Search

Background: Evaluating moral principles in the Society of Medical Sciences and health care workers (HCWs) is imperative due to their direct contact with the community and the significant impact of their attitudes and decisions on people's lives. This study aimed to determine the components related to ethical decisions in medical sciences students. Methods: One thousand two hundred thirty-five eligible students in the Alborz University of Medical Sciences participated in this descriptive study. We gathered their socio-demographic information, assessed their moral reasoning, and used the ethical decisions questionnaire, Lutsen moral sensitivity questionnaire, and general health questionnaire (GHQ) for data gathering. The data were analyzed with SPSS software version 25 and LISREL version 8.8. Results: According to the path analysis test findings, ethical reasoning significantly correlated with ethical decision-making (B = 0.40). The number of clinical courses passed, moral sensation (moral sensitivity), and the total number of passed academic semesters had the greatest positive and negative association with ethical decision-making, respectively. (B = 0.54), (B = 0.524) and (B = -0.11). Conclusion: Based on the findings of the moral reasoning test, the moral sensation was associated with ethical decision-making, which indicates the necessity of attending to ethical aspects, promoting moral reasoning, sensitivity, and students' accuracy. [ABSTRACT FROM AUTHOR]

Objective: The unprecedented events of 2020 required a pivot in scientific training to better prepare the biomedical research workforce to address global pandemics, structural racism, and social inequities that devastate human health individually and erode it collectively. Furthermore, this pivot had to be accomplished in the virtual environment given the nation-wide lockdown. Methods: These needs and context led to leveraging of the San Francisco Building Infrastructure Leading to Diversity (SF BUILD) theories of change to innovate a Virtual BUILD Research Collaboratory (VBRC). The purpose of VBRC was to train Black, Indigenous, and people of color (BIPOC) students to apply their unique perspectives to biomedical research. These training activities were evaluated using a pre-post survey design that included both validated and new psychosocial scales. A new scale was piloted to measure culturally relevant pedagogy. Results: VBRC scholars increased science identity on two items: thinking of myself as a scientist (+1point, p = 0.006) and belonging to a community of scientists (+1point, p = 0.069). Overall, scholars perceived stress also decreased over VBRC (-2.35 points, p = 0.02). Post VBRC, scholars had high agency scores (μ = 11.02, Md = 12, range = 6–12, σ = 1.62) and cultural humility scores (μ = 22.11, Md = 23, range = 12–24, σ = 2.71). No notable race/ethnic differences were found in any measures. Conclusions: Taken together, our innovative approach to data science training for BIPOC in unprecedented times shows promise for better preparing the workforce critically needed to address the fundamental gaps in knowledge at the intersection of public health, structural racism, and biomedical sciences. [ABSTRACT FROM AUTHOR]

High rates of irreproducibility and of poor mental health in graduate students have been reported in the biomedical sciences in the past ten years, but to date, little research has investigated whether these two trends interact. In this study, we ask whether the experience of failing to replicate an expected finding impacts graduate students' mental health. Using an online survey paired with semi-structured qualitative interviews, we examined how often biomedical science doctoral students at a large American public university experienced events that could be interpreted as failures to replicate and how they responded to these experiences. We found that almost all participants had experience with irreproducibility: 84% had failed to replicate their own results, 70% had failed to replicate a colleague's finding, and 58% had failed to replicate a result from the published literature. Participants reported feelings of self-doubt, frustration, and depression while experiencing irreproducibility, and in 24% of cases, these emotional responses were strong enough to interfere with participants' eating, sleeping, or ability to work. A majority (82%) of participants initially believed that the anomalous results could be attributed to their own error. However, after further experimentation, most participants concluded that the original result was wrong (38%), that there was a key difference between the original experiment and their own (17%), or that there was a problem with the protocol (17%). These results suggest that biomedical science graduate students may be biased towards initially interpreting failures to replicate as indicative of a lack of skill, which may trigger or perpetuate feelings of anxiety, depression, or impostorism. [ABSTRACT FROM AUTHOR]

Gul and Mohsin 2021 developed a new modified form of renowned "Half logistic" distribution introduced by Balakrishnan (1991) and named it half logistic-truncated exponential distribution (HL-TEXPD). Some mathematical characteristics are studied, including hazard function, Pth percentile, moment generating function and Shannon entropy. Simulation study is performed to examine the behaviour of parameter estimates. The proposed model is fitted on three real data sets to check its efficacy. Additionally, TTT (total time on test) plot is drawn to study the failure rate of the three data sets. The results verdict that HL-TEXPD can be efficiently utilized in the field of engineering and medical sciences based on the data sets under study contrary to the classical and baseline models. [ABSTRACT FROM AUTHOR]

Background and aims: Healthcare staff are at high risk of occupational exposure to Hepatitis B and other blood-borne diseases. Lack of education about the knowledge of Hepatitis B virus contributes to an increase in cases. This study aims to determine the knowledge of the Hepatitis B virus among the medical professionals in Duhok province, Kurdistan Region of Iraq, and to determine their knowledge of the importance of vaccination. Materials and methods: This cross-sectional study was conducted in Duhok province, Kurdistan Region of Iraq, among medical science students from November 2022 to February 2023 and a total of 511 students participated in the study. A Self-administered questionnaire comprising 22 items categorized into five sections was distributed to the students either electronically or by paper and pen method. The survey utilized a Five-point Likert scale when assessing respondents' opinions on knowledge, attitude, and practice (KAP). Microsoft Excel and GraphPad Prism 9 were used for statistical analysis. Results: A total of 511 responses were collected from medical, dental, pharmacy, and laboratory students. The average age of the participants was 20.74 ±1.43 years. Among the respondents, only 96 (18.8%) were fully vaccinated against the Hepatitis B virus (received 3 or more doses of the vaccine), while 294 (57.5%) were not vaccinated. Lack of vaccination programs was the major reason for not receiving a vaccination (n = 182, 62%). About 286 (55.96%) of the participants had good knowledge, attitude, and practice on Hepatitis B, manifesting median scores of 26, 18, and 20, respectively. Conclusion: In our study, half of the students were found to be unvaccinated, mainly due to the absence of vaccination programs. Vaccinated students exhibited better knowledge, attitude, and practice toward the infection than non-vaccinated students. Therefore, we recommend the implementation of a vaccination program as well as training on infection prevention guidelines to increase awareness and encourage vaccination. [ABSTRACT FROM AUTHOR]

We present a simple, spreadsheet-based method to determine the statistical significance of the difference between any two arbitrary curves. This modified Chi-squared method addresses two scenarios: A single measurement at each point with known standard deviation, or multiple measurements at each point averaged to produce a mean and standard error. The method includes an essential correction for the deviation from normality in measurements with small sample size, which are typical in biomedical sciences. Statistical significance is determined without regard to the functionality of the curves, or the signs of the differences. Numerical simulations are used to validate the procedure. Example experimental data are used to demonstrate its application. An Excel spreadsheet is provided for performing the calculations for either scenario. [ABSTRACT FROM AUTHOR]

Computer-aided classification of diseases of the gastrointestinal tract (GIT) has become a crucial area of research. Medical science and artificial intelligence have helped medical experts find GIT diseases through endoscopic procedures. Wired endoscopy is a controlled procedure that helps the medical expert in disease diagnosis. Manual screening of the endoscopic frames is a challenging and time taking task for medical experts that also increases the missed rate of the GIT disease. An early diagnosis of GIT disease can save human beings from fatal diseases. An automatic deep feature learning-based system is proposed for GIT disease classification. The adaptive gamma correction and weighting distribution (AGCWD) preprocessing procedure is the first stage of the proposed work that is used for enhancing the intensity of the frames. The deep features are extracted from the frames by deep learning models including InceptionNetV3 and GITNet. Ant Colony Optimization (ACO) procedure is employed for feature optimization. Optimized features are fused serially. The classification operation is performed by variants of support vector machine (SVM) classifiers, including the Cubic SVM (CSVM), Coarse Gaussian SVM (CGSVM), Quadratic SVM (QSVM), and Linear SVM (LSVM) classifiers. The intended model is assessed on two challenging datasets including KVASIR and NERTHUS that consist of eight and four classes respectively. The intended model outperforms as compared with existing methods by achieving an accuracy of 99.32% over the KVASIR dataset and 99.89% accuracy using the NERTHUS dataset. [ABSTRACT FROM AUTHOR]

Academic output of students is considered as a crucial element and it is affected by various aspects. Teacher-class relationship, emotional intelligence and generic competence are the elements which can have a considerable effect on the academic output of the students. Current study was intended to find out the moderating role of teacher-class relationship, emotional intelligence in the academic output and generic competence of higher education students. All the teachers and students of University of Sargodha were the population of the study. The sample was taken from four departments of different faculties of University of Sargodha i.e., Faculty of Agriculture, Faculty of Medical and Health Sciences, Faculty of Arts and Humanities and Faculty of Social Sciences. For this study, a sample of 21 teachers and 320 students from regular and self-support programs was selected conveniently from University of Sargodha. For data collection, three adapted instruments were used. Findings of current study concluded an insignificant moderating role of teacher-class relationship and emotional intelligence in the academic output and generic competence of students at higher education. The results of present study provide guideline to curriculum developers for developing the generic competence of students so that they can progress in future prospects which will eventually make contribution towards economy, moreover, stakeholder may take steps in order to develop the emotional intelligence of students by providing them needful counseling and trainings which will improve the academic output of students. [ABSTRACT FROM AUTHOR]

The recent replicability crisis in social and biomedical sciences has highlighted the need for improvement in the honest transmission of scientific content. We present the results of two studies investigating whether nudges and soft social incentives enhance participants' readiness to transmit high-quality scientific news. In two online randomized experiments (Total N = 2425), participants had to imagine that they were science journalists who had to select scientific studies to report in their next article. They had to choose between studies reporting opposite results (for instance, confirming versus not confirming the effect of a treatment) and varying in traditional signs of research credibility (large versus small sample sizes, randomized versus non-randomized designs). In order to steer participants' choices towards or against the trustworthy transmission of science, we used several soft framing nudges and social incentives. Overall, we find that, although participants show a strong preference for studies using high-sample sizes and randomized design, they are biased towards positive results, and express a preference for results in line with previous intuitions (evincing confirmation bias). Our soft framing nudges and social incentives did not help to counteract these biases. On the contrary, the social incentives against honest transmission of scientific content mildly exacerbated the expression of these biases. [ABSTRACT FROM AUTHOR]

Diversity enriches the educational experience by improving intellectual engagement, self-motivation, citizenship, cultural engagement, and academic skills like critical thinking, problem-solving, and writing for students of all races. Faculty role models from similar backgrounds are essential for students from traditionally underrepresented groups as it sends a powerful message of support, belonging, and the confidence to pursue higher education. However, in the biomedical sciences, the percentage of historically underrepresented tenure-track faculty is far lower than that of their white colleagues. For this to change, a strong strategic plan and commitment from the university are imperative. This scoping review will assess the size and scope of available peer-reviewed research literature on diversity programs that aim to increase the recruitment and retention of biomedical sciences research faculty and are implemented and evaluated at American Universities. The information provided in this scoping review will help universities identify novel, successful diversity-based approaches for recruiting and retaining biomedical science faculty that might suit their own unique academic and geographic needs and be incorporated into their diversity initiatives and policies. The review follows the Population-Concept-Context methodology for Joanna Briggs Institution Scoping Reviews. Relevant peer-reviewed studies published in English between June 1, 2012, to June 1, 2022, will be identified from the following electronic databases; MEDLINE (PubMed), Scopus (Elsevier), EMBASE (Elsevier), CINAHL (EBSCO), and ERIC (EBSCO). The search strings using the key variables "biomedical research faculty," "recruitment/retention," "diversity/ minority/ underrepresented, and "mentoring" will be conducted using Boolean logic. Two independent reviewers will conduct all title and abstract screening, followed by a full article screening and data extraction. Due to the possible heterogeneity of the studies, we hope to use either a narrative analysis and/or descriptive figures/tables to depict the results. [ABSTRACT FROM AUTHOR]

Women are under-represented among authors of scientific papers. Although the number of retractions has been rising over the past few decades, gender differences among authors of retracted papers remain poorly understood. Therefore, this study investigated gender differences in authorship of retracted papers in biomedical sciences available on RetractionWatch. Among 35,635 biomedical articles retracted between 1970 and 2022, including 20,849 first authors and 20,413 last authors, women accounted for 27.4% [26.8 to 28.0] of first authors and 23.5% [22.9 to 24.1] of last authors. The lowest representation of women was found for fraud (18.9% [17.1 to 20.9] for first authors and 13.5% [11.9 to 15.1] for last authors) and misconduct (19.5% [17.3 to 21.9] for first authors and 17.8% [15.7 to 20.3] for last authors). Women's representation was the highest for issues related to editors and publishers (35.1% [32.2 to 38.0] for first authors and 24.8% [22.9 to 26.8] for last authors) and errors (29.5% [28.0 to 31.0] for first authors and 22.1% [20.7 to 23.4] for last authors). Most retractions (60.9%) had men as first and last authors. Gender equality could improve research integrity in biomedical sciences. [ABSTRACT FROM AUTHOR]

Substantial guidance is available on undergraduate quantitative training for biologists, including reports focused on biomedical science. Far less attention has been paid to the graduate curriculum and the particular challenges of the diversity of specialization within the life sciences. We propose an innovative approach to quantitative education that goes beyond recommendations of a course or set of courses or activities, derived from analysis of the expectations for students in particular programs. Due to the plethora of quantitative methods, it is infeasible to expect that biomedical PhD students can be exposed to more than a minority of the quantitative concepts and techniques employed in modern biology. We collected key recent papers suggested by the faculty in biomedical science programs, chosen to include important scientific contributions that the faculty consider appropriate for all students in the program to be able to read with confidence. The quantitative concepts and methods inherent in these papers were then analyzed and categorized to provide a rational basis for prioritization of those concepts to be emphasized in the education program. This novel approach to prioritization of quantitative skills and concepts provides an effective method to drive curricular focus based upon program-specific faculty input for science programs of all types. The results of our particular application to biomedical science training highlight the disconnect between typical undergraduate quantitative education for life science students, focused on continuous mathematics, and the concepts and skills in graphics, statistics, and discrete mathematics that arise from priorities established by biomedical science faculty. There was little reference in the key recent papers chosen by faculty to classic mathematical areas such as calculus which make up a large component of the formal undergraduate mathematics training of graduate students in biomedical areas. [ABSTRACT FROM AUTHOR]

This article, titled "Retraction: Overexpression of SATB1 Is Associated with Biologic Behavior in Human Renal Cell Carcinoma," was retracted due to concerns about image reuse. The retraction was based on similarities found in several panels of Figure 4, as well as partial overlaps between the Figure 4C Migration Control vector and Invasion Control vector panels. The first author claimed to be unaware of these duplications and provided image files, but the concerns were not resolved. The article was retracted by the PLOS ONE Editors due to the image concerns, which cast doubt on the reliability of the reported results. The authors did not respond to the retraction decision or could not be reached. [Extracted from the article]

Licenses of drug-related biotechnologies from academic institutions to commercial firms are intended to promote practical applications of public sector research and a return on government investments in biomedical science. This empirical study compares the economic terms of 239 biotechnology licenses from academic institutions to biotechnology companies with 916 comparable licenses between commercial firms. Academic licenses had lower effective royalty rates (median 3% versus 8%, p<0.001), deal size (median $0.9M versus $31.0M, p<0.001), and precommercial payments (median $1.1M versus $25.4M, p<0.001) than corporate licenses. Controlling for the clinical phase of the most advanced product included in the license reduced the median difference in effective royalty rate between academic and corporate licenses from 5% (95% CI 4.3–5.7) to 3% (95% C.I. 2.4–3.6) but did not change the difference in deal size or precommercial payments. Excluding licenses for co-commercialization did not change the effective royalty rate but reduced the median difference in deal size from $15.8M (95% CI 14.9–16.6) to $11.4M (95% CI 10.4–12.3) and precommercial payments from $9.0M (95% CI 8.0–10.0) to $7.6M (95% CI 6.8–8.4). Controlling for deal terms including exclusivity, equity, or R&D in multivariable regression had no substantive effect on the difference in economic terms. This analysis suggests the economic returns associated with biotechnology licenses from academic institutions are systematically lower than licenses between commercial firms and that this difference is only partially accounted for by differences in the intrinsic terms of the license agreements. These results are discussed in the context of a reasonable royalty rate, recognizing that factors extrinsic to the license agreement may reasonably impact the negotiated value of the license, as well as economic theories that view government as an early investor in innovation and technology licenses as a mechanism for achieving a return on investment. [ABSTRACT FROM AUTHOR]

Objectives: In order to generate independent performance data regarding accuracy of COVID-19 antigen-based rapid diagnostic tests (Ag-RDTs), prospective diagnostic evaluation studies across multiple sites are required to evaluate their performance in different clinical settings. This report describes the clinical evaluation the GENEDIA W COVID-19 Ag Device (Green Cross Medical Science Corp., Chungbuk, Korea) and the ActiveXpress+ COVID-19 Complete Testing Kit (Edinburgh Genetics Ltd, UK), in two testing sites Peru and the United Kingdom. Methods: Nasopharyngeal swabs collected from 456 symptomatic patients at primary points of care in Lima, Peru and 610 symptomatic participants at a COVID-19 Drive-Through testing site in Liverpool, England were analyzed by Ag-RDT and compared to RT-PCR. Analytical evaluation of both Ag-RDTs was assessed using serial dilutions of direct culture supernatant of a clinical SARS-CoV-2 isolate from the B.1.1.7 lineage. Results: For GENEDIA brand, the values of overall sensitivity and specificity were 60.4% [95% CI 52.4–67.9%], and 99.2% [95% CI 97.6–99.7%] respectively; and for Active Xpress+ the overall values of sensitivity and specificity were 66.2% [95% CI 54.0–76.5%], and 99.6% [95% CI 97.9–99.9%] respectively. The analytical limit of detection was determined at 5.0 x 102 pfu/ml what equals to approximately 1.0 x 104 gcn/ml for both Ag-RDTs. The UK cohort had lower median Ct values compared to that of Peru during both evaluations. When split by Ct, both Ag-RDTs had optimum sensitivities at Ct<20 (in Peru; 95% [95% CI 76.4–99.1%] and 100.0% [95% CI 74.1–100.0%] and in the UK; 59.2% [95% CI 44.2–73.0%] and 100.0% [95% CI 15.8–100.0%], for the GENDIA and the ActiveXpress+, respectively). Conclusions: Whilst the overall clinical sensitivity of the Genedia did not meet WHO minimum performance requirements for rapid immunoassays in either cohort, the ActiveXpress+ did so for the small UK cohort. This study illustrates comparative performance of Ag-RDTs across two global settings and considers the different approaches in evaluation methods. [ABSTRACT FROM AUTHOR]

Background: Application of a Clinical Information System (CIS) like Electronic Patient Record (EPR), PACS system and CPOE has turned into one of the most important criteria of priorities of health care systems. The aims of the clinical information system include improving the physicians' efficiency level, integrating the caring process, and expanding the fuzzy quality of the services offered to patients. Achievement of these benefits in reality is not an easy task, and there are lots of plans in this field which are doomed to failure. About 50% of the implementation plans of clinical information systems in health care organizations have failed, and this trend is significantly affecting industrial countries. Proper implementation of hospital information systems lies in identifying and assessing the relationships among the most important risk factors of fuzzy. The present study aimed to provide an applicable model for identifying, ranking and evaluating the risk factors associated with projects of clinical information technology in hospitals of Shiraz University of Medical Sciences. Method: This is an applied study which evaluates the risk factors associated with implementation of clinical information technology projects in hospitals of Shiraz Medical Sciences University. The participants consisted of professionals and senior experts of clinical information technology. Fuzzy logic was used in this study. We also applied ANP-DEMATEL combined model with fuzzy procedure to provide the analytic model of the study Results: According to the study findings, lack of top-executive supports, and unstable organizational environment were the two most important risk factors, while the main organizational factors and technology were also highly important. In addition, the factors associated with technology had the highest influence on the other studied risk factors. Conclusion: Hospital authorities can benefit from this proposed model to reduce the risk of implementing the projects of clinical information technology and improve the success coefficient of the risk of such projects. [ABSTRACT FROM AUTHOR]

How can governments invest in the public good of science in a way that accelerates advancement and encourages innovation at the frontier of science–all the while acknowledging that investing in science means investing in scientists? The Ruth L. Kirschstein National Research Service Award (NRSA) program is a research-training program administered by the National Institutes of Health (NIH) that makes such investments. This study examines the impact of NRSA postdoctoral fellowships on subsequent career outcomes using NIH administrative records on applicants for the fellowship from 1996 to 2008. It finds that fellowships increased the probability of receiving subsequent research awards from 4.0 to 6.3 percentage points and of achieving a major independent research award from 2.6 to 4.6 percentage points. The findings demonstrate that federally funded fellowships promote the retention of scientists in the biomedical research workforce. [ABSTRACT FROM AUTHOR]

Graduate admissions committees throughout the United States examine both quantitative and qualitative data from applicants to make admissions determinations. A number of recent studies have examined the ability of commonly used quantitative metrics such as the GRE and undergraduate GPA to predict the likelihood of applicant success in graduate programs. We examined whether an admissions committee could predict applicant success at The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences based on quantitative metrics. We analyzed the predictive validity of admissions scores, undergraduate GPA, and the GRE for student success. We observed nuanced differences based on gender, ethnicity, race, and citizenship status. The scores assigned to applicants by the admissions committee could not predict time to degree in PhD students regardless of demographic group. Undergraduate GPA was correlated with time to degree in some instances. Interestingly, while GRE scores could predict time to degree, GRE percentile scores could predict both time to degree and PhD candidacy examination results. These findings suggest that there is a level of nuance that is required for interpretation of these quantitative metrics by admissions committees. [ABSTRACT FROM AUTHOR]

Postgraduate trainees elevate the academic strength of institutions by conducting research, promoting innovation, securing grant funding, training undergraduate students, and building alliances. Rigorous and systematic program evaluation can help ensure that postgraduate training programs are achieving the program's intended outcomes. The purpose of this project was to develop evidence-based evaluation tools that could be shared across federally funded biomedical training programs to enhance program evaluation capacity. This manuscript describes the evidence-based process used to determine program evaluation needs of these programs at a research-intensive university. Using a multi-phased sequential exploratory mixed methods approach, data were collected from trainees, employers, leaders, and program directors. Data analyses included document analysis of program plans, inductive coding of focus groups and interviews, and descriptive analysis of surveys. Two overarching categories–Trainee Skills and Program Characteristics—were identified including six themes each. Program directors prioritized communication, social and behavioral skills, and collaboration as the trainee skills that they needed the most help evaluating. Furthermore, program directors prioritized the following program characteristics as those that they needed the most help evaluating: training environment, trainee outcomes, and opportunities offered. Surveys, interview scripts, and related resources for the categories and themes were developed and curated on a publicly available website for program directors to use in their program evaluations. [ABSTRACT FROM AUTHOR]

Automatic operations of multi-functional and time-lapse live-cell imaging are necessary for the biomedical science community to study active, multi-faceted, and long-term biological phenomena. To achieve automatic control, most existing solutions often require the purchase of extra software programs and hardware that rely on the manufacturers' own specifications. However, these software programs are usually non-user-programmable and unaffordable for many laboratories. To address this unmet need, we have developed a novel open-source software program, titled Automatic Multi-functional Integration Program (AMFIP), as a new Java-based and hardware-independent system that provides proven advantages over existing alternatives to the scientific community. Without extra hardware, AMFIP enables the functional synchronization of the μManager software platform, the Nikon NIS-Elements platform, and other 3rd party software to achieve automatic operations of most commercially available microscopy systems, including but not limited to those from Nikon. AMFIP provides a user-friendly and programmable graphical user interface (GUI), opening the door to expanding the customizability for myriad hardware and software systems according to user-specific experimental requirements and environments. To validate the intended purposes of developing AMFIP, we applied it to elucidate the question whether single cells, prior to their full spreading, can sense and respond to a soft solid substrate, and if so, how does the interaction depend on the cell spreading time and the stiffness of the substrate. Using a CRISPR/Cas9-engineered human epithelial Beas2B (B2B) cell line that expresses mNeonGreen2-tagged mechanosensitive Yes-associated protein (YAP), we show that single B2B cells develop distinct substrate-stiffness-dependent YAP expressions within 10 hours at most on the substrate, suggesting that cells are able to sense, distinguish, and respond to mechanical cues prior to the establishment of full cell spreading. In summary, AMFIP provides a reliable, open-source, and cost-free solution that has the validated long-term utility to satisfy the need of automatic imaging operations in the scientific community. [ABSTRACT FROM AUTHOR]

Retractions have been on the rise in the life and clinical sciences in the last decade, likely due to both broader accessibility of published scientific research and increased vigilance on the part of publishers. In this same period, there has been a greater than ten-fold increase in the posting of preprints by researchers in these fields. While this development has significantly accelerated the rate of research dissemination and has benefited early-career researchers eager to show productivity, it has also introduced challenges with respect to provenance tracking, version linking, and, ultimately, back-propagation of events such as corrigenda, expressions of concern, and retractions that occur on the journal-published version. The aim of this study was to understand the extent of this problem among preprint servers that routinely link their preprints to the corollary versions published in journals. To present a snapshot of the current state of downstream retractions of articles preprinted in three large preprint servers (Research Square, bioRxiv, and medRxiv), the DOIs of the journal-published versions linked to preprints were matched to entries in the Retraction Watch database. A total of 30 retractions were identified, representing only 0.01% of all content posted on these servers. Of these, 11 retractions were clearly noted by the preprint servers; however, the existence of a preprint was only acknowledged by the retracting journal in one case. The time from publication to retraction averaged 278 days, notably lower than the average for articles overall (839 days). In 70% of cases, retractions downstream of preprints were due–at least in part–to ethical or procedural misconduct. In 63% of cases, the nature of the retraction suggested that the conclusions were no longer reliable. Over time, the lack of propagation of critical information across the publication life cycle will pose a threat to the scholarly record and to scientific integrity. It is incumbent on preprint servers, publishers, and the systems that connect them to address these issues before their scale becomes untenable. [ABSTRACT FROM AUTHOR]

Immortalized kidney cell lines are widely used in basic and applied research such as cell permeability tests and drug screening. Although many cell lines have been established from kidney tissues, the immortalization process has not been clarified in these cell lines. In this study, we analyzed the phenotypic changes that occurred during the immortalization of kidney cells derived from Chinese hamster tissue in terms of karyotype and gene expression profiles. In the newly established cell line, designated as CHK-Q, gene expression profiles at each stage of the immortalization process and during the adaptation to serum-free conditions were analyzed by DNA microarray. Renal stem cell markers CD24 and CD133 were expressed in CHK-Q cells, suggesting that CHK-Q cells were transformed from renal stem cells. Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis to identify the pathways of upregulated and downregulated genes revealed that the immortalization of CHK-Q cells was associated with increased fluctuations in the expression of specific proto-oncogenes. Karyotype analysis of spontaneously immortalized CHK-Q cells indicated that CHK-Q chromosomes had a typical modal number of 23 but possessed slight chromosomal abnormalities. In this study, we investigated the mechanism of cell environmental adaptation by analyzing gene expression behavior during the immortalization process and serum-free adaptation. CHK-Q cells are applicable to the fields of biotechnology and biomedical science by utilizing their characteristics as kidney-derived cells. [ABSTRACT FROM AUTHOR]

Background: Medical and health science students are among the frontline health care workers who are at high risk of acquiring COVID-19 infection during their clinical attachments and future career. As health care providers, they are expected to promote and administer the COVID-19 vaccine and counsel vaccine-hesitant patients. It is, therefore, imperative to assess COVID-19 vaccine hesitancy among medical and health science students. Thus, this study aimed to assess COVID-19 vaccine hesitancy and its associated factors among medical and health science students of Wolkite University. Method: An institutional-based cross-sectional study design was conducted among 420 medical and health science students attending Wolkite University from March 1 to 30, 2021. Simple random sampling technique was used to select study participants. Self-administered and structured questionnaires were used to collect data. Data were entered into Epi-Data version 4.2.0 and exported to SPSS version 23 software package for further analysis. Bivariable and multivariable analysis was used to identify associated factors. P values <0.05 result were considered as a statistically significant association. Results: The level of COVID-19 vaccine hesitancy was 41.2% (95% CI; 35.2%-50.4%). Student age ≤23 years were 1.9 times more likely vaccine hesitant [aOR = 1.94, 95% CI; 1.14–3.28], being female were 1.7 times more likely vaccine hesitant [aOR = 1.76, 95% CI; 1.14–2.72], resided in rural area were 1.6 times more likely vaccine hesitant [aOR = 1.63, 95% CI; 1.06–2.49], source of information from social media were 2.7 times more likely vaccine hesitant [aOR = 2.68, 95% CI; 1.58–4.54], and good practice to COVID-19 mitigation measures were 47% less likely vaccine hesitant [aOR = 0.53, 95% CI; 0.34–0.83] compared to their counterpart. Conclusions: COVID-19 vaccine hesitancy is found to be high. Therefore, students are advised to receive COVID-19 vaccine information from government lead mass media (i.e. television and radio), increase awareness and adherence to COVID-19 mitigation measures is recommended. [ABSTRACT FROM AUTHOR]

This document is a correction notice for an article titled "The biotoxin BMAA promotes dysfunction via distinct mechanisms in neuroblastoma and glioblastoma cells." The correction addresses errors in the Funding section and provides the correct funding statement. The research was supported by the South Dakota Biomedical Research Infrastructure Network (SD BRIN) through an Institutional Development Award (IDeA) from the National Institute of General Medical Sciences of the National Institutes of Health. The authors state that the funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. [Extracted from the article]

Lymphoblastoid cell lines (LCLs) have been critical to establishing genetic resources for biomedical science. They have been used extensively to study human genetic diversity, genome function, and inform the development of tools and methodologies for augmenting disease genetics research. While the validity of variant callsets from LCLs has been demonstrated for most of the genome, previous work has shown that DNA extracted from LCLs is modified by V(D)J recombination within the immunoglobulin (IG) loci, regions that harbor antibody genes critical to immune system function. However, the impacts of V(D)J on short read sequencing data generated from LCLs has not been extensively investigated. In this study, we used LCL-derived short read sequencing data from the 1000 Genomes Project (n = 2,504) to identify signatures of V(D)J recombination. Our analyses revealed sample-level impacts of V(D)J recombination that varied depending on the degree of inferred monoclonality. We showed that V(D)J associated somatic deletions impacted genotyping accuracy, leading to adulterated population-level estimates of allele frequency and linkage disequilibrium. These findings illuminate limitations of using LCLs and short read data for building genetic resources in the IG loci, with implications for interpreting previous disease association studies in these regions. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the short-term effect on body weight (BW) gain after intravitreal bevacizumab (IVB) for retinopathy of prematurity (ROP). Methods: This was a retrospective 1:1 matched case-control study. Infants with ROP treated by IVB or photocoagulation (PC) at Shiga University of Medical Science Hospital between April 2010 and December 2019 were included in the study. To match BWs at treatment between the IVB and PC groups, 1:1 matching for BWs at treatment within 100 g was performed. The BW gains for the 7 days before treatment (pre-treatment week), the 7 days after treatment (first post-treatment week), and the period from 7 to 14 days after treatment (second post-treatment week) were compared between the IVB and PC groups. Results: Following 1:1 matching, 13 infants in both groups were enrolled in the analysis. The weekly BW gain for the first post-treatment week was significantly lower in the IVB group compared with the PC group (86 g vs. 145 g; P = 0.046), whereas the weekly BW gains for the pre-treatment week (173 g vs. 159 g; P = 0.71) and the second post-treatment week (154 g vs. 152 g; P = 0.73) were comparable between the two groups. The short-term inhibitive effect of IVB on BW gain was particularly observed in infants weighing less than 1500 g at treatment (<1500 g: 47 g vs. ≥1500 g: 132 g; P = 0.03). Conclusion: IVB could have a short-term inhibitive effect on BW gain in infants with ROP, and this effect is more likely to occur in infants with a lower BW at the time of treatment. [ABSTRACT FROM AUTHOR]

The Sign test is a famous nonparametric test from classical statistics used to assess the one or two sample averages. The test is practical when the sample size is small, or the distributional assumption under a parametric test does not satisfy. One of the limitations of the Sign test is the exact form of the data, and the existing methodology of the test does not cover the interval-valued data. The interval-valued data often comes from the fuzzy logic where the experiment's information is not sure and possesses some kind of vagueness, uncertainty or indeterminacy. This research proposed a modified version of the Sign test by considering the indeterminate state and the exact form of the data—the newly proposed sign test methodology is designed for both one-sample and two-sample hypothesis testing problems. The performance of the proposed modified versions of the Sign test is evaluated through two real-life data examples comprised of covid-19 reproduction rate and covid-positive daily occupancy in ICU in Pakistan. The findings of the study suggested that our proposed methodologies are suitable in nonparametric decision-making problems with an interval–valued data. Therefore, applying the new neutrosophic sign test is explicitly recommended in biomedical sciences, engineering, and other statistical fields under an indeterminate environment. [ABSTRACT FROM AUTHOR]

Background: Visual impairment (VI) is a decreased ability to see things which is critical problem for health professionals and students to whom normal vision is essential for their daily activity. If it is not timely managed, visual impairment leads to physical, psychological, and socio-economic malfunctions to the victims and nation. Despite the above impacts, currently there is no study in Ethiopia on this topic. Therefore, this study aimed to determine the prevalence of visual impairment and its associated factors among Medical and Health Science students at the University of Gondar. Methods: A cross-sectional study was conducted from January to March 2020 among Medical and Health Science students. After recruiting study participants using systematic random sampling technique, we applied pre-tested self-administered questionnaire for sociodemographic variables and also visual acuity measurement was performed using Snellen chart placed at a distance of 6 meters. Visual acuity tested separately for each eye and for both eyes in a well- illuminated area. Pinhole was used for those participants with a visual acuity of < 6/9. Participants with a presenting visual acuity of < 6/12 in the better eye were diagnosed as having visual impairment. Epi data version 3.1 and stata version 14 were used for data entry and statistical analysis, respectively. Binary logistic regression was used, and the Adjusted Odds Ratio (AOR) with the 95% Confidence Interval (CI) was reported to declare the statistical significance and strength of association between VI and independent variables. Results: A total of 654 students were screened for visual acuity. The prevalence of visual impairment was 12.5% (95% CI: 10.21, 15.31). Age above 25 years (AOR = 1.8; 95% CI: 1.02, 3.26) and current alcohol drinking (AOR = 2.9; 95% CI: 1.7, 5.00), were statistically significant factors of visual impairment. Conclusion: The prevalence of visual impairment among medical and health science students was high. Age of study participant and current alcohol consumption were statically significant factors. This study warrants the routine screening of Medical and Health science students for visual impairment. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic is the largest viral pandemic of the 21st century. We aimed to study COVID-19 knowledge, attitudes, and practices (KAP) among medical and health sciences students in the United Arab Emirates (UAE). We performed a cross-sectional study between 2 June and 19 August 2020. The survey was distributed online using Survey Monkey. It was conducted in English and comprised two parts: socio-demographic characteristics, and KAP towards COVID-19. 712 responses to the questionnaire were collected. 90% of respondents (n = 695) were undergraduate students, while 10% (n = 81) were postgraduates. The majority (87%, n = 647) stated that they obtained COVID-19 information from multiple reliable sources. They were highly knowledgeable about the COVID-19 pandemic, but 76% (n = 539) did not recognize its routes of transmission. Medical students were significantly more knowledgeable compared with allied health students (P<0.0001, Mann Whitney U test) but there was no difference in knowledge between undergraduate and postgraduate students (P = 0.14, Mann Whitney U test). Medical students thought that more could be done to mitigate the COVID-19 situation compared with the allied health students (66.2% compared with 51.6%, p = 0.002 Fisher's Exact test). 63% (n = 431) were worried about getting COVID-19 infection, while 92% (n = 633)) were worried that a family member could be infected with the virus. 97% (n = 655) took precautions when accepting home deliveries, 94% (n = 637) had been washing their hands more frequently, and 95% (n = 643) had been wearing face masks. In conclusion, medical and health sciences students in the UAE showed high levels of knowledge and good attitudes and practices towards the COVID-19 pandemic. Nevertheless, they were worried about themselves or their family members becoming infected. Medical students had more knowledge about COVID-19 pandemic which was reflected in their opinion that more can be done to mitigate its effects. [ABSTRACT FROM AUTHOR]

Background: Conflicts of interest in biomedical research can influence research results and drive research agendas away from public health priorities. Previous agenda-setting studies share two shortfalls: they only account for direct connections between academic institutions and firms, as well as potential bias based on researchers' personal beliefs. This paper's goal is to determine the key actors and contents of the prevailing health and biomedical sciences (HBMS) research agenda, overcoming these shortfalls. Methods: We performed a bibliometric and lexical analysis of 95,415 scientific articles published between 1999 and 2018 in the highest impact factor journals within HBMS, using the Web of Science database and the CorText platform. HBMS's prevailing knowledge network of institutions was proxied with network maps where nodes represent affiliations and edges the most frequent co-authorships. The content of the prevailing HBMS research agenda was depicted through network maps of prevalent multi-terms found in titles, keywords, and abstracts. Results: The HBMS research agendas of large private firms and leading academic institutions are intertwined. The prevailing HBMS agenda is mostly based on molecular biology (40% of the most frequent multi-terms), with an inclination towards cancer and cardiovascular research (15 and 8% of the most frequent multi-terms, respectively). Studies on pathogens and biological vectors related to recent epidemics are marginal (1% of the most frequent multi-terms). Content of the prevailing HBMS research agenda prioritizes research on pharmacological intervention over research on socio-environmental factors influencing disease onset or progression and overlooks, among others, the study of infectious diseases. Conclusions: Pharmaceutical corporations contribute to set HBMS's prevailing research agenda, which is mainly focused on a few diseases and research topics. A more balanced research agenda, together with epistemological approaches that consider socio-environmental factors associated with disease spreading, could contribute to being better prepared to prevent and treat more diverse pathologies and to improve overall health outcomes. [ABSTRACT FROM AUTHOR]

The continually expanding distributed global compendium of biomedical knowledge is diffuse, heterogeneous and huge, posing a serious challenge for biomedical researchers in knowledge harvesting: accessing, compiling, integrating and interpreting data, information and knowledge. In order to accelerate research towards effective medical treatments and optimizing health, it is critical that efficient and automated tools for identifying key research concepts and their experimentally discovered interrelationships are developed. As an activity within the feasibility phase of a project called "Translator" (https://ncats.nih.gov/translator) funded by the National Center for Advancing Translational Sciences (NCATS) to develop a biomedical science knowledge management platform, we designed a Representational State Transfer (REST) web services Application Programming Interface (API) specification, which we call a Knowledge Beacon. Knowledge Beacons provide a standardized basic API for the discovery of concepts, their relationships and associated supporting evidence from distributed online repositories of biomedical knowledge. This specification also enforces the annotation of knowledge concepts and statements to the NCATS endorsed the Biolink Model data model and semantic encoding standards (https://biolink.github.io/biolink-model/). Implementation of this API on top of diverse knowledge sources potentially enables their uniform integration behind client software which will facilitate research access and integration of biomedical knowledge. Availability: The API and associated software is open source and currently available for access at https://github.com/NCATS-Tangerine/translator-knowledge-beacon. [ABSTRACT FROM AUTHOR]

The explosion of disinformation accompanying the COVID-19 pandemic has overloaded fact-checkers and media worldwide, and brought a new major challenge to government responses worldwide. Not only is disinformation creating confusion about medical science amongst citizens, but it is also amplifying distrust in policy makers and governments. To help tackle this, we developed computational methods to categorise COVID-19 disinformation. The COVID-19 disinformation categories could be used for a) focusing fact-checking efforts on the most damaging kinds of COVID-19 disinformation; b) guiding policy makers who are trying to deliver effective public health messages and counter effectively COVID-19 disinformation. This paper presents: 1) a corpus containing what is currently the largest available set of manually annotated COVID-19 disinformation categories; 2) a classification-aware neural topic model (CANTM) designed for COVID-19 disinformation category classification and topic discovery; 3) an extensive analysis of COVID-19 disinformation categories with respect to time, volume, false type, media type and origin source. [ABSTRACT FROM AUTHOR]

Background: Despite ~90% of sickle cell disease (SCD) occurring in low-and middle-income countries (LMICs), the vast majority of people are not receiving evidence-based interventions (EBIs) to reduce SCD-related adverse outcomes and mortality, and data on implementation research outcomes (IROs) and SCD is limited. This study aims to synthesize available data on EBIs for SCD and assess IROs. Methods: We conducted a systematic review of RCTs reporting on EBIs for SCD management implemented in LMICs. We identified articles from PubMed/Medline, Global Health, PubMed Central, Embase, Web of Science medical subject heading (MeSH and Emtree) and keywords, published from inception through February 23, 2020, and conducted an updated search through December 24, 2020. We provide intervention characteristics for each study, EBI impact on SCD, and evidence of reporting on IROs. Main results: 29 RCTs were analyzed. EBIs identified included disease modifying agents, supportive care agents/analgesics, anti-malarials, systemic treatments, patient/ provider education, and nutritional supplements. Studies using disease modifying agents, nutritional supplements, and anti-malarials reported improvements in pain crisis, hospitalization, children's growth and reduction in severity and prevalence of malaria. Two studies reported on the sustainability of supplementary arginine, citrulline, and daily chloroquine and hydroxyurea for SCD patients. Only 13 studies (44.8%) provided descriptions that captured at least three of the eight IROs. There was limited reporting of acceptability, feasibility, fidelity, cost and sustainability. Conclusion: EBIs are effective for SCD management in LMICs; however, measurement of IROs is scarce. Future research should focus on penetration of EBIs to inform evidence-based practice and sustainability in the context of LMICs. Clinical trial registration: This review is registered in PROSPERO #CRD42020167289. [ABSTRACT FROM AUTHOR]

Metabolic pathway comparison and interaction between different species can detect important information for drug engineering and medical science. In the literature, proposals for reconstructing and comparing metabolic networks present two main problems: network reconstruction requires usually human intervention to integrate information from different sources and, in metabolic comparison, the size of the networks leads to a challenging computational problem. We propose to automatically reconstruct a metabolic network on the basis of KEGG database information. Our proposal relies on a two-level representation of the huge metabolic network: the first level is graph-based and depicts pathways as nodes and relations between pathways as edges; the second level represents each metabolic pathway in terms of its reactions content. The two-level representation complies with the KEGG database, which decomposes the metabolism of all the different organisms into "reference" pathways in a standardised way. On the basis of this two-level representation, we introduce some similarity measures for both levels. They allow for both a local comparison, pathway by pathway, and a global comparison of the entire metabolism. We developed a tool, MetNet, that implements the proposed methodology. MetNet makes it possible to automatically reconstruct the metabolic network of two organisms selected in KEGG and to compare their two networks both quantitatively and visually. We validate our methodology by presenting some experiments performed with MetNet. [ABSTRACT FROM AUTHOR]

Background: Stroke contributes to a significant proportion of deaths and disability worldwide, with a high fatality rate within 30 days following a first ever stroke. We describe the outcomes within one year among patients who succumbed a first ever stroke and survived the first 30 days. Methods: Participants were patients who survived after 30 days from succumbing a first ever stroke admitted at the Muhimbili University of Health and Allied Sciences Academic Medical Center. Stroke survivors or their next of kin were contacted at one year after succumbing a first stroke to determine the outcomes. We assessed participants' vital status and level of disability using the modified Rankin scale. Assessment on utilization of stroke secondary preventive measures among survivors was done by an interviewer-based questionnaire that assessed the number of times participants attended follow up clinics, medication refill and adherence. Participants were examined for waist-hip ratio, body mass index and blood pressure. Cholesterol levels were assessed at one year post first stroke for survivors. Outcomes were summarized as proportions, survival at one year was estimated by using the Kaplan Meier analysis and Cox regression analysis was performed to determine for predictors of mortality. Results: We recruited 130 first stroke survivors. Mortality within one year was 53/130 (40.8%) and disability rate measured by Modified Rankin Scale with scores of 3–5 was 29/77 (37.7%) among survivors. Factors associated with mortality were residual disability HR = 8.60, {95% CI (1.16–63.96)}, severe stroke, HR = 2.67 {95% CI (1.44–4.95)} and residing in Dar-es-Salaam HR = 2.15 {95% (CI 1.06–4.36)}. Non-adherence rates to antihypertensives, antiplatelets and statins was 11/73 (15.1%), 9/23 (39.1%) and 18/22 (81.8%) respectively. Attendance rates of follow-up clinics among all survivors and physiotherapy among survivors with disability are 45/77 (58.4%) and 16/29 (55.2%) respectively. Conclusions: The mortality and disability rates within a year following a first ever stroke among 30 days stroke survivors is high. Secondary stroke preventive measures should be enhanced to mitigate stroke adverse outcomes. Community outreach programs could be useful interventions in preventing the adverse outcomes of stroke. [ABSTRACT FROM AUTHOR]

The purpose of this study was to identify performance measures of racially underrepresented minority (RUM) Ph.D. trainees who needed additional training initiatives to assist with completing the UAMS biomedical science degree. A sample of 37 trainees in the 10-year NIH-NIGMS funded Initiative for Maximizing Student Development (IMSD) program at the University of Arkansas for Medical Sciences (UAMS) were examined. Descriptive statistics and correlations examined process measures (GRE scores, GPAs, etc.) and outcome measures (time-to-degree, publications, post-doctoral fellowship, etc.) While differences were found, there were no statistically significant differences between how these two groups (Historically Black Colleges and Universities (HBCUs) and Predominately White Institutions (PWIs)) of students performed over time as Ph.D. students. Graduates who scored lower on the verbal section of the GRE also had a higher final graduate school grade point average in graduates who received their undergraduate training from HBCUs. Of the graduates who received their undergraduate training from PWIs, graduates who scored lower on the quantitative section of the GRE had higher numbers of publications. These findings stimulate the need to 1) reduce reliance on the use of the GRE in admission committee decisions, 2) identify psychometrically valid indicators that tailored to assess outcome variables that are relevant to the careers of biomedical scientists, and 3) ensure the effective use of the tools in making admission decisions. [ABSTRACT FROM AUTHOR]

Microscopy is the main technique to visualize and study the structure and function of cells. The impact of optical and electron microscopy techniques is enormous in all fields of biomedical research. It is possible that different research areas rely on microscopy in diverse ways. Here, we analyzed comparatively the use of microscopy in pharmacology and cell biology, among other biomedical sciences fields. We collected data from articles published in several major journals in these fields. We analyzed the frequency of use of different optical and electron microscopy techniques: bright field, phase contrast, differential interference contrast, polarization, conventional fluorescence, confocal, live cell imaging, super resolution, transmission and scanning electron microscopy, and cryoelectron microscopy. Our analysis showed that the use of microscopy has a distinctive pattern in each research area, and that nearly half of the articles from pharmacology journals did not use any microscopy method, compared to the use of microscopy in almost all the articles from cell biology journals. The most frequent microscopy methods in all the journals in all areas were bright field and fluorescence (conventional and confocal). Again, the pattern of use was different: while the most used microscopy methods in pharmacology were bright field and conventional fluorescence, in cell biology the most used methods were conventional and confocal fluorescence, and live cell imaging. We observed that the combination of different microscopy techniques was more frequent in cell biology, with up to 6 methods in the same article. To correlate the use of microscopy with the research theme of each article, we analyzed the proportion of microscopy figures with the use of cell culture. We analyzed comparatively the vocabulary of each biomedical sciences field, by the identification of the most frequent words in the articles. The collection of data described here shows a vast difference in the use of microscopy among different fields of biomedical sciences. The data presented here could be valuable in other scientific and educational contexts. [ABSTRACT FROM AUTHOR]

This correction notice provides additional information and updates to a research article titled "Microbial Gene Ontology informed deep neural network for microbe functionality discovery in human diseases." The last author, Seiya Imoto, should also be listed as an additional corresponding author. The acknowledgments section should include a statement acknowledging the super-computing resource provided by the Human Genome Center, Institute of Medical Science, The University of Tokyo. The funding statement should include support from the Japan Society for the Promotion of Science and the Uehara Memorial Foundation, as well as the provision of computing resources by the Human Genome Center, the Institute of Medical Science, the University of Tokyo. The authors of the article are Yunjie Liu, Yao-zhong Zhang, and Seiya Imoto. [Extracted from the article]

The correct Funding statement is: This work was supported by National Cancer Institute (NCI) grant P30CA016056 involving the use of Roswell Park Comprehensive Cancer Center's Pathology Network, Genomics and Biomedical Data Science Shared Resources. Reference 1 Yan L (2022) Confidence interval estimation of the common mean of several gamma populations. [Extracted from the article]

Background: Artificial and virtual technologies in healthcare have advanced rapidly, and healthcare systems have been adapting care accordingly. An intriguing new development is the virtual physician, which can diagnose and treat patients independently. Methods and findings: This qualitative study of advanced degree students aimed to assess their perceptions of using a virtual primary care physician as a patient. Four focus groups were held: first year medical students, fourth year medical students, first year engineering/data science graduate students, and fourth year engineering/data science graduate students. The focus groups were audiotaped, transcribed verbatim, and content analyses of the transcripts was performed using a data-driven inductive approach. Themes identified concerned advantages, disadvantages, and the future of virtual primary care physicians. Within those main categories, 13 themes emerged and 31 sub-themes. Discussion: While participants appreciated that a virtual primary care physician would be convenient, efficient, and cost-effective, they also expressed concern about data privacy and the potential for misdiagnosis. To garner trust from its potential users, future virtual primary physicians should be programmed with a sufficient amount of trustworthy data and have a high level of transparency and accountability for patients. [ABSTRACT FROM AUTHOR]

Biological and medical sciences are increasingly acknowledging the significance of gene co-expression-networks for investigating complex-systems, phenotypes or diseases. Typically, complex phenotypes are investigated under varying conditions. While approaches for comparing nodes and links in two networks exist, almost no methods for the comparison of multiple networks are available and—to best of our knowledge—no comparative method allows for whole transcriptomic network analysis. However, it is the aim of many studies to compare networks of different conditions, for example, tissues, diseases, treatments, time points, or species. Here we present a method for the systematic comparison of an unlimited number of networks, with unlimited number of transcripts: Co-expression Differential Network Analysis (CoDiNA). In particular, CoDiNA detects links and nodes that are common, specific or different among the networks. We developed a statistical framework to normalize between these different categories of common or changed network links and nodes, resulting in a comprehensive network analysis method, more sophisticated than simply comparing the presence or absence of network nodes. Applying CoDiNA to a neurogenesis study we identified candidate genes involved in neuronal differentiation. We experimentally validated one candidate, demonstrating that its overexpression resulted in a significant disturbance in the underlying gene regulatory network of neurogenesis. Using clinical studies, we compared whole transcriptome co-expression networks from individuals with or without HIV and active tuberculosis (TB) and detected signature genes specific to HIV. Furthermore, analyzing multiple cancer transcription factor (TF) networks, we identified common and distinct features for particular cancer types. These CoDiNA applications demonstrate the successful detection of genes associated with specific phenotypes. Moreover, CoDiNA can also be used for comparing other types of undirected networks, for example, metabolic, protein-protein interaction, ecological and psychometric networks. CoDiNA is publicly available as an R package in CRAN (https://CRAN.R-project.org/package=CoDiNA). [ABSTRACT FROM AUTHOR]

Scientific and/or technical breakthroughs require the exploration of novel ideas and technologies. Yet, it has not been studied quantitatively how national institutional contexts either facilitate or stifle organizational support for exploration. Available qualitative evidence suggests that institutional contexts that exert weak control over universities and research organizations strengthen their capabilities to achieve scientific breakthroughs, while contexts with strong control constrain them. The paper is based on an analysis of the population of Nobel laureates in Physics, Chemistry and Physiology or Medicine. We examine to what extent existing qualitative findings for the biomedical sciences, which are partly based on Nobel laureates in Physiology or Medicine, can be substantiated both quantitatively and across the three Nobel Prize fields of science. We find that for most of the 20th century and the early 21st century, countries with weak institutional control (United Kingdom, United States) have outperformed those exerting strong control (France, Germany). These results are further corroborated when controlled by population sizes and by GDP per capita. In addition, these results hold not only for the biomedical sciences, but also for Physics and Chemistry. Furthermore, countries with weak institutional control have attracted many future Nobel laureates from countries with strong environments. In this regard, the United States appears to be a particularly attractive setting for conducting innovative research, and thus has been a magnet for young and promising scientists. However, future laureates working in institutional environments exerting weak control are not faster in accomplishing their prize-winning work compared to those laureates working in more restrictive institutional settings. [ABSTRACT FROM AUTHOR]

A solid understanding of basic sciences is a prerequisite for successful completion of medical education. Therefore, it is essential to improve the quality of teaching and to ensure the applicability of basic sciences. Based on practical experiences and previous research, we developed an innovative step-by-step concept, called ENHANCE, for the implementation or revision of teaching units, especially for basic sciences. We used comparative self-assessment gains, a questionnaire to assess teaching quality as well as end-of-semester evaluations (students' satisfaction and open-ended questions) to evaluate the ENHANCE concept. It was found that ENHANCE-based teaching units were related to increased students' satisfaction, high attendance rates and that restructuring the course curriculum yielded in a positive assessment of teaching effectiveness. The revised courses were rated as the very best of all classes in several semesters. Qualitative data showed that students particularly appreciated the level of comprehension and how helpful the courses were for the understanding and preparation of the regular curriculum. [ABSTRACT FROM AUTHOR]

Background: In biomedical science and clinical practice, an estimation of the stable frozen zone volume and distribution of concentration fields of injected diagnostic and healing solutions in the tissues of living organisms is of great importance and does not currently have any mathematical solution aimed at its precise evaluation. Objective: The aim of this research is the estimation of the stable frozen zone volume at ultra-low temperatures as well as the distribution of temperature areas and concentration fields of injected diagnostic and healing substances in vitro. The results can improve our understanding of the stable frozen zone volume and the extent of contrast for a therapeutic substance. Materials and methods: A cryogenic zone (ice ball) was generated at -180°C using liquid nitrogen without any difficulties in vitro. The effects of freeze-thaw processes using ultra-low temperature and the cryogenic response of a 1.5% gelatin solution in water (%g/v) kept at a constant temperature of 20°C and continuously stirred were mathematically analyzed. The stable frozen zone volume was illustrated in vitro and measured in terms of its length, depth and cryogenic margin using a standard medical ruler and Vernier caliper after a freezing period at -180°C, using liquid nitrogen to provide cooling and freezing of a small portion of this solution in the vessel at room temperature (20°C). Round-shaped cryoprobes with diameters of 15 mm and 50 mm were applied to create a frozen zone volume in vitro. A single cryoprobe was used per procedure. The sample exposure time was 3 min. After this time, the volume of the frozen region remains unchanged, which indicates that the equilibrium stationary state has been reached. The experimental design, cryogenic procedure and freeze-thaw processes of the hemisphere were described and illustrated in vitro item by item. The statistical analysis manifested significant differences that were found between the 50 mm and 15 mm cryoprobes with regards to the freezing diameter, depth, and cryogenic margin (P < 0.001). Results: An illustrated analytical mathematical solution of equations determined the stable frozen zone volume and the radius of the sphere of the frozen medium in the equilibrium stationary state. The resulting assessment provided the basis for the creation of mini- and micro-cryoprobes as well as cryoneedles for local tissue freezing in living biological structures. A solution to the equations was obtained under the boundary conditions with a set stable temperature value on the boundary surface of the cryoprobe as well as at the surface well-away from it, where the temperature is equal to the stable temperature of the environment. For example, this solution gives that in the case of a hemispherical cryoprobe radius of 1 mm, the frozen zone volume was more than three orders of magnitude greater than the volume of the cryoprobe itself and was equal to approximately 4 cm3. The determination of the fractal dimension can consider the individual characteristics of the spread of the contrast medium or therapeutic substance(s) in living tissue. Based on fractal theory, our innovative mathematical formulas allow for the assessment of the effective distribution of contrast medium in living biological structures, specifically for tissues assessed for diagnostic purposes, and they enable the selection of an optimal treatment strategy in medical practice. Conclusion: A simple mathematical approach to solving the problems of assessing the stable frozen zone volume and distribution of temperature areas and concentration fields of injected diagnostic and healing substances in living biological structures, particularly living tissue in vitro, is presented in this study. The expressed quantitative mathematical formulas determine the stable stationary frozen zone volume and provide the basis for the creation of mini- and micro-cryoprobes. The application of fractal theory is proposed for assessing the distribution efficiency of contrast medium and therapeutic substance(s) in living biological structures for diagnostic purposes and for selecting a compassionate treatment strategy in medical professional practice. [ABSTRACT FROM AUTHOR]

Health advances are contingent on continuous development of new methods and approaches to foster data-driven discovery in the biomedical and clinical sciences. Open-science and team-based scientific discovery offer hope for tackling some of the difficult challenges associated with managing, modeling, and interpreting of large, complex, and multisource data. Translating raw observations into useful information and actionable knowledge depends on effective domain-independent reproducibility, area-specific replicability, data curation, analysis protocols, organization, management and sharing of health-related digital objects. This study expands the functionality and utility of an ensemble semi-supervised machine learning technique called Compressive Big Data Analytics (CBDA). Applied to high-dimensional data, CBDA (1) identifies salient features and key biomarkers enabling reliable and reproducible forecasting of binary, multinomial and continuous outcomes (i.e., feature mining); and (2) suggests the most accurate algorithms/models for predictive analytics of the observed data (i.e., model mining). The method relies on iterative subsampling, combines function optimization and statistical inference, and generates ensemble predictions for observed univariate outcomes. The novelty of this study is highlighted by a new and expanded set of CBDA features including (1) efficiently handling extremely large datasets (>100,000 cases and >1,000 features); (2) generalizing the internal and external validation steps; (3) expanding the set of base-learners for joint ensemble prediction; (4) introducing an automated selection of CBDA specifications; and (5) providing mechanisms to assess CBDA convergence, evaluate the prediction accuracy, and measure result consistency. To ground the mathematical model and the corresponding computational algorithm, CBDA 2.0 validation utilizes synthetic datasets as well as a population-wide census-like study. Specifically, an empirical validation of the CBDA technique is based on a translational health research using a large-scale clinical study (UK Biobank), which includes imaging, cognitive, and clinical assessment data. The UK Biobank archive presents several difficult challenges related to the aggregation, harmonization, modeling, and interrogation of the information. These problems are related to the complex longitudinal structure, variable heterogeneity, feature multicollinearity, incongruency, and missingness, as well as violations of classical parametric assumptions. Our results show the scalability, efficiency, and usability of CBDA to interrogate complex data into structural information leading to derived knowledge and translational action. Applying CBDA 2.0 to the UK Biobank case-study allows predicting various outcomes of interest, e.g., mood disorders and irritability, and suggests new and exciting avenues of evidence-based research in the context of identifying, tracking, and treating mental health and aging-related diseases. Following open-science principles, we share the entire end-to-end protocol, source-code, and results. This facilitates independent validation, result reproducibility, and team-based collaborative discovery. [ABSTRACT FROM AUTHOR]

To examine changes in U.S. medical school basic science faculty over the last 20 years (1998–2018), we undertook an observational study utilizing data from the American Association of Medical Colleges Faculty Roster. Rank (Instructor, Assistant Professor, Associate Professor, and Professor), sex (Female), and race/ethnicity (Asian, Black or African American, Hispanic, Latino, Spanish Origin, or Multiple Race-Hispanic, and White) were analyzed; this reflected a population of 14,047 (1998) to 18,601 (2018) faculty. Summary percent of faculty in various gender, race/ethnicity origin categories were analyzed across years of the study using regression models. We found that females (24.47% to 35.32%) were underrepresented at all timepoints and a minority of faculty identified as Black or African American (1.57% to 1.99%), Hispanic, Latino, Spanish Origin, or Multiple Race-Hispanic (3.03% to 4.44%), or Asian (10.90% to 20.41%). The largest population at all time points was White Male Professors (30.53% to 20.85%), followed by White Male Associate Professors (15.67% to 9.34%), and White Male Assistant Professors (13.22% to 9.75%). Small statistically significant increases were observed among female faculty and faculty at multiple ranks who identified as Black or African American or Hispanic, Latino, Spanish Origin, or Multiple Race-Hispanic. We then completed secondary analyses looking at the interaction of race/ethnicity and Gender. We found: (1) a significant increase (p<0.0001) in both genders who identify as Asian although males had a higher rate of increase (6 point difference, p<0.0001); (2) a significant increase for Black or African American females (P<0.01) not found among males; (3) significant increases (p<0.0001) among both genders of faculty who identify as Hispanic, Latino, Spanish Origin, or Multiple Race-Hispanic although females had an approximately 1% higher rate of increase; and (4) among faculty who identify as White, males had a significant decrease (p<0.0001) while females demonstrated an increase (p<0.0001). [ABSTRACT FROM AUTHOR]

Theory: The perceived value of study material may have implications on learning and long-term retention. This study compares the perceived value of basic science of medical students from schools with a traditional "2+2" curriculum and the USMLE Step 1 placed before core clerkships to those from medical schools that have undergone curricular revisions, resulting in shortened pre-clerkship curricula and administration of the USMLE Step 1 after core clerkships. Hypothesis: We hypothesize that differences in curricula, particularly duration of pre-clerkship curriculum and timing of the USMLE Step 1, affect medical students' perceived value of basic science. Methods: A twenty item anonymous questionnaire using a 5-point Likert scale was developed to assess medical students' perceptions of basic science. The questionnaire was distributed to third-year medical students across four medical schools. Generalized linear models and p-values were calculated comparing the perceived value and use of basic science between medical schools with the USMLE Step 1 before clerkships and 2-years of basic science (BC) and medical schools with the USMLE Step 1 after core clerkships and 1.5-years of basic science (AC). Results: The questionnaire was distributed to 695 eligible students and completed by 287 students. Students at BC schools tended to view basic science as more essential for clinical practice than students at AC schools across both outcomes (rating independence of basic science and clinical practice, AC school mean = 2.97, BC school mean = 2.73, p = 0.0017; rating importance of basic science to clinical practice, AC school mean = 3.30, BC schools mean = 3.50, p = 0.0135). Conclusions: Our study suggests that students who have a longer basic science curriculum tend to value basic science greater than students with a shorter basic science curriculum. The timing of the USMLE Step 1 may also influence this relationship. Curricular decisions, such as reductions in pre-clerkship curricula and administration of the USMLE Step 1 after clerkships, may impact medical students' perceptions of the value of basic science to clinical practice. This can have implications on their future engagement with basic science and should be considered when modifying curriculum. [ABSTRACT FROM AUTHOR]

The number of biomedical sciences PhDs persisting in academic faculty careers has been declining. As one potential influence on trainees' intention to persist, we investigate the development of scientific communication (SC) skills, hypothesizing that attitudes and behaviors regarding scientific writing, speaking, and presenting predict academic research career intention, through science identity. After adapting a social-cognitive career theoretical model of SC to include science identity and mentor practices, we conducted a longitudinal survey of 185 doctoral and postdoctoral fellows. Structural equation modeling was used to examine relationships among SC productivity, SC self-efficacy, SC outcome expectations, mentor practices in SC, science identity, and research career intention. Results confirmed the overall model and revealed additional specific pathways: SC productivity and SC outcome expectations directly predicted career intention; SC productivity and mentor practices predicted science identity through SC self-efficacy. Demographic factors did not predict intention when controlling for SC variables. Findings support a model of SC skill development as a predictor of research career intention (R2 =.32). The finding that SC language use predicts science identity has important sociolinguistic implications. The key factors in this process are actionable at the trainee, mentor, and institutional levels, suggesting potential for SC interventions to increase career persistence. [ABSTRACT FROM AUTHOR]

Globally, many millions of animals are used by humans every year and much of this usage causes public concern. A new scale, devised to measure attitudes to animal use in relation to the purpose of use and species, the Animal Purpose Questionnaire (APQ), was completed by in total 483 participants, 415 British nationals and 68 participants from 39 other countries. The APQ was presented in two survey formats, alongside an established Animal Attitudes Scale (AAS). In both surveys, participants also provided demographic details to provide a context to their attitudes to animals. As might be expected, and consistent with the validity of the new scale, overall scores on the AAS and APQ were highly correlated. However, the APQ provided a more differentiated measure of attitudes to animal use across a variety of settings. The results showed that there was overall higher levels of agreement with the use of animals in medical research and basic science, less endorsement for food production and pest control, and the use of animals for other cultural practices was generally disapproved of, irrespective of species. Participants overall disagreed with the use of rabbits, monkeys, badgers, tree shrews (survey 1), chimpanzees, dogs, dolphins and parrots (survey 2), but were neutral about the use of rats, mice, pigs, octopus, chickens, zebrafish (survey 1), carp, chickens, pigs, pigeons, rabbits and rats (survey 2). Interactions between species and purpose were largely driven by the consideration of using diverse species for food production. In general, females and vegetarians expressed less agreement with the use of animals with some differences by purpose of use. Pet keeping consistently predicted reduced willingness to use animals for basic science (only). The APQ provides a new tool to unpack how public attitudes depend on the intersectionality of demographics, species and purpose of use. [ABSTRACT FROM AUTHOR]

Background: Animal trials contribute to major achievements in medical science. The so-called lavage model is frequently used to evaluate ventilation strategies in acute respiratory distress syndrome (ARDS) using electrical impedance tomography (EIT). But, the lavage model itself might have systematic impacts on EIT parameters. Therefore, we established an additional experimental model, in which ARDS is caused by intravenously administered lipopolysaccharide (LPS). In this study, we want to examine if EIT measurements provide consistent results in both experimental models or whether the pathophysiology of the model influences the findings. Overall, we want to compare both experimental models regarding clinical parameters and EIT-derived indices, namely the global inhomogeneity (GI) index and the regional ventilation delay (RVD) index. Methods: Nineteen pigs were included in this study, allocated to the control group (CO; n = 5), lavage group (LAV; n = 7) and LPS group (LPS; n = 7). After baseline measurements and the establishment of ARDS, assessment of respiratory mechanics, hemodynamics, gas exchange and EIT recordings were performed hourly over eight hours. Results: In both experimental ARDS models, EIT measurements provided reliable results. But, the GI and the RVD index did not show consistent results as compared to the CO group. Initially, GI and RVD index were higher in the LAV group but not in the LPS group as compared to the CO group. This effect disappeared during the study. Furthermore, the GI index and the RVD index were higher in the LAV group compared to the LPS group in the beginning as well. This, once again, disappeared. Clinical lung injury parameters remained more stable when using LPS. Conclusion: The two models showed quite different influences on the GI and RVD index. This implies, that the underlying pathophysiology affects EIT parameters and thus the findings. Hence, translation to EIT-guided clinical therapy in humans suffering from ARDS might be limited. [ABSTRACT FROM AUTHOR]