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The growing significance of social media in research demands new ethical standards and practices. Although a substantial body of literature on social media ethics exists, studies on the ethics of conducting research using social media are scarce. The emergence of new evidence sources, like social media, requires innovative methods and renewed consideration of research ethics. Therefore, we pose the following question: What are the defining characteristics of ethics papers on social media research? Following a modified version of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol, we analyzed 34 publications based on ten variables: author gender, publication year, region, academic discipline, type, design, methodology, social media platform in focus, positionality statement, and ethical issues. Our findings suggest contemporary social media research ethics primarily reflects the ethical ideals of the Global North, with limited representation from the Global South. Women authors have published more papers than men authors. Previous studies have prioritized ethical concerns such as privacy, informed consent, and anonymity while overlooking researchers' risks and the ethics of social media sites. We particularly emphasized the lack of researchers' positionality statements in research. Our findings will pave the way to understanding social media ethics better, especially with the rapid growth of social media research in global scholarship.

Abstract Epileptogenesis is the process by which a normal brain becomes hyperexcitable and capable of generating spontaneous recurrent seizures. The extensive dysregulation of gene expression associated with epileptogenesis is shaped, in part, by microRNAs (miRNAs) – short, non-coding RNAs that negatively regulate protein levels. Functional miRNA-mediated regulation can, however, be difficult to elucidate due to the complexity of miRNA-mRNA interactions. Here, we integrated miRNA and mRNA expression profiles sampled over multiple time-points during and after epileptogenesis in rats, and applied bi-clustering and Bayesian modelling to construct temporal miRNA-mRNA-mRNA interaction networks. Network analysis and enrichment of network inference with sequence- and human disease-specific information identified key regulatory miRNAs with the strongest influence on the mRNA landscape, and miRNA-mRNA interactions closely associated with epileptogenesis and subsequent epilepsy. Our findings underscore the complexity of miRNA-mRNA regulation, can be used to prioritise miRNA targets in specific systems, and offer insights into key regulatory processes in epileptogenesis with therapeutic potential for further investigation.

Aggression toward peers who are perceived as weaker or different is a widespread problem for middle school students including those attending Catholic middle schools. Middle school students' normative beliefs about the acceptability of various types of aggressive behavior influences their own potential involvement in bullying. Therefore, how middle schoolers decide to respond to situations of peer aggression may affect their standing as either victims, bystanders to bullies, or as bully-victims in school environments over time. This study looks at how middle schoolers (sixth, seventh, and eighth grade girls and boys) in Catholic schools think it best to respond to peer aggression by examining their decision-making preferences for how targeted peers (from a vulnerable group) should respond to physical, verbal, or cyber aggression situations. Although significant effects regarding gender, grade, and type of peer aggression were found for the decision-making of the middle schoolers, findings reveal that overall middle schoolers' preferences were well developed for resisting peer aggression. The study provides important insights for how to supplement commonly existing curricula on social emotional learning in Catholic Schools with decision-making training inputs for the design of future school-based bullying prevention programs. Preparing middle schoolers in Catholic schools to respond to stop peer aggression in a proactive way supports the mission of Catholic schools to create safe and caring school environments.

IntroductionCancer patients may have increased risk for adverse cardiac events, but our understanding of cardiovascular risk in thymic cancer patients is not clear. We sought to characterize baseline cardiometabolic risk factors before thymic cancer diagnosis and the potential association between cancer treatment and subsequent cardiac events.MethodsThis was a retrospective cohort study evaluating patients with thymic cancer from 2003 to 2020 compared to age- and sex-matched controls without cancer. Baseline cardiovascular risk factors, cancer characteristics, and incidence of cardiac events were collected from the health information exchange. Multivariable regression was used to examine the impact of cardiovascular risk factors and cancer therapies.ResultsWe compared 296 patients with pathology-confirmed thymic cancer to 2,960 noncancer controls. Prior to cancer diagnosis, thymic cancer patients (TCPs) had lower prevalence of hypertension, dyslipidemia, and diabetes mellitus and similar rates of obesity, tobacco use, and pre-existing cardiovascular disease (CVD) compared to controls. After diagnosis, high-risk TCPs (>2 cardiovascular risk factors or pre-existing CVD) had higher risk for cardiac events (HR 3.73, 95% CI 2.88–4.83, p

The population of patients with cancer is rapidly expanding, and the diagnosis and monitoring of cardiovascular complications greatly rely on imaging. Numerous advances in the field of cardio-oncology and imaging have occurred in recent years. This review presents updated and practical approaches for multimodality cardiovascular imaging in the cardio-oncology patient and provides recommendations for imaging to detect the myriad of adverse cardiovascular effects associated with antineoplastic therapy, such as cardiomyopathy, atherosclerosis, vascular toxicity, myocarditis, valve disease, and cardiac masses. Uniquely, we address the role of cardiovascular imaging in patients with pre-existing cardiomyopathy, pregnant patients, long-term survivors, and populations with limited resources. We also address future avenues of investigation and opportunities for artificial intelligence applications in cardio-oncology imaging. This review provides a uniform practical approach to cardiovascular imaging for patients with cancer.

Background: Children had been affected less by COVID-19 than adults. But as the pandemic progressed more cases of severe pediatric COVID infection were reported. Aim of this study is to describe the clinical characteristics, laboratory parameters, treatments, and predictors of pediatric intensive care unit (PICU) admission among hospitalized children with SARS-CoV-2 infection. Subjects and Methods: This was a retrospective, observational study performed in a tertiary care COVID referral hospital among hospitalized children aged from 1 month to 12 years, from May 2020 to March 2021. Children treated in the pediatric ward were compared with those admitted in the PICU to assess predictors of intensive care admission. Results: Out of 447 hospitalized patients with confirmed COVID-19 infection, 92 (20.58%) required admission in the PICU. Mean age of the study population was 44.58 (16.77–72.39) months. Thirty-eight patients (8.50%) fulfilled multisystem inflammatory syndrome in children (MIS-C) diagnostic criteria. Invasive mechanical ventilation and inotropic support were needed for 28.26% and 36.96% of PICU-admitted patients, respectively. The mortality rate was 1.57%. Independent risk factors for PICU admission were infant age group, longer duration of fever (>5 days), shortness of breath, presence of shock, underlying comorbidities and higher pediatric early warning score (PEWS ≥5), poor Glasgow coma scale (GCS 50 mg/L), neutrophil–lymphocyte ratio (NLR ≥4.5), and hypoalbuminemia (

We report the results of a DREAM challenge designed to predict relative genetic essentialities based on a novel dataset testing 98,000 shRNAs against 149 molecularly characterized cancer cell lines. We analyzed the results of over 3,000 submissions over a period of 4 months. We found that algorithms combining essentiality data across multiple genes demonstrated increased accuracy; gene expression was the most informative molecular data type; the identity of the gene being predicted was far more important than the modeling strategy; well-predicted genes and selected molecular features showed enrichment in functional categories; and frequently selected expression features correlated with survival in primary tumors. This study establishes benchmarks for gene essentiality prediction, presents a community resource for future comparison with this benchmark, and provides insights into factors influencing the ability to predict gene essentiality from functional genetic screens. This study also demonstrates the value of releasing pre-publication data publicly to engage the community in an open research collaboration.