Advanced glycation end product-its receptor axis participates in myoblast senescence in vitro and delayed muscle regeneration of senescence/aging skeletal muscles in vivo.

Retrospective study. To determine the prevalence of new chronic pain conditions within one year of whiplash and the factors associated with chronic pain following whiplash exposure. Whiplash is among the most common injuries that occur following motor vehicle accidents. Many have postulated that whiplash is a progenitor for the development of chronic pain. Prior research in this arena has been limited. We retrospectively identified TRICARE beneficiaries who sustained a whiplash injury between 2017 and 2023. The records of eligible beneficiaries were abstracted to obtain age at the time of injury, race, sex, US census region, sponsor rank, mental health diagnoses, environment of care, beneficiary status, time period of injury, and number of comorbidities. We considered junior enlisted sponsor rank indicative of lower socioeconomic strata. The primary outcome was the development of a chronic pain condition. We used multivariable logistic regression with reweighting to account for confounders. We examined interactions between sex/mental health conditions, sex/socioeconomic status, and sex/time period to address secular trends. The development of new chronic pain conditions occurred in 23.4%. After adjusting for confounders, we found that women (OR=1.57; 95% CI: 1.49-1.65), pre-existing mental health conditions (OR=1.35; 95% CI: 1.28-1.42) and our proxy for lower socioeconomic status (OR=1.15; 95% CI: 1.04-1.27) were significantly associated with the likelihood of developing chronic pain disorders within one year of whiplash injury. There were interactions between women and mental health conditions, as well as between women and socioeconomic status. This represents the largest study that longitudinally surveys the development of chronic pain conditions following whiplash. The incidence of chronic pain after whiplash is lower than has been previously postulated. We believe these findings can inform management during the postinjury time period and recommendations for surveillance.

Australia's growing demand for specialist nurses in acute care settings coincides with an aging population and rising prevalence of chronic and complex conditions. Postgraduate specialty nursing education plays a critical role in preparing nurses to meet these demands. However, in the absence of mandatory regulatory standards for most specialty areas, the landscape of postgraduate education remains diverse and under-examined. This scoping review aimed to map and synthesise the existing literature on postgraduate education in acute care specialty nursing in Australia, identifying patterns, gaps, and implications for practice, policy, and future research. Comprehensive literature search was conducted in MEDLINE Complete (EBSCO), CINAHL Complete (EBSCO), ERIC (EBSCO), PsycINFO (EBSCO) to identify relevant literature to postgraduate specialty nursing education. The review was guided by Arksey and O'Malley's framework and the Joanna Briggs Institute methodology. To structure and interpret findings, the PAGER framework was applied, enabling analysis across five domains: Patterns, Advances, Gaps, Evidence for practice, and Research recommendations. A total of 103 sources were thematically analysed, including empirical studies, discussion papers, and grey literature published since 1986. Five overarching themes were identified: (1) facilitators and barriers to enrolment and completion; (2) integration of education and healthcare systems; (3) curriculum design variability; (4) course outcomes including career progression, learner development, and patient impact; and (5) evolving trends in nursing education and technological integration. Key gaps were identified in standardisation, clinical-academic collaboration, learner support, and evaluation of patient outcomes linked to postgraduate qualifications. Despite advancements in postgraduate specialty nursing education, significant inconsistencies and structural barriers persist. Strengthening academic-health service partnerships, standardising curriculum frameworks, and enhancing learner and organisational readiness are essential to ensure quality, sustainability, and responsiveness of nursing education in high-acuity settings. Further research is warranted to examine the impact of postgraduate education on patient outcomes and healthcare workforce resilience.

Influence of intrinsic and extrinsic factors on quality of Asian elephant semen - Current knowledge and new research directions.

Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) is a highly prevalent chronic liver condition, and effective therapeutic targets remain urgently needed. This study integrated multiple data sources to identify and functionally validate protein targets implicated in MASLD. In the UK Biobank, we identified participants with MASLD, and selected those with imaging-derived corrected T1 (cT1) and plasma proteomic data. Proteins significantly associated with cT1 were identified through association analyses. Two-sample bidirectional Mendelian randomisation (MR) was then conducted to assess the causal effects of candidate proteins on MASLD and cirrhosis. Hepatic expression of the candidate gene was assessed using bulk and single-cell RNA-seq datasets, complemented by immunostaining. Functional validation was performed invitro by silencing or overexpressing Cadherin-Related Family Member 2 (CDHR2) in FFA-treated primary hepatocytes as well as HepG2 and AML12 cells, followed by evaluation of lipid accumulation and related signalling pathways. A total of 36 proteins were identified as significantly associated with cT1 in patients with fatty liver. MR analysis revealed that only genetically predicted higher levels of CDHR2 were causally associated with an increased risk of both MASLD and liver cirrhosis. CDHR2 was up-regulated in MASLD patients primarily in hepatocytes compared with healthy controls. Invitro, CDHR2 knockdown significantly alleviated adipogenesis and enhanced the antioxidant response in steatotic hepatocytes. These findings identify CDHR2 as a novel regulator of MASLD development and progression, and highlight it as a potential therapeutic target.

The global prevalence of diet-related chronic conditions, such as obesity and Type 2 diabetes, has created an urgent need for objective, low-burden dietary monitoring tools. Traditional mobile health applications often suffer from high user friction due to manual data entry requirements and significant recall bias. This paper proposes an integrated system for meal image recognition and healthy meal recommendations designed to simplify personalized nutrition management. The system utilizes a sophisticated multimodal architecture, leveraging the Gemini 1.5 Flash API as a visual reasoning engine to identify ingredients and dishes directly from user-captured images with high precision. The backend is built on Supabase, employing a relational PostgreSQL database to maintain strict data integrity across multidimensional user biometric models, nutritional histories, and curated recipe datasets. A key innovation is the dual mode “Fridge Vision” pipeline, which integrates a real-time ingredient scanner for immediate health impact summaries and an automated recipe recommendation engine. The architecture utilizes Supabase Edge Functions for low- latency, serverless execution of generative AI logic, complemented by client-side image compression to optimize scan times and minimize API latency. Experimental evaluations of similar multimodal pipelines in literature indicate a Top 1 classification accuracy of approximately 89% and high correlation with dietitian-led assessments for caloric content. The results demonstrate that the proposed system offers a scalable, secure, and user-centric solution that effectively bridges the gap between automated image perception and personalized metabolic guidance, fostering long-term dietary adherence in health-conscious populations worldwide

Diabetes mellitus remains one of the most prevalent chronic conditions worldwide, demanding continuous and accurate monitoring of blood glucose levels to prevent life-threatening complications such as hypoglycemia and hyperglycemia. Traditional glucose prediction systems rely solely on historical glucose readings, overlooking the physiological relationship between cardiovascular activity and glycemic fluctuations. In this work, a lightweight Sequential Transformer model is proposed that integrates heart rate signals alongside conventional diabetes management inputs — including basal insulin, bolus insulin, and carbohydrate intake — to achieve more physiologically informed blood glucose forecasting across multiple prediction horizons ranging from 5 to 30 minutes. The model is trained and evaluated on the OhioT1DM dataset comprising six Type-1 diabetic patients. To address the clinically critical problem of hypoglycemia detection, a Combined Focal-Asymmetric Huber Loss is introduced alongside a hypoglycemia-aware oversampling strategy. A post-training threshold calibration further tunes the decision boundary by maximising the F2-score on the validation set. The proposed system achieves a root mean square error of 5.81 mg/dL, a mean absolute percentage error of 1.28%, and an R² of 0.877, with 98.89% of predictions falling within the clinically safe Zone A of the Clarke Error Grid. Hypoglycemia sensitivity improved from 0% in the baseline to 66.7% at the critical 5-minute prediction horizon, demonstrating that targeted loss design and sampling strategies can transform a clinically unsafe model into a practically deployable glucose forecasting system.

Generalized anxiety disorder (GAD) is a prevalent chronic condition affecting quality of life. While pharmacotherapy remains common, its limitations include delayed therapeutic response and intolerable adverse effects. Repetitive transcranial magnetic stimulation (rTMS), a noninvasive neuromodulation technique, is emerging as a potential therapeutic option for GAD. However, its comparative efficacy against established pharmacotherapies, such as sertraline, remains unclear. Is low-frequency right dorsal lateral prefrontal cortex (DLPFC) rTMS, alone or combined with low-dose sertraline, superior to low-dose sertraline monotherapy in reducing anxiety symptoms at 4 weeks in treatment-naïve GAD? We conducted a randomized, single-blind, exploratory superiority trial comparing two active treatments (low-frequency right DLPFC rTMS monotherapy or combined with low-dose sertraline) against a common reference (low-dose sertraline monotherapy). The study enrolled 35 treatment-naïve patients with GAD randomized to three arms over 4 weeks. Anxiety symptoms were assessed using the Hamilton Anxiety Rating Scale (HARS) at baseline and weeks 1, 2, and 4. The primary end point was change from baseline in HARS total score at week 4 (ΔHARS). In the primary modified intent-to-treat population (n = 32), rTMS monotherapy demonstrated significantly greater symptom reduction compared with sertraline (adjusted mean difference = -3.13, P = 0.018, Cohen d = -0.47), confirmed in the intent-to-treat sensitivity analysis (n = 35). Combination therapy showed no significant advantage over sertraline (P = 0.684). In this exploratory trial, low-frequency right DLPFC rTMS monotherapy reduced anxiety symptoms more than low-dose sertraline monotherapy during the initial 4-week period, whereas the combination therapy achieved efficacy comparable with sertraline monotherapy. These preliminary findings suggest rTMS may serve as an alternative for treatment-naïve patients with GAD, but larger confirmatory trials are required.

Highlights This study examines the challenges to medication adherence among individuals with type 2 diabetes living in remote Amazonian areas. Environmental, social, and systemic factors significantly influence patients' ability to sustain consistent use of prescribed antidiabetic medications. Community health workers play a crucial role in bridging gaps in Diabetes care within hard-to-reach Amazonian communities. The findings underscore the need for culturally adapted, territory-based strategies to improve medication adherence and chronic disease management. Introduction: Type 2 diabetes mellitus (T2DM) is a prevalent chronic condition with global impact. Medication adherence is essential for disease control, but it remains a challenge in socially vulnerable contexts such as the Brazilian Amazon. Objective: To identify barriers and facilitators of medication adherence in the management of T2DM in the Amazon population. Materials and Methods: A qualitative, descriptive study was conducted in Iranduba (Amazonas) involving individuals with T2DM and community health workers (CHWs). The World Café method and semi-structured interviews were used. Data were analyzed with the support of ATLAS.ti software, using Thematic Network Analysis. Results: A total of 64 participants were included (47 individuals with T2DM and 17 CHWs). Reported barriers included difficulty remembering medication schedules, adverse effects, limited financial resources, lack of medication availability in primary care, and insufficient professional support. Facilitators included self-management strategies, commitment to treatment, purchasing power, family support, and CHWs' actions. Discussion: Medication adherence in diabetes is shaped by barriers such as forgetfulness, adverse effects, and limited access to medications, while family support, professional guidance, and personal strategies facilitate treatment. These factors interact and affect self-care. Conclusion: Medication adherence among individuals with T2DM in the Amazon is shaped by intrapersonal, interpersonal, and environmental factors. Culturally adapted strategies, greater professional support, and public policies ensuring medication availability are essential to improving care and preventing complications. How to cite this article: Andrade, Raquel Coelho de; Ueno, Thalyta Mariany Rêgo Lopes; Farias, Tiago Assunção dos Santos; Monteiro, Wagner Ferreira; Campos, Hércules Lázaro Morais; De Leon, Elisa Brosina. Barriers and facilitators of medication adherence in the management of Diabetes among the Brazilian Amazon population. Revista Cuidarte. 2026;17(1):e5207. https://doi.org/10.15649/cuidarte.5207

Knee osteoarthritis (KOA) is a highly prevalent chronic condition that substantially impairs functional capacity and quality of life among middle-aged and older adults. Sensory loss, including hearing and vision loss, is another major health concern in aging populations. Dual sensory loss (DSL), the coexistence of visual and auditory impairment, leads to more severe clinical consequences than single sensory deficits, largely due to disrupted sensory integration and diminished neural compensatory mechanisms. Emerging evidence indicates that osteoarthritis is linked to progressive deterioration of auditory and visual function, highlighting the need for early identification of individuals at risk. Therefore, this study aimed to develop a machine learning-based time-to-event prediction model for DSL among middle-aged patients with symptomatic KOA and to externally validate its performance in an independent hospital-based cohort, then identify its risk factors through interpretable analysis, providing essential evidence to support early preventive interventions. Data from the China Health and Retirement Longitudinal Study (N = 605) were utilized in model development phase. After data preprocessing steps, we trained and tested four time-to-event ML algorithms. Model performance was evaluated in 10-fold cross-validation by using the concordance index (C-index), Brier scores and calibration plots. A sensitivity analysis was conducted by redefining DSL using a broader cutoff and re-training all models under the same cross-validation framework to assess the robustness and stability of the finding. An independent hospital-based cohort (N = 195) was used for preliminary external validation. The optimal model was further evaluated by the decision curve analysis (DCA) to assess its clinical utility and interpreted with SHapley Additive exPlanations (SHAP) to quantify feature contributions and directional effects. 15 variables with the highest predictive capacity were retained. The DeepSurv model demonstrated superior performance in both the construction and validation phase, achieving C-index exceeding 0.8, with a Brier score below 0.1. The sensitivity analyses results were largely consistent with our primary findings, supporting the robustness of the associations. SHAP analysis revealed self-rated health and sleep duration as the most important predictors, both negatively influencing DSL risk. The DeepSurv model effectively predicts time-to-event risk of DSL in KOA patients, highlighting subjective health perception and sleep duration as critical modifiable factors. These findings support the development of targeted early preventive strategies in clinical practice to preserve sensory function and reduce the long-term disease burden associated with KOA.

Abstract The rising global prevalence of chronic conditions, notably obesity and type 2 diabetes, demands innovative approaches to mitigate their health and economic impacts. Complications, including neuropathy and chronic limb-threatening ischemia (CLTI), dramatically increase the risk of lower limb amputation, cardiovascular events, and cerebrovascular events, underscoring the urgent need for effective interventions. Emerging neuromodulation and regenerative strategies provide novel approaches to addressing diabetes-related complications. High-frequency (10-kHz) spinal cord stimulation (SCS) demonstrates marked pain relief and sensory improvement in patients with refractory painful diabetic neuropathy. Peripheral focused ultrasound (pFUS), including splenic-targeted stimulation, shows promise in reducing systemic inflammation, accelerating wound repair, and enhancing vascular function. Remote ischemic conditioning (RIC) leverages brief controlled ischemic reperfusion cycles to enhance microcirculation and promote diabetic foot ulcer healing. In severe cases, surgical techniques such as tibial transverse transport (TTT) and lateral tibial periosteum distraction (LTPD) stimulate angiogenesis and enhance distal limb perfusion. Integrated wound care protocols, incorporating these procedures alongside debridement, negative pressure wound therapy, and skin grafting, may further optimize outcomes. Collectively, these therapies address both local and systemic pathophysiology, frequently producing physiologic effects at sites distant from the primary intervention. These seemingly disparate therapies represent a single unifying concept: generating a physiologic effect at locations remote from the primary target. This systematic approach, engaging neural, vascular, and immune pathways, may be key to improving outcomes in diabetic foot ulcers and CLTI. Early clinical data appears promising; however, larger randomized trials are required to validate efficacy, refine patient selection, and determine optimal integration with standard care. If confirmed, these strategies may shift management toward patient-centered, regenerative interventions that preserve limbs, reduce recurrence, and enhance quality of life for the expanding global patient population. Further research is warranted to confirm or refute these early promising physiologic effects.

Both non-alcoholic fatty liver disease (NAFLD) and periodontitis are prevalent chronic conditions. While prior research indicates a possible connection between these diseases, the conclusions in the existing literature are highly variable and the findings are inconsistent. Consequently, there is an urgent need for a comprehensive evaluation of this relationship. This study conducted a systematic search of the PubMed, Embase, Scopus, and Web of Science databases, encompassing research published up to June 25, 2025, to assess the association between NAFLD and periodontitis. The review incorporated cross-sectional, case-control, and cohort studies. A meta-analysis was performed utilizing a random effects model, with subgroup and sensitivity analyses conducted to investigate potential sources of heterogeneity. From 628 initially identified records, 11 studies (8 cross-sectional, 3 cohort) involving a total of 225,091 participants were included. The meta-analysis of cross-sectional studies demonstrated a significant positive association between periodontitis and NAFLD (OR:1.34, 95% CI:1.13,1.58), albeit with substantial heterogeneity (I² =68%). Subgroup analysis revealed that studies using clinical attachment loss (CAL) for periodontitis diagnosis showed a stronger and more robust association (OR: 1.38, 95% CI: 1.19, 1.60) with low heterogeneity (I² = 25%), unlike those using probing depth. The limited cohort studies suggested a potential bidirectional relationship, but heterogeneity precluded quantitative synthesis, highlighting the need for more high-quality prospective studies. Current evidence confirms a significant association between periodontitis and NAFLD, which is strongest and most consistent when periodontitis is defined by CAL, a marker of cumulative tissue destruction. These findings underscore the importance of standardized, tissue-based periodontitis diagnosis in future research and suggest potential implications for interdisciplinary patient management between dental and hepatology practices.

Nonalcoholic fatty liver disease (NAFLD) is a prevalent chronic condition, yet therapeutic targets remain elusive. Nicotinamide phosphoribosyl transferase (NAMPT) and six-transmembrane epithelial antigen of the prostate 4 (STEAP4) are integral regulators in various metabolic disorders. This study investigates the role and molecular mechanisms of NAMPT in NAFLD pathogenesis. We found that inhibiting NAMPT or silent information regulator 1 (SIRT1) exacerbates liver steatosis and impairs hepatic antioxidant defenses in high-fat diet (HFD)-induced obese mice, while reducing STEAP4 expression in liver tissues, suggesting that NAMPT and SIRT1 are pivotal in NAFLD progression and may regulate STEAP4. The role of NAMPT in SIRT1 expression involves nicotinamide adenine dinucleotide synthesis. Our results indicate that inhibiting SIRT1's deacetylase activity impairs CCAAT/enhancer-binding protein β (C/EBPβ) deacetylation and consequently its function. Additionally, STEAP4, previously identified as a C/EBPβ target, can upregulate the expression and nuclear translocation of NF-E2-related factor 2 (NRF2) to combat oxidative stress in NAFLD. This study confirms that NAMPT ameliorates NAFLD via the SIRT1-C/EBPβ-STEAP4-NRF2 signaling axis in HFD-induced obese mice, proposing a novel strategy for the prevention and treatment of NAFLD.

This study aimed to report the physical and mental health of a population-based cohort of Gulf War and Gulf Era veterans 30 years after the war. A follow-up health survey of 12,377 Gulf War and Gulf Era veterans included questions about general, physical, mental, and functional health. Adjusted odds ratios weighted by final survey weights were calculated to determine risk of health conditions associated with deployment. Gulf War veterans report a higher prevalence of a range of physical and mental health conditions. The population has a significant burden of disease, including high body mass index and multiple comorbid conditions. Three decades after deployment, Gulf War veterans experience a significantly higher prevalence of chronic health conditions. These findings describe the challenges faced by this population and reinforce the importance of addressing their ongoing healthcare needs.

Validated tools to assess gender are essential for clinical and population research but remain scarce and unstandardized. Understanding how sociocultural gender interacts with biological sex in shaping disease risk is critical for precision medicine. We aimed to investigate the association of sex and gender with cardiovascular risk factors and common comorbidities, and to refine an existing composite Gender score in a Swiss cohort. This multicenter prospective study conducted in three tertiary and one regional hospital included outpatients and inpatients with PCR-confirmed SARS-CoV-2 infection (n = 2,690; estimation and internal validation sets) and outpatients with periodontitis (n = 337; external validation set). Gender-related variables were acquired via questionnaire. Logistic regression models and propensity score matching were used to assess associations between sex, gender, and the prevalence of cardiometabolic and chronic health conditions. A total of 3,027 individuals (46.3% women; mean age 45 ± 17years) were included. The composite Gender Score predicted biological sex with good accuracy (ROC 0.776-0.809). Biological sex was more strongly associated with most cardiometabolic risk factors, stroke, immune disorders, and bone diseases, whereas gender showed limited independent associations. For diabetes, female sex was inversely associated with diabetes prevalence, while a more feminine gender profile was positively associated. These opposing associations persisted after accounting for gender in matched analyses, illustrating that sex and gender may contribute differently to specific metabolic outcomes. Sociocultural variables can accurately approximate biological sex and are differentially associated with health outcomes. In this cohort, biological sex explained most associations with cardiometabolic and chronic conditions, while gender effects were modest and condition-specific. The divergent associations observed for diabetes highlight that sex and gender are related but distinct constructs that should be considered jointly. Integrating both dimensions may improve future approaches to risk stratification, although these findings require confirmation in prospective and diverse populations.

Aim: Juvenile idiopathic arthritis (JIA) is the most prevalent chronic rheumatologic condition in children. Determining radiological progression in relation to clinical and laboratory parameters is crucial for initiating early intervention. This study aimed to investigate the association between diagnostic delay, human leukocyte antigen B27 (HLA-B27) positivity, and the development of late radiological changes in children with JIA.Methods: This retrospective single-center study included 96 patients diagnosed with JIA between January 2006 and April 2015. Demographic, clinical, laboratory, and radiological data were reviewed. Radiological changes emerging after one year of disease onset were defined as late radiological findings. Clinical features, laboratory markers, and treatment modalities were compared between patients with early and late radiological changes.Results: The mean age at diagnosis was 8.8 ± 4.0 years; 67.7% were female. Oligoarticular JIA was the most common subtype, occurring in 67 patients (69.8%), followed by systemic JIA in 20 patients (20.8%) and polyarticular JIA in 9 patients (9.4%). Late radiological changes were observed in 35 patients (36.5%). HLA-B27 positivity (20.0% vs. 6.6%, p=0.049), longer diagnostic delay (3.3 ± 2.0 vs 2.0 ± 1.8 years, p=0.002), higher joint involvement (5.6 ± 3.6 vs. 4.2 ± 2.7, p=0.033), and extra-articular findings (68.6% vs. 27.9%, p=0.001) were associated with late radiological changes. Antinuclear antibody (ANA) test positivity was inversely associated (40.0% vs. 62.3%, p=0.034). Conclusions: HLA-B27 positivity and diagnostic delay were associated with late radiological changes in children with JIA. Early diagnosis and close radiological monitoring may help prevent long-term joint damage.

Periodontitis (PD) and atrial fibrillation (AF) are two prevalent chronic conditions with substantial public health burdens worldwide. While traditionally studied separately, increasing evidence reveals a complex interplay between PD and AF, mediated primarily by shared inflammatory and immune mechanisms. Chronic periodontal inflammation can trigger systemic immune activation, leading to atrial structural remodeling, fibrosis, and electrical disturbances that predispose individuals to AF. Observational and longitudinal studies consistently demonstrate a higher incidence and recurrence of AF in patients with moderate to severe PD, independent of established cardiovascular risk factors. Key periodontal pathogens, especially Porphyromonas gingivalis, and altered immune cell profiles are implicated in this association, further supported by genetic analyses revealing common molecular pathways. Mechanistic insights from experimental models highlight the role of inflammation-related atrial fibrosis and immune dysregulation as critical drivers linking oral disease to arrhythmogenesis. Additionally, better oral hygiene practices and periodontal treatment have been associated with a reduced risk of AF, suggesting modifiable intervention potential. This review synthesizes current clinical, epidemiological, molecular, and experimental evidence to elucidate the PD-AF relationship, emphasizing periodontal health as a promising target in cardiovascular disease prevention strategies.

ABSTRACTBACKGROUNDRecent studies consisting primarily of white participants have found lowered plasmalogen levels to be associated with lower cognitive function. We explore the association of blood plasmalogen levels with global cognition and brain imaging metrics in older African Americans.METHODSIncluded in these cross-sectional analyses were participants in the Minority Aging Research Study (MARS) and the Rush Clinical Core without dementia, available serum lipid levels, and a concurrent cognitive function assessment. A plasmalogen biosynthesis value (PBV) was calculated for each participant utilizing five ratios of four key glycerophospholipids. A linear regression model of global cognition was constructed with PBV, adjusted for sex, age, education, total cholesterol, and body mass index. In participants with 3T MRI brain imaging, the association between PBV and white matter hyperintensities (WMH) was explored.RESULTSOf the 298 participants, the mean age was 74.6 years, mean education was 15.6 years, and 84% were women. The median PBV was 0.42 (interquartile range: 0.22 to 1.14). A unit higher in PBV was suggestively associated with a 0.17 β-unit higher cognitive z-score (SE =0.09, p = 0.06). In 254 participants with MRI data, an increase in log10SD of PBV suggested the less white matter hyperintensities (estimate = –0.20, SE = 0.12, p = 0.08).DISCUSSIONIn older African Americans, higher PBV was associated with higher level of global cognition, and potentially lower levels of brain white matter hyperintensities. Larger studies are needed in additional cohorts to determine if PBV is associated with annual rate of change in cognitive function.KEY POINTSWhat was known before this study?Recent studies, in primarily older, white participants have found increased plasmalogen levels to be associated with better cognition. Given the prevalence of lipid related chronic conditions and disproportionate burden of cognitive impairment in African Americans, we explored whether plasmalogen ratios may be associated with brain function and structure in this population.What did we learn in this analysis?Utilizing data from 298 participants recruited from the Minority Aging Research Study (MARS) and Rush Clinical Core, we tested whether higher blood plasmalogen levels were associated with (1) lowered cognitive scores, and (2) increased white matter hyperintensities (WMH) on brain imaging. We found that higher PBV values showed a trend towards better global cognition. We found that PBV was associated with WMH.What do we still have to learn?Future studies may need to investigate these novel biomarkers and their neuroprotective capabilities in persons with cognitive impairment or in later stages of cognitive decline in addition to their longitudinal fluctuations to better gauge their role in dementia and AD.

Metabolic dysfunction-associated steatotic liver disease (MASLD) has become one of the most prevalent chronic liver conditions worldwide, with its incidence steadily rising. However, the underlying mechanisms linking MASLD to colorectal adenoma remain unclear, and the role of gut microbiota and metabolites in this association requires further investigation. This study aims to characterise the gut microbiota and metabolites in patients with MASLD and colorectal adenoma. A cohort of 58 MASLD patients was enrolled and stratified into two groups based on colorectal adenoma status: the MASLD with colorectal adenoma group (M-CA group, n = 30) and the MASLD without colorectal adenoma group (M-NCA group, n = 28). The gut microbial ecosystem in the M-CA group showed significant dysregulation, evidenced by a decreased Gut Microbiome Health Index (GMHI) and significantly increased Microbiome Dysbiosis Index (MDI). Linear Discriminant Analysis Effect Size (LEfSe) identified 75 differentially abundant microbial taxa between groups, with Bacteroides vulgatus, Bacteroides ovatus, uncultured bacterium of norank genus of Muribaculaceae family, Muribaculaceae, and norank of Muribaculaceae family being significantly enriched in the M-CA group, representing potential microbial biomarkers for this cohort. Partial Least Squares Discriminant Analysis (PLS-DA) screened 116 differential metabolites. When combined with Random Forest (RF), Support Vector Machine (SVM) and Least Absolute Shrinkage and Selection Operator (LASSO) machine learning algorithms, 16 significantly identified biomarkers were discovered. The joint analysis of both omics revealed that variations in differential metabolite levels were associated with changes in specific microbiota abundances. Kyoto encyclopedia of genes and genomes (KEGG) functional prediction analysis indicated that the coordinated alterations in metabolites and microbiota may collectively influence multiple metabolic pathways, including lipid metabolism, xenobiotics biodegradation and metabolism, amino acid metabolism, carbohydrate metabolism, biosynthesis of other secondary metabolites and nucleotide metabolism. This study revealed that patients with MASLD and colorectal adenoma exhibited significant alterations in the gut microbiota composition and metabolic profile, indicating potential impacts on associated metabolic pathways. These findings provided novel insights and a foundation for future research into potential intervention strategies for this clinical complication.

Objectives. To provide current prevalence estimates for diagnosed multiple chronic conditions (MCC) among the noninstitutionalized, civilian US adult population. Methods. We analyzed data from the 2024 National Health Interview Survey (n = 32 629) to produce estimates and population counts for adults with 0, 1, or 2 or more conditions by demographic characteristics. Results. In 2024, 51.1% of US adults had at least 1 of 10 selected diagnosed chronic conditions, and 26.4% had MCC. Variations in the prevalence of MCC were observed by sex, race and Hispanic origin, age, health insurance coverage, and urbanization level. Conclusions. The National Health Interview Survey can be used to provide timely estimates on population prevalence of MCC. Prevalence of MCC in 2024 was similar to that of 2010 estimates, and subgroup differences have persisted. Results may inform public health efforts and guide prevention strategies aimed at addressing multiple chronic conditions among adults in the US population. (Am J Public Health. Published online ahead of print March 26, 2026:e1-e4. https://doi.org/10.2105/AJPH.2026.308427).