Improving the Quality of Research in the Biological Sciences

The American Academy of Microbiology convened a colloquium to discuss problems in the biological sciences, with emphasis on identifying mechanisms to improve the quality of research. Participants from various disciplines made six recommendations: (i) design rigorous and comprehensive evaluation criteria to recognize and reward high-quality scientific research; (ii) require universal training in good scientific practices, appropriate statistical usage, and responsible research practices for scientists at all levels, with training content regularly updated and presented by qualified scientists; (iii) establish open data at the timing of publication as the standard operating procedure throughout the scientific enterprise; (iv) encourage scientific journals to publish negative data that meet methodologic standards of quality; (v) agree upon common criteria among scientific journals for retraction of published papers, to provide consistency and transparency; and (vi) strengthen research integrity oversight and training. These recommendations constitute an actionable framework that, in combination, could improve the quality of biological research.

Life Science's Average Publishable Unit (APU) Has Increased over the Past Two Decades

Quantitative analysis of the scientific literature is important for evaluating the evolution and state of science. To study how the density of biological literature has changed over the past two decades we visually inspected 1464 research articles related only to the biological sciences from ten scholarly journals (with average Impact Factors, IF, ranging from 3.8 to 32.1). By scoring the number of data items (tables and figures), density of composite figures (labeled panels per figure or PPF), as well as the number of authors, pages and references per research publication we calculated an Average Publishable Unit or APU for 1993, 2003, and 2013. The data show an overall increase in the average ± SD number of data items from 1993 to 2013 of approximately 7±3 to 14±11 and PPF ratio of 2±1 to 4±2 per article, suggesting that the APU has doubled in size over the past two decades. As expected, the increase in data items per article is mainly in the form of supplemental material, constituting 0 to 80% of the data items per publication in 2013, depending on the journal. The changes in the average number of pages (approx. 8±3 to 10±3), references (approx. 44±18 to 56±24) and authors (approx. 5±3 to 8±9) per article are also presented and discussed. The average number of data items, figure density and authors per publication are correlated with the journal's average IF. The increasing APU size over time is important when considering the value of research articles for life scientists and publishers, as well as, the implications of these increasing trends in the mechanisms and economics of scientific communication.

The Prevalence of Inappropriate Image Duplication in Biomedical Research Publications

Inaccurate data in scientific papers can result from honest error or intentional falsification. This study attempted to determine the percentage of published papers that contain inappropriate image duplication, a specific type of inaccurate data. The images from a total of 20,621 papers published in 40 scientific journals from 1995 to 2014 were visually screened. Overall, 3.8% of published papers contained problematic figures, with at least half exhibiting features suggestive of deliberate manipulation. The prevalence of papers with problematic images has risen markedly during the past decade. Additional papers written by authors of papers with problematic images had an increased likelihood of containing problematic images as well. As this analysis focused only on one type of data, it is likely that the actual prevalence of inaccurate data in the published literature is higher. The marked variation in the frequency of problematic images among journals suggests that journal practices, such as prepublication image screening, influence the quality of the scientific literature.

The Prevalence of Inappropriate Image Duplication in Biomedical Research Publications

Inaccurate data in scientific papers can result from honest error or intentional falsification. This study attempted to determine the percentage of published papers that contain inappropriate image duplication, a specific type of inaccurate data. The images from a total of 20,621 papers published in 40 scientific journals from 1995 to 2014 were visually screened. Overall, 3.8% of published papers contained problematic figures, with at least half exhibiting features suggestive of deliberate manipulation. The prevalence of papers with problematic images has risen markedly during the past decade. Additional papers written by authors of papers with problematic images had an increased likelihood of containing problematic images as well. As this analysis focused only on one type of data, it is likely that the actual prevalence of inaccurate data in the published literature is higher. The marked variation in the frequency of problematic images among journals suggests that journal practices, such as prepublication image screening, influence the quality of the scientific literature.

Retracted Publications Within Radiology Journals

OBJECTIVE

The purpose of this study was to characterize trends related to retracted publications within radiology journals.

MATERIALS AND METHODS

PubMed was queried to identify all articles with the publication type "retracted publication" or "notification of retraction." Articles published within radiology journals were identified using Journal Citation Reports' journal categories. Available versions of original articles and publication notices were accessed from journal websites. Citations to retracted publications were identified using Web of Science. Overall trends were assessed.

RESULTS

Forty-eight retracted original research articles were identified within radiology journals since 1983, which included 1.1% of all PubMed "retracted publication" entries. Distinct PubMed entries were available for the retracted publication and retraction notification in 39 of 48 articles. The original PDF was available for 37 articles, although the articles were not watermarked as retracted in 23 cases. In six cases with a watermarked PDF, further searches identified nonwatermarked versions. Original HTML versions were available for 13 articles but 11 were not watermarked. The mean (± SD) delay between publication and retraction was 2.7 ± 2.8 years (range, 0-16 years). The mean number of citations to retracted articles was 10.9 ± 17.1 (range, 0-94 citations). Reasons for retraction included problematic or incorrect methods or results (although it typically was unclear whether these represented honest errors or misconduct) in 33.3% of cases, complete or partial duplicate publication in 33.3% of cases, plagiarism in 14.6% of cases, a permission issue in 8.3% of cases, the publisher's error in 6.3% of cases, and no identified reason in 6.3% of cases. One or no retractions occurred annually from 1986 to 2001, although two or more retractions occurred annually in nine of the 12 years from 2002 through 2013.

CONCLUSION

Retraction represents an uncommon, yet potentially increasing, issue within radiology journals that publishers have inconsistently and insufficiently addressed. Greater awareness and training in proper biomedical research conduct, as well as establishment and enforcement of standardized publishers' policies, are warranted.

Harnessing QbD, Programming Languages, and Automation for Reproducible Biology

Building robust manufacturing processes from biological components is a task that is highly complex and requires sophisticated tools to describe processes, inputs, and measurements and administrate management of knowledge, data, and materials. We argue that for bioengineering to fully access biological potential, it will require application of statistically designed experiments to derive detailed empirical models of underlying systems. This requires execution of large-scale structured experimentation for which laboratory automation is necessary. This requires development of expressive, high-level languages that allow reusability of protocols, characterization of their reliability, and a change in focus from implementation details to functional properties. We review recent developments in these areas and identify what we believe is an exciting trend that promises to revolutionize biotechnology.

Impacted science: impact is not importance

The journal impact factor (IF) exerts a tremendous influence on the conduct of scientists. The obsession with IF has been compared to a medical condition, sometimes referred to as “IF mania” or “impactitis.” Here, we analyze the difference between impact and importance, using examples from the history of science to show that these are not equivalent. If impact does not necessarily equal importance, but scientists are focused on high-impact work, there is a danger that misuse of the IF may adversely affect scientific progress. We suggest five measures to fight this malady: (i) diversify journal club selections, (ii) do not judge science on the publication venue, (iii) reduce the reliance on journal citation metrics for employment and advancement, (iv) discuss the misuse of the IF in ethics courses, and (v) cite the most appropriate sources. If IF mania is indeed a medical condition, the most appropriate course of action may be disimpaction.

(A)Historical science

In contrast to many other human endeavors, science pays little attention to its history. Fundamental scientific discoveries are often considered to be timeless and independent of how they were made. Science and the history of science are regarded as independent academic disciplines. Although most scientists are aware of great discoveries in their fields and their association with the names of individual scientists, few know the detailed stories behind the discoveries. Indeed, the history of scientific discovery is sometimes recorded only in informal accounts that may be inaccurate or biased for self-serving reasons. Scientific papers are generally written in a formulaic style that bears no relationship to the actual process of discovery. Here we examine why scientists should care more about the history of science. A better understanding of history can illuminate social influences on the scientific process, allow scientists to learn from previous errors, and provide a greater appreciation for the importance of serendipity in scientific discovery. Moreover, history can help to assign credit where it is due and call attention to evolving ethical standards in science. History can make science better.

Is cell culture a risky business? Risk analysis based on scientist survey data

Cell culture is a technique that requires vigilance from the researcher. Common cell culture problems, including contamination with microorganisms or cells from other cultures, can place the reliability and reproducibility of cell culture work at risk. Here we use survey data, contributed by research scientists based in Australia and New Zealand, to assess common cell culture risks and how these risks are managed in practice. Respondents show that sharing of cell lines between laboratories continues to be widespread. Arrangements for mycoplasma and authentication testing are increasingly in place, although scientists are often uncertain how to perform authentication testing. Additional risks are identified for preparation of frozen stocks, storage and shipping.

Increasing disparities between resource inputs and outcomes, as measured by certain health deliverables, in biomedical research

Society makes substantial investments in biomedical research, searching for ways to better human health. The product of this research is principally information published in scientific journals. Continued investment in science relies on society's confidence in the accuracy, honesty, and utility of research results. A recent focus on productivity has dominated the competitive evaluation of scientists, creating incentives to maximize publication numbers, citation counts, and publications in high-impact journals. Some studies have also suggested a decreasing quality in the published literature. The efficiency of society's investments in biomedical research, in terms of improved health outcomes, has not been studied. We show that biomedical research outcomes over the last five decades, as estimated by both life expectancy and New Molecular Entities approved by the Food and Drug Administration, have remained relatively constant despite rising resource inputs and scientific knowledge. Research investments by the National Institutes of Health over this time correlate with publication and author numbers but not with the numerical development of novel therapeutics. We consider several possibilities for the growing input-outcome disparity including the prior elimination of easier research questions, increasing specialization, overreliance on reductionism, a disproportionate emphasis on scientific outputs, and other negative pressures on the scientific enterprise. Monitoring the efficiency of research investments in producing positive societal outcomes may be a useful mechanism for weighing the efficacy of reforms to the scientific enterprise. Understanding the causes of the increasing input-outcome disparity in biomedical research may improve society's confidence in science and provide support for growing future research investments.

Scientific Misconduct

Scientific misconduct has been defined as fabrication, falsification, and plagiarism. Scientific misconduct has occurred throughout the history of science. The US government began to take systematic interest in such misconduct in the 1980s. Since then, a number of studies have examined how frequently individual scientists have observed scientific misconduct or were involved in it. Although the studies vary considerably in their methodology and in the nature and size of their samples, in most studies at least 10% of the scientists sampled reported having observed scientific misconduct. In addition to studies of the incidence of scientific misconduct, this review considers the recent increase in paper retractions, the role of social media in scientific ethics, several instructional examples of egregious scientific misconduct, and potential methods to reduce research misconduct.

Redrawing the frontiers in the age of post-publication review

Publication forms the core structure supporting the development and transmission of scientific knowledge. For this reason, it is essential that the highest standards of quality control be maintained, in particular to ensure that the information being transmitted allows reproducible replication of the described experiments, and that the interpretation of the results is sound. Quality control has traditionally involved editorial decisions based on anonymous pre-publication peer review. Post-publication review of individual articles took the lesser role since it did not feed directly back to the original literature. Rapid advances in computer and communications technologies over the last thirty years have revolutionized scientific publication, and the role and scope of post-publication review has greatly expanded. This perspective examines the ways in which pre- and post-publication peer review influence the scientific literature, and in particular how they might best be redrawn to deal with the twin problems of scientific non-reproducibility and fraud increasingly encountered at the frontiers of science.

FAST: FAST Analysis of Sequences Toolbox

FAST (FAST Analysis of Sequences Toolbox) provides simple, powerful open source command-line tools to filter, transform, annotate and analyze biological sequence data. Modeled after the GNU (GNU's Not Unix) Textutils such as grep, cut, and tr, FAST tools such as fasgrep, fascut, and fastr make it easy to rapidly prototype expressive bioinformatic workflows in a compact and generic command vocabulary. Compact combinatorial encoding of data workflows with FAST commands can simplify the documentation and reproducibility of bioinformatic protocols, supporting better transparency in biological data science. Interface self-consistency and conformity with conventions of GNU, Matlab, Perl, BioPerl, R, and GenBank help make FAST easy and rewarding to learn. FAST automates numerical, taxonomic, and text-based sorting, selection and transformation of sequence records and alignment sites based on content, index ranges, descriptive tags, annotated features, and in-line calculated analytics, including composition and codon usage. Automated content- and feature-based extraction of sites and support for molecular population genetic statistics make FAST useful for molecular evolutionary analysis. FAST is portable, easy to install and secure thanks to the relative maturity of its Perl and BioPerl foundations, with stable releases posted to CPAN. Development as well as a publicly accessible Cookbook and Wiki are available on the FAST GitHub repository at https://github.com/tlawrence3/FAST. The default data exchange format in FAST is Multi-FastA (specifically, a restriction of BioPerl FastA format). Sanger and Illumina 1.8+ FastQ formatted files are also supported. FAST makes it easier for non-programmer biologists to interactively investigate and control biological data at the speed of thought.

What studies of retractions tell us

The retraction is receiving a growing amount of attention as an important event in scientific and scholarly publishing. Not only are some journals becoming increasingly open in their handling of the articles they withdraw-allowing researchers to gain important insights into the work of their colleagues-but scholars, too, have greater access to the reasons for retractions, information that is dramatically reshaping our understanding of such events. As this article will demonstrate, recent research has inverted the accepted lore about why retractions happen and their impact.

Financial costs and personal consequences of research misconduct resulting in retracted publications

The number of retracted scientific articles has been increasing. Most retractions are associated with research misconduct, entailing financial costs to funding sources and damage to the careers of those committing misconduct. We sought to calculate the magnitude of these effects. Data relating to retracted manuscripts and authors found by the Office of Research Integrity (ORI) to have committed misconduct were reviewed from public databases. Attributable costs of retracted manuscripts, and publication output and funding of researchers found to have committed misconduct were determined. We found that papers retracted due to misconduct accounted for approximately $58 million in direct funding by the NIH between 1992 and 2012, less than 1% of the NIH budget over this period. Each of these articles accounted for a mean of $392,582 in direct costs (SD $423,256). Researchers experienced a median 91.8% decrease in publication output and large declines in funding after censure by the ORI.

DOI:http://dx.doi.org/10.7554/eLife.02956.001