The increasing urgency for standards in basic biologic research

Building living systematic reviews and reporting standards for comparative microscopic analysis of white diseases in hard corals

Over the last 4 decades, coral disease research has continued to provide reports of diseases, the occurrence and severity of disease outbreaks and associated disease signs. Histology using systematic protocols is a gold standard for the microscopic assessment of diseases in veterinary and medical research, while also providing valuable information on host condition. However, uptake of histological analysis for coral disease remains limited. Increasing disease outbreaks on coral reefs as human impacts intensify highlights a need to understand the use of histology to date in coral disease research. Here, we apply a systematic approach to collating, mapping and reviewing histological methods used to study coral diseases with 'white' signs (i.e., white diseases) in hard coral taxa and map research effort in this field spanning study design, sample processing and analysis in the 33 publications identified between 1984 and 2022. We find that studies to date have not uniformly detailed methodologies, and terminology associated with reporting and disease description is inconsistent between studies. Combined these limitations reduce study repeatability, limiting the capacity for researchers to compare disease reports. A primary outcome of this study is the provision of transparent and repeatable protocols for systematically reviewing literature associated with white diseases of hard coral taxa, and development of recommendations for standardised reporting procedures with the aim of increasing uptake of histology in addition to allowing for ongoing comparative analysis through living systematic reviews for the coral disease field.

AI for life: Trends in artificial intelligence for biotechnology

Due to popular successes (e.g., ChatGPT) Artificial Intelligence (AI) is on everyone's lips today. When advances in biotechnology are combined with advances in AI unprecedented new potential solutions become available. This can help with many global problems and contribute to important Sustainability Development Goals. Current examples include Food Security, Health and Well-being, Clean Water, Clean Energy, Responsible Consumption and Production, Climate Action, Life below Water, or protect, restore and promote sustainable use of terrestrial ecosystems, sustainably manage forests, combat desertification, and halt and reverse land degradation and halt biodiversity loss. AI is ubiquitous in the life sciences today. Topics include a wide range from machine learning and Big Data analytics, knowledge discovery and data mining, biomedical ontologies, knowledge-based reasoning, natural language processing, decision support and reasoning under uncertainty, temporal and spatial representation and inference, and methodological aspects of explainable AI (XAI) with applications of biotechnology. In this pre-Editorial paper, we provide an overview of open research issues and challenges for each of the topics addressed in this special issue. Potential authors can directly use this as a guideline for developing their paper.

How to think about and do successful research What you probable did not learn when you first entered the laboratory

There is a logic to doing successful research, but graduate students and indeed postdoctoral fellows and young independent investigators often learn it apprentice style, by experience. The purpose of this essay is to provide the product of that experience and advice that I have found useful to young researchers as they begin their training and careers.

Integrated analysis of circulating cell free nucleic acids for cancer genotyping and immune phenotyping of tumor microenvironment

The circulating cell-free nucleic acids (ccfNAs) consist of a heterogenous cocktail of both single (ssNA) and double-stranded (dsNA) nucleic acids. These ccfNAs are secreted into the blood circulation by both healthy and malignant cells via various mechanisms including apoptosis, necrosis, and active secretion. The major source of ccfNAs are the cells of hematopoietic system under healthy conditions. These ccfNAs include fragmented circulating cell free DNA (ccfDNA), coding or messenger RNA (mRNA), long non-coding RNA (lncRNA), microRNA (miRNA), and mitochondrial DNA/RNA (mtDNA and mtRNA), that serve as prospective biomarkers in assessment of various clinical conditions. For, e.g., free fetal DNA and RNA migrate into the maternal plasma, whereas circulating tumor DNA (ctDNA) has clinical relevance in diagnostic, prognostic, therapeutic targeting, and disease progression monitoring to improve precision medicine in cancer. The epigenetic modifications of ccfDNA as well as circulating cell-free RNA (ccfRNA) such as miRNA and lncRNA show disease-related variations and hold potential as epigenetic biomarkers. The messenger RNA present in the circulation or the circulating cell free mRNA (ccf-mRNA) and long non-coding RNA (ccf-lncRNA) have gradually become substantial in liquid biopsy by acting as effective biomarkers to assess various aspects of disease diagnosis and prognosis. Conversely, the simultaneous characterization of coding and non-coding RNAs in human biofluids still poses a significant hurdle. Moreover, a comprehensive assessment of ccfRNA that may reflect the tumor microenvironment is being explored. In this review, we focus on the novel approaches for exploring ccfDNA and ccfRNAs, specifically ccf-mRNA as biomarkers in clinical diagnosis and prognosis of cancer. Integrating the detection of circulating tumor DNA (ctDNA) for cancer genotyping in conjunction with ccfRNA both quantitatively and qualitatively, may potentially hold immense promise towards precision medicine. The current challenges and future directions in deciphering the complexity of cancer networks based on the dynamic state of ccfNAs will be discussed.

Rigor, Reproducibility, and Transparency in Shared Research Resources: Follow-Up Survey and Recommendations for Improvements

Rigor, reproducibility, and transparency (RR&T) are essential components of all scientific pursuits. Shared research resources, also known as core facilities, are on the frontlines of ensuring robust RR&T practices. The Association of Biomolecular Resource Facilities Committee on Core Rigor and Reproducibility conducted a follow-up survey 4 years after the initial 2017 survey to determine if core facilities have seen a positive impact of new RR&T initiatives (including guidance from the National Institutes of Health, new scientific journal requirements on transparency and data provenance, and educational tools from professional organizations). While there were fewer participants in the most recent survey, the respondents' opinions on the role of core facilities and level of best practices adoption remained the same. Overall, the respondents agreed that procedures should be implemented by core facilities to ensure scientific RR&T. They also indicated that there is a strong correlation between institutions that emphasize RR&T and core customers using this expertise in grant applications and publications. The survey also assessed the impact of the COVID-19 pandemic on core operations and RR&T. The answers to these pandemic-related questions revealed that many of the strategies aimed at increasing efficiencies are also best practices related to RR&T, including the development of standard operating procedures, supply chain management, and cross training. Given the consistent and compelling awareness of the importance of RR&T expressed by core directors in 2017 and 2021 contrasted with the lack of apparent improvements over this time period, the authors recommend an adoption of RR&T statements by all core laboratories. Adhering to the RR&T guidelines will result in more efficient training, better compliance, and improved experimental approaches empowering cores to become "rigor champions."

Blind spots on western blots: Assessment of common problems in western blot figures and methods reporting with recommendations to improve them

Western blotting is a standard laboratory method used to detect proteins and assess their expression levels. Unfortunately, poor western blot image display practices and a lack of detailed methods reporting can limit a reader's ability to evaluate or reproduce western blot results. While several groups have studied the prevalence of image manipulation or provided recommendations for improving western blotting, data on the prevalence of common publication practices are scarce. We systematically examined 551 articles published in the top 25% of journals in neurosciences (n = 151) and cell biology (n = 400) that contained western blot images, focusing on practices that may omit important information. Our data show that most published western blots are cropped and blot source data are not made available to readers in the supplement. Publishing blots with visible molecular weight markers is rare, and many blots additionally lack molecular weight labels. Western blot methods sections often lack information on the amount of protein loaded on the gel, blocking steps, and antibody labeling protocol. Important antibody identifiers like company or supplier, catalog number, or RRID were omitted frequently for primary antibodies and regularly for secondary antibodies. We present detailed descriptions and visual examples to help scientists, peer reviewers, and editors to publish more informative western blot figures and methods. Additional resources include a toolbox to help scientists produce more reproducible western blot data, teaching slides in English and Spanish, and an antibody reporting template.

Current challenges and best practices for cell-free long RNA biomarker discovery

The analysis of biomarkers in biological fluids, also known as liquid biopsies, is seen with great potential to diagnose complex diseases such as cancer with a high sensitivity and minimal invasiveness. Although it can target any biomolecule, most liquid biopsy studies have focused on circulating nucleic acids. Historically, studies have aimed at the detection of specific mutations on cell-free DNA (cfDNA), but recently, the study of cell-free RNA (cfRNA) has gained traction. Since 2020, a handful of cfDNA tests have been approved for therapy selection by the FDA, however, no cfRNA tests are approved to date. One of the main drawbacks in the field of RNA-based liquid biopsies is the low reproducibility of the results, often caused by technical and biological variability, a lack of standardized protocols and insufficient cohorts. In this review, we will identify the main challenges and biases introduced during the different stages of biomarker discovery in liquid biopsies with cfRNA and propose solutions to minimize them.

Lightweight Distributed Provenance Model for Complex Real-world Environments

Provenance is information describing the lineage of an object, such as a dataset or biological material. Since these objects can be passed between organizations, each organization can document only parts of the objects life cycle. As a result, interconnection of distributed provenance parts forms distributed provenance chains. Dependant on the actual provenance content, complete provenance chains can provide traceability and contribute to reproducibility and FAIRness of research objects. In this paper, we define a lightweight provenance model based on W3C PROV that enables generation of distributed provenance chains in complex, multi-organizational environments. The application of the model is demonstrated with a use case spanning several steps of a real-world research pipeline — starting with the acquisition of a specimen, its processing and storage, histological examination, and the generation/collection of associated data (images, annotations, clinical data), ending with training an AI model for the detection of tumor in the images. The proposed model has become an open conceptual foundation of the currently developed ISO 23494 standard on provenance for biotechnology domain.

The African Female Breast Cancer Epidemiology Study Protocol

Breast cancer is now the commonest cancer in most sub-Saharan African countries. Few studies of the epidemiology and genomics of breast cancer and its molecular subtypes in these countries have been done. The African Female Breast Cancer Epidemiology (AFBRECANE) study, a part of the Human Heredity and Health in Africa (H3Africa) initiative, is designed to study the genomics and epidemiology of breast cancer and its molecular subtypes in Nigerian women. We link recruitment of breast cancer cases at study sites with population-based cancer registries activities to enable ascertainment of the incidence of breast cancer and its molecular subtypes. We use centralized laboratory processing to characterize the histopathological and molecular diagnosis of breast cancer and its subtypes using multiple technologies. By combining genome-wide association study (GWAS) data from this study with that generated from 12,000 women participating in our prospective cohort study of cervical cancer, we conduct GWAS of breast cancer in an entirely indigenous African population. We test associations between dietary intakes and breast cancer and focus on vitamin D which we measure using dietary intakes, serum vitamin D, and Mendelian randomization. This paper describes the AFBRECANE project, its design, objectives and anticipated contributions to knowledge and understanding of breast cancer.

A 3D-printable device allowing fast and reproducible longitudinal preparation of mouse intestines

Accurate and reproducible analysis of murine small and large intestinal tissue is key for preclinical models involving intestinal pathology. Currently, there is no easily accessible, standardized method that allows researchers of different skill levels to consistently dissect intestines in a time-efficient manner. Here, we describe the design and use of the 3D-printed "Mouse Intestinal Slicing Tool" (MIST), which can be used to longitudinally dissect murine intestines for further analysis. We benchmarked the MIST against a commonly used procedure involving scissors to make a longitudinal cut along the intestines. Use of the MIST halved the time per mouse to prepare the intestines and outperformed alternative methods in smoothness of the cutting edge and overall reproducibility. By sharing the plans for printing the MIST, we hope to contribute a uniformly applicable method for saving time and increasing consistency in studies of the mouse gastrointestinal tract.

Best Practices for Authentication of Cell Lines to Ensure Data Reproducibility and Integrity

Cell line misidentification and contamination are major contributors to the reproducibility crisis in academic research. Authentication of cell lines provides assurances of the data generated; however, commercially available cells are often not subjected to rigorous identification testing. In this study, commercially available cell lines underwent testing to confirm cell identity and purity. The methods reported here outline the best practices for cell line authentication. Briefly, a commercially available primary rabbit aortic endothelial cell line was purchased for the intent of producing target proteins necessary for generating species-specific recombinant antibodies. These rabbit-specific antibodies would then be utilized for the development of in-house enzyme-linked immunosorbent assays (ELISA) to evaluate blood-based biomarkers of vascular injury after total-body irradiation. To authenticate the cell line, cell identity and purity were determined by single tandem repeat (STR) testing, flow cytometry, polymerase chain reaction (PCR), and cytochrome c oxidase subunit 1 (CO1) DNA Barcoding in-house and/or through commercial vendors. Fresh cells obtained from a New Zealand White rabbit (Charles River, Wilmington, DE) were used as a positive control. The results of STR and flow cytometry analyses indicated the cells were not contaminated with human or mouse cells, and that the cells were not of endothelial origin. PCR demonstrated that cells were also not of rabbit origin, which was further confirmed by a third-party vendor. An unopened vial of cells was submitted to another vendor for CO1 DNA Barcoding analysis, which identified the cells as being purely of bovine origin. Results revealed that despite purchase through a commercial vendor, the cell line marketed as primary rabbit aortic endothelial cells were of bovine origin. Purity analysis found cells were misidentified rather than contaminated. Further investigation to determine the cell type was not performed. The most cost-effective and efficient methodology for confirming cell line identity was found to be CO1 DNA Barcoding performed by a commercial vendor.

New Challenges for Biobanks: Accreditation to the New ISO 20387:2018 Standard Specific for Biobanks

Background: The emergence of “multi-omics” and “multi-parametric” types of analysis based on a high number of biospecimens enforces the use of a great number of high-quality “Biological Materials and Associated Data” (BMaD). To meet the demands of biomedical research, several Biological Resource Centers (BRCs) or Biobanks world-wide have implemented a specific Quality Management System (QMS) certified ISO 9001:2015 or accredited by CAP⁹ ISO 20387:2018. For the first time, ISO, with the support of several Biobanking experts, issued the ISO 20387:2018 which is the first ISO norm specific for Biobanks. The fundamental difference with present certification/accreditation standards is that the ISO 20387:2018 focuses not only on the operational aspects of the Biobank, but also on the “competence of the Biobank to carry our specific Biobanking tasks”. Methods: The accreditation process for ISO 20387:2018 required the definition of: (1) objectives, goals and organizational structure of the Biobank, including procedures for governance, confidentiality and impartiality policies; (2) standard operating procedures (SOPs) of all activities performed, including acquisition, analysis, collection, data management, distribution, preparation, preservation, testing facility and equipment maintenance, calibration, and monitoring; (3) procedures for control of documents and records, the identification of risks and opportunities, improvements, corrective actions, nonconforming records and evaluation of external providers (4) an internal audit and management reviews, verification of QMS performance, monitoring of quality objectives and personnel qualification and competency in carrying out specific Biobanking tasks. Results: The accreditation process is performed by an independent authorized organization which certifies that all processes are performed according to the QMS, and that the infrastructure is engineered and managed according to the GDP and/or GMP guidelines. Conclusion: Accreditation is given by an accreditation body, which recognizes formally that the Biobank is “competent to carry out specific Biobanking tasks”.

Lack of parent-of-origin effects in Nasonia jewel wasp: A replication and extension study

In diploid cells, the paternal and maternal alleles are, on average, equally expressed. There are exceptions from this: a small number of genes express the maternal or paternal allele copy exclusively. This phenomenon, known as genomic imprinting, is common among eutherian mammals and some plant species; however, genomic imprinting in species with haplodiploid sex determination is not well characterized. Previous work reported no parent-of-origin effects in the hybrids of closely related haplodiploid Nasonia vitripennis and Nasonia giraulti jewel wasps, suggesting a lack of epigenetic reprogramming during embryogenesis in these species. Here, we replicate the gene expression dataset and observations using different individuals and sequencing technology, as well as reproduce these findings using the previously published RNA sequence data following our data analysis strategy. The major difference from the previous dataset is that they used an introgression strain as one of the parents and we found several loci that resisted introgression in that strain. Our results from both datasets demonstrate a species-of-origin effect, rather than a parent-of-origin effect. We present a reproducible workflow that others may use for replicating the results. Overall, we reproduced the original report of no parent-of-origin effects in the haplodiploid Nasonia using the original data with our new processing and analysis pipeline and replicated these results with our newly generated data.

Advancing Biomarker Development Through Convergent Engagement: Summary Report of the 2nd International Danube Symposium on Biomarker Development, Molecular Imaging and Applied Diagnostics; March 14-16, 2018; Vienna, Austria

Here, we report on the outcome of the 2nd International Danube Symposium on advanced biomarker development that was held in Vienna, Austria, in early 2018. During the meeting, cross-speciality participants assessed critical aspects of non-invasive, quantitative biomarker development in view of the need to expand our understanding of disease mechanisms and the definition of appropriate strategies both for molecular diagnostics and personalised therapies. More specifically, panelists addressed the main topics, including the current status of disease characterisation by means of non-invasive imaging, histopathology and liquid biopsies as well as strategies of gaining new understanding of disease formation, modulation and plasticity to large-scale molecular imaging as well as integrative multi-platform approaches. Highlights of the 2018 meeting included dedicated sessions on non-invasive disease characterisation, development of disease and therapeutic tailored biomarkers, standardisation and quality measures in biospecimens, new therapeutic approaches and socio-economic challenges of biomarker developments. The scientific programme was accompanied by a roundtable discussion on identification and implementation of sustainable strategies to address the educational needs in the rapidly evolving field of molecular diagnostics. The central theme that emanated from the 2nd Donau Symposium was the importance of the conceptualisation and implementation of a convergent approach towards a disease characterisation beyond lesion-counting "lumpology" for a cost-effective and patient-centric diagnosis, therapy planning, guidance and monitoring. This involves a judicious choice of diagnostic means, the adoption of clinical decision support systems and, above all, a new way of communication involving all stakeholders across modalities and specialities. Moreover, complex diseases require a comprehensive diagnosis by converging parameters from different disciplines, which will finally yield to a precise therapeutic guidance and outcome prediction. While it is attractive to focus on technical advances alone, it is important to develop a patient-centric approach, thus asking "What can we do with our expertise to help patients?"

The need for standardisation in life science research - an approach to excellence and trust

Today, academic researchers benefit from the changes driven by digital technologies and the enormous growth of knowledge and data, on globalisation, enlargement of the scientific community, and the linkage between different scientific communities and the society. To fully benefit from this development, however, information needs to be shared openly and transparently. Digitalisation plays a major role here because it permeates all areas of business, science and society and is one of the key drivers for innovation and international cooperation. To address the resulting opportunities, the EU promotes the development and use of collaborative ways to produce and share knowledge and data as early as possible in the research process, but also to appropriately secure results with the European strategy for Open Science (OS). It is now widely recognised that making research results more accessible to all societal actors contributes to more effective and efficient science; it also serves as a boost for innovation in the public and private sectors. However  for research data to be findable, accessible, interoperable and reusable the use of standards is essential. At the metadata level, considerable efforts in standardisation have already been made (e.g. Data Management Plan and FAIR Principle etc.), whereas in context with the raw data these fundamental efforts are still fragmented and in some cases completely missing. The CHARME consortium, funded by the European Cooperation in Science and Technology (COST) Agency, has identified needs and gaps in the field of standardisation in the life sciences and also discussed potential hurdles for implementation of standards in current practice. Here, the authors suggest four measures in response to current challenges to ensure a high quality of life science research data and their re-usability for research and innovation.

A Review of the Scientific Rigor, Reproducibility, and Transparency Studies Conducted by the ABRF Research Groups

Shared research resource facilities, also known as core laboratories (Cores), are responsible for generating a significant and growing portion of the research data in academic biomedical research institutions. Cores represent a central repository for institutional knowledge management, with deep expertise in the strengths and limitations of technology and its applications. They inherently support transparency and scientific reproducibility by protecting against cognitive bias in research design and data analysis, and they have institutional responsibility for the conduct of research (research ethics, regulatory compliance, and financial accountability) performed in their Cores. The Association of Biomolecular Resource Facilities (ABRF) is a FASEB-member scientific society whose members are scientists and administrators that manage or support Cores. The ABRF Research Groups (RGs), representing expertise for an array of cutting-edge and established technology platforms, perform multicenter research studies to determine and communicate best practices and community-based standards. This review provides a summary of the contributions of the ABRF RGs to promote scientific rigor and reproducibility in Cores from the published literature, ABRF meetings, and ABRF RGs communications.

The relationship of polarity of post-publication peer review to citation count

Purpose

The purpose of this study is to investigate the relationship of the post-publication peer review (PPPR) polarity of a paper to that paper's citation count.

Design/methodology/approach

Papers with PPPRs from Publons.com as the experimental groups were manually matched 1:2 with the related papers without PPPR as the control group, by the same journal, the same issue (volume), the same access status (gold open access or not) and the same document type. None of the papers in the experimental group or control group received any comments or recommendations from ResearchGate, PubPeer or F1000. The polarity of the PPPRs was coded by using content analysis. A negative binomial regression analysis was conducted to examine the data by controlling the characteristics of papers.

Findings

The four experimental groups and their corresponding control groups were generated as follows: papers with neutral PPPRs, papers with both negative and positive PPPRs, papers with negative PPPRs and papers with positive PPPRs as well as four corresponding control groups (papers without PPPRs). The results are as follows: while holding the other variables (such as page count, number of authors, etc.) constant in the model, papers that received neutral PPPRs, those that received negative PPPRs and those that received both negative and positive PPPRs had no significant differences in citation count when compared to their corresponding control pairs (papers without PPPRs). Papers that received positive PPPRs had significantly greater citation count than their corresponding control pairs (papers without PPPRs) while holding the other variables (such as page count, number of authors, etc.) constant in the model.

Originality/value

Based on a broader range of PPPR sentiments, by controlling many of the confounding factors (including the characteristics of the papers and the effects of the other PPPR platforms), this study analyzed the relationship of various polarities of PPPRs to citation count.

A systematic approach to quantitative Western blot analysis

Attaining true quantitative data from WB requires that all the players involved in the procedure are quality controlled including the user. Appropriate protein extraction method, electrophoresis, and transfer of proteins, immunodetection of blotted protein by antibodies, and the ultimate step of imaging and analyzing the data is nothing short of a symphony. Like with any other technology in life-sciences research, Western blotting can produce erroneous and irreproducible data. We provide a systematic approach to generate quantitative data from Western blot experiments that incorporates critical validation steps to identify and minimize sources of error and variability throughout the Western blot process.

Cellular Metrology: Scoping for a Value Proposition in Extra- and Intracellular Measurements

The symptomatic irreproducibility of data in biomedicine and biotechnology prompts the need for higher order measurements of cells in their native and near-native environments. Such measurements may support the adoption of new technologies as well as the development of research programs across different sectors including healthcare and clinic, environmental control and national security. With an increasing demand for reliable cell-based products and services, cellular metrology is poised to help address current and emerging measurement challenges faced by end-users. However, metrological foundations in cell analysis remain sparse and significant advances are necessary to keep pace with the needs of modern medicine and industry. Herein we discuss a role of metrology in cell and cell-related R&D activities to underpin growing international measurement capabilities. Relevant measurands are outlined and the lack of reference methods and materials, particularly those based on functional cell responses in native environments, is highlighted. The status quo and current challenges in cellular measurements are discussed in the light of metrological traceability in cell analysis and applications (e.g., a functional cell count). An emphasis is made on the consistency of measurement results independent of the analytical platform used, high confidence in data quality vs. quantity, scale of measurements and issues of building infrastructure for end-users.

Antibody validation for Western blot: By the user, for the user

Well-characterized antibody reagents play a key role in the reproducibility of research findings, and inconsistent antibody performance leads to variability in Western blotting and other immunoassays. The current lack of clear, accepted standards for antibody validation and reporting of experimental details contributes to this problem. Because the performance of primary antibodies is strongly influenced by assay context, recommendations for validation and usage are unique to each type of immunoassay. Practical strategies are proposed for the validation of primary antibody specificity, selectivity, and reproducibility using Western blot analysis. The antibody should produce reproducible results within and between Western blotting experiments and the observed effect confirmed with a complementary or orthogonal method. Routine implementation of standardized antibody validation and reporting in immunoassays such as Western blotting may promote improved reproducibility across the global life sciences community.

Targets, pitfalls and reference materials for liquid biopsy tests in cancer diagnostics

Assessment of cell free DNA (cfDNA) and RNA (cfRNA), circulating tumor cells (CTC) and extracellular vesicles (EV) in blood or other bodily fluids can enable early cancer detection, tumor dynamics assessment, minimal residual disease detection and therapy monitoring. However, few liquid biopsy tests progress towards clinical application because results are often discordant and challenging to reproduce. Reproducibility can be enhanced by the development and implementation of standard operating procedures and reference materials to identify and correct for pre-analytical variables. In this review we elaborate on the technological considerations, pre-analytical variables and the use and availability of reference materials for the assessment of liquid biopsy targets in blood and highlight initiatives towards the standardization of liquid biopsy testing.

Survey on Scientific Shared Resource Rigor and Reproducibility

Shared scientific resources, also known as core facilities, support a significant portion of the research conducted at biomolecular research institutions. The Association of Biomolecular Resource Facilities (ABRF) established the Committee on Core Rigor and Reproducibility (CCoRRe) to further its mission of integrating advanced technologies, education, and communication in the operations of shared scientific resources in support of reproducible research. In order to first assess the needs of the scientific shared resource community, the CCoRRe solicited feedback from ABRF members via a survey. The purpose of the survey was to gain information on how U.S. National Institutes of Health (NIH) initiatives on advancing scientific rigor and reproducibility influenced current services and new technology development. In addition, the survey aimed to identify the challenges and opportunities related to implementation of new reporting requirements and to identify new practices and resources needed to ensure rigorous research. The results revealed a surprising unfamiliarity with the NIH guidelines. Many of the perceived challenges to the effective implementation of best practices (i.e., those designed to ensure rigor and reproducibility) were similarly noted as a challenge to effective provision of support services in a core setting. Further, most cores routinely use best practices and offer services that support rigor and reproducibility. These services include access to well-maintained instrumentation and training on experimental design and data analysis as well as data management. Feedback from this survey will enable the ABRF to build better educational resources and share critical best-practice guidelines. These resources will become important tools to the core community and the researchers they serve to impact rigor and transparency across the range of science and technology.

Biomedical Image Processing with Containers and Deep Learning: An Automated Analysis Pipeline: Data architecture, artificial intelligence, automated processing, containerization, and clusters orchestration ease the transition from data acquisition to insights in medium-to-large datasets

Here, a streamlined, scalable, laboratory approach is discussed that enables medium-to-large dataset analysis. The presented approach combines data management, artificial intelligence, containerization, cluster orchestration, and quality control in a unified analytic pipeline. The unique combination of these individual building blocks creates a new and powerful analysis approach that can readily be applied to medium-to-large datasets by researchers to accelerate the pace of research. The proposed framework is applied to a project that counts the number of plasmonic nanoparticles bound to peripheral blood mononuclear cells in dark-field microscopy images. By using the techniques presented in this article, the images are automatically processed overnight, without user interaction, streamlining the path from experiment to conclusions.

Scientific Integrity Principles and Best Practices: Recommendations from a Scientific Integrity Consortium

A Scientific Integrity Consortium developed a set of recommended principles and best practices that can be used broadly across scientific disciplines as a mechanism for consensus on scientific integrity standards and to better equip scientists to operate in a rapidly changing research environment. The two principles that represent the umbrella under which scientific processes should operate are as follows: (1) Foster a culture of integrity in the scientific process. (2) Evidence-based policy interests may have legitimate roles to play in influencing aspects of the research process, but those roles should not interfere with scientific integrity. The nine best practices for instilling scientific integrity in the implementation of these two overarching principles are (1) Require universal training in robust scientific methods, in the use of appropriate experimental design and statistics, and in responsible research practices for scientists at all levels, with the training content regularly updated and presented by qualified scientists. (2) Strengthen scientific integrity oversight and processes throughout the research continuum with a focus on training in ethics and conduct. (3) Encourage reproducibility of research through transparency. (4) Strive to establish open science as the standard operating procedure throughout the scientific enterprise. (5) Develop and implement educational tools to teach communication skills that uphold scientific integrity. (6) Strive to identify ways to further strengthen the peer review process. (7) Encourage scientific journals to publish unanticipated findings that meet standards of quality and scientific integrity. (8) Seek harmonization and implementation among journals of rapid, consistent, and transparent processes for correction and/or retraction of published papers. (9) Design rigorous and comprehensive evaluation criteria that recognize and reward the highest standards of integrity in scientific research.

Guidelines for Experiments Using Antisense Oligonucleotides and Double-Stranded RNAs

After decades of research and development, synthetic nucleic acids are beginning to enjoy significant success in the clinic. Approved drugs have increased interest in the field, and many basic research studies have focused on synthetic nucleic acids to control the action of messenger RNA and noncoding RNAs. Unfortunately, experimental designs are often inadequate, resulting in misleading interpretation of data and unconvincing work that wastes resources and does little to advance the field. The goal of this commentary is to outline the problems facing many researchers, especially those new to the use of synthetic oligonucleotides. We describe the minimum control experiments necessary to build a strong case for real effects that are likely due to interactions at the intended molecular target. A common set of standards for preparing and judging experiments should facilitate better interpretation of data and publications that contribute positively to using synthetic nucleic acids as tools and drugs.

DataPackageR: Reproducible data preprocessing, standardization and sharing using R/Bioconductor for collaborative data analysis

A central tenet of reproducible research is that scientific results are published along with the underlying data and software code necessary to reproduce and verify the findings. A host of tools and software have been released that facilitate such work-flows and scientific journals have increasingly demanded that code and primary data be made available with publications. There has been little practical advice on implementing reproducible research work-flows for large ’omics’ or systems biology data sets used by teams of analysts working in collaboration. In such instances it is important to ensure all analysts use the same version of a data set for their analyses. Yet, instantiating relational databases and standard operating procedures can be unwieldy, with high "startup" costs and poor adherence to procedures when they deviate substantially from an analyst’s usual work-flow. Ideally a reproducible research work-flow should fit naturally into an individual’s existing work-flow, with minimal disruption. Here, we provide an overview of how we have leveraged popular open source tools, including Bioconductor, Rmarkdown, git version control, R, and specifically R’s package system combined with a new tool DataPackageR, to implement a lightweight reproducible research work-flow for preprocessing large data sets, suitable for sharing among small-to-medium sized teams of computational scientists. Our primary contribution is the DataPackageR tool, which decouples time-consuming data processing from data analysis while leaving a traceable record of how raw data is processed into analysis-ready data sets. The software ensures packaged data objects are properly documented and performs checksum verification of these along with basic package version management, and importantly, leaves a record of data processing code in the form of package vignettes. Our group has implemented this work-flow to manage, analyze and report on pre-clinical immunological trial data from multi-center, multi-assay studies for the past three years.

DataPackageR: Reproducible data preprocessing, standardization and sharing using R/Bioconductor for collaborative data analysis

A central tenet of reproducible research is that scientific results are published along with the underlying data and software code necessary to reproduce and verify the findings. A host of tools and software have been released that facilitate such work-flows and scientific journals have increasingly demanded that code and primary data be made available with publications. There has been little practical advice on implementing reproducible research work-flows for large ’omics’ or systems biology data sets used by teams of analysts working in collaboration. In such instances it is important to ensure all analysts use the same version of a data set for their analyses. Yet, instantiating relational databases and standard operating procedures can be unwieldy, with high "startup" costs and poor adherence to procedures when they deviate substantially from an analyst’s usual work-flow. Ideally a reproducible research work-flow should fit naturally into an individual’s existing work-flow, with minimal disruption. Here, we provide an overview of how we have leveraged popular open source tools, including Bioconductor, Rmarkdown, git version control, R, and specifically R’s package system combined with a new tool DataPackageR, to implement a lightweight reproducible research work-flow for preprocessing large data sets, suitable for sharing among small-to-medium sized teams of computational scientists. Our primary contribution is the DataPackageR tool, which decouples time-consuming data processing from data analysis while leaving a traceable record of how raw data is processed into analysis-ready data sets. The software ensures packaged data objects are properly documented and performs checksum verification of these along with basic package version management, and importantly, leaves a record of data processing code in the form of package vignettes. Our group has implemented this work-flow to manage, analyze and report on pre-clinical immunological trial data from multi-center, multi-assay studies for the past three years.

A practical blueprint to systematically study life-long health consequences of novel medically assisted reproductive treatments

In medicine, safety and efficacy are the two pillars on which the implementation of novel treatments rest. To protect the patient from unnecessary or unsafe treatments, usually, a stringent path of (pre) clinical testing is followed before a treatment is introduced into routine patient care. However, in reproductive medicine several techniques have been clinically introduced without elaborate preclinical studies. Moreover, novel reproductive techniques may harbor safety risks not only for the patients undergoing treatment, but also for the offspring conceived through these techniques. If preclinical (animal) studies were performed, efficacy and functionality the upper hand. When a new medically assisted reproduction (MAR) treatment was proven effective (i.e. if it resulted in live birth) the treatment was often rapidly implemented in the clinic. For IVF, the first study on the long-term health of IVF children was published a decade after its clinical implementation. In more recent years, prospective follow-up studies have been conducted that provided the opportunity to study the health of large groups of children derived from different reproductive techniques. Although such studies have indicated differences between children conceived through MAR and children conceived naturally, results are often difficult to interpret due to the observational nature of these studies (and the associated risk of confounding factors, e.g. subfertility of the parents), differences in definitions of clinical outcome measures, lack of uniformity in assessment protocols and heterogeneity of the underlying reasons for fertility treatment. With more novel MARs waiting at the horizon, there is a need for a framework on how to assess safety of novel reproductive techniques in a preclinical (animal) setting before they are clinically implemented. In this article, we provide a blueprint for preclinical testing of safety and health of offspring generated by novel MARs using a mouse model involving an array of tests that comprise the entire lifespan. We urge scientists to perform the proposed extensive preclinical tests for novel reproductive techniques with the goal to acquire knowledge on efficacy and the possible health effects of to-be implemented reproductive techniques to safeguard quality of novel MARs.

How often should we expect to be wrong? Statistical power, P values, and the expected prevalence of false discoveries

There is a clear perception in the literature that there is a crisis in reproducibility in the biomedical sciences. Many underlying factors contributing to the prevalence of irreproducible results have been highlighted with a focus on poor design and execution of experiments along with the misuse of statistics. While these factors certainly contribute to irreproducibility, relatively little attention outside of the specialized statistical literature has focused on the expected prevalence of false discoveries under idealized circumstances. In other words, when everything is done correctly, how often should we expect to be wrong? Using a simple simulation of an idealized experiment, it is possible to show the central role of sample size and the related quantity of statistical power in determining the false discovery rate, and in accurate estimation of effect size. According to our calculations, based on current practice many subfields of biomedical science may expect their discoveries to be false at least 25% of the time, and the only viable course to correct this is to require the reporting of statistical power and a minimum of 80% power (1 - β = 0.80) for all studies.

Incorporating Data Citation in a Biomedical Repository: An Implementation Use Case

Research data is a dynamic and evolving entity and the ability to cite such data depends on recreating the same datasets utilized in the original research. Despite the availability of several existing technologies, most data repositories lack the necessary setup to recreate a point-in-time snapshot of data, let alone long-term sustainability of dynamic data without restoring an entire database. Through this project, we adopted a subset of the Research Data Alliance data citation working group recommendations to establish a robust informatics system supporting dynamic data and its use for reproducible research within our evolving clinical data repository. We implemented key recommendations: data versioning, times-stamping, query storing, query time-stamping, query PID, and data citation in one data repository, implemented entirely at the database level, and were able to successfully reproduce a previous dataset as it existed at a specific point-in-time using only the PID as provided in a citation.

LITTLE FISH, BIG DATA: ZEBRAFISH AS A MODEL FOR CARDIOVASCULAR AND METABOLIC DISEASE

The burden of cardiovascular and metabolic diseases worldwide is staggering. The emergence of systems approaches in biology promises new therapies, faster and cheaper diagnostics, and personalized medicine. However, a profound understanding of pathogenic mechanisms at the cellular and molecular levels remains a fundamental requirement for discovery and therapeutics. Animal models of human disease are cornerstones of drug discovery as they allow identification of novel pharmacological targets by linking gene function with pathogenesis. The zebrafish model has been used for decades to study development and pathophysiology. More than ever, the specific strengths of the zebrafish model make it a prime partner in an age of discovery transformed by big-data approaches to genomics and disease. Zebrafish share a largely conserved physiology and anatomy with mammals. They allow a wide range of genetic manipulations, including the latest genome engineering approaches. They can be bred and studied with remarkable speed, enabling a range of large-scale phenotypic screens. Finally, zebrafish demonstrate an impressive regenerative capacity scientists hope to unlock in humans. Here, we provide a comprehensive guide on applications of zebrafish to investigate cardiovascular and metabolic diseases. We delineate advantages and limitations of zebrafish models of human disease and summarize their most significant contributions to understanding disease progression to date.

Serendipitous discovery of light-induced (In Situ) formation of an Azo-bridged dimeric sulfonated naphthol as a potent PTP1B inhibitor

BACKGROUND

Protein tyrosine phosphatases (PTPs) like dual specificity phosphatase 5 (DUSP5) and protein tyrosine phosphatase 1B (PTP1B) are drug targets for diseases that include cancer, diabetes, and vascular disorders such as hemangiomas. The PTPs are also known to be notoriously difficult targets for designing inihibitors that become viable drug leads. Therefore, the pipeline for approved drugs in this class is minimal. Furthermore, drug screening for targets like PTPs often produce false positive and false negative results.

RESULTS

Studies presented herein provide important insights into: (a) how to detect such artifacts, (b) the importance of compound re-synthesis and verification, and (c) how in situ chemical reactivity of compounds, when diagnosed and characterized, can actually lead to serendipitous discovery of valuable new lead molecules. Initial docking of compounds from the National Cancer Institute (NCI), followed by experimental testing in enzyme inhibition assays, identified an inhibitor of DUSP5. Subsequent control experiments revealed that this compound demonstrated time-dependent inhibition, and also a time-dependent change in color of the inhibitor that correlated with potency of inhibition. In addition, the compound activity varied depending on vendor source. We hypothesized, and then confirmed by synthesis of the compound, that the actual inhibitor of DUSP5 was a dimeric form of the original inhibitor compound, formed upon exposure to light and oxygen. This compound has an IC50 of 36 μM for DUSP5, and is a competitive inhibitor. Testing against PTP1B, for selectivity, demonstrated the dimeric compound was actually a more potent inhibitor of PTP1B, with an IC50 of 2.1 μM. The compound, an azo-bridged dimer of sulfonated naphthol rings, resembles previously reported PTP inhibitors, but with 18-fold selectivity for PTP1B versus DUSP5.

CONCLUSION

We report the identification of a potent PTP1B inhibitor that was initially identified in a screen for DUSP5, implying common mechanism of inhibitory action for these scaffolds.

Non-coding RNAs as drug targets

Most of the human genome encodes RNAs that do not code for proteins. These non-coding RNAs (ncRNAs) may affect normal gene expression and disease progression, making them a new class of targets for drug discovery. Because their mechanisms of action are often novel, developing drugs to target ncRNAs will involve equally novel challenges. However, many potential problems may already have been solved during the development of technologies to target mRNA. Here, we discuss the growing field of ncRNA - including microRNA, intronic RNA, repetitive RNA and long non-coding RNA - and assess the potential and challenges in their therapeutic exploitation.

Considerations for the design and execution of protocols for animal research and treatment to improve reproducibility and standardization: "DEPART well-prepared and ARRIVE safely"

OBJECTIVE

To review the factors in experimental design that contribute to poor translation of pre-clinical research to therapies for patients with osteoarthritis (OA) and how this might be improved.

METHODS

Narrative review of the literature, and evaluation of the different stages of design conduct and analysis of studies using animal models of OA to define specific issues that might reduce quality of evidence and how this can be minimised.

RESULTS

Preventing bias and improving experimental rigour and reporting are important modifiable factors to improve translation from pre-clinical animal models to successful clinical trials of therapeutic agents. Despite publication and adoption by many journals of guidelines such as Animals in Research: Reporting In Vivo Experiments (ARRIVE), experimental animal studies published in leading rheumatology journals are still deficient in their reporting. In part, this may be caused by researchers first consulting these guidelines after the completion of experiments, at the time of publication. This review discusses factors that can (1) bias the outcome of experimental studies using animal models of osteoarthritis or (2) alter the quality of evidence for translation. We propose a checklist to consult prior to starting experiments; in the Design and Execution of Protocols for Animal Research and Treatment (DEPART).

CONCLUSIONS

Following DEPART during the design phase will enable completion of the ARRIVE checklist at the time of publication, and thus improve the quality of evidence for inclusion of experimental animal research in meta-analyses and systematic reviews: "DEPART well-prepared and ARRIVE safely".

Approaches and Guidelines for the Identification of Novel Substrates of Protein Lysine Methyltransferases

Protein lysine methylation is emerging as a general post-translational modification (PTM) with essential functions regulating protein stability, activity, and protein-protein interactions. One of the outstanding challenges in this field is linking protein lysine methyltransferases (PKMTs) with specific substrates and lysine methylation events in a systematic manner. Inability to validate reported PKMT substrates delayed progress in the field and cast unnecessary doubt about protein lysine methylation as a truly general PTM. Here, we aim to provide a concise guide to help avoid some of the most common pitfalls in studies searching for new PKMT substrates and propose a set of seven basic biochemical rules: (1) include positive controls; (2) use target lysine mutations of substrate proteins as negative controls; (3) use inactive enzyme variants as negative controls; (4) report quantitative methylation data; (5) consider PKMT specificity; (6) validate methyl lysine antibodies; and (7) connect cellular and in vitro results. We explain the logic behind them and discuss how they should be implemented in the experimental work.

Biospecimen Complexity-the Next Challenge for Cancer Research Biobanks?

Purpose: Biospecimens (e.g., tissues, bloods, fluids) are critical for translational cancer research to generate the necessary knowledge to guide implementation of precision medicine. Rising demand and the need for higher quality biospecimens are already evident.Experimental Design: The recent increase in requirement for biospecimen complexity in terms of linked biospecimen types, multiple preservation formats, and longitudinal data was explored by assessing trends in cancer research publications from 2000 to 2014.Results: A PubMed search shows that there has been an increase in both raw numbers and the relative proportion (adjusted for total numbers of articles in each period) of the subgroups of articles typically associated with the use of biospecimens and both dense treatment and/or outcomes data and multiple biospecimen formats.Conclusions: Increasing biospecimen complexity is a largely unrecognized and new pressure on cancer research biobanks. New approaches to cancer biospecimen resources are needed such as the implementation of more efficient and dynamic consent mechanisms, stronger participant involvement in biobank governance, development of requirements for registration of collections, and models to establish stock targets for biobanks. In particular, the latter two approaches would enable funders to establish a better balance between biospecimen supply and research demand, reduce expenditure on duplicate collections, and encourage increased efficiency of biobanks to respond to the research need for more complex cases. This in turn would also enable biobanks to focus more on quality and standardization that are surely factors in the even more important arena of research reproducibility. Clin Cancer Res; 23(4); 894-8. ©2016 AACR.

Changes of heterogeneous cell populations in the Ishikawa cell line during long-term culture: Proposal for an in vitro clonal evolution model of tumor cells

Genomic changes in tumor cell lines can occur during culture, leading to differences between cell lines carrying the same name. In this study, genome profiles between low and high passages were investigated in the Ishikawa 3-H-12 cell line (JCRB1505). Cells contained between 43 and 46 chromosomes and the modal number changed from 46 to 45 during culture. Cytogenetic analysis revealed that a translocation t(9;14), observed in all metaphases, is a robust marker for this cell line. Single-nucleotide polymorphism microarrays showed a heterogeneous copy number in the early passages and distinct profiles at late passages. These results demonstrate that cell culture can lead to elimination of ancestral clones by sequential selection, resulting in extensive replacement with a novel clone. Our observations on Ishikawa cells in vitro are different from the in vivo heterogeneity in which ancestral clones are often retained during tumor evolution and suggest a model for in vitro clonal evolution.

Irreproducibility in Preclinical Biomedical Research: Perceptions, Uncertainties, and Knowledge Gaps

Concerns regarding the reliability of biomedical research outcomes were precipitated by two independent reports from the pharmaceutical industry that documented a lack of reproducibility in preclinical research in the areas of oncology, endocrinology, and hematology. Given their potential impact on public health, these concerns have been extensively covered in the media. Assessing the magnitude and scope of irreproducibility is limited by the anecdotal nature of the initial reports and a lack of quantitative data on specific failures to reproduce published research. Nevertheless, remediation activities have focused on needed enhancements in transparency and consistency in the reporting of experimental methodologies and results. While such initiatives can effectively bridge knowledge gaps and facilitate best practices across established and emerging research disciplines and therapeutic areas, concerns remain on how these improve on the historical process of independent replication in validating research findings and their potential to inhibit scientific innovation.

Immobilized Metal Affinity Chromatography Coupled to Multiple Reaction Monitoring Enables Reproducible Quantification of Phospho-signaling

A major goal in cell signaling research is the quantification of phosphorylation pharmacodynamics following perturbations. Traditional methods of studying cellular phospho-signaling measure one analyte at a time with poor standardization, rendering them inadequate for interrogating network biology and contributing to the irreproducibility of preclinical research. In this study, we test the feasibility of circumventing these issues by coupling immobilized metal affinity chromatography (IMAC)-based enrichment of phosphopeptides with targeted, multiple reaction monitoring (MRM) mass spectrometry to achieve precise, specific, standardized, multiplex quantification of phospho-signaling responses. A multiplex immobilized metal affinity chromatography- multiple reaction monitoring assay targeting phospho-analytes responsive to DNA damage was configured, analytically characterized, and deployed to generate phospho-pharmacodynamic curves from primary and immortalized human cells experiencing genotoxic stress. The multiplexed assays demonstrated linear ranges of ≥3 orders of magnitude, median lower limit of quantification of 0.64 fmol on column, median intra-assay variability of 9.3%, median inter-assay variability of 12.7%, and median total CV of 16.0%. The multiplex immobilized metal affinity chromatography- multiple reaction monitoring assay enabled robust quantification of 107 DNA damage-responsive phosphosites from human cells following DNA damage. The assays have been made publicly available as a resource to the community. The approach is generally applicable, enabling wide interrogation of signaling networks.