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Research over the past 20 years indicates the amount of task-specific walking practice provided to individuals with stroke, brain injury, or incomplete spinal cord injury can strongly influence walking recovery. However, more recent data suggest that attention towards 2 other training parameters, including the intensity and variability of walking practice, may maximize walking recovery and facilitate gains in non-walking outcomes. The combination of these training parameters represents a stark contrast from traditional strategies, and confusion regarding the potential benefits and perceived risks may limit their implementation in clinical practice. The purpose of this perspective is to delineate the evidence regarding the contributions of intensity and variability of locomotor training to improve mobility outcomes in individuals with acute-onset brain and spinal cord injury. The rationale and evidence supporting the utility of these training parameters in controlled laboratory settings is first described by integrating concepts in the field of neuroscience, motor learning, biomechanics, and exercise physiology into a rehabilitation intervention. Subsequently, the evidence supporting the efficacy of this paradigm is addressed, including discussions of some of the misconceptions regarding perceived negative consequences of these strategies in an effort to mitigate common clinical concerns. Finally, the utility of these strategies implemented during inpatient rehabilitation is delineated to facilitate a more comprehensive understanding of the feasibility and potential benefits early following neurologic injury. A greater understanding of how and why to integrate higher intensity, variable stepping practice will support therapists to take the next step to maximize mobility in the patients they serve., (© The Author(s) 2025. Published by Oxford University Press on behalf of the American Physical Therapy Association. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

This review assessed the effect of strategies designed to sustain the delivery of evidenced based interventions (EBIs) which target behavioural risk factors linked to leading causes of chronic disease in clinical and community settings. Seven electronic databases were searched for randomised controlled studies published from earliest record to November 2022. Studies were included if they tested a strategy to sustain the delivery of an EBI within clinical or community settings. Results were synthesised using vote counting based on direction of effect, and reported in accordance with non-meta-analytic review standards following the Synthesis Without Meta-analysis (SWiM) guidelines. Three studies met the study inclusion criteria. Two studies were community-based, with one conducted in Australian community sports clubs and the second in afterschool clubs in the United States. The single clinical-based study was conducted in community health care centres in the United States. Across the three studies, 25 strategies were employed and only two strategies were common across all studies. Synthesis using vote counting based on direction of effect indicated that two of three studies favoured the intervention as positively impacting sustainment of EBIs. Few studies have been conducted to assess the effect of strategies designed to support sustainment of EBIs for chronic disease prevention in clinical and community settings. As such, it is difficult to determine the effect of strategies designed to support sustainment. Further research with comprehensive reporting of the selection, use and testing of sustainment strategies is needed to advance understanding of how to sustain EBIs in clinical and community settings., (© The Author(s) 2025. Published by Oxford University Press on behalf of the Society of Behavioral Medicine.)

Digital health tools are positive for delivering evidence-based care. However, few studies have applied rigorous frameworks to understand their use in community settings. This study aimed to identify implementation determinants of the Automated Heart-Health Assessment (AH-HA) tool within outpatient oncology settings as part of a hybrid effectiveness-implementation trial. A mixed-methods approach informed by the Consolidated Framework for Implementation Research (CFIR) examined barriers and facilitators to AH-HA implementation in four NCI Community Oncology Research Program (NCORP) practices participating in the WF-1804CD AH-HA trial. Provider surveys were analyzed using descriptive statistics. Interviews with providers (n = 15) were coded using deductive (CFIR) and inductive codes by trained analysts. The CFIR rating tool was used to rate each quote for (i) valence, defined as a positive (+) or negative (-) influence, and (ii) strength, defined as a neutral (0), weak (1), or strong (2) influence on implementation. All providers considered discussing cardiovascular health with patients as important (61.5%, n = 8/13) or somewhat important (38.5%, n = 5/13). The tool was well-received by providers and was feasible to use in routine care among cancer survivors. Providers felt the tool was acceptable and usable, had a relative advantage over routine care, and had the potential to generate benefits for patients. Common reasons clinicians reported not using AH-HA were (i) insufficient time and (ii) the tool interfering with workflow. Systematically identifying implementation determinants from this study will guide the broader dissemination of the AH-HA tool across clinical settings and inform implementation strategies for future scale-up hybrid trials., (© Society of Behavioral Medicine 2024. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Context: A national assessment of osteoporosis drug therapy (ODT) use can inform the extent of underdiagnosis and undertreatment of osteoporosis., Objective: The aim was to describe trends in ODT use by age, sex, fragility fracture, and documented osteoporosis., Methods: This was a retrospective analysis of patient-quarter observations for adults aged ≥50 years with commercial or Medicare Advantage health insurance in the OptumLabs Data Warehouse between 2011 and 2022. The primary outcome was the proportion of patient-quarter observations with ODT use stratified by age, sex, fragility fracture, and documented osteoporosis. Cuzick tests were performed to assess trends ODT use., Results: Analysis of 166 673 420 patient-quarter observations revealed that over 70% of patients with fragility fractures did not have documented osteoporosis. Among women aged ≥65 years with documented osteoporosis, ODT fill rates increased between 2011 and 2022 from 36.3% to 50.1% for women without fragility fractures (P < .001) and from 30.8% to 43.7% for women with fragility fractures (P < .001). However, ODT fill rates declined (9.2% to 7.4% between 2011 and 2022) for women with fragility fractures and no documented osteoporosis (P = .015). Similar trends were observed among women aged 50-64 years and men., Conclusion: ODT use for patients with documented osteoporosis has increased but remains low. Low rates of ODT use for patients with fragility fractures in the absence of documented osteoporosis suggests that underdiagnosis of osteoporosis contributes to underuse of ODTs., (© The Author(s) 2025. Published by Oxford University Press on behalf of the Endocrine Society. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com. See the journal About page for additional terms.)

Study Objectives: The association between snoring, a very common condition that increases with age, and dementia risk is controversial. We aimed to investigate the observational and causal relationship between snoring and dementia, and to elucidate the role of body mass index (BMI)., Methods: Using data from 451 250 participants who were dementia-free at baseline, we examined the association between self-reported snoring and incident dementia using Cox proportional-hazards models. Causal relationship between snoring and Alzheimer's disease (AD) was examined using bidirectional two-sample Mendelian randomization (MR) analysis., Results: During a median follow-up of 13.6 years, 8325 individuals developed dementia. Snoring was associated with a lower risk of all-cause dementia (hazard ratio [HR] 0.93; 95% confidence interval [CI] 0.89 to 0.98) and AD (HR 0.91; 95% CI 0.84 to 0.97). The association was slightly attenuated after adjusting for BMI, and was stronger in older individuals, APOE ε4 allele carriers, and during shorter follow-up periods. MR analyses suggested no causal effect of snoring on AD; however, genetic liability to AD was associated with a lower risk of snoring. Multivariable MR indicated that the effect of AD on snoring was primarily driven by BMI., Conclusions: The phenotypic association between snoring and lower dementia risk likely stems from reverse causation, with genetic predisposition to AD associated with reduced snoring. This may be driven by weight loss in prodromal AD. Increased attention should be paid to reduced snoring and weight loss in older adults as potential early indicators of dementia risk., (© The Author(s) 2024. Published by Oxford University Press on behalf of Sleep Research Society. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Cryptococcus neoformans is an opportunistic fungal pathogen with a polysaccharide capsule that becomes greatly enlarged in the mammalian host and during in vitro growth under host-like conditions. To understand how individual environmental signals affect capsule size and gene expression, we grew cells in all combinations of 5 signals implicated in capsule size and systematically measured cell and capsule sizes. We also sampled these cultures over time and performed RNA-seq in quadruplicate, yielding 881 RNA-seq samples. Analysis of the resulting data sets showed that capsule induction in tissue culture medium, typically used to represent host-like conditions, requires the presence of either CO2 or exogenous cyclic AMP. Surprisingly, adding either of these pushes overall gene expression in the opposite direction from tissue culture media alone, even though both are required for capsule development. Another unexpected finding was that rich medium blocks capsule growth completely. Statistical analysis further revealed many genes whose expression is associated with capsule thickness; deletion of one of these significantly reduced capsule size. Beyond illuminating capsule induction, our massive, uniformly collected data set will be a significant resource for the research community., Competing Interests: Conflicts of interest: The author(s) declare no conflicts of interest., (© The Author(s) 2024. Published by Oxford University Press on behalf of The Genetics Society of America.)

Background: Stress plays a pivotal role in physical health. Although many studies have linked stress reactivity (daily within-person associations between stress exposure and negative affect) to physical health outcomes, we know surprisingly little about how changes in stress reactivity are related to changes in physical health., Purpose: The current study examines how change in stress reactivity over 18 years is related to changes in functional health and chronic health conditions., Methods: Three measurement bursts from the National Study of Daily Experiences (N = 2880; 55% female) each included daily measures of stressor exposure and negative affect across 8 consecutive days, yielding 33 944 days of data across 18 years of adulthood. At each wave, participants reported their functional health limitations (ie, basic activities of daily living [ADL] and instrumental activities of daily living [IADL]) and chronic health conditions. Multilevel structural equation models simultaneously modeled stress reactivity at Level 1, longitudinal changes in stress reactivity at Level 2, and the association between changes in stress reactivity and changes in functional limitations and chronic conditions at Level 3., Results: Higher levels of stress reactivity at baseline were associated with more functional health limitations 18 years later (ADLs: Est. = 0.90, P = .001; IADLs: Est. = 1.78, P < .001). Furthermore, individuals who increased more in their stress reactivity across the 18-year period also showed greater increases in their functional health limitations (ADLs: Est. = 4.02, P = .017; IADLs: Est. = 5.74, P < .001) and chronic conditions (Est. = 11.17, P = .008)., Conclusions: These findings highlight the strong connection between health and stress in daily life, and how they travel together across adulthood., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Society of Behavioral Medicine.)

Background: Antiretroviral therapy (ART) is recommended for all individuals with HIV infection, including those with acute HIV-1 infection (AHI). While recommendations are similar to those for chronic infection, efficacy data regarding treatment of acute HIV is limited., Methods: This was a single arm, 96-week study of a once-daily integrase inhibitor (INSTI)-based regimen using elvitegravir/cobicistat/emtricitabine/tenofovir disoproxil fumarate (EVG/COBI/FTC/TDF) in AHI. Primary endpoint was proportion of participants with HIV-1 RNA <200 copies/mL and <50 copies/mL by treatment weeks 24 and 48, respectively. We also examined time to viral suppression and weight gain after treatment initiation. Outcomes and characteristics were compared with a historical AHI cohort using a non-nucleoside reverse transcriptase inhibitor (NNRTI)-based regimen with efavirenz/emtricitabine/tenofovir disoproxil fumarate (EFV/FTC/TDF)., Results: Thirty-three participants with AHI were enrolled with 31 available for analyses. Most were African American (61%) and men who have sex with men (73%). Median age was 26 (IQR 22-42). Demographics were similar between the two AHI cohorts. By Week 24, 100% in the INSTI and 99% in the NNRTI cohort were <200 copies/mL; by Week 48, 100% in both cohorts were <50 copies/mL. Time to viral suppression was shorter in the INSTI cohort (median 54 versus 99 days). Mean weight change was similar with a 3.6 kg increase in the INSTI cohort and 2.4 kg in the NNRTI cohort at 96 weeks., Conclusions: INSTI-based ART during AHI resulted in rapid and sustained viral suppression. Over 96 weeks, weight increased in the INSTI-based cohort but was similar to weight increase in a historical NNRTI-based AHI cohort., (© The Author(s) 2024. Published by Oxford University Press on behalf of British Society for Antimicrobial Chemotherapy.)

Background: As survival rates for individuals with sickle cell disease (SCD) increase, calls have been made to improve their reproductive healthcare and outcomes. The research team created a web-based program entitled Fertility edUcaTion to Understand ReproductivE health in Sickle cell disease (FUTURES). The study aim was to use the Consolidated Framework for Implementation Research (CFIR) during pre-implementation to identify challenges and opportunities from the individual to systems level of implementation to ultimately optimize the integration of FUTURES into clinical practice., Methods: Semi-structured interviews were conducted with clinicians, research team members, and adolescent and young adult (AYA) males with SCD and their caregivers who participated in pilot testing. Interviews (N = 31) were coded inductively and then mapped onto CFIR domains (i.e., outer setting, inner setting, characteristics of individuals, and intervention characteristics)., Results: Research team interviews indicated the lack of universal guidelines for reproductive care in this population and gaps in reproductive health knowledge as key reasons for developing FUTURES, also highlighting the importance of collaboration with community members during development. Clinicians reported intraorganizational communication as essential to implementing FUTURES and discussed challenges in addressing reproductive health due to competing priorities. Clinicians, AYAs, and caregivers reported positive views of FUTURES regarding length, engagement, accessibility, and content. Suggestions for the best setting and timing for implementation varied., Conclusions: Using CFIR during the pre-implementation phase highlighted challenges and opportunities regarding integrating this program into SCD care. These findings will inform adaptation and further testing of FUTURES to ensure effective implementation of this novel education program., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Society of Pediatric Psychology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Objectives: Successful implementation of machine learning-augmented clinical decision support systems (ML-CDSS) in perioperative care requires the prioritization of patient-centric approaches to ensure alignment with societal expectations. We assessed general public and surgical patient attitudes and perspectives on ML-CDSS use in perioperative care., Materials and Methods: A sequential explanatory study was conducted. Stage 1 collected public opinions through a survey. Stage 2 ascertained surgical patients' experiences and attitudes via focus groups and interviews., Results: For Stage 1, a total of 281 respondents' (140 males [49.8%]) data were considered. Among participants without ML awareness, males were almost three times more likely than females to report more acceptance (OR = 2.97; 95% CI, 1.36-6.49) and embrace (OR = 2.74; 95% CI, 1.23-6.09) of ML-CDSS use by perioperative teams. Males were almost twice as likely as females to report more acceptance across all perioperative phases with ORs ranging from 1.71 to 2.07. In Stage 2, insights from 10 surgical patients revealed unanimous agreement that ML-CDSS should primarily serve a supportive function. The pre- and post-operative phases were identified explicitly as forums where ML-CDSS can enhance care delivery. Patients requested for education on ML-CDSS's role in their care to be disseminated by surgeons across multiple platforms., Discussion and Conclusion: The general public and surgical patients are receptive to ML-CDSS use throughout their perioperative care provided its role is auxiliary to perioperative teams. However, the integration of ML-CDSS into perioperative workflows presents unique challenges for healthcare settings. Insights from this study can inform strategies to support large-scale implementation and adoption of ML-CDSS by patients in all perioperative phases. Key strategies to promote the feasibility and acceptability of ML-CDSS include clinician-led discussions about ML-CDSS's role in perioperative care, established metrics to evaluate the clinical utility of ML-CDSS, and patient education., (© The Author(s) 2024. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Background and Aims: Leaf variegation is common in plants and confers diverse adaptive functions. However, its genetic underpinnings remain largely unresolved; this is particularly true for variegation that arises through modified leaf tissue structure that affects light reflection. White clover is naturally polymorphic for structure-based white leaf mark variegation. It therefore provides a useful system in which to examine the genetic basis of this phenotype and to assess potential costs to photosynthetic efficiency resulting from modified leaf structures. In this study, we sought to map the loci controlling the white leaf mark in white clover and to evaluate the relationship between white leaf mark, leaf thickness and photosynthetic efficiency., Methods: We generated a high-density genetic linkage map from an F3 mapping population, using reference genome-based single nucleotide polymorphism markers. White leaf mark was quantified through detailed phenotypic evaluations alongside leaf thickness to test how tissue thickness might affect the variegation phenotype. Mapping of quantitative trait loci was performed to characterize their genetic basis. Photosynthetic efficiency measurements were used to test for physiological trade-offs between variegation and photosynthetic output., Key Results: The V locus, a major gene responsible for the white leaf mark polymorphism, was mapped to the distal end of chromosome 5, and several modifier loci were also mapped that contribute additively to the intensity of variegation. The presence and intensity of white leaf mark were associated with greater leaf thickness; however, increased variegation did not affect photosynthetic efficiency detectably., Conclusions: We have successfully mapped the major locus governing the white leaf mark in white clover, along with several modifier loci, revealing a complex basis for this structure-based variegation. The apparent absence of compromised photosynthesis in variegated leaves challenges the notion that variegation creates fitness trade-offs between photosynthetic efficiency and other adaptive functions. This finding suggests that other factors might maintain the white leaf mark polymorphism in white clover., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Objective: Early detection of surgical complications allows for timely therapy and proactive risk mitigation. Machine learning (ML) can be leveraged to identify and predict patient risks for postoperative complications. We developed and validated the effectiveness of predicting postoperative complications using a novel surgical Variational Autoencoder (surgVAE) that uncovers intrinsic patterns via cross-task and cross-cohort presentation learning., Materials and Methods: This retrospective cohort study used data from the electronic health records of adult surgical patients over 4 years (2018-2021). Six key postoperative complications for cardiac surgery were assessed: acute kidney injury, atrial fibrillation, cardiac arrest, deep vein thrombosis or pulmonary embolism, blood transfusion, and other intraoperative cardiac events. We compared surgVAE's prediction performance against widely-used ML models and advanced representation learning and generative models under 5-fold cross-validation., Results: 89 246 surgeries (49% male, median [IQR] age: 57 [45-69]) were included, with 6502 in the targeted cardiac surgery cohort (61% male, median [IQR] age: 60 [53-70]). surgVAE demonstrated generally superior performance over existing ML solutions across postoperative complications of cardiac surgery patients, achieving macro-averaged AUPRC of 0.409 and macro-averaged AUROC of 0.831, which were 3.4% and 3.7% higher, respectively, than the best alternative method (by AUPRC scores). Model interpretation using Integrated Gradients highlighted key risk factors based on preoperative variable importance., Discussion and Conclusion: Our advanced representation learning framework surgVAE showed excellent discriminatory performance for predicting postoperative complications and addressing the challenges of data complexity, small cohort sizes, and low-frequency positive events. surgVAE enables data-driven predictions of patient risks and prognosis while enhancing the interpretability of patient risk profiles., (© The Author(s) 2024. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

In this review, we focus on how purple non sulfur bacteria (PNSB) can be leveraged for sustainable bioproduction to support the circular economy (CE). We discuss the state of the field with respect to the use of purple bacteria for energy production, their role in wastewater treatment, as a fertilizer, and as a chassis for bioplastic production. We explore their ability to serve as single cell protein and production platforms for fine chemicals from waste materials. We also introduce more avant-garde technologies that leverage the unique metabolisms of purple bacteria, including microbial electrosynthesis and co-culture. These technologies will be pivotal in our efforts to mitigate climate change and circularize the economy in the next two decades., (© The Author(s) 2024. Published by Oxford University Press on behalf of Society of Industrial Microbiology and Biotechnology.)

Cross-national comparisons of dementia prevalence are essential for identifying unique determinants and cultural-specific risk factors, but methodological differences in dementia classification across countries hinder global comparisons. This study maps the 10/66 algorithm for dementia classification, widely used and validated in low- and middle-income countries (LMICs), to the U.S. Aging, Demographics, and Memory Study (ADAMS), the dementia sub-study of the Health and Retirement Study, and assesses its performance in ADAMS. We identified the subset of 10/66 algorithm items comparably measured in ADAMS, then used these items to re-train the 10/66 algorithm against the ADAMS clinical dementia diagnosis, employing k-fold cross-validation to assess performance. We compared the modified 10/66 algorithm to four other dementia classification algorithms previously validated in ADAMS, both for overall dementia estimation as well as for estimating education gradients. The modified 10/66 algorithm had higher sensitivity (87%) and specificity (93%) than the comparison algorithms. All of the algorithms over-estimated the education gradient in dementia, although the modest ADAMS sample size precludes precise comparisons of education gradient accuracy. Overall, we found that the modified 10/66 algorithm performs well in classifying dementia status in the U.S. Our results support the validity of risk factor comparisons between U.S. and 10/66 LMIC dementia datasets., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: Among patients with structural heart disease with ventricular tachycardia (VT) refractory to medical therapy and catheter ablation, cardiac stereotactic body radiotherapy (SBRT) is a paradigm-changing treatment option., Aims: To assess the efficacy of cardiac SBRT in refractory VT by comparing the rates of VT episodes, anti-tachycardia pacing (ATP) therapies, and implantable cardioverter-defibrillator (ICD) shocks post-SBRT with pre-SBRT., Methods: We performed a comprehensive literature search and included all clinical studies reporting outcomes on cardiac SBRT for VT. Treatment efficacy was evaluated as random-effects pooled rate-ratios of VT episodes, ATP therapies and ICD shocks post-SBRT (after 6-week blanking) and pre-SBRT, with patients serving as their own controls. Post-SBRT overall survival was assessed using Kaplan-Meier method., Results: We included 23 studies published 2017-2024 reporting on 225 patients who received cardiac SBRT, with median follow-up 5.8-28 months. There was significant heterogeneity among the studies for all 3 efficacy endpoints (p<0.00001). The random-effects pooled rate-ratios of VT episodes, ATP therapies and ICD shocks post- versus pre-SBRT were 0.10 (95% CI 0.06, 0.16), 0.09 (0.05, 0.15), and 0.09 (0.05, 0.17), respectively (all p<0.00001). The most common reported complications included pericardial (8.0%, including 0.9% late gastroesophageo-pericardial fistula) and pulmonary (5.8%). There was no change in left ventricular ejection fraction post-SBRT (p=0.3) but some studies reported an increase in mitral regurgitation. The combined 3-, 12- and 24-month overall patient survival was 0.86 (0.80, 0.90), 0.72 (0.65, 0.78) and 0.57 (0.47, 0.67) respectively., Conclusion: Among patients with refractory VT in context of structural heart disease, VT burden and ICD shocks are dramatically reduced following cardiac SBRT. The overall mortality in this population with heart failure and refractory VT receiving palliative cardiac SBRT remains high., (© The Author(s) 2024. Published by Oxford University Press on behalf of the European Society of Cardiology.)

Elevated human chorionic gonadotropin (hCG) of unknown etiology is often a diagnostic dilemma. Determination of its source is vital in order to provide proper medical treatment and prevent possible unneeded therapeutic interventions. The differential diagnosis for elevated hCG is broad and includes pregnancy, chronic kidney disease, heterophile antibody, macro-hCG, exogenous hCG administration, pituitary secretion, tumor-associated secretion, etc. One entity that is emerging in the published literature as a cause of elevated hCG is familial hCG syndrome. This syndrome is characterized by persistently elevated concentrations from a yet to be determined source in individuals of the same family. In this special report, we review a recently published case of elevated hCG in a 56-year-old male proposed to be due to familial hCG syndrome. We discuss why we feel the presented case is not consistent with familial hCG syndrome and explore other possible explanations for the patient's elevated hCG concentrations., (© Association for Diagnostics & Laboratory Medicine 2024. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Background: Clostridioides difficile infection (CDI) causes substantial mortality and healthcare burden. We assessed the detoxified toxin-A/B PF-06425090 vaccine for primary CDI prevention., Methods: This phase 3 observer-blinded study randomized (1:1) ≥50-year-olds at increased CDI risk (N = 17 535) to receive 3 PF-06425090 or placebo doses (0, 1, and 6 months). Primary end points were first CDI episode (≥3 unformed stools within 24 hours; central laboratory-confirmed toxin A/B positive) ≥14 days post-dose 3 (PD3; first primary) and post-dose 2 (PD2; second primary). CDI duration, need for CDI-related medical attention (secondary end points), and antibiotic use (post hoc analysis) PD3 were evaluated. Tolerability and safety were assessed., Results: The primary end point was not met (17 PF-06425090 and 25 placebo recipients had first CDI episode ≥14 days PD3 [vaccine efficacy (VE) = 31.0% (96.4% confidence interval [CI], -38.7% to 66.6%)]; 24 PF-06425090 and 34 placebo recipients had first CDI episode ≥14 days PD2 [VE = 28.6% (96.4% CI, -28.4% to 61.0%)]. Median CDI duration was lower with PF-06425090 (1 day) versus placebo (4 days; 2-sided nominal P = .02). Of participants with first CDI episode, 0 PF-06425090 and 11 placebo recipients sought CDI-related medical attention (post hoc analysis estimated VE = 100%; 95% CI, 59.6% to 100.0%) and 0 PF-06425090 and 10 placebo recipients required antibiotic treatment (VE = 100%; 95% CI, 54.8% to 100.0%). Local reactions were more frequent in PF-06425090 recipients, and systemic events were generally similar between groups; most were mild to moderate. Adverse event rates were similar between groups., Conclusions: Three PF-06425090 doses were safe and well tolerated. Although the primary end point was not met, PF-06425090 reduced symptom duration, CDI that required medical attention, and CDI-directed antibiotic treatment, highlighting its potential to reduce CDI-associated healthcare burden., Clinical Trials Registration: NCT03090191., Competing Interests: Potential conflicts of interest. C. J. D. receives research support from Pfizer, Clorox, and Ecolab. E. R. D. receives research support from Theriva Biologics, Ferring, and Pfizer and is a consultant for Merck, Pfizer, Seres, Ferring, AstraZeneca, Abbott, Summit, and GSK. N. P. K. receives research support from Pfizer, Merck, Sanofi Pasteur, and GSK. E. G. L. receives research support from Pfizer. K. S. reports no conflicts of interest. M. H. W. has received consulting fees from Ferring, GSK, Nestlé, Paion, Pfizer, Phico Therapeutics, Qpex Biopharma, Seres, Summit, Tillotts, and Vedanta; lecture fees from GSK, Pfizer, Seres, and Tillotts; and grant support from GSK, Pfizer, Seres, Summit, the European Tissue Symposium, and Tillotts. J. L., S. B., H. Z., K. K., R. B., H. M. S., S. L., E. L., W. V. K., M. W. P. C. W., A. S. A., K. U. J., W. C. G., and N. K. are current or former employees of Pfizer and may hold stock or stock options. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed., (© The Author(s) 2024. Published by Oxford University Press on behalf of Infectious Diseases Society of America.)

Background and Objectives: Selective pressures on human childbirth have led to the evolution of cooperative birth practices, with birth attendants playing a crucial role in providing emotional support during labor., Methodology: We leveraged COVID-19-related healthcare disruptions to investigate the impact of the evolutionary mismatch in the availability of emotional support persons on perceived birth stress among a US-based convenience sample ( N  = 1082)., Results: Individuals who stated during pregnancy that they desired support from their partner or a doula but who did not receive this support had significantly higher perceived childbirth stress ( B  = 12.5, P  < .0001; and B  = 5.2, P  = .02, respectively, measured on a scale of 0-100). The absence of any support persons ( B  = 6.7, P  < .001), the number of emotional support persons present ( B  = -5.8 for each additional support person, P  = .01), and the feeling that the healthcare provider was busy or distracted during labor ( B  = 15, P  < .001) was significantly associated with childbirth stress. Virtual support did not attenuate these effects., Conclusions and Implications: Not being able to have desired emotional support during labor was associated with significantly higher childbirth stress, even after adjusting for clinical childbirth complications. These effect sizes were substantial, comparable to the elevated stress associated with cesarean section delivery and other childbirth complications. These findings underscore the importance of preventing an evolutionary mismatch in emotional needs during labor by ensuring access to continuous support, even during public health emergencies., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Foundation for Evolution, Medicine, and Public Health.)

Although the public health field has increasingly studied the collateral consequences of incarceration, we know little about the health consequences of other forms of criminal legal contact, including probation and parole. Understanding spatial and racial-ethnic variation in probation/parole across US states provides new insights into how community supervision impacts population health disparities. However, state-level probation/parole prevalence has not been adequately described. Using data from the Bureau of Justice Statistics and the Census for the years 2001 to 2018, we provide the first state-level estimates of probation and parole populations by race over time in the US. We find large variation in disparities across states and time that is masked by national-level estimates. The US probation population decreased, and its racial composition remained steady between 2001 and 2018. However, in all but five states, the Black-White gap in probation rates declined. The Black-White gap in parole rates declined in all but seven states. The extent to which these race-specific changes in probation or parole over time reflect adjudication processes favoring White people, and/or affect population health, warrant further investigation., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health.)

Arousal states are thought to influence many aspects of cognition and behavior by broadly modulating neural activity. Many studies have observed arousal-related modulations of alpha (~8 to 15 Hz) and gamma (~30 to 50 Hz) power and coherence in local field potentials across relatively small groups of brain regions. However, the global pattern of arousal-related oscillatory modulation in local field potentials is yet to be fully elucidated. We simultaneously recorded local field potentials in numerous cortical and subcortical regions in the primate brain and assessed oscillatory activity and inter-regional coherence associated with arousal state. In high arousal states, we found a uniquely strong and coherent gamma oscillation between the amygdala and basal forebrain. In low arousal rest-like states, a relative increase in coherence at alpha frequencies was present across sampled brain regions, with the notable exception of the medial temporal lobe. We consider how these patterns of activity may index arousal-related brain states that support the processing of incoming sensory stimuli during high arousal states and memory-related functions during rest., (© The Author(s) 2024. Published by Oxford University Press.)

This study examined how race/ethnicity, sex/gender, and sexual orientation intersect under interlocking systems of oppression to socially pattern depression among US adults. With cross-sectional data from the 2015-2020 National Survey on Drug Use and Health (n = 234 722), we conducted a design-weighted, multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA) under an intersectional framework to predict past-year and lifetime major depressive episodes (MDEs). With 42 intersectional groups constructed from 7 race/ethnicity, 2 sex/gender, and 3 sexual orientation categories, we estimated age-standardized prevalence and excess or reduced prevalence attributable to 2-way or higher interaction effects. Models revealed heterogeneity across groups, with prevalence ranging from 1.9% to 19.7% (past-year) and 4.5% to 36.5% (lifetime). Approximately 12.7% (past year) and 12.5% (lifetime) of total individual variance was attributable to between-group differences, indicating key relevance of intersectional groups in describing the population distribution of depression. Main effects indicated, on average, that people who were White, women, gay/lesbian, or bisexual had greater odds of MDE. Main effects explained most between-group variance. Interaction effects (past year: 10.1%; lifetime: 16.5%) indicated another source of heterogeneity around main effects average values, with some groups experiencing excess or reduced prevalence compared with main effects expectations. We extend the MAIHDA framework to calculate nationally representative estimates from complex sample survey data using design-weighted, Bayesian methods. This article is part of a Special Collection on Mental Health., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

We introduce PhyloJunction, a computational framework designed to facilitate the prototyping, testing, and characterization of evolutionary models. PhyloJunction is distributed as an open-source Python library that can be used to implement a variety of models, thanks to its flexible graphical modeling architecture and dedicated model specification language. Model design and use are exposed to users via command-line and graphical interfaces, which integrate the steps of simulating, summarizing, and visualizing data. This article describes the features of PhyloJunction-which include, but are not limited to, a general implementation of a popular family of phylogenetic diversification models-and, moving forward, how it may be expanded to not only include new models, but to also become a platform for conducting and teaching statistical learning., (The Author(s) 2024. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Background: Kidney complications associated with anticancer drug therapy have greatly increased recently. We aimed to investigate the real-world clinical outcomes of anticancer drug therapy-associated renal complications in Japan using the national kidney biopsy database, Japan Renal Biopsy Registry (J-RBR)., Methods: From 2018 to 2021, 449 cases from 49 facilities identified as 'drug-induced' histopathology in the J-RBR were screened, of which a total of 135 were confirmed as anticancer drug-related cases and included in the analysis. Overall survival rates were estimated using the Kaplan-Meier method and compared by logrank test. The Cox regression model was used to evaluate the association between variables and deaths., Results: The most common primary sites of malignancies were the lung (33.3%), followed by gastrointestinal (16.3%) and gynaecological (11.1%) cancers. Tubulointerstitial nephritis (TIN; 47.4%) and thrombotic microangiopathy (TMA; 35.6%) were the most frequent diagnoses. All immunoglobulin A nephropathy, minimal change disease and crescentic glomerulonephritis (CrGN) cases were immune checkpoint inhibitor related. All CrGN cases were anti-neutrophil cytoplasmic antibody negative. Antibiotics were most frequently used concomitantly with anticancer drugs in TMA cases among subgroups (TMA versus others: 62.5 versus 27.5%; P  < .001). Among TMA cases, the serum lactate dehydrogenase level tended to be higher in cytotoxic agent-associated TMA (CTx-TMA) than in other TMAs, but was not significant between groups (415.5 versus 219.0 U/l; P  = .06). Overall survival was worse in CTx-TMA than in other TMAs ( P  = .007). The Cox model demonstrated proton pump inhibitor (PPI) use (hazard ratio 2.49, P  = .001) as a significant prognostic factor, as well as the presence of metastasis and serum albumin level., Conclusions: Our registry analysis highlighted various presentations of biopsy-proven kidney complications associated with anticancer drug therapy. Clinicians should be aware of worse outcomes associated with CTx-TMA and the prognostic role of PPI use., Competing Interests: None declared., (© The Author(s) 2024. Published by Oxford University Press on behalf of the ERA.)

Background: clinical guidelines recommend initiation of antiviral therapy as soon as possible for patients hospitalized with confirmed or suspected influenza., Methods: A multicenter US observational sentinel surveillance network prospectively enrolled adults (aged ≥18 years) hospitalized with laboratory-confirmed influenza at 24 hospitals during October 1, 2022-July 21, 2023. A multivariable proportional odds model was used to compare peak pulmonary disease severity (no oxygen support, standard supplemental oxygen, high-flow oxygen/non-invasive ventilation, invasive mechanical ventilation, or death) after the day of hospital admission among patients starting oseltamivir treatment on the day of admission (early) versus those who did not (late or not treated), adjusting for baseline (admission day) severity, age, sex, site, and vaccination status. Multivariable logistic regression models were used to evaluate the odds of intensive care unit (ICU) admission, acute kidney replacement therapy or vasopressor use, and in-hospital death., Results: A total of 840 influenza-positive patients were analyzed, including 415 (49%) who started oseltamivir treatment on the day of admission, and 425 (51%) who did not. Compared with late or not treated patients, those treated early had lower peak pulmonary disease severity (proportional aOR: 0.60, 95% CI: 0.49-0.72), and lower odds of intensive care unit admission (aOR: 0.24, 95% CI: 0.13-0.47), acute kidney replacement therapy or vasopressor use (aOR: 0.40, 95% CI: 0.22-0.67), and in-hospital death (aOR: 0.36, 95% CI: 0.18-0.72)., Conclusion: Among adults hospitalized with influenza, treatment with oseltamivir on day of hospital admission was associated reduced risk of disease progression, including pulmonary and extrapulmonary organ failure and death., (Published by Oxford University Press on behalf of Infectious Diseases Society of America 2024.)

Pediatric hospitals are uniquely positioned to be impacted by antimicrobial waste. To explore this issue, we reviewed the current literature to identify the reasons, costs, and potential solutions to waste. Identified reasons for waste included weight-based dosing, medication order changes due to changing patient status, loss or expiration of doses, and medication errors. The cost of waste included financial costs, promotion of antimicrobial resistance, and generation of greenhouse gases. Proposed interventions to reduce waste included an early switch from intravenous to oral administration, required stop dates, standardized dosing times, and optimization of the pharmacy batching process. However, additional studies are needed to assess the potential correlation between these proposed interventions and waste reduction. Antimicrobial stewardship programs have been identified as a group that can play a crucial role in partnering to implement these interventions to potentially reduce antimicrobial waste and promote better healthcare sustainability., (© The Author(s) 2024. Published by Oxford University Press on behalf of The Journal of the Pediatric Infectious Diseases Society. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Psychedelics (e.g., 3,4-Methylenedioxymethamphetamine [MDMA], lysergic acid diethylamide [LSD], psilocybin) are molecules that have the potential to produce rapid therapeutic effects when paired with psychotherapy. Randomized clinical trials of psychedelic-assisted psychotherapy (PAT) have shown promising results for post-traumatic stress disorder (PTSD), depression, and substance use disorders. The U.S. Food and Drug Administration has acknowledged the promise of PAT, signaling potential approval of psilocybin-assisted therapy for depression by 2026. Given this timeline, implementation scientists must engage with PAT researchers, policymakers, and practitioners to think critically about bringing these promising new treatments into routine practice settings while maintaining quality and safety. This commentary aims to initiate a dialogue between implementation scientists and PAT researchers and practitioners on addressing these questions with a lens toward equity. Specifically, we discuss how the field of implementation science can support PAT stakeholders to accelerate the translational process from research into practice, focusing specifically on safety-net settings (i.e., Federally Qualified Health Centers and Veterans Affairs health systems) that serve historically marginalized populations. We use the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) Framework to illustrate five critical areas where implementation science can help move PAT from research into real-world practice. For each RE-AIM dimension, we highlight ways the field of implementation science can contribute tools (e.g., implementation strategies), methodologies (e.g., pragmatic hybrid implementation-effectiveness trials), and approaches (community-based participatory research) for establishing the safety, effectiveness, and accessibility of PAT for historically underserved communities., (© Society of Behavioral Medicine 2024. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Diet profoundly influences the composition of an animal's microbiome, especially in holometabolous insects, offering a valuable model to explore the impact of diet on gut microbiome dynamics throughout metamorphosis. Here, we use monarch butterflies (Danaus plexippus), specialist herbivores that feed as larvae on many species of chemically well-defined milkweed plants (Asclepias sp.), to investigate the impacts of development and diet on the composition of the gut microbial community. While a few microbial taxa are conserved across life stages of monarchs, the microbiome appears to be highly dynamic throughout the life cycle. Microbial diversity gradually diminishes throughout the larval instars, ultimately reaching its lowest point during the pupal stage and then recovering again in the adult stage. The microbial composition then undergoes a substantial shift upon the transition from pupa to adult, with female adults having significantly different microbial communities than the eggs that they lay, indicating limited evidence for vertical transmission of gut microbiota. While diet did not significantly impact overall microbial composition, our results suggest that fourth instar larvae exhibit higher microbial diversity when consuming milkweed with high concentrations of toxic cardenolide phytochemicals. This study underscores how diet and developmental stage collectively shape the monarch's gut microbiota., (© The Author(s) 2024. Published by Oxford University Press on behalf of FEMS.)

The role of Notch signaling in direct neuronal reprogramming remains unknown despite its importance to brain development in vivo. Here, we use microRNA-induced neurons that are directly reprogrammed from human fibroblasts to determine how Notch signaling contributes to neuronal identity. We found that Notch inhibition during the first week of reprogramming was both necessary and sufficient to enhance neurite outgrowth at a later timepoint, indicating an important role in erasure of the original cell identity. Accordingly, transcriptomic analysis showed that the effect of Notch inhibition was likely due to improvements in fibroblast fate erasure and silencing of non-neuronal genes. To this effect, we identify MYLIP, whose downregulation in response to Notch inhibition significantly promoted neurite outgrowth. Moreover, Notch inhibition resulted in cells with neuronal transcriptome signature defined by expressing long genes at a faster rate than the control, demonstrating the effect of accelerated fate erasure on neuronal fate acquisition. Our results demonstrate the antagonistic role of Notch signaling to the pro-neuronal microRNAs 9 and 124 and the benefits of its inhibition to the acquisition of neuronal morphology., (© The Author(s) 2024. Published by Oxford University Press. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

The spatial and environmental features of regions where clades are evolving are expected to impact biogeographic processes such as speciation, extinction, and dispersal. Any number of regional features (such as elevation, distance, area, etc.) may be directly or indirectly related to these processes. For example, it may be that distances or differences in elevation or both may limit dispersal rates. However, it is difficult to disentangle which features are most strongly related to rates of different processes. Here, we present an extensible Multi-feature Feature-Informed GeoSSE (MultiFIG) model that allows for the simultaneous investigation of any number of regional features. MultiFIG provides a conceptual framework for incorporating large numbers of features of different types, including categorical, quantitative, within-region, and between-region features, along with a mathematical framework for translating those features into biogeographic rates for statistical hypothesis testing. Using traditional Bayesian parameter estimation and reversible-jump Markov chain Monte Carlo, MultiFIG allows for the exploration of models with different numbers and combinations of feature-effect parameters, and generates estimates for the strengths of relationships between each regional feature and core process. We validate this model with a simulation study covering a range of scenarios with different numbers of regions, tree sizes, and feature values. We also demonstrate the application of MultiFIG with an empirical case study of the South American lizard genus Liolaemus, investigating sixteen regional features related to area, distance, and elevation. Our results show two important feature-process relationships: a negative distance/dispersal relationship, and a negative area/extinction relationship. Interestingly, although speciation rates were found to be higher in Andean versus non-Andean regions, the model did not assign significance to Andean- or elevation-related parameters. These results highlight the need to consider multiple regional features in biogeographic hypothesis testing., (© The Author(s) 2024. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Background: Intravenous (IV) fluid contamination within clinical specimens causes an operational burden on the laboratory when detected, and potential patient harm when undetected. Even mild contamination is often sufficient to meaningfully alter results across multiple analytes. A recently reported unsupervised learning approach was more sensitive than routine workflows, but still lacked sensitivity to mild but significant contamination. Here, we leverage ensemble learning to more sensitively detect contaminated results using an approach which is explainable and generalizable across institutions., Methods: An ensemble-based machine learning pipeline of general and fluid-specific models was trained on real-world and simulated contamination and internally and externally validated. Benchmarks for performance assessment were derived from in silico simulations, in vitro experiments, and expert review. Fluid-specific regression models estimated contamination severity. SHapley Additive exPlanation (SHAP) values were calculated to explain specimen-level predictions, and algorithmic fairness was evaluated by comparing flag rates across demographic and clinical subgroups., Results: The sensitivities, specificities, and Matthews correlation coefficients were 0.858, 0.993, and 0.747 for the internal validation set, and 1.00, 0.980, and 0.387 for the external set. SHAP values provided plausible explanations for dextrose- and ketoacidosis-related hyperglycemia. Flag rates from the pipeline were higher than the current workflow, with improved detection of contamination events expected to exceed allowable limits for measurement error and reference change values., Conclusions: An accurate, generalizable, and explainable ensemble-based machine learning pipeline was developed and validated for sensitively detecting IV fluid contamination. Implementing this pipeline would help identify errors that are poorly detected by current clinical workflows and a previously described unsupervised machine learning-based method., (© Association for Diagnostics & Laboratory Medicine 2024. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Basic leucine zipper transcription factor ATF-like 2 (BATF2) is a transcription factor that is known to exhibit tumor-suppressive activity in cancer cells. Within recent years, however, BATF2 has also emerged as an important transcriptional regulator of the immune system. Through its immunomodulatory function, BATF2 has been implicated in a variety of (patho)physiological processes, including host defense against infection, anti-tumor immunity, and maintenance of tissue inflammatory homeostasis. Below, we discuss recent literature that has provided insight into the role of BATF2 as a transcriptional regulator of immune responses in health and disease, including the cell types that express BATF2, the different diseases in which the immunomodulatory effects of BATF2 have been shown to play a role, and the molecular mechanisms through which BATF2 is thought to exert those effects. In doing so, we highlight that the immunological effects of BATF2 are highly context-dependent, and we point out overlap between the mechanisms of action of BATF2 in infectious disease and non-infectious disease. We also discuss areas of interest for future research, the clinical relevance of better understanding BATF2 function, and potential strategies for therapeutic modulation of BATF2., (© The Author(s) 2024. Published by Oxford University Press on behalf of Society for Leukocyte Biology. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Background: Machine learning solutions offer tremendous promise for improving clinical and laboratory operations in pathology. Proof-of-concept descriptions of these approaches have become commonplace in laboratory medicine literature, but only a scant few of these have been implemented within clinical laboratories, owing to the often substantial barriers in validating, implementing, and monitoring these applications in practice. This mini-review aims to highlight the key considerations in each of these steps., Content: Effective and responsible applications of machine learning in clinical laboratories require robust validation prior to implementation. A comprehensive validation study involves a critical evaluation of study design, data engineering and interoperability, target label definition, metric selection, generalizability and applicability assessment, algorithmic fairness, and explainability. While the main text highlights these concepts in broad strokes, a supplementary code walk-through is also provided to facilitate a more practical understanding of these topics using a real-world classification task example, the detection of saline-contaminated chemistry panels.Following validation, the laboratorian's role is far from over. Implementing machine learning solutions requires an interdisciplinary effort across several roles in an organization. We highlight the key roles, responsibilities, and terminologies for successfully deploying a validated solution into a live production environment. Finally, the implemented solution must be routinely monitored for signs of performance degradation and updated if necessary., Summary: This mini-review aims to bridge the gap between theory and practice by highlighting key concepts in validation, implementation, and monitoring machine learning solutions effectively and responsibly in the clinical laboratory., (© Association for Diagnostics & Laboratory Medicine 2024.)

Introduction: The rapid advancement of artificial intelligence (AI) has led to significant transformations in health and healthcare. As AI technologies continue to evolve, there is an urgent need to establish a unified framework that guides the design, implementation, and evaluation of AI-driven interventions across individual and population health contexts., Approach: In response to this need, the National Academy of Medicine (NAM) has initiated the development of an AI code of conduct (AICC) through its Digital Health Action Collaborative. This code of conduct is grounded in shared principles and commitments, aiming to actualize ethical and effective AI practices within the broader health and healthcare ecosystem. Given its specialized expertise and insight, the biomedical informatics (BMI) community plays a pivotal role in shaping and applying these guidelines., Recommendations: We, as members of the AICC Steering Committee and the NAM Digital Health Action Collaborative, urge BMI educators, researchers, and practitioners to engage actively in refining and implementing the AICC. This involvement is critical to ensuring that the code is robust, applicable, and continuously improved to meet the evolving challenges facing health and healthcare., (© The Author(s) 2024. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Stem cell-derived islets (SC-islets) offer the potential to be an unlimited source of cells for disease modeling and the treatment of diabetes. SC-islets can be genetically modified, treated with chemical compounds, or differentiated from patient derived stem cells to model diabetes. These models provide insights into disease pathogenesis and vulnerabilities that may be targeted to provide treatment. SC-islets themselves are also being investigated as a cell therapy for diabetes. However, the transplantation process is imperfect; side effects from immunosuppressant use have reduced SC-islet therapeutic potential. Alternative methods to this include encapsulation, use of immunomodulating molecules, and genetic modification of SC-islets. This review covers recent advances using SC-islets to understand different diabetes pathologies and as a cell therapy., (© The Author(s) 2024. Published by Oxford University Press.)

Motivation: Multi-omics data, i.e. genomics, epigenomics, transcriptomics, proteomics, characterize cellular complex signaling systems from multi-level and multi-view and provide a holistic view of complex cellular signaling pathways. However, it remains challenging to integrate and interpret multi-omics data for mining critical biomarkers. Graph AI models have been widely used to analyze graph-structure datasets, and are ideal for integrative multi-omics data analysis because they can naturally integrate and represent multi-omics data as a biologically meaningful multi-level signaling graph and interpret multi-omics data via graph node and edge ranking analysis. Nevertheless, it is nontrivial for graph-AI model developers to pre-analyze multi-omics data and convert the data into biologically meaningful graphs, which can be directly fed into graph-AI models., Results: To resolve this challenge, we developed mosGraphGen (multi-omics signaling graph generator), generating Multi-omics Signaling graphs (mos-graph) of individual samples by mapping multi-omics data onto a biologically meaningful multi-level background signaling network with data normalization by aggregating measurements and aligning to the reference genome. With mosGraphGen, AI model developers can directly apply and evaluate their models using these mos-graphs. In the results, mosGraphGen was used and illustrated using two widely used multi-omics datasets of The Cancer Genome Atlas (TCGA) and Alzheimer's disease (AD) samples., Availability and Implementation: The code of mosGraphGen is open-source and publicly available via GitHub: https://github.com/FuhaiLiAiLab/mosGraphGen., Competing Interests: The authors declare no conflict of interest., (© The Author(s) 2024. Published by Oxford University Press.)

For population-wide impact of interventions, evidence-based programs must be successfully disseminated and adopted at scale. Research-practice partnerships can legitimize programs and support organizational adoption, however, ways of leveraging the contributions of partners during dissemination processes are less clear. TransformUs is a school-based physical activity and sedentary behaviour program, and since 2018, has been disseminated at scale to all primary schools in Victoria, Australia, in partnership with 16 state and national organizations. The study objective was to investigate the experiences of partner organizations disseminating TransformUs within their networks, and factors associated with awareness and adoption of the program in schools, from the perspective of partner organizations. Semi-structured interviews with representatives from 15 (out of 16) partner organizations in 2019 involved in disseminating TransformUs state-wide. An interview guide was informed by the RE-AIM framework. Interviews were audio-recorded, transcribed, and coded anonymously. Data were analysed thematically. Four themes (and 13 sub-themes) were identified: (i) organizational barriers and facilitators to dissemination; (ii) implementation support for partners; (iii) overall research experience; and (iv) dissemination strategy. Partners used multiple dissemination channels to increase adoption, and strong alignment between TransformUs and the partner organization's goals appeared to enable dissemination. Partners outlined several local, regional, and state organizations to partner with, and offered suggestions regarding preferred content and timing of dissemination activities for their networks. Researchers planning research-practice partnerships should proactively consider organizational barriers partners may face during dissemination. Regular communication and feedback on dissemination outcomes may contribute to positive research-practice experiences and allow for tailored dissemination strategies., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Society of Behavioral Medicine.)

Multicomponent, community-based programs aiming to improve health behaviors in youth are needed but can be challenging to implement. Research is needed to better understand the factors that facilitate and inhibit effective implementation of these programs especially for youth at increased risk of health disparities. This study aimed to identify and explore the implementation determinants and outcomes of a multicomponent health intervention conducted from 2021 to 2022 for middle school students living in underserved communities in Philadelphia, PA, USA. Mixed methods approaches, including self-report surveys and semi-structured qualitative interviews, were administered to 18 members of the implementation staff at the end of the program, including coaches (n = 7), assistant coaches (n = 2), school champions (n = 6), administrative leaders (n = 2), and a school district administrator (n = 1). Survey and interview questions were guided by the Consolidated Framework for Implementation Research (CFIR), and interviews were thematically coded following transcription based on 26 CFIR constructs. Innovation source, evidence strength and quality, cosmopolitanism, and the personal attributes of individuals were key constructs associated with implementation effectiveness. Data revealed three multidimensional themes that highlighted broader challenges influencing implementation: (i) broad consensus, different interpretations, (ii) staffing challenges, and (iii) continuity is key. The need for the program was clearly recognized and overall belief in the purpose of the intervention was strong among key program staff and administration. However, issues including limited engagement with training, staffing turnover, and the rotational programming design hindered implementation. Future projects aiming to implement multicomponent after-school time interventions must ensure a consistent vision among partners and continuity in program delivery., (© Society of Behavioral Medicine 2024. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Alternative complex III (ACIII) couples quinol oxidation and electron acceptor reduction with potential transmembrane proton translocation. It is compositionally and structurally different from the cytochrome bc1/b6f complexes but functionally replaces these enzymes in the photosynthetic and/or respiratory electron transport chains (ETCs) of many bacteria. However, the true compositions and architectures of ACIIIs remain unclear, as do their structural and functional relevance in mediating the ETCs. We here determined cryogenic electron microscopy structures of photosynthetic ACIII isolated from Chloroflexus aurantiacus (CaACIIIp), in apo-form and in complexed form bound to a menadiol analog 2-heptyl-4-hydroxyquinoline-N-oxide. Besides 6 canonical subunits (ActABCDEF), the structures revealed conformations of 2 previously unresolved subunits, ActG and I, which contributed to the complex stability. We also elucidated the structural basis of menaquinol oxidation and subsequent electron transfer along the [3Fe-4S]-6 hemes wire to its periplasmic electron acceptors, using electron paramagnetic resonance, spectroelectrochemistry, enzymatic analyses, and molecular dynamics simulations. A unique insertion loop in ActE was shown to function in determining the binding specificity of CaACIIIp for downstream electron acceptors. This study broadens our understanding of the structural diversity and molecular evolution of ACIIIs, enabling further investigation of the (mena)quinol oxidoreductases-evolved coupling mechanism in bacterial energy conservation., Competing Interests: Conflict of interest statement. The authors declare no conflict of interest., (© The Author(s) 2024. Published by Oxford University Press on behalf of American Society of Plant Biologists. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Objectives: To improve firearm injury encounter classification (new vs follow-up) using machine learning (ML) and compare our ML model to other common approaches., Materials and Methods: This retrospective study used data from the St Louis region-wide hospital-based violence intervention program data repository (2010-2020). We randomly selected 500 patients with a firearm injury diagnosis for inclusion, with 808 total firearm injury encounters split (70/30) for training and testing. We trained a least absolute shrinkage and selection operator (LASSO) regression model with the following predictors: admission type, time between firearm injury visits, number of prior firearm injury emergency department (ED) visits, encounter type (ED or other), and diagnostic codes. Our gold standard for new firearm injury encounter classification was manual chart review. We then used our test data to compare the performance of our ML model to other commonly used approaches (proxy measures of ED visits and time between firearm injury encounters, and diagnostic code encounter type designation [initial vs subsequent or sequela]). Performance metrics included area under the curve (AUC), sensitivity, and specificity with 95% confidence intervals (CIs)., Results: The ML model had excellent discrimination (0.92, 0.88-0.96) with high sensitivity (0.95, 0.90-0.98) and specificity (0.89, 0.81-0.95). AUC was significantly higher than time-based outcomes, sensitivity was slightly (but not significantly) lower than other approaches, and specificity was higher than all other methods., Discussion: ML successfully delineated new firearm injury encounters, outperforming other approaches in ruling out encounters for follow-up., Conclusion: ML can be used to identify new firearm injury encounters and may be particularly useful in studies assessing re-injuries., (© The Author(s) 2024. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Objectives: To develop and validate a novel measure, action entropy, for assessing the cognitive effort associated with electronic health record (EHR)-based work activities., Materials and Methods: EHR-based audit logs of attending physicians and advanced practice providers (APPs) from four surgical intensive care units in 2019 were included. Neural language models (LMs) were trained and validated separately for attendings' and APPs' action sequences. Action entropy was calculated as the cross-entropy associated with the predicted probability of the next action, based on prior actions. To validate the measure, a matched pairs study was conducted to assess the difference in action entropy during known high cognitive effort scenarios, namely, attention switching between patients and to or from the EHR inbox., Results: Sixty-five clinicians performing 5 904 429 EHR-based audit log actions on 8956 unique patients were included. All attention switching scenarios were associated with a higher action entropy compared to non-switching scenarios (P < .001), except for the from-inbox switching scenario among APPs. The highest difference among attendings was for the from-inbox attention switching: Action entropy was 1.288 (95% CI, 1.256-1.320) standard deviations (SDs) higher for switching compared to non-switching scenarios. For APPs, the highest difference was for the to-inbox switching, where action entropy was 2.354 (95% CI, 2.311-2.397) SDs higher for switching compared to non-switching scenarios., Discussion: We developed a LM-based metric, action entropy, for assessing cognitive burden associated with EHR-based actions. The metric showed discriminant validity and statistical significance when evaluated against known situations of high cognitive effort (ie, attention switching). With additional validation, this metric can potentially be used as a screening tool for assessing behavioral action phenotypes that are associated with higher cognitive burden., Conclusion: An LM-based action entropy metric-relying on sequences of EHR actions-offers opportunities for assessing cognitive effort in EHR-based workflows., (© The Author(s) 2024. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Background: Congenital syphilis disproportionately affects individuals impacted by adverse social determinants of health. Understanding these determinants may help facilitate holistic care., Methods: We performed a retrospective review of mother-infant dyads with potential congenital syphilis in a Missouri hospital system. Cases were classified per Centers for Disease Control and Prevention clinical scenarios. Information was collected regarding demographics, prenatal care, substance use, and other social factors. Dyads with confirmed/highly probable or possible congenital syphilis ("congenital syphilis outcomes") were compared to those with less likely/unlikely congenital syphilis ("noncongenital syphilis outcomes") using descriptive statistics., Results: We identified 131 dyads with infant dates of birth from 2015 to 2022: 74 (56%) with congenital syphilis outcomes and 56 (43%) with noncongenital syphilis outcomes. Most mothers were Black/African American (n = 84 [65%]) and lived in areas with a high Social Vulnerability Index. Many had inadequate prenatal care (n = 61 [47%]) and/or had substance use histories (n = 55 [42%]). Significant associations (odds ratio [95% confidence interval]) with congenital syphilis outcomes included limited prenatal care (3.01 [1.38-6.56]), no prenatal care (16.08 [1.96-132.11]), substance use (3.42 [1.61-7.25]), housing instability (3.42 [1.39-8.38]), and justice system interactions (2.29 [1.00-5.24]). Substance use correlated with prenatal care adequacy (P < .001). One-third of infants with congenital syphilis outcomes were taken into protective custody., Conclusions: Adverse social determinants of health are common in dyads impacted by congenital syphilis. Health systems should consider interdisciplinary programming to improve testing and linkage to care. Future studies should evaluate social support for congenital syphilis prevention and management., Competing Interests: Potential conflicts of interest. The authors: No reported conflicts of interest. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest., (© The Author(s) 2024. Published by Oxford University Press on behalf of Infectious Diseases Society of America. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Background: Acute otitis media (AOM) accounts for roughly 25% of antibiotics prescribed to children annually. Despite national guidelines that recommend short (5-7 days) durations of antibiotics for children 2 years and older with AOM, most receive long (10 day) courses. This study aims to evaluate antibiotic durations prescribed for children aged 2-17 years with uncomplicated AOM across two pediatric academic health systems, and to assess the variability in prescribed durations between and within each system., Methods: Electronic medical record data from 135 care locations at two health systems were retrospectively analyzed. Outpatient encounters for children aged 2-17 years with a diagnosis of AOM from 2019 to 2022 were included. The primary outcome was the percent of 5-day prescriptions. Secondary outcomes included the proportion of 7-day prescriptions, 10-day prescriptions, prescriptions for nonfirst-line antibiotics, cases associated with treatment failure, AOM recurrence, and adverse drug events., Results: Among 73 198 AOM encounters for children 2 years and older, 61 612 (84%) encounters resulted in an antibiotic prescription. Most prescriptions were for 10 days (45 689; 75%), 20% were for 7 days (12 060), and only 5% were for 5 days (3144). Treatment failure, AOM recurrence, adverse drug events, hospitalizations, and office, emergency department or urgent-care visits for AOM within 30 days after the index visit were rare., Conclusions: Despite national guidelines that recommend shorter durations for children with uncomplicated AOM, 75% of our cohort received 10-day durations. Shortening durations of therapy for AOM could reduce antibiotic exposure and should be a priority of pediatric antibiotic stewardship programs., (© The Author(s) 2024. Published by Oxford University Press on behalf of The Journal of the Pediatric Infectious Diseases Society.)

Background: The polypill is an emerging strategy for the prevention and management of cardiovascular disease. We assessed the participation of females in randomised controlled trials evaluating polypills for prevention of cardiovascular disease and subsequent sex-specific analyses and reporting., Methods: Cardiovascular polypill trials were identified through a systematic review. Data were extracted on the use of sex-specific eligibility criteria, female participation, and the conduct, findings, and interpretation of sex-specific analyses., Results: Of 26 trials included, 12 (46%) excluded groups of females, mainly if pregnant or lactating or of childbearing potential. Female participation ranged from 10% to 73% across trials. Overall, 42% of included participants were female. Of 18 trials conducted in a mostly primary prevention population, females represented 49% of trial participants. In mixed or exclusively secondary prevention trials (n=8), females represented 26% of trial participants. Females represented 46% of trial participants in trials that excluded groups of females (n=12). In trials without explicit exclusion criteria (n=13), females represented 32% of trial participants. Nine out of 26 trials reported sex-stratified analyses (35% of trials; 70% of all participants). Of these, two found some evidence for possible sex differences, both reporting larger blood pressure effects in females than males. Four trials provided sex considerations in the discussion section of the report., Conclusion: The participation of females in cardiovascular polypill trials is substantially higher in primary prevention trials as compared to trials conducted in mixed or exclusively secondary prevention populations. The use of sex-specific eligibility criteria was not linked to lower female participation. Sex-specific reporting is sparsely conducted, although most frequent in larger trials., (© The Author(s) 2024. Published by Oxford University Press on behalf of the European Society of Cardiology. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

The brain develops rapidly from the final trimester of gestation through childhood, with cortical surface area expanding greatly in the first decade of life. However, it is unclear exactly where and how cortical surface area changes after birth, or how prematurity affects these developmental trajectories. Fifty-two very preterm (gestational age at birth = 26 ± 1.6 weeks) and 41 full-term (gestational age at birth = 39 ± 1.2 weeks) infants were scanned using structural magnetic resonance imaging at term-equivalent age and again at 9/10 years of age. Individual cortical surface reconstructions were extracted for each scan. Infant and 9/10 cortical surfaces were aligned using anatomically constrained Multimodal Surface Matching (aMSM), a technique that allows calculation of local expansion gradients across the cortical surface for each individual subject. At the neonatal time point, very preterm infants had significantly smaller surface area than their full-term peers ( P < 0.001), but at the age 9/10-year time point, very preterm and full-term children had comparable surface area ( P > 0.05). Across all subjects, cortical expansion by age 9/10 years was most pronounced in frontal, temporal, and supramarginal/inferior parietal junction areas, which are key association cortices ( P < 0.001). Very preterm children showed greater cortical surface area expansion between term-equivalent age and age 9/10 compared to their full-term peers in the medial and lateral frontal areas, precuneus, and middle temporal/banks of the superior sulcus junction ( Spin < 0.05). Furthermore, within the very preterm group, expansion was highly variable within the orbitofrontal cortex and posterior regions of the brain. By mapping these patterns across the cortex, we identify differences in association cortices that are known to be important for executive functioning, emotion processing, and social cognition. Additional longitudinal work will be needed to understand if increased expansion in very preterm children is adaptive, or if differences persist into adulthood.P < 0.05). Furthermore, within the very preterm group, expansion was highly variable within the orbitofrontal cortex and posterior regions of the brain. By mapping these patterns across the cortex, we identify differences in association cortices that are known to be important for executive functioning, emotion processing, and social cognition. Additional longitudinal work will be needed to understand if increased expansion in very preterm children is adaptive, or if differences persist into adulthood., Competing Interests: The authors report no competing interests., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Guarantors of Brain.)

Traits often do not evolve in isolation or vary independently of other traits. Instead, they can be affected by covariation, both within and across species. However, the importance of within-species trait covariation and, critically, the degree to which it varies between species has yet to be thoroughly studied. Brain morphology is a trait of great ecological and behavioral importance, with regions that are hypothesized to vary in size based on behavioral and cognitive demands. Sizes of brain regions have also been shown to covary with each other across various taxa. Here, we test the degree to which covariation in brain region sizes within species has been conserved across 10 teleost fish species. These 10 species span five orders, allowing us to examine how phylogenetic proximity influences similarities in intraspecific trait covariation. Our results showed a trend that similar patterns of brain region size covariation occur in more closely related species. Interestingly, there were certain brain region pairs that showed similar levels of covariation across all species regardless of phylogenetic distance, such as the telencephalon and optic tectum, while others, such as the olfactory bulb and the hypothalamus, varied more independently. Ultimately, the patterns of brain region covariation shown here suggest that evolutionary mechanisms or constraints can act on specific brain regions independently, and that these constraints can change over evolutionary time., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology.)

Over 35% of reproductive-age women in the USA have obesity, putting them at increased risk for numerous obstetric complications due to abnormal labor. While the association between maternal obesity and abnormal labor has been well documented, the mechanisms responsible for this remain understudied. The uterine smooth muscle, myometrium, has high energy needs in order to fuel regular uterine contractions during parturition. However, the precise mechanisms by which the myometrium meets its energy demands has not been defined. Here, our objective was to define the effects of obesity on energy utilization in the myometrium during labor. We generated a mouse model of maternal diet-induced obesity and found that these mice had a higher rate of dystocia than control chow-fed mice. Moreover, compared to control chow-fed mice, DIO mice at term, both before and during labor had lower in vivo spontaneous uterine contractility. Untargeted transcriptomic and metabolomic analyses suggest that diet-induced obesity is associated with elevated long-chain fatty acid uptake and utilization in the uterus, but also an accumulation of medium-chain fatty acids. Diet-induced obesity uteri also had an increase in the abundance of long chain-specific beta-oxidation enzymes, which may be responsible for the observed increase in long-chain fatty acid utilization. This altered energy substrate utilization may be a contributor to the observed contractile dysfunction., (© The Author(s) 2024. Published by Oxford University Press on behalf of Society for the Study of Reproduction. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)