RPM: An open-source Rotation Platform for open- and closed-loop vestibular stimulation in head-fixed Mice

Head fixation allows the recording and presentation of controlled stimuli and is used to study neural processes underlying spatial navigation. However, it disrupts the head direction system because of the lack of vestibular stimulation. To overcome this limitation, we developed a novel rotation platform which can be driven by the experimenter (open-loop) or by animal movement (closed-loop). The platform is modular, affordable, easy to build and open source. Additional modules presented here include cameras for monitoring eye movements, visual virtual reality, and a micro-manipulator for positioning various probes for recording or optical interference. We demonstrate the utility of the platform by recording eye movements and showing the robust activation of head-direction cells. This novel experimental apparatus combines the advantages of head fixation and intact vestibular activity in the horizontal plane. The open-loop mode can be used to study e.g., vestibular sensory representation and processing, while the closed-loop mode allows animals to navigate in rotational space, providing a better substrate for 2-D navigation in virtual environments. The full build documentation is maintained at https://ranczlab.github.io/RPM/.

SGABU computational platform for multiscale modeling: Bridging the gap between education and research

BACKGROUND AND OBJECTIVE

In accordance with the latest aspirations in the field of bioengineering, there is a need to create a web accessible, but powerful cloud computational platform that combines datasets and multiscale models related to bone modeling, cancer, cardiovascular diseases and tissue engineering. The SGABU platform may become a powerful information system for research and education that can integrate data, extract information, and facilitate knowledge exchange with the goal of creating and developing appropriate computing pipelines to provide accurate and comprehensive biological information from the molecular to organ level.

METHODS

The datasets integrated into the platform are obtained from experimental and/or clinical studies and are mainly in tabular or image file format, including metadata. The implementation of multiscale models, is an ambitious effort of the platform to capture phenomena at different length scales, described using partial and ordinary differential equations, which are solved numerically on complex geometries with the use of the finite element method. The majority of the SGABU platform's simulation pipelines are provided as Common Workflow Language (CWL) workflows. Each of them requires creating a CWL implementation on the backend and a user-friendly interface using standard web technologies. Platform is available at https://sgabu-test.unic.kg.ac.rs/login.

RESULTS

The main dashboard of the SGABU platform is divided into sections for each field of research, each one of which includes a subsection of datasets and multiscale models. The datasets can be presented in a simple form as tabular data, or using technologies such as Plotly.js for 2D plot interactivity, Kitware Paraview Glance for 3D view. Regarding the models, the usage of Docker containerization for packing the individual tools and CWL orchestration for describing inputs with validation forms and outputs with tabular views for output visualization, interactive diagrams, 3D views and animations.

CONCLUSIONS

In practice, the structure of SGABU platform means that any of the integrated workflows can work equally well on any other bioengineering platform. The key advantage of the SGABU platform over similar efforts is its versatility offered with the use of modern, modular, and extensible technology for various levels of architecture.

Open Science Practices in Psychiatric Genetics: A Primer

Open science ensures that research is transparently reported and freely accessible for all to assess and collaboratively build on. Psychiatric genetics has led among the health sciences in implementing some open science practices in common study designs, such as replication as part of genome-wide association studies. However, thorough open science implementation guidelines are limited and largely not specific to data, privacy, and research conduct challenges in psychiatric genetics. Here, we present a primer of open science practices, including selection of a research topic with patients/nonacademic collaborators, equitable authorship and citation practices, design of replicable, reproducible studies, preregistrations, open data, and privacy issues. We provide tips for informative figures and inclusive, precise reporting. We discuss considerations in working with nonacademic collaborators and distributing research through preprints, blogs, social media, and accessible lecture materials. Finally, we provide extra resources to support every step of the research process.

[The different models of scientific journals]

Introduction

Scientific journals are the main source of scientific data, ensuring their registration, validation, distribution and archiving. With over 2.6 million scientific articles published each year, the turnover of scientific journals exceeds $25 billion annually. Five publishers share nearly half of this lucrative market. Scientists are the key players in the process, but other stakeholders have gradually been introduced, building various business models whose similarities and differences are described here.

Concepts underlying scientific publication

Open access to scientific papers dates back to the scientific and technical revolution of the 17th century. However, its evolution has been considerably boosted by the development of the Internet and the recognition of science as "commons".Scientific integrity is under the control of research institutions to ensure the prevention of fraud and misconduct in the course of scientific production. Usually, the scientific integrity is questioned during the manuscript reviewing process which may result in identification of flaws.

Models of scientific publications

In the historical model, readers pay for access to the document. Authors are not remunerated and renounce copyright on their articles to the publisher. The limits of the historical model became clear in the 90s, facing the cost of publishing, reduction in the number of subscribers, development of the Internet and willingness to improve manuscript evaluation.With the development of the Internet and the paradigm of open access, publishers proposed a new model in the 2000s, replacing the cost of access to articles for the reader with the payment of Article Processing Charges (APCs) paid by the author or its institution ("author pays" model). In this model, the content of the article can be freely reproduced and used, provided that the original author is credited. In addition to the evaluation of the manuscript which remains a critical factor, the cost of publication appears inequitable. However, all or part of the APCs may be waived, particularly for authors from low- and middle-income countries.For the past 15 years or so, publishers, learned societies and academic or research institutions (including libraries) have been seeking to publish reliable, open access manuscripts that respect scientific integrity while being affordable for the author.Predatory journals emerged in the late 2000s, taking advantage of the success of the authorpays model to capture APCs. Lacking a proper evaluation process resulting in poor-quality publications, these journals are rejected by most scientific institutions. On the other hand, they are particularly attractive in low- and middle-income countries because of their aggressive commercial practices (insistent invitation to submit a manuscript, low rejection rate, rapid publication, reduced APC, etc.).The purpose of each journal is to secure its economic model. This goes through ensuring its visibility, which is determined by the number of citations (online and social media citations) rather than the quality of the articles published.

Peer review

This very old concept has not been widely used until the 20th century. In the historical model, manuscript evaluation is generally carried out by members of the learned society that publishes the journal. Evaluation can be either unblinded, single-blinded (referee is anonymous) or double-blinded (author and referee are anonymous). Several studies have shown that blind procedures do not alter the quality of the evaluation. Since the early 90s, post-publication evaluation has emerged, of which there are several variants. The aim is to shorten times to publication and open up the evaluation process more widely in order to limit the bias. Apart from the fact that this system does not guarantee a better evaluation of the manuscript, its main disadvantage is that the article is accessible without validation of the data collection and analysis throughout the entire process, which can be lengthy.

Cost and funding of scientific journals

The cost of an article depends on charges that vary according to the conditions and places of production. Reviewers are volunteers. On the other hand, manuscript management, editing and distribution are carried out by professionals, which entail financial charges. Some of these costs are lower in low- and medium-resource countries, where economies of scale and higher benefits are possible.

Conclusion

The limits of the historical model have led to the development of several business models of scientific journals, that are in constant evolution, especially the author pays model which promises open access to publications but impacts scientific production. However, the evaluation of scientific production is heterogeneous due to a limited pool of reviewers inadequately selected. Scientific publishing is looking for solutions to find a virtuous model that respects open science, open access to data and scientific integrity. The "Diamond open access" model, free of charge for both readers and authors with the guarantee of an irrevocable license to reproduce the content of the article provided that the original source is cited, perfectly fits.

Perspectives on systematic review protocol registration: a survey amongst stakeholders in the clinical research publication process

BACKGROUND

As systematic reviews (SRs) inform healthcare decisions, it is key that they address relevant questions and use rigorous methodology. Registration of SR protocols helps researchers identify relevant topics for future reviews and aims to prevent bias and duplication of effort. However, most SRs protocols are currently not registered, despite its significance. To guide future recommendations to enhance preregistration of SRs, it is important to gain a comprehensive understanding of the perspectives within the research community. Therefore, this study aims to examine the experiences with and factors of influence (barriers and facilitators) on prospective SR registration amongst researchers, peer reviewers and journal editors.

METHODS

Two different surveys were distributed to two groups: researchers and journal editors both identified from an existing sample of SRs. Researchers who indicated to have peer reviewed a SR were surveyed on their perspectives as peer reviewers as well. Survey design and analysis were informed by the Consolidated Framework for Implementation Research (CFIR). Shared and unique subthemes from the perspectives of researchers, peer reviewers and journal editors were identified and linked to the SR registration process (Innovation), to team, organisation (Inner setting) and (inter)national research community (Outer setting), and to characteristics of researchers, peer reviewers or journal editors (Individuals).

RESULTS

The survey's response rates were 65/727 (9%) for researchers, of which 37 were peer reviewers, and 22/308 (7%) for journal editors. Most respondents (n = 76, 94%) were familiar with SR protocol registration and 81% of researchers had registered minimally one SR protocol. Shared SR registration process subthemes were the importance and advantages of SR protocol registration, as well as barriers such as a high administrative burden. Shared subthemes regarding the inner and outer setting centred on journal processes, external standards and time. Shared individual factors were knowledge, skills and awareness.

CONCLUSIONS

The majority of the respondents were familiar with SR protocol registration and had a positive attitude towards it. This study identified suboptimal registration process, administrative burden and lack of mandatory SR protocol registration as barriers. By overcoming these barriers, SR protocol registration could contribute more effectively to the goals of open science.

SYSTEMATIC REVIEW REGISTRATION

osf.io/gmv6z.

Global change research needs international collaboration

Tackling the grand challenges of global climate change for the sustainability of ecological and societal systems requires data and expertise from Russia, the world's largest country that has the longest Arctic shoreline and the largest forest biome, peatland and permafrost zones. Academic relations and scientific collaborations with Russian scholars and institutions must continue despite the ensuing geopolitical crisis since 2022.

"On the ruins of seriality": The scientific journal and the nature of the scientific life

Twenty-first-century discourse on science has been marked by narratives of crisis. Science is said to be experiencing crises of public trust, of peer review and publishing, of reproducibility and replicability, and of recognition and reward. The dominant response has been to "repair" the scientific literature and the system of scientific publishing through open science. This paper places the current predicament of scholarly communication in historical perspective by exploring the evolution of the scientific journal in the second half of the twentieth century. I focus on a new genre of scientific journal invented by Dutch commercial publishers shortly after World War II, and on its effects on the nature of the scientific life. I show that profit-oriented publishers and discipline-building scientists worked together to make postwar science more open, while also arguing that formats of scientific publication have their own agency.

FAB: A "Dummy's" program for self-paced forward and backward reading

The self-paced reading paradigm has been popular and widely used in psycholinguistic research for several decades. The tool described in this paper, FAB (Forward and Backward reading), is a tool created to hopefully and maximally reduce the coding demands and simplify the operation costs for experimental researchers and clinical researchers who are doing experimental work, in their designing, coding, implementing, and analyzing self-paced reading tasks. Its basis in web languages (HTML, JavaScript) also promotes experimental implementation and material sharing in our era of open science. In addition, FAB has a unique forward-and-backward mode that can track regressive-like behaviors that are usually only recordable using eye-tracking or mouse-tracking equipment. In this paper, the specific application and usage of FAB is demonstrated in one laboratory and two online validation experiments. We hope this free and open-sourced tool can benefit research in a diverse range of contexts where self-paced reading is desirable.

Trail making test B in postoperative delirium: a replication study

Background

The Trail Making Test B (TMT-B) is indicative of cognitive flexibility and several other cognitive domains. Previous studies suggest that it might be associated with the risk of developing postoperative delirium, but evidence is limited and conflicting. We therefore aimed to replicate the association of preoperative TMT-B results with postoperative delirium.

Methods

We included older adults (≥65 yr) scheduled for major surgery and without signs of dementia to participate in this binational two-centre longitudinal observational cohort study. Presurgical TMT-B scores were obtained. Delirium was assessed twice daily using validated instruments. Logistic regression was applied and the area under the receiver operating characteristic curve calculated to determine the predictive performance of TMT-B. We subsequently included covariates used in previous studies for consecutive sensitivity analyses. We further analysed the impact of outliers, missing or impaired data.

Results

Data from 841 patients were included and of those, 151 (18%) developed postoperative delirium. TMT-B scores were statistically significantly associated with the incidence of postoperative delirium {odds ratio per 10-s increment 1.06 (95% confidence interval [CI] 1.02-1.09), P=0.001}. The area under the receiver operating characteristic curve was 0.60 ([95% CI 0.55-0.64], P<0.001). The association persisted after removing 21 outliers (1.07 [95% CI 1.03-1.07], P<0.001). Impaired or missing TMT-B data (n=88) were also associated with postoperative delirium (odds ratio 2.74 [95% CI 1.71-4.35], P<0.001).

Conclusions

The TMT-B was associated with postoperative delirium, but its predictive performance as a stand-alone test was low. The TMT-B alone is not suitable to predict delirium in a clinical setting.

Clinical trial registration

NCT02265263. (https://clinicaltrials.gov/ct2/show/results/NCT02265263).

Deep Generative Models: The winning key for large and easily accessible ECG datasets?

Large high-quality datasets are essential for building powerful artificial intelligence (AI) algorithms capable of supporting advancement in cardiac clinical research. However, researchers working with electrocardiogram (ECG) signals struggle to get access and/or to build one. The aim of the present work is to shed light on a potential solution to address the lack of large and easily accessible ECG datasets. Firstly, the main causes of such a lack are identified and examined. Afterward, the potentials and limitations of cardiac data generation via deep generative models (DGMs) are deeply analyzed. These very promising algorithms have been found capable not only of generating large quantities of ECG signals but also of supporting data anonymization processes, to simplify data sharing while respecting patients' privacy. Their application could help research progress and cooperation in the name of open science. However several aspects, such as a standardized synthetic data quality evaluation and algorithm stability, need to be further explored.

Art driven by visual representations of chemical space

Science and art have been connected for centuries. With the development of new computational methods, new scientific disciplines have emerged, such as computational chemistry, and related fields, such as cheminformatics. Chemoinformatics is grounded on the chemical space concept: a multi-descriptor space in which chemical structures are described. In several practical applications, visual representations of the chemical space of compound datasets are low-dimensional plots helpful in identifying patterns. However, the authors propose that the plots can also be used as artistic expressions. This manuscript introduces an approach to merging art with chemoinformatics through visual and artistic representations of chemical space. As case studies, we portray the chemical space of food chemicals and other compounds to generate visually appealing graphs with twofold benefits: sharing chemical knowledge and developing pieces of art driven by chemoinformatics. The art driven by chemical space visualization will help increase the application of chemistry and art and contribute to general education and dissemination of chemoinformatics and chemistry through artistic expressions. All the code and data sets to reproduce the visual representation of the chemical space presented in the manuscript are freely available at https://github.com/DIFACQUIM/Art-Driven-by-Visual-Representations-of-Chemical-Space- . Scientific contribution: Chemical space as a concept to create digital art and as a tool to train and introduce students to cheminformatics.

YCharOS open antibody characterisation data: Lessons learned and progress made

YCharOS is a collaborative initiative aimed at characterising antibodies against the entire human proteome. As of August 2023, they have presented comprehensive knockout characterisation data for 812 antibodies and 78 proteins using techniques such as Western blot, immunoprecipitation, and immunofluorescence. YCharOS consolidates its data into reports (one protein per report) available on Zenodo, a public repository controlled by CERN, to ensure open access. To enhance the visibility of their work, the group is progressively converting their Zenodo reports into F1000 articles, collected on the YCharOS Gateway, and indexed via PubMed. Their data is also accessible through searches on the Antibody Registry. The provided data is a valuable resource for researchers when selecting antibodies for specific applications, although certain limitations should be considered. The data accumulated thus far has illuminated the extent of the problem when poorly performing antibodies are employed in research. While the scientific community was already aware that this was likely a widespread issue, the establishment of a collaborative open science project with industry partners introduces an innovative solution that holds the potential to yield significant returns on investment in the public interest. This potential is substantiated by the number of antibodies that have either been withdrawn or had their recommended usage altered by the vendor. However, despite the discovery of high-performing renewable antibodies for most of the studied proteins, this accounts for a tiny fraction of the human proteome and the commercial antibody market. To realise the full potential of this work, end-users must adjust their antibody procurement and usage practises in line with the provided data. This editorial offers a guide on how individual scientists can utilise the YCharOS data, in addition to sharing the insights gained from the data thus far with the wider scientific community.

Open Science Standards at Journals that Inform Evidence-Based Policy

Evidence-based policy uses intervention research to inform consequential decisions about resource allocation. Research findings are often published in peer-reviewed journals. Because detrimental research practices associated with closed science are common, journal articles report more false-positives and exaggerated effect sizes than would be desirable. Journal implementation of standards that promote open science-such as the transparency and openness promotion (TOP) guidelines-could reduce detrimental research practices and improve the trustworthiness of research evidence on intervention effectiveness. We evaluated TOP implementation at 339 peer-reviewed journals that have been used to identify evidence-based interventions for policymaking and programmatic decisions. Each of ten open science standards in TOP was not implemented in most journals' policies (instructions to authors), procedures (manuscript submission systems), or practices (published articles). Journals implementing at least one standard typically encouraged, but did not require, an open science practice. We discuss why and how journals could improve implementation of open science standards to safeguard evidence-based policy.

Transparency in Artificial Intelligence Research: a Systematic Review of Availability Items Related to Open Science in Radiology and Nuclear Medicine

RATIONALE AND OBJECTIVES

Reproducibility of artificial intelligence (AI) research has become a growing concern. One of the fundamental reasons is the lack of transparency in data, code, and model. In this work, we aimed to systematically review the radiology and nuclear medicine papers on AI in terms of transparency and open science.

MATERIALS AND METHODS

A systematic literature search was performed in PubMed to identify original research studies on AI. The search was restricted to studies published in Q1 and Q2 journals that are also indexed on the Web of Science. A random sampling of the literature was performed. Besides six baseline study characteristics, a total of five availability items were evaluated. Two groups of independent readers including eight readers participated in the study. Inter-rater agreement was analyzed. Disagreements were resolved with consensus.

RESULTS

Following eligibility criteria, we included a final set of 194 papers. The raw data was available in about one-fifth of the papers (34/194; 18%). However, the authors made their private data available only in one paper (1/161; 1%). About one-tenth of the papers made their pre-modeling (25/194; 13%), modeling (28/194; 14%), or post-modeling files (15/194; 8%) available. Most of the papers (189/194; 97%) did not attempt to create a ready-to-use system for real-world usage. Data origin, use of deep learning, and external validation had statistically significantly different distributions. The use of private data alone was negatively associated with the availability of at least one item (p<0.001).

CONCLUSION

Overall rates of availability for items were poor, leaving room for substantial improvement.

Optimizing network neuroscience computation of individual differences in human spontaneous brain activity for test-retest reliability

A rapidly emerging application of network neuroscience in neuroimaging studies has provided useful tools to understand individual differences in intrinsic brain function by mapping spontaneous brain activity, namely intrinsic functional network neuroscience (ifNN). However, the variability of methodologies applied across the ifNN studies-with respect to node definition, edge construction, and graph measurements-makes it difficult to directly compare findings and also challenging for end users to select the optimal strategies for mapping individual differences in brain networks. Here, we aim to provide a benchmark for best ifNN practices by systematically comparing the measurement reliability of individual differences under different ifNN analytical strategies using the test-retest design of the Human Connectome Project. The results uncovered four essential principles to guide ifNN studies: (1) use a whole brain parcellation to define network nodes, including subcortical and cerebellar regions; (2) construct functional networks using spontaneous brain activity in multiple slow bands; and (3) optimize topological economy of networks at individual level; and (4) characterize information flow with specific metrics of integration and segregation. We built an interactive online resource of reliability assessments for future ifNN (https://ibraindata.com/research/ifNN).

Exploring the use of preprints in dentistry

OBJECTIVE

This study aims to assess the use, impact, and dissemination of preprints in dentistry.

METHODS

This is a meta-research study with a cross-sectional design. We included preprints published in dentistry, regardless of the year of publication. Searches were performed in the medRxiv.org and Preprints.org platforms and restricted to English. One researcher extracted the data, and another researcher verified data consistency. The following data were extracted: year of publication, country of the corresponding author, number of abstract and full-text views and downloads, Altmetric attention score, whether the preprint was mentioned in other servers such as Twitter and Publons, number of mentions in other servers, number of citations in the Dimensions database, and whether the preprint had already been published in a peer-reviewed journal. If already published, we extracted the journal's impact factor (JCR 2021) and the number of citations in the Dimensions database. We conducted a descriptive analysis of the extracted characteristics and explored relationships between metrics using the Spearman correlation.

RESULTS

We identified 276 preprints. Most of the studies were published between 2020 and 2022 (n = 229), especially those from ten countries. The most-cited preprint and published article are the same study. Only the correlation between the number of preprint citations and peer-reviewed article citations in the Dimensions database showed a large positive association (Spearman's rho = 0.5809).

CONCLUSION

Preprints gained popularity over the last several years due to the COVID-19 pandemic and reached a larger audience, especially on platforms such as Twitter.

CLINICAL SIGNIFICANCE

Preprint publishing allows faster dissemination of science for the benefit of society.

Open hardware in microscopy

The field of microscopy has been empowering humankind for many centuries by enabling the observation of objects that are otherwise too small to detect for the naked human eye. Microscopy techniques can be loosely divided into three main branches, namely photon-based optical microscopy, electron microscopy, and scanning probe microscopy with optical microscopy being the most prominent one. On the high-end level, optical microscopy nowadays enables nanometer resolution covering many scientific disciplines ranging from material sciences over the natural sciences and life sciences to the food sciences. On the lower-end level, simplified hardware and openly available description and blueprints have helped to make powerful microscopes widely available to interested scientists and researchers. For this special issue, we invited contributions from the community to share their latest ideas, designs, and research results on open-source hardware in microscopy. With this collection of articles, we hope to inspire the community to further increase the accessibility, interoperability, and reproducibility of microscopy. We further touch on the standardization of methodologies and devices including the use of computerized control of data acquisition and data analysis to achieve high quality and efficiency in research and development.

Is shape in the eye of the beholder? Assessing landmarking error in geometric morphometric analyses on live fish

Geometric morphometrics is widely used to quantify morphological variation between biological specimens, but the fundamental influence of operator bias on data reproducibility is rarely considered, particularly in studies using photographs of live animals taken under field conditions. We examined this using four independent operators that applied an identical landmarking scheme to replicate photographs of 291 live Atlantic salmon (Salmo salar L.) from two rivers. Using repeated measures tests, we found significant inter-operator differences in mean body shape, suggesting that the operators introduced a systematic error despite following the same landmarking scheme. No significant differences were detected when the landmarking process was repeated by the same operator on a random subset of photographs. Importantly, in spite of significant operator bias, small but statistically significant morphological differences between fish from the two rivers were found consistently by all operators. Pairwise tests of angles of vectors of shape change showed that these between-river differences in body shape were analogous across operator datasets, suggesting a general reproducibility of findings obtained by geometric morphometric studies. In contrast, merging landmark data when fish from each river are digitised by different operators had a significant impact on downstream analyses, highlighting an intrinsic risk of bias. Overall, we show that, even when significant inter-operator error is introduced during digitisation, following an identical landmarking scheme can identify morphological differences between populations. This study indicates that operators digitising at least a sub-set of all data groups of interest may be an effective way of mitigating inter-operator error and potentially enabling data sharing.

Reproducibility in Neuroimaging Analysis: Challenges and Solutions

Recent years have marked a renaissance in efforts to increase research reproducibility in psychology, neuroscience, and related fields. Reproducibility is the cornerstone of a solid foundation of fundamental research-one that will support new theories built on valid findings and technological innovation that works. The increased focus on reproducibility has made the barriers to it increasingly apparent, along with the development of new tools and practices to overcome these barriers. Here, we review challenges, solutions, and emerging best practices with a particular emphasis on neuroimaging studies. We distinguish 3 main types of reproducibility, discussing each in turn. Analytical reproducibility is the ability to reproduce findings using the same data and methods. Replicability is the ability to find an effect in new datasets, using the same or similar methods. Finally, robustness to analytical variability refers to the ability to identify a finding consistently across variation in methods. The incorporation of these tools and practices will result in more reproducible, replicable, and robust psychological and brain research and a stronger scientific foundation across fields of inquiry.

Next steps after airing disagreement on a scientific issue with policy implications: a meta-analysis, multi-lab replication and adversarial collaboration

Canadian policymakers are interested in determining whether farmed Atlantic salmon, frequently infected with Piscine orthoreovirus (PRV), may threaten wild salmon populations in the Pacific Northwest. A relevant work has been published in BMC Biology by Polinksi and colleagues, but their conclusion that PRV has a negligible impact on the energy expenditure and respiratory performance of sockeye salmon is disputed by Mordecai and colleagues, whose re-analysis is presented in a correspondence article. So, what is the true effect and what should follow this unresolved dispute? We suggest a 'registered multi-lab replication with adversaries'.

Biomedical supervisors' role modeling of open science practices

Supervision is one important way to socialize Ph.D. candidates into open and responsible research. We hypothesized that one should be more likely to identify open science practices (here publishing open access and sharing data) in empirical publications that were part of a Ph.D. thesis when the Ph.D. candidates' supervisors engaged in these practices compared to those whose supervisors did not or less often did. Departing from thesis repositories at four Dutch University Medical centers, we included 211 pairs of supervisors and Ph.D. candidates, resulting in a sample of 2062 publications. We determined open access status using UnpaywallR and Open Data using Oddpub, where we also manually screened publications with potential open data statements. Eighty-three percent of our sample was published openly, and 9% had open data statements. Having a supervisor who published open access more often than the national average was associated with an odds of 1.99 to publish open access. However, this effect became nonsignificant when correcting for institutions. Having a supervisor who shared data was associated with 2.22 (CI:1.19-4.12) times the odds to share data compared to having a supervisor that did not. This odds ratio increased to 4.6 (CI:1.86-11.35) after removing false positives. The prevalence of open data in our sample was comparable to international studies; open access rates were higher. Whilst Ph.D. candidates spearhead initiatives to promote open science, this study adds value by investigating the role of supervisors in promoting open science.

A construction and empirical research of the journal disruption index based on open citation data

For many years, the journal evaluation system has been centered on impact indicators, resulting in evaluation results that do not reflect the academic innovation of journals. To solve this issue, this study attempts to construct the Journal Disruption Index (JDI) from the perspective of measuring the disruption of each journal article. In the actual study, we measured the disruption of articles of 22 selected virology journals based on the OpenCitations Index of Crossref open DOI-to-DOI citations (COCI) first. Then we calculated the JDI of 22 virology journals based on the absolute disruption index (D Z ) of the articles. Finally, we conducted an empirical study on the differences and correlations between the impact indicators and disruption indicators as well as the evaluation effect of the disruption index. The results of the study show: (1) There are large differences in the ranking of journals based on disruption indicators and impact indicators. Among the 22 journals, 12 are ranked higher by JDI than Cumulative Impact Factor for 5 years (CIF5), the Journal Index for PR6 (JIPR6) and average Percentile in Subject Area (aPSA). The ranking difference of 17 journals between the two kinds of indicators is greater than or equal to 5. (2) There is a medium correlation between disruption indicators and impact indicators at the level of journals and papers. JDI is moderately correlated with CIF5, JIPR6 and aPSA, with correlation coefficients of 0.486, 0.471 and - 0.448, respectively. D Z was also moderately correlated with Cumulative Citation (CC), Percentile Ranking with 6 Classifications (PR6) and Percentile in Subject Area (PSA) with correlation coefficients of 0.593, 0.575 and - 0.593, respectively. (3) Compared with traditional impact indicators, the results of journal disruption evaluation are more consistent with the evaluation results of experts' peer review. JDI reflects the innovation level of journals to a certain extent, which is helpful to promote the evaluation of innovation in sci-tech journals.

Iranian researchers' perspective about concept and effect of open science on research publication

BACKGROUND

Sharing research outputs with open science methods for different stakeholders causes better access to different studies to solve problems in diverse fields, which leads to equal access conditions to research resources, as well as greater scientific productivity. Therefore, the aim of this study was to perceive the concept of openness in research among Iranian health researchers.

METHODS

From the beginning of August to the middle of November 2021, twenty semi-structured interviews were held with Iranian health researchers from different fields using purposeful, snowball, and convenience sampling. The interviews continued until data saturation. Data analysis was performed with thematic analysis using MAXQDA 20. Finally, seven main issues related to open science were identified.

RESULTS

Through analysis of the interviews, 235 primary codes and 173 main codes were extracted in 22 subclasses. After careful evaluation and integration of subclasses and classes, they were finally classified into nine categories and three main themes. Analysis showed that openness in research was related to three main themes: researchers' understanding of open science, the impact of open science on publication and sharing of research, concerns and reluctance to open research.

CONCLUSION

The conditions of access to research output should be specified given the diversity of studies conducted in the field of health; issues like privacy as an important topic of access to data and information in the health system should also be specified. Our analysis indicated that the conditions of publication and sharing of research processes should be stated according to different scopes of health fields. The concept of open science was related to access to findings and other research items regardless of cost, political, social, or racial barriers, which could create collective wisdom in the development of knowledge. The process of publication and sharing of research related to open access applies to all types of outputs, conditions of access, increasing trust in research, creation of diverse publication paths, and broader participation of citizens in research. Open science practices should be promoted to increase the circulation and exploitation rates of knowledge while adjusting and respecting the limits of privacy, intellectual property and national security rights of countries.

Assessing the publishing priorities and preferences among STEM researchers at a large R1 institution

The cost of academic publishing has increased substantially despite the ease with which information can be shared on the web. Open Access publishing is a key mechanism for amplifying research access, inclusivity, and impact. Despite this, shifting to a free-to-read publishing environment requires navigating complex barriers that vary by career status and publishing expectations. In this article, we investigate the motivations and preferences of researchers situated within our large research institution as a case study for publishing attitudes at similar institutions. We surveyed the publishing priorities and preferences of researchers at various career stages in STEM fields as they relate to openness, data practices, and assessment of research impact. Our results indicate that publishing preferences, data management experience and research impact assessment vary by career status and departmental approaches to promotion. We find that open access publishing is widely appreciated regardless of career status, but financial limitations and publishing expectations were common barriers to publishing in Open Access journals. Our findings shed light on publishing attitudes and preferences among researchers at a major R1 research institution, and offer insight into advocacy strategies that incentivize open access publishing.