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Health professions education (HPE) research in the General Practice domain (GP-HPE) is vital for high-quality healthcare. Collaboration among GP-HPE researchers is crucial but challenging. Formulating a research agenda, involving stakeholders, and fostering inter-institutional collaboration can address these challenges and connect educational research and practice. We used Q-methodology to explore perspectives on GP-HPE research of participants from all Dutch postgraduate GP training institutes. Participants individually sorted statements based on the relevance of future GP-HPE research for educational practice. Data analysis comprised inverted factor analysis, rotation, and qualitative interpretation of configurations of all statements. The National Meeting on Educational Research took a participatory approach. We included 73 participants with diverse involvement in GP-HPE research. We identified five distinct perspectives, each representing a research focus area for developing and innovating GP education: the clinician scientist, the socially engaged GP, the specific GP identity, the GP as an entrepreneur, and the GP engaged in lifelong learning. The resulting five perspectives align with General Practice hallmarks. Q-methodology and a participatory approach facilitated collaboration among stakeholders. Successful inter-institutional collaboration requires a common goal, neutral leadership, participant commitment, regular meetings, audit trail support, process transparency, and reflexivity. Future research should address evidence gaps within these perspectives. Using Q-methodology turned out to be valuable for compiling a national research agenda for GP-HPE research. The research process helped to cross boundaries between researchers in different institutions, thus putting inter-institutional collaborative advantage center stage. Our approach could provide a conceivable procedure for HPE researchers worldwide.

There has been little attention to personality in research on school refusal (SR). This study examined personality traits among 41 adolescents receiving cognitive-behavioral therapy (CBT) during participation in a School Refusal Program in the Netherlands. Traits were examined via clinical scales and 2-point code types derived from the Minnesota Multiphasic Personality Inventory--Adolescent. The influence of personality traits on treatment outcome was examined at post-treatment and 1-year follow-up. At pretreatment, eight of the 10 clinical scales were disproportionately skewed toward the "high to very high" range relative to a norm group. Social introversion and depressive symptomatology were significantly increased relative to the norm group, and nearly one-half of the adolescents were characterized by code type 2-3/3-2 (depression/hysteria) or 2-0/0-2 (depression/social introversion). Adolescents characterized by a 2-0/0-2 code type were almost twice as likely (odds ratio = 1.78) to be treatment responders at post-treatment. There was no relation between personality traits and treatment outcome at follow-up. The small sample size limits generalization of the study's findings. If the results are replicated, personality traits may provide useful indications for personalizing treatment when employing interventions recommended in CBT manuals for SR.

A student's middle school science experience strongly impacts their future science, technology, engineering, and mathematics interest. The Japanese lesson study (JLS) model strengthens the student's experience through a research-based, collaborative, multistep, teaching-centered process focused on transforming local instructional practices. The JLS model has seen very limited application to middle school life science classrooms. The six-year-long implementation of JLS to core standards in the seventh-grade life science curriculum at a Los Angeles area school serving a historically underrepresented population found large, gender-independent increases in student mastery of key science standards, increased teacher collaboration in the areas of lesson development and data analysis, and school-site reform yielding district and statewide recognition.

Objectives: Overweight and obesity among school-aged children pose a threat to both their academic performance and public health. The Healthy Primary School of the Future (HPSF) initiative was established to address this issue. Our objective was to explore the conditions that make HPSF sustainable based on the perspectives of relevant stakeholders. Design: The study utilised Group Concept Mapping, a structured methodology for conducting mixed-methods participative research, combining qualitative data collection with quantitative data analysis measures. Method: Participants included parents, teachers, school directors, politicians, labour unions, educational, nutrition and health scientists and policymakers. They were asked to respond to the prompt, 'A necessary condition to make the HPSF sustainable is . . .'. The statements generated were then assessed for their importance and feasibility. Using multidimensional scaling and hierarchical cluster analyses, we identified the shared vision among the stakeholders. Results: A total of 106 unique statements were generated and grouped statistically into 10 clusters. The most significant clusters were identified as Financing; Accessibility for everyone; and Content/Lifestyle/School Programme. The clusters that were deemed most feasible included Content/Lifestyle/School Programme; Accessibility for everyone; and Evaluation. Conclusion: Achieving sustainability for the HPSF requires a comprehensive approach that addresses the conditions outlined in all 10 clusters. Based on the ratings of feasibility and importance, our recommendation is to prioritise implementation of Content/Lifestyle/School Programme and Accessibility for everyone. Subsequently, efforts should be directed towards realising the less feasible but crucial conditions, such as Financing and Evaluation, followed by the remaining six clusters of conditions as identified.

AIMS: The concept of atrial cardiomyopathy (AtCM) had been percolating through the literature since its first mention in 1972. Since then, publications using the term were sporadic until the decision was made to convene an expert working group with representation from four multinational arrhythmia organizations to prepare a consensus document on atrial cardiomyopathy in 2016 (EHRA/HRS/APHRS/SOLAECE expert consensus on atrial cardiomyopathies: definition, characterization, and clinical implication). Subsequently, publications on AtCM have increased progressively. METHODS AND RESULTS: The present consensus document elaborates the 2016 AtCM document further to implement a simple AtCM staging system (AtCM stages 1-3) by integrating biomarkers, atrial geometry, and electrophysiological changes. However, the proposed AtCM staging needs clinical validation. Importantly, it is clearly stated that the presence of AtCM might serve as a substrate for the development of atrial fibrillation (AF) and AF may accelerates AtCM substantially, but AtCM per se needs to be viewed as a separate entity. CONCLUSION: Thus, the present document serves as a clinical consensus statement of the European Heart Rhythm Association (EHRA) of the ESC, the Heart Rhythm Society (HRS), the Asian Pacific Heart Rhythm Society (APHRS), and the Latin American Heart Rhythm Society (LAHRS) to contribute to the evolution of the AtCM concept.

In drug discovery, the in silico prediction of binding affinity is one of the major means to prioritize compounds for synthesis. Alchemical relative binding free energy (RBFE) calculations based on molecular dynamics (MD) simulations are nowadays a popular approach for the accurate affinity ranking of compounds. MD simulations rely on empirical force field parameters, which strongly influence the accuracy of the predicted affinities. Here, we evaluate the ability of six different small-molecule force fields to predict experimental protein-ligand binding affinities in RBFE calculations on a set of 598 ligands and 22 protein targets. The public force fields OpenFF Parsley and Sage, GAFF, and CGenFF show comparable accuracy, while OPLS3e is significantly more accurate. However, a consensus approach using Sage, GAFF, and CGenFF leads to accuracy comparable to OPLS3e. While Parsley and Sage are performing comparably based on aggregated statistics across the whole dataset, there are differences in terms of outliers. Analysis of the force field reveals that improved parameters lead to significant improvement in the accuracy of affinity predictions on subsets of the dataset involving those parameters. Lower accuracy can not only be attributed to the force field parameters but is also dependent on input preparation and sampling convergence of the calculations. Especially large perturbations and nonconverged simulations lead to less accurate predictions. The input structures, Gromacs force field files, as well as the analysis Python notebooks are available on GitHub.

Glioblastoma is a clinically and molecularly heterogeneous disease, and new predictive biomarkers are needed to identify those patients most likely to respond to specific treatments. Through prospective genomic profiling of 459 consecutive primary treatment-naïve IDH-wildtype glioblastomas in adults, we identified a unique subgroup (2%, 9/459) defined by somatic hypermutation and DNA replication repair deficiency due to biallelic inactivation of a canonical mismatch repair gene. The deleterious mutations in mismatch repair genes were often present in the germline in the heterozygous state with somatic inactivation of the remaining allele, consistent with glioblastomas arising due to underlying Lynch syndrome. A subset of tumors had accompanying proofreading domain mutations in the DNA polymerase POLE and resultant "ultrahypermutation". The median age at diagnosis was 50 years (range 27-78), compared with 63 years for the other 450 patients with conventional glioblastoma (p

PURPOSE OF REVIEW: Glioblastoma remains resistant to most conventional treatments. Despite scientific advances in the past three decades, there has been a dearth of effective new treatments. New approaches to drug delivery and clinical trial design are needed. RECENT FINDINGS: We discuss how the blood-brain barrier and tumor microenvironment pose challenges for development of effective therapies for glioblastoma. Next, we discuss treatments in development that aim to overcome these barriers, including novel drug designs such as nanoparticles and antibody-drug conjugates, novel methods of drug delivery, including convection-enhanced and intra-arterial delivery, and novel methods to enhance drug penetration, such as blood-brain barrier disruption by focused ultrasound and laser interstitial thermal therapy. Lastly, we address future opportunities, positing combination therapy as the best strategy for effective treatment, neoadjuvant and window-of-opportunity approaches to simultaneously enhance therapeutic effectiveness with interrogation of on-treatment biologic endpoints, and adaptive platform and basket trials as imperative for future trial design. New approaches to GBM treatment should account for the blood-brain barrier and immunosuppression by improving drug delivery, combining treatments, and integrating novel clinical trial designs.

This comprehensive Review delves into the chemical principles governing RNA-mediated crowding events, commonly referred to as granules or biological condensates. We explore the pivotal role played by RNA sequence, structure, and chemical modifications in these processes, uncovering their correlation with crowding phenomena under physiological conditions. Additionally, we investigate instances where crowding deviates from its intended function, leading to pathological consequences. By deepening our understanding of the delicate balance that governs molecular crowding driven by RNA and its implications for cellular homeostasis, we aim to shed light on this intriguing area of research. Our exploration extends to the methodologies employed to decipher the composition and structural intricacies of RNA granules, offering a comprehensive overview of the techniques used to characterize them, including relevant computational approaches. Through two detailed examples highlighting the significance of noncoding RNAs, NEAT1 and XIST, in the formation of phase-separated assemblies and their influence on the cellular landscape, we emphasize their crucial role in cellular organization and function. By elucidating the chemical underpinnings of RNA-mediated molecular crowding, investigating the role of modifications, structures, and composition of RNA granules, and exploring both physiological and aberrant phase separation phenomena, this Review provides a multifaceted understanding of the intriguing world of RNA-mediated biological condensates.

BACKGROUND AND OBJECTIVES: Vamorolone is a dissociative agonist of the glucocorticoid receptor that has shown similar efficacy and reduced safety concerns in comparison with prednisone in Duchenne muscular dystrophy (DMD). This study was conducted to determine the efficacy and safety of vamorolone over 48 weeks and to study crossover participants (prednisone to vamorolone; placebo to vamorolone). METHODS: A randomized, double-blind, placebo-controlled and prednisone-controlled clinical trial of 2 doses of vamorolone was conducted in participants with DMD, in the ages from 4 years to younger than 7 years at baseline. The interventions were 2 mg/kg/d of vamorolone and 6 mg/kg/d of vamorolone for 48 weeks (period 1: 24 weeks + period 2: 24 weeks) and 0.75 mg/kg/d of prednisone and placebo for the first 24 weeks (before crossover). Efficacy was evaluated through gross motor outcomes and safety through adverse events, growth velocity, body mass index (BMI), and bone turnover biomarkers. This analysis focused on period 2. RESULTS: A total of 121 participants with DMD were randomized. Vamorolone at a dose of 6 mg/kg/d showed maintenance of improvement for all motor outcomes to week 48 (e.g., for primary outcome, time to stand from supine [TTSTAND] velocity, week 24 least squares mean [LSM] [SE] 0.052 [0.0130] rises/s vs week 48 LSM [SE] 0.0446 [0.0138]). After 48 weeks, vamorolone at a dose of 2 mg/kg/d showed similar improvements as 6 mg/kg/d for North Star Ambulatory Assessment (NSAA) (vamorolone 6 mg/kg/d-vamorolone 2 mg/kg/d LSM [SE] 0.49 [1.14]; 95% CI -1.80 to 2.78, p = 0.67), but less improvement for other motor outcomes. The placebo to vamorolone 6 mg/kg/d group showed rapid improvements after 20 weeks of treatment approaching benefit seen with 48-week 6 mg/kg/d of vamorolone treatment for TTSTAND, time to run/walk 10 m, and NSAA. There was significant improvement in linear growth after crossover in the prednisone to vamorolone 6 mg/kg/d group, and rapid reversal of prednisone-induced decline in bone turnover biomarkers in both crossover groups. There was an increase in BMI after 24 weeks of treatment that then stabilized for both vamorolone groups. DISCUSSION: Improvements of motor outcomes seen with 6 mg/kg/d of vamorolone at 24 weeks of treatment were maintained to 48 weeks of treatment. Vamorolone at a dose of 6 mg/kg/d showed better maintenance of effect compared with vamorolone at a dose of 2 mg/kg/d for most (3/5) motor outcomes. Bone morbidities of prednisone (stunting of growth and declines in serum bone biomarkers) were reversed when treatment transitioned to vamorolone. TRIAL REGISTRATION INFORMATION: ClinicalTrials.gov Identifier: NCT03439670. CLASSIFICATION OF EVIDENCE: This study provides Class I evidence that for boys with DMD, the efficacy of vamorolone at a dose of 6 mg/kg/d was maintained over 48 weeks.

Evaluations of treatment efficacy in Duchenne muscular dystrophy (DMD), a rare genetic disease that results in progressive muscle wasting, require an understanding of the meaningfulness of changes in functional measures. We estimated the minimal detectable change (MDC) for selected motor function measures in ambulatory DMD, i.e., the minimal degree of measured change needed to be confident that true underlying change has occurred rather than transient variation or measurement error. MDC estimates were compared across multiple data sources, representing >1000 DMD patients in clinical trials and real-world clinical practice settings. Included patients were ambulatory, aged ≥4 to 80% confidence in true change were 2.8 units for the North Star Ambulatory Assessment (NSAA) total score, 1.3 seconds for the 4-stair climb (4SC) completion time, 0.36 stairs/second for 4SC velocity and 36.3 meters for the 6-minute walk distance (6MWD). MDC estimates were similar across clinical trial and real-world data sources, and tended to be slightly larger than MCIDs for these measures. The identified thresholds can be used to inform endpoint definitions, or as benchmarks for monitoring individual changes in motor function in ambulatory DMD.

Glioblastoma (GBM) is the most common primary malignant brain tumor, with a median overall survival of less than 2 years and a nearly 100% mortality rate under standard therapy that consists of surgery followed by combined radiochemotherapy. Therefore, new therapeutic strategies are urgently needed. The success of chimeric antigen receptor (CAR) T cells in hematological cancers has prompted preclinical and clinical investigations into CAR-T-cell treatment for GBM. However, recent trials have not demonstrated any major success. Here, we delineate existing challenges impeding the effectiveness of CAR-T-cell therapy for GBM, encompassing the cold (immunosuppressive) microenvironment, tumor heterogeneity, T-cell exhaustion, local and systemic immunosuppression, and the immune privilege inherent to the central nervous system (CNS) parenchyma. Additionally, we deliberate on the progress made in developing next-generation CAR-T cells and novel innovative approaches, such as low-intensity pulsed focused ultrasound, aimed at surmounting current roadblocks in GBM CAR-T-cell therapy.