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Introduction: There is a growing concern for physician and medical student well-being and burnout. Growth mindset, or the belief that ability can be developed, as well as students' perception of their instructors' growth mindset, have been associated with better academic outcomes for a wide range of students. The primary purpose of the present study was to investigate the effects of growth mindset on medical student well-being., Method: We recruited all graduating osteopathic medical students in the class of 2023. This survey included items about student demographics (including identifiable items), experiences in medical school, practice plans, along with financial and other information. The survey of 667 items required a median time of 33 min to complete. Our sample consisted of 4,180 students. Students self-reported growth mindset, perception of instructor growth mindset, and four measures of well-being: flourishing, resilience, burnout, and maladaptive psychological symptoms., Results: Growth mindset and perception of instructor growth mindset were significant predictors of medical student well-being. Further, significant interactions showed that these effects were strongest for students from historically marginalized backgrounds., Discussion: Our work provides a first step toward addressing physician burnout by targeting medical students, which could prevent them from beginning their careers already in a state of burnout. We argue that systemic change is needed to improve student well-being, such as emphasizing growth mindset-supportive pedagogy, which places the emphasis on changing systems instead of individuals. Future research should include causal analyses to better understand the effect and persistence of growth mindset-supportive environments on student well-being. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Motivation: The analysis of circulating cell-free DNA (cfDNA) holds immense promise as a non-invasive diagnostic tool across various human conditions. However, extracting biological insights from cfDNA fragments entails navigating complex and diverse bioinformatics methods, encompassing not only DNA sequence variation, but also epigenetic characteristics like nucleosome footprints, fragment length, and methylation patterns., Results: We introduce Liquid Biopsy Feature extract (LBFextract), a comprehensive package designed to streamline feature extraction from cfDNA sequencing data, with the aim of enhancing the reproducibility and comparability of liquid biopsy studies. LBFextract facilitates the integration of preprocessing and postprocessing steps through alignment fragment tags and a hook mechanism. It incorporates various methods, including coverage-based and fragment length-based approaches, alongside two novel feature extraction methods: an entropy-based method to infer TF activity from fragmentomics data and a technique to amplify signals from nucleosome dyads. Additionally, it implements a method to extract condition-specific differentially active TFs based on these features for biomarker discovery. We demonstrate the use of LBFextract for the subtype classification of advanced prostate cancer patients using coverage signals at transcription factor binding sites from cfDNA. We show that LBFextract can generate robust and interpretable features that can discriminate between different clinical groups. LBFextract is a versatile and user-friendly package that can facilitate the analysis and interpretation of liquid biopsy data., Data and Code Availability and Implementation: LBFextract is freely accessible at https://github.com/Isy89/LBF. It is implemented in Python and compatible with Linux and Mac operating systems. Code and data to reproduce these analyses have been uploaded to 10.5281/zenodo.10964406., Competing Interests: A patent application has been filed for aspects of the paper (inventors: I.L.; S.O.H.; M.R.S.). S.O.H. is a co-founder of Vessel FlexCo and is on the advisory board of CureMatch. The remaining authors declare no competing interests., (© 2024 The Authors.)

Importance: Given the high rates of burnout and associated negative mental health outcomes (eg, depression, suicidal ideation, substance abuse) among medical students and physicians, it is imperative to identify strategies for supporting the future health workforce, particularly when considering trends indicating a future shortage of physicians. Understanding the associations of medical school students' learning mindsets (eg, growth mindset, purpose and relevance, and sense of belonging) with indicators of well-being (eg, flourishing) and ill-being (eg, burnout) could provide a foundation for future research to consider when attempting to combat the negative mental health trends among medical students and physicians., Objectives: To understand the associations of medical school students' learning mindsets (ie, their beliefs about themselves as learners and their learning environment) with critical student health outcomes (ie, well-being and ill-being)., Design, Setting, and Participants: This survey study used a nationally representative sample of first-year osteopathic medical school students across the US who responded to a survey of learning mindsets as well as measures of well-being and ill-being in fall 2022. Data were analyzed from January to April 2024., Main Outcomes and Measures: Learning mindsets were categorized as growth mindset, purpose and relevance, and sense of belonging. Well-being was categorized as flourishing and resilience, and ill-being was categorized as burnout and psychological symptoms. Outcomes were regressed on learning mindset and demographics variables, and interactions of demographic variables and learning mindsets were assessed., Results: A total of 7839 students were surveyed, and 6622 students (mean [SD] age, 25.05 [3.20]; 3678 [55.5%] women) responded and were included in analyses. The 3 learning mindsets were significantly associated with flourishing (growth mindset: b = 0.34; 95% CI, 0.23 to 0.45; P < .001; purpose and relevance: b = 2.02; 95% CI, 1.83 to 2.20; P < .001; belonging uncertainty: b = -0.98; 95% CI, -1.08 to -0.89; P < .001) and resilience (growth mindset: b = 0.28; 95% CI, 0.17 to 0.40; P < .001; purpose and relevance: b = 1.62; 95% CI, 1.43 to 1.82; P < .001; belonging uncertainty: b = -1.50; 95% CI, -1.60 to -1.40; P < .001) well-being outcomes and burnout (growth mindset: b = -0.09; 95% CI, -0.11 to -0.07; P < .001; purpose and relevance: b = -0.29; 95% CI, -0.32 to -0.25; P < .001; belonging uncertainty: b = 0.28; 95% CI, 0.26 to 0.30; P < .001) and psychological symptoms (growth mindset: b = -0.22; 95% CI, -0.30 to -0.14; P < .001; purpose and relevance: b = -0.51; 95% CI, -0.64 to -0.38; P < .001; belonging uncertainty: b = 1.33; 95% CI, 1.27 to 1.40; P < .001) ill-being outcomes, even when controlling for important demographic characteristics (eg, race and ethnicity, gender identity, age). Furthermore, several significant interactions indicated that these learning mindsets may be particularly salient for students from historically marginalized communities: there was a significant interaction between growth mindset and race and ethnicity (b = 0.58; 95% CI, 0.08 to 1.09, P = .02), such that growth mindset was more strongly associated with flourishing among American Indian or Alaska Native, Black, Latine, or Native Hawaiian students., Conclusions and Relevance: These findings suggest that identifying strategies for supporting students' learning mindsets may be an effective way to support medical student well-being and reduce ill-being, particularly among students from historically marginalized backgrounds.

Importance: More information is needed to guide referring subspecialists on the appropriate patient evaluation before magnetic resonance defecography (MRD)., Objectives: This study aimed to evaluate how often health care providers perform digital rectal examination (DRE) before ordering MRD to investigate causes of bowel and pelvic floor complaints., Study Design: We conducted a retrospective cohort review, including MRD performed on female patients at an integrated health care system from 2016 through 2020. The primary outcome was the presence or absence of documented rectal examination in the year before defecography by the referring provider or 6 months prior by a primary care physician or pelvic floor physical therapist. We hypothesized that the overall rate of rectal examination would be high and unaffected by the referring provider's subspecialty., Results: Three hundred-four defecography tests were performed, with 209 patients (68.8%) referred by gastroenterology providers and 95 (31.2%) from other specialties. Gastroenterologists performed DRE in 32.8% of patients, in contrast to 84.4% of patients referred by other specialties ( P < 0.001). When comparing subspecialties that most commonly refer patients for MRD (gastroenterology, colorectal surgery and urogynecology), there was a statistically significant difference between gastroenterologists and colorectal surgeons ( P < 0.001) as well as urogynecologists ( P < 0.001) but no difference in the rate of rectal examination between colorectal surgeons and urogynecologists ( P = 1.00)., Conclusions: At our single integrated health system, the rate of DRE before MRD testing varied significantly by specialty. Our findings highlight the need for better understanding of DRE utility in the algorithms for evaluation of bowel and pelvic floor disorders., (Copyright © 2024 American Urogynecologic Society. All rights reserved.)

Background: Cell-free DNA (cfDNA), a broadly applicable biomarker commonly sourced from urine or blood, is extensively used for research and diagnostic applications. In various settings, genetic and epigenetic information is derived from cfDNA. However, a unified framework for its processing is lacking, limiting the universal application of innovative analysis strategies and the joining of data sets., Findings: Here, we describe cfDNA UniFlow, a unified, standardized, and ready-to-use workflow for processing cfDNA samples. The workflow is written in Snakemake and can be scaled from stand-alone computers to cluster environments. It includes methods for processing raw genome sequencing data as well as specialized approaches for correcting sequencing errors, filtering, and quality control. Sophisticated methods for detecting copy number alterations and estimating and correcting GC-related biases are readily incorporated. Furthermore, it includes methods for extracting, normalizing, and visualizing coverage signals around user-defined regions in case-control settings. Ultimately, all results and metrics are aggregated in a unified report, enabling easy access to a wide variety of information for further research and downstream analysis., Conclusions: We provide an automated pipeline for processing cell-free DNA sampled from liquid biopsies, including a wide variety of additional functionalities like bias correction and signal extraction. With our focus on scalability and extensibility, we provide a foundation for future cfDNA research and faster clinical applications. The source code and extensive documentation are available on our GitHub repository (https://github.com/kircherlab/cfDNA-UniFlow)., (© The Author(s) 2024. Published by Oxford University Press GigaScience.)

Analyses of cell-free DNA (cfDNA) are increasingly being employed for various diagnostic and research applications. Many technologies aim to increase resolution, e.g. for detecting early-stage cancer or minimal residual disease. However, these efforts may be confounded by inherent base composition biases of cfDNA, specifically the over - and underrepresentation of guanine (G) and cytosine (C) sequences. Currently, there is no universally applicable tool to correct these effects on sequencing read-level data. Here, we present GCparagon, a two-stage algorithm for computing and correcting GC biases in cfDNA samples. In the initial step, length and GC base count parameters are determined. Here, our algorithm minimizes the inclusion of known problematic genomic regions, such as low-mappability regions, in its calculations. In the second step, GCparagon computes weights counterbalancing the distortion of cfDNA attributes (correction matrix). These fragment weights are added to a binary alignment map (BAM) file as alignment tags for individual reads. The GC correction matrix or the tagged BAM file can be used for downstream analyses. Parallel computing allows for a GC bias estimation below 1 min. We demonstrate that GCparagon vastly improves the analysis of regulatory regions, which frequently show specific GC composition patterns and will contribute to standardized cfDNA applications., (© The Author(s) 2023. Published by Oxford University Press on behalf of NAR Genomics and Bioinformatics.)

This paper reviews the current literature to examine what elements of osteopathic medicine can be used in psychiatry. The aim of this study was to use the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to conduct a systematic review of studies describing the efficacy of osteopathic manipulative medicine (OMM) in treating psychiatric problems directly and indirectly. The authors searched the databases PubMed, PsycINFO, and CINAHL (Cumulative Index to Nursing and Allied Health Literature), reviewing peer-reviewed articles from 1980 to April 2023. The literature demonstrates that OMM has a positive effect on psychiatric symptoms indirectly when treating certain medical conditions, such as chronic pain, fibromyalgia, and irritable bowel syndrome; however, there are many limitations on these studies, and further research is required prior to making firm recommendations. The evidence is lacking for osteopathic manual medicine being used directly to treat psychiatric conditions. This review demonstrates that in some populations, such as individuals with chronic pain, fibromyalgia, and irritable bowel syndrome, OMM could be considered by an osteopathic psychiatrist as an adjunct treatment. More research should be conducted in this area due to the many limitations in the available studies but current research suggests that the use of OMM by osteopathic psychiatrists could be beneficial for some patient populations., Competing Interests: The authors have declared that no competing interests exist., (Copyright © 2023, Bowes et al.)

Background The process for program directors (PDs) to provide feedback to medical schools about their graduates' readiness for postgraduate year 1 (PGY-1) training is burdensome and does not generate national benchmarking data. Objective The Association of American Medical Colleges (AAMC) tested the feasibility of administering a standardized Resident Readiness Survey (RRS) to PDs nationally about their PGY-1 residents' preparedness for residency. Methods In 2020 and 2021, the AAMC invited PDs via email to complete RRSs for their PGY-1s who graduated from participating schools; the AAMC provided schools with reports of identified RRS data for their graduates. Outcome measures included school participation rates, PD response rates, PGY-1s' coverage rates (RRSs completed/RRSs PDs invited to complete), RRS completion time (time-stamp difference: RRS opening-submission), and participating schools' feedback about the process collected via AAMC evaluation questionnaires sent to school leaders. Chi-square tested significance of differences between proportions. Results School participation increased from 43.8% (2020: 77 of 176) to 72.4% (2021: 131 of 181). PD response rates, similar in both years overall (2020: 1786 of 2847 [62.7%]; 2021: 2107 of 3406 [61.9%]; P =.48), varied by specialty ( P <.001; range 65 of 154 [42.2%], neurology; 109 of 136 [80.1%], internal medicine-pediatrics, both years combined). PGY-1s' coverage rates were similar ( P =.21) in 2020 (5567 of 10 712 [52.0%]) and 2021 (9688 of 18 372 [52.7%]). RRS completion time averaged less than 3 minutes. Numerous school leaders reported that RRS data stimulated new, or supported ongoing, curricular quality improvement. Conclusions Administration of a standardized RRS to PDs nationally about PGY-1s preparedness for residency is feasible and will continue.

Prostate cancer (PCa) is a common and fatal type of cancer in men. Metastatic PCa (mPCa) is a major factor contributing to its lethality, although the mechanisms remain poorly understood. PTEN is one of the most frequently deleted genes in mPCa. Here we show a frequent genomic co-deletion of PTEN and STAT3 in liquid biopsies of patients with mPCa. Loss of Stat3 in a Pten-null mouse prostate model leads to a reduction of LKB1/pAMPK with simultaneous activation of mTOR/CREB, resulting in metastatic disease. However, constitutive activation of Stat3 led to high LKB1/pAMPK levels and suppressed mTORC1/CREB pathway, preventing mPCa development. Metformin, one of the most widely prescribed therapeutics against type 2 diabetes, inhibits mTORC1 in liver and requires LKB1 to mediate glucose homeostasis. We find that metformin treatment of STAT3/AR-expressing PCa xenografts resulted in significantly reduced tumor growth accompanied by diminished mTORC1/CREB, AR and PSA levels. PCa xenografts with deletion of STAT3/AR nearly completely abrogated mTORC1/CREB inhibition mediated by metformin. Moreover, metformin treatment of PCa patients with high Gleason grade and type 2 diabetes resulted in undetectable mTORC1 levels and upregulated STAT3 expression. Furthermore, PCa patients with high CREB expression have worse clinical outcomes and a significantly increased risk of PCa relapse and metastatic recurrence. In summary, we have shown that STAT3 controls mPCa via LKB1/pAMPK/mTORC1/CREB signaling, which we have identified as a promising novel downstream target for the treatment of lethal mPCa., (© 2023. BioMed Central Ltd., part of Springer Nature.)

Cell-free circulating DNA (cfDNA) analyses may enable multi-cancer early detection (MCED), but the most suitable method is unknown. In this issue of Cancer Cell, Jamshidi et al. compare ten machine-learning classifiers using various cfDNA features and conclude that cfDNA methylation patterns are most promising for MCED testing., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Background: Mucopolysaccharidoses (MPS) are monogenic metabolic disorders that significantly affect the skeleton. Eleven enzyme defects in the lysosomal degradation of glycosaminoglycans (GAGs) have been assigned to the known MPS subtypes (I-IX). Arylsulfatase K (ARSK) is a recently characterised lysosomal hydrolase involved in GAG degradation that removes the 2-O-sulfate group from 2-sulfoglucuronate. Knockout of Arsk in mice was consistent with mild storage pathology, but no human phenotype has yet been described., Methods: In this study, we report four affected individuals of two unrelated consanguineous families with homozygous variants c.250C>T, p.(Arg84Cys) and c.560T>A, p.(Leu187Ter) in ARSK , respectively. Functional consequences of the two ARSK variants were assessed by mutation-specific ARSK constructs derived by site-directed mutagenesis, which were ectopically expressed in HT1080 cells. Urinary GAG excretion was analysed by dimethylene blue and electrophoresis, as well as liquid chromatography/mass spectrometry (LC-MS)/MS analysis., Results: The phenotypes of the affected individuals include MPS features, such as short stature, coarse facial features and dysostosis multiplex. Reverse phenotyping in two of the four individuals revealed additional cardiac and ophthalmological abnormalities. Mild elevation of dermatan sulfate was detected in the two subjects investigated by LC-MS/MS. Human HT1080 cells expressing the ARSK-Leu187Ter construct exhibited absent protein levels by western blot, and cells with the ARSK-Arg84Cys construct showed markedly reduced enzyme activity in an ARSK-specific enzymatic assay against 2-O-sulfoglucuronate-containing disaccharides as analysed by C18-reversed-phase chromatography followed by MS., Conclusion: Our work provides a detailed clinical and molecular characterisation of a novel subtype of mucopolysaccharidosis, which we suggest to designate subtype X., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Genes implicated in the Golgi and endosomal trafficking machinery are crucial for brain development, and mutations in them are particularly associated with postnatal microcephaly (POM)., Methods: Exome sequencing was performed in three affected individuals from two unrelated consanguineous families presenting with delayed neurodevelopment, intellectual disability of variable degree, POM and failure to thrive. Patient-derived fibroblasts were tested for functional effects of the variants., Results: We detected homozygous truncating variants in ATP9 A. While the variant in family A is predicted to result in an early premature termination codon, the variant in family B affects a canonical splice site. Both variants lead to a substantial reduction of ATP9A mRNA expression. It has been shown previously that ATP9A localises to early and recycling endosomes, whereas its depletion leads to altered gene expression of components from this compartment. Consistent with previous findings, we also observed overexpression of ARPC3 and SNX3 , genes strongly interacting with ATP9A ., Conclusion: In aggregate, our findings show that pathogenic variants in ATP9A cause a novel autosomal recessive neurodevelopmental disorder with POM. While the physiological function of endogenous ATP9A is still largely elusive, our results underline a crucial role of this gene in endosomal transport in brain tissue., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: The promise of precision cancer medicine presently centers around the genomic sequence of a patient's tumor being translated into timely, actionable information to inform clinical care. The analysis of cell-free DNA from liquid biopsy, which contains circulating tumor DNA (ctDNA) in patients with cancer, has proven to be amenable to various settings in oncology. However, open questions surrounding the clinical validity and utility of plasma-based analyses have hindered widespread clinical adoption., Main Body: Owing to the rapid evolution of the field, studies supporting the use of ctDNA as a biomarker throughout a patient's journey with cancer have accumulated in the last few years, warranting a review of the latest status for clinicians who may employ ctDNA in their precision oncology programs. In this work, we take a step back from the intricate coverage of detection approaches described extensively elsewhere and cover basic concepts around the practical implementation of next generation sequencing (NGS)-guided liquid biopsy. We compare relevant targeted and untargeted approaches to plasma DNA analysis, describe the latest evidence for clinical validity and utility, and highlight the value of genome-wide ctDNA analysis, particularly as it relates to early detection strategies and discovery applications harnessing the non-coding genome., Conclusions: The maturation of liquid biopsy for clinical application will require interdisciplinary efforts to address current challenges. However, patients and clinicians alike may greatly benefit in the future from its incorporation into routine oncology care., (© 2022. The Author(s).)