Multifactorial inherited disorders (MIDs) arise from complex interactions between polygenic risk and environmental exposures, presenting major challenges for mechanistic discovery, patient stratification, and targeted therapy development. While traditional approaches like genome-wide association studies (GWAS) and bulk omics profiling have identified broad associations, they often struggle to resolve the cellular context in which these interactions drive pathogenesis.Emergingsingle-cell technologies now offer unprecedented resolution to dissect tissue heterogeneity, define rare or transient disease-relevant cell states, and map dynamic trajectories across tissues and disease stages. This reviewprovides a comprehensive synthesis ofcurrent single-cell methodologies including transcriptomic, epigenomic, proteomic, and spatial techniques and their application to MID research. We explore how these toolsare revealingcell-type-specific regulatory circuits,contextualizingthe functional impact of inherited risk variants, andelucidatingcellular responses to environmental perturbations.We propose thatintegrating single-cell multi-omics data is critical for illuminating the mechanistic basis of complex traits and for advancing biomarker discovery. However, significant challenges remain, including technical variability, limited cohort scalability, difficulties in multi-modal data integration, and a lack of standardized analytical workflows for polygenic diseases. Overcoming these barriers will require harmonized study designs, robust computational frameworks, and the incorporation of longitudinal and environmental exposure data.Ultimately, we conclude thatsingle-cell analysis is poised to transform MID research, offering a powerful new paradigm for mechanistic insight, therapeutic innovation, and the realization of precision medicine.

With the growing availability of cannabis and increasing public support for legalization, cannabis use disorder (CUD) rates have risen, particularly among veterans, who face disproportionately high rates of co-occurring posttraumatic stress disorder (PTSD) and CUD. Veterans often use cannabis to manage PTSD symptoms, yet research suggests cannabis may exacerbate and maintain these symptoms. Predicting symptom escalation remains challenging due to the complexity of PTSD-CUD interactions and a lack of predictive tools. Advances in mobile and wearable technology provide new opportunities for real-time monitoring, integrating active (self-reported) and passive (sensor-based) data to improve symptom prediction and intervention timing. This longitudinal study examined the feasibility of collecting data among recently discharged veterans with PTSD and cannabis use. The study employed the MAVERICK mobile app, integrating passive data (e.g., heart rate, sleep, activity) and active data (e.g., self-report surveys) over three months. Phase 1 involved beta testing with 20 veterans, assessing feasibility and acceptability, while Phase 2 recruited 75 veterans to evaluate recruitment, retention, and data completeness. Findings indicate high feasibility, with 91.9% of participants providing passive data and a 68% response rate for daily self-report measures. However, data availability varied across measures. These results highlight the potential for integrating passive and active data to improve symptom prediction and early intervention efforts for PTSD and CUD in veterans. Future research should explore long-term engagement strategies and clinical applications of these digital tools to enhance veteran mental health care.

During deployments, Navy personnel have reported concerning levels of mental health symptoms, as well as suicidal ideation. Upstream efforts are needed to identify and mitigate symptoms, thereby, reducing the risk of suicide. Based on recent advances, research suggests that phone-based applications can be used to identify those at risk and facilitate treatment engagement. Toward this end, using a randomized controlled trial design, members of this study team: (a) evaluated the feasibility (application download/use and technical challenges) and acceptability (satisfaction) of the Cogito Companion phone application among a cohort of Naval personnel; (b) longitudinally characterized time to risk identification by cohort (Cogito/Active Control); and (c) identified patterns of symptoms (distress, depressive, posttraumatic, suicide-related thoughts, and mental and physical health functioning) over time and by study group. Two hundred seventy-nine Active Duty Navy personnel were enrolled and randomized, with 139 participants being randomized to Cogito and 140 to the Active Control arm. Findings suggested that those in the Cogito group were outreached more quickly than those in the Active Control group, highlighting the potential utility of employing technology to identify those at risk. However, there were significant feasibility issues in terms of implementing Cogito among Naval personnel on Active Duty. Interestingly, there were no significant differences in the proportion of serial self-report measures completed between those randomized to Cogito versus the Active Control, highlighting that, at present, implementing serial self-report measures may be a more feasible strategy to identify those at potential risk. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

Non-alcoholic fatty liver disease (NAFLD) is seen as a health concern globally and is identified via complex interactions of metabolic dysfunctions. Metabolomic and lipidomic profiling has been emerged as a promising tool for non-invasive diagnosis and precision therapy. This systematic review and meta-analysis aimed to assess the affect of metabolic signatures associated with NAFLD progression and their utility in paving path for precision medicine. A comprehensive literature search was conducted in adherence to the guidelines of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020. Appropriate data studies were pooled to check the disease progression using a random effects model. Risk of bias and certainty of evidence were assessed using the Cochrane risk of bias tool, ROBINS-I ("Risk Of Bias In Non-randomized Studies - of Interventions"), and the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) framework respectively. Studies found distinct metabolite patterns especially in amino acids, lipids, and gut-derived metabolites that correlated with the severity of NAFLD. The meta-analysis findings revealed a pooled hazard ratio of 0.98 (95% CI: 0.83-1.15) that indicated that no significant association was found between studies for assessment of metabolic signatures and their link to disease progression. High heterogeneity was observed (I[2] = 82%). Risk of bias was generally low to moderate, but overall certainty of evidence was rated low to moderate due to inconsistency and imprecision. Metabolic profiling offered valuable insights and discoveries into pathophysiology of NAFLD and stratification. However, high heterogeneity found across studies limited current clinical applicability. Standardized methodologies and longitudinal validation were needed to combine metabolic signatures into precision NAFLD care.

Artificial intelligence (AI) models trained on audio data may have the potential to rapidly perform clinical tasks, enhancing medical decision-making and potentially improving outcomes through early detection. Existing technologies depend on limited datasets collected with expensive recording equipment in high-income countries, which challenges deployment in resource-constrained, high-volume settings where audio data may have a profound impact on health equity.

Introduction Hemorrhage is the leading cause of preventable death in trauma in both the military and civilian settings worldwide. Medical studies from Operation Enduring Freedom (OEF) and Operation Iraqi Freedom (OIF) informed change in military prehospital medicine by influencing widespread tourniquet distribution and training on their use to stop life-threatening extremity hemorrhage. In the military setting, there has been a significant reduction in preventable death due to extremity exsanguination since the widespread implementation of tourniquets within the Department of Defense. However, noncompressible hemorrhage remains a significant cause of mortality, especially in the prehospital setting. In select patients, resuscitative endovascular balloon occlusion of the aorta (REBOA) is an adjunct that can be utilized to slow or stop non-compressible hemorrhage until the patient reaches definitive care. However, frontline medical providers face the challenge of reliable, accurate blood pressure measurement in REBOA patients. REBOA, used in conjunction with a small disposable pressure monitor, can bridge the gap in capabilities, creating a more balanced resuscitation and reducing blood product requirements with the added benefit of invasive blood pressure monitoring capability. The authors of this study propose the sustained use and further validation of a small, disposable pressure monitor in REBOA to monitor beat-to-beat variation in both hemodynamically stable and unstable patients and seek to offer a pathway for use in austere environments. Materials and methods Yorkshire swine (n = 4) were selected for partial REBOA (pREBOA) placement and compass transducer measurement in conjunction with a vascular experimental protocol. Appropriate vascular and arterial line access was obtained, hemorrhagic shock was initiated, and REBOA with an in-line Compass™ device (CD) pressure transducer (Centurion Medical Products, Williamston, MI) was used to occlude the aorta. Mean arterial pressures were measured via the CD, recorded, and compared to the control arterial line at hypotensive, normotensive, and hypertensive pressures. Results At hypotensive pressures, 30% of the CD readings fell within 1 mmHg of control arterial line readings, and 52.3% were within 2 mmHg. At normotensive pressures, 46% of the CD readings fell within 1 mmHg of control arterial line readings, and 64.2% were within 2 mmHg. At hypertensive pressures, 60% of the CD readings fell within 1 mmHg of control arterial line readings, and 82% were within 2 mmHg. All CD data points at all pressures were within 8 mmHg of the control arterial line readings. Conclusions In conclusion, the CD is a compact, inexpensive, portable pressure-sensing device that may potentially augment the safety and functionality of the REBOA in trauma patients both at the point of injury and in the hospital. This novel study conducted on four swine subjects demonstrated a remarkable correlation to the traditional equipment intensive arterial line setups, and issues of stasis and non-pulsatility were easily troubleshot. Future studies should investigate CD use in REBOA catheters under different physiological conditions, specifically arrhythmias, and in different environments (prehospital, air medical transport, and austere locations).

In May 2022, cases of mpox emerged beyond its historically endemic parts of Central and West Africa, primarily affecting men who have sex with men (MSM), and spreading via sexual networks. During this global outbreak the novel clinical and epidemiological characteristics of mpox disease were thoroughly documented in civilian populations but comparable data have not been reported for Military Health System (MHS) populations including beneficiaries. MHS cases were identified through a variety of data sources, including the Disease Reporting System internet (DRSi) and a customized query of ICD-10-CM (International Classification of Diseases, 10th Revision, Clinical Modification) encounter codes. Contemporaneous chart reviews of patients' electronic health records in the Armed Forces Health Longitudinal Technology Application (AHLTA) and MHS GENESIS were performed to characterize cases. A total of 146 confirmed and probable MHS cases were identified from May 2022 through April 2024. Most cases occurred among MSM, with the majority developing classic prodromal symptoms and some experiencing anogenital and urinary symptoms.