Policy Points The One Big Beautiful Bill Act (OBBBA) may impose the largest coverage losses in US history, causing the number uninsured to rise by 55% in the coming decade. We examined four prior coverage contractions-Reagan-era Medicaid cuts, the 2005 TennCare disenrollment, 2019 Arkansas work requirements, and the Medicaid Unwinding-to shed light on the OBBBA's impacts. These suggest that most who lose Medicaid do not find alternative coverage, and that states are unlikely to compensate for federal cuts, findings that run counter to some assumptions adopted by the Congressional Budget Office in predicting the impacts of Medicaid cuts. Studies of coverage contractions complement data from coverage expansions in predicting worse health care access, household finances, and health for needy individuals due to the OBBBA. Studies also suggest that the magnitude of harms from contractions may exceed that suggested by expansions.

The so-called One Big Beautiful Bill Act signed into law by President Trump on July 4, 2025 will cut $1 trillion from federal health care programs over the coming decade and cause 10 million individuals to become uninsured according to the Congressional Budget Office. Most analyses of the bill's impacts have assumed they would be the inverse of those documented from previous coverage expansions. An examination of past coverage cuts might yield additional insights into the probable impacts of this legislation on the medical care and health of the needy.

We reviewed studies of four prior large scale coverage contractions: Reagan-era Medicaid cuts, the 2005 Tenncare Disenrollment, the 2019 implementation of work requirements in Arkansas, and the postpandemic "Unwinding" of Medicaid.

The experience of these prior coverage contractions complements evidence from analyses of coverage expansions in predicting that widespread insurance loss will lead to a reduction in care utilization, an increase in household financial strain, and worsened physical and mental health for low-income individuals. These coverage contractions additionally suggest that most who lose Medicaid coverage will not find alternative coverage; that work requirements will impose burdensome administrative costs on states; that states are unlikely to offset reductions in federal Medicaid funding with internal funds; and that the second-order effects of coverage losses may, in some instances, be greater (in magnitude) than the benefits seen after coverage expansions.

Cuts to federal health care programs will produce sharp contractions in public coverage that will worsen existing problems in US health care such as insurance churn, degrading care, and worsening health inequality. While states may take some steps to mitigate harmful impacts, better protection of the medically needy would require repeal of the legislation, while full protection would require universal, seamless coverage.

Severe mental illness (SMI) is associated with substantial barriers to competitive employment, including stigma, cognitive impairments, and limited social support. The Individual Placement and Support (IPS) model is an evidence-based intervention that provides individualized assistance for job search, placement, and retention. Although IPS has shown effectiveness in high-income countries, there is limited evidence regarding its feasibility and preliminary outcomes in low- and middle-income settings, particularly in Latin America.

This pilot randomized controlled trial will assess the feasibility of implementing the IPS model for adults with SMI in Jalisco, Mexico. We will recruit 120 participants who are actively seeking employment and randomly assign them to either the IPS intervention or a control group receiving standard employment services. The intervention includes tailored support from trained IPS Employment Specialists in resume building, interview preparation, job search, and follow-up after job placement. Primary feasibility outcomes include recruitment and retention rates, participant acceptance, implementation fidelity, and identification of contextual barriers and facilitators. Secondary outcomes will explore employment status at 12 months, financial well-being, and health-related outcomes.

Findings from this pilot study will contribute to addressing the current gap in implementation research on IPS in Latin America. Findings will offer preliminary insights into the feasibility, acceptability, and contextual adaptability of the model in a public mental health setting. These results are expected to guide the refinement of study procedures and support planning for a future definitive trial. Additionally, exploratory data on employment and quality of life outcomes may help identify relevant domains for further investigation.

ClinicalTrials.gov NCT06019247. Registered on August 31, 2023.

Regular physical activity confers substantial cardiovascular benefits, yet it may in rare cases precipitate sudden cardiac arrest (SCA) or sudden cardiac death (SCD) in predisposed individuals. Although preventive frameworks have largely targeted competitive athletes, the rapidly expanding population of recreational participants remains insufficiently addressed.

Recreational athletes have a low but significant incidence of SCA/SCD (0.02 to 13 per 100,000 person-years). Coronary artery disease is most common in middle-aged individuals, while inherited cardiomyopathies account for fewer cases.

Contemporary preparticipation evaluation for recreational athletes has shifted from universal electrocardiogram-based screening to a risk-stratified, individualized approach emphasizing cardiovascular assessment, symptom recognition, and selective testing based on exercise intensity. Digital and wearable technologies are under evaluation to support symptom-triggered assessment and cardiac rhythm documentation; however, their effectiveness for preventing sports-related SCA/SCD and their optimal clinical workflows remain unproven.

Risk-based, symptom-driven preparticipation evaluation enhances safety, reduces unnecessary testing, and promotes lifelong participation in recreational sports.

Military-civilian reintegration represents a multidimensional transition, with 47 to 75% of Veterans reporting reintegration challenges. Emerging research suggests that challenges related to purpose in life, social connection, and financial stability are associated with suicide risk and broader well-being outcomes among Veterans. Guided by a normative transitions theory framework integrating psychosocial challenges (M-CARM) and enrichment (ELS), this cross-sectional study examined reintegration among 410 post-9/11 Veterans. Secure housing loss and unmet mental health needs were associated with multiple reintegration outcomes including Genuine Relationships, Sense of Purpose, Resentment and Regret, and Mental Health. A higher VA disability rating was associated with lower Physical Health and Engaged Citizenship. Unmet mental health needs were inversely associated with seven of nine reintegration outcomes. These findings underscore the value of multidimensional assessment and highlight the importance of housing stability, mental health needs, and broader reintegration challenges. Longitudinal research is needed to clarify how psychosocial challenge and enrichment interact over time and how challenges and enrichment may inform reintegration support and suicide prevention efforts.

The menopausal transition represents a pivotal period in female aging, marked by profound endocrine, metabolic and cellular shifts. Increasing evidence indicates that menopausal symptoms - vasomotor instability, sleep disturbances, fatigue and cognitive complaints - are more than consequences of estrogen withdrawal, and may serve as a potential clinical indicator of biological aging. Experimental and clinical data suggest that declining estrogen signaling contributes to mitochondrial dysfunction, inflammation and telomere attrition, processes that are closely linked to cellular senescence and tissue deterioration. In addition to estrogen decline, the menopausal transition involves broader endocrine changes. Rising follicle stimulating hormone (FSH) levels, alteration in androgen balance and cortisol dysregulation of the hypothalamic-pituitary-adrenal axis may influence metabolic regulation, musculoskeletal health, stress physiology and body composition. Through these mechanisms, menopausal hormonal changes may contribute to increased cardiometabolic, musculoskeletal and neurocognitive vulnerability in midlife women. Clinical observations increasingly show that severe menopausal symptoms are associated with adverse cardiometabolic profiles, vascular dysfunction and markers of accelerated biological aging. Sleep disturbances and fatigue may further exacerbate metabolic dysregulation and systemic vulnerability, while cognitive complaints may reflect neuroinflammatory and vascular processes associated with aging. By restoring estrogen signaling, menopausal hormone therapy alleviates menopausal symptoms and may influence biological pathways involved in aging. Whether these effects translate into a modification of the aging trajectory remains unclear.

Obesity and mental health disorders are among the greatest public health challenges of the 21st century. Interestingly, an altered microbiome profile has been associated with both conditions. The aim of this randomized, double-blind, placebo-controlled clinical trial was to evaluate the effects of dietary supplementation with a specific probiotic strain (Lactiplantibacillus plantarum KABP051) on body composition and gut microbiome balance, together with measures of mood state, in a population of healthy overweight subjects. Sixty healthy, moderately stressed, nondepressed and overweight or obese volunteers were supplemented for 12 weeks with probiotic (L. plantarum KABP051; 1 billion colony forming units/day) or placebo (microcrystalline cellulose). The KABP051 group experienced significantly greater improvements compared with placebo on body composition measurements, including a reduction in body weight and waist circumference, which decreased in 1.97 ± 0.77 (mean ± SE) kg and 2.15 ± 0.81 (mean ± SE) cm versus placebo at the end of the intervention (both P < .05, mixed model for repeated measures [MMRM] and post-hoc analysis). Microbiome composition improved in KABP051 group, with significant increase in the relative abundance of Lactiplantibacillus spp. versus placebo. Body fat percentage, profile of mood states fatigue, and confusion sub-scores showed a global trend toward improvement compared with placebo, with the change at 12 weeks being significant in the three measurements in post-hoc analysis (P = .015, P = .014, and P = .016, respectively). No serious adverse events were registered during the intervention period. These results suggest that a specific strain of probiotic bacteria (L. plantarum KABP051) may have both metabolic and psychobiotic effects and may be beneficial for enhancing weight loss and body composition, improving energy (less fatigue) and mood levels while embarking on a healthy lifestyle regimen. ClinicalTrials.gov identifier: NCT06808061.

The integration of machine learning (ML) approaches with immune biomarker research may facilitate the identification of candidate markers for achieving personalized medicine approaches in severe mental illnesses (SMI). This systematic review synthesizes the available evidence on ML algorithms applied to immune biomarkers in major depressive (MDD), bipolar (BD) and schizophrenic spectrum disorders (SZ), examining their performance across different clinical uses including diagnostic, prediction, monitoring, prognostic categories, in accordance with the Food and Drug Administration - Biomarker, EndpointS, and other Tools (FDA BEST) framework. We performed a PRISMA-compliant systematic search of PubMed, Web of Science, Scopus and PsycINFO databases until 14 July 2025, including 43 eligible studies with a total sample of 11,556 participants, 8339 with SMI (3228 MDD, 2614 BD and 2497 SZs) and 3217 healthy controls. We systematically described population, ML input data (including blood collection conditions, pre-processing steps, sample type, laboratory assay, missing data, and multimodality), and algorithms (supervised versus unsupervised models, feature selection, validation strategy, outcomes, and performance metrics). Overall, ML models showed moderate to high but heterogeneous performance. Diagnostic applications were the most common (AUC = 0.650-0.990), though predictive, monitoring, and prognostic uses were underrepresented and more variable. Across disorders, pro-inflammatory markers (IL-6, IL-8, TNF-α, IFN-γ, CRP) and IL-10 emerged most consistently, and data-driven approaches suggested shared immune subtypes beyond categorical diagnoses. However, substantial methodological and biological heterogeneity was observed, including inconsistent handling of missing data, limited external validation, and variable feature selection. Immunology-specific sources of variability (such as fasting status, circadian rhythms, and measurement batch effects) were rarely addressed, and the long-term stability of immune-based ML signatures remains largely unexplored. These gaps currently limit clinical translation and underscore the need for standardized protocols and more rigorous ML pipelines.

Childhood trauma (CT) is a major risk factor for major depressive disorder (MDD), potentially via altered stress system development. Previous studies have shown stress-related changes in brain network function in clinical populations, but evidence in MDD with CT remains scarce. This study examined changes in functional brain networks in adults with MDD and CT during acute and delayed phases following stress.

Resting-state functional magnetic resonance imaging (fMRI) was acquired during acute (15 min) and delayed (135 min) stress phases following the Trier Social Stress Test in 66 adults with MDD and CT and 33 controls. Voxel-wise eigenvector centrality (EC) mapping quantified the network importance of eight functional brain networks. Subjective stress and affect were measured using visual analog scales.

Both groups showed significant subjective stress responses, with greater increases in tension in the MDD + CT group; affective reactivity did not differ. No significant changes in EC were observed between acute and delayed phases in any network, nor were there main effects of group or group × time interactions. Sensitivity analyses in severe MDD and multiple CT subtypes confirmed these null findings.

Network centrality did not differentiate individuals with MDD and CT from controls following stress, while subjective tension responses were higher in the MDD + CT group. These results suggest that global resting-state network centrality may not be a sensitive indicator of stress vulnerability following CT. Future multimodal studies incorporating task-based paradigms and biological markers are warranted to elucidate the neural and behavioral pathways linking MDD, CT, and stress reactivity.

Childhood maltreatment (CM) is a risk factor for adult psychiatric and substance use disorders (SUD). Retrospectively assessed CM has been linked to increased proinflammatory cytokines, including IL-6. Induced by inflammation, the neurotoxic branch of the kynurenine pathway has been implicated in psychiatric disorders and SUD. This study explored proinflammatory responses and kynurenine metabolites following acute stress in participants with, and without, prospectively recorded CM, with or without, lifetime SUD.

The study included 89 participants, divided into 4 groups based on the presence or absence of prospectively assessed CM and lifetime SUD: CM + SUD, n = 24, CM only, n = 20, SUD only, n = 22, and healthy controls (HC), n = 23. Participants underwent an acute stress task. Blood was collected at five time-points measuring IL-6 and kynurenine metabolites. Linear mixed models assessed the effects of CM, SUD, and time on IL-6 and kynurenine metabolite levels.

Participants with prospectively recorded CM had higher baseline IL-6 compared to those without CM (mean difference = 0.37, 95% CI = 0.09-0.57, p = 0.008). Stress increased IL-6 in all participants (p < 0.001), with no significant group differences. We found no association between CM exposure and KYNA or QUIN concentrations. Participants with SUD, irrespective of CM-status, had a lower KYNA/QUIN ratio (mean difference: 0.02, 95% CI: 0.00-0.04, p = 0.047).

Our findings of low-grade proinflammatory activity support the hypothesis that CM contributes to long-term immune system alterations, but these findings do not support the role of the kynurenine pathway in this process. However, increased neurotoxicity through kynurenine metabolism was associated to SUD-diagnosis.

For decades, disorders of gut-brain interaction (DGBI) have been ensnared in an epistemological bottleneck, clinically managed as diagnoses of exclusion despite the absence of structural pathology on conventional endoscopy. Traditional bottom-up models of visceral hypersensitivity fail to explain the profound subjective-objective symptom mismatches observed in clinical practice. This Perspective proposes a radical paradigm shift: leveraging the Predictive Processing (PP) framework to reconceptualize DGBI as a hierarchical computational dysfunction termed "interoceptive overfitting". We postulate that rigid, high-precision threat priors force the salience network (dACC and aIns) to misallocate pathologically high precision weighting to baseline physiological noise, such as healthy 3-cycles-per-minute (cpm) gastric slow waves. This top-down failure synthesizes illusory pain and triggers genuine autonomic disruption via active inference, creating a self-fulfilling loop of GI micro-sabotage. We present a clinical roadmap utilizing high-resolution body surface gastric mapping (BSGM) and Ecological Momentary Assessment (EMA) to identify "Probabilistic Mismatch Points" within a multimodal diagnostic matrix that accounts for non-rhythmic peripheral modulators. To resolve therapeutic stagnation, we propose closed-loop digital therapeutics (DTx) designed to recalibrate the brain's predictive engine through validation-correction loops, targeted extinction learning, and dual-stream telemetry. This computational framework provides a rigorously scientific blueprint to resolve therapeutic stagnation in DGBI.