Cardiovascular diseases remain the leading cause of global mortality, yet traditional preclinical models fail to accurately capture the physiological and genetic complexity of the human heart, hindering the development of targeted therapies. Cardiac microphysiological systems (cardiac MPS), including self-organizing human cardiac organoids and engineered cardiac tissue models, have emerged as promising human-relevant platforms for recapitulating selected aspects of cardiac development, tissue organization, and function. This review evaluates current strategies for the construction of these cardiac microphysiological systems through a systematic comparison of two major approaches: development-driven self-organization based on intrinsic stem-cell programs, and engineering-driven assembly supported by bioactive materials, 3D bioprinting, and microfluidic technologies. To address key bottlenecks limiting translational utility, we outline a multidimensional maturity assessment framework encompassing sarcomeric ultrastructural organization, the fidelity of electromechanical coupling, and metabolic reprogramming toward fatty acid β-oxidation. Furthermore, we discuss the translational applications of cardiac microphysiological systems in elucidating early cardiogenesis, modeling complex genetic and ischemic cardiovascular diseases, and enabling high-throughput cardiotoxicity screening. Despite persistent challenges in building perfusable multi-scale vascular networks, reducing batch-to-batch variability, and modeling multi-organ crosstalk, the integration of cardiac microphysiological systems with spatial multi-omics, next-generation biomaterials, and artificial intelligence-assisted culture systems may enhance their translational relevance, provided that these approaches are supported by rigorous benchmarking and cross-laboratory validation.
Older-onset diabetes is often accompanied by multimorbidity, frailty, and variable metabolic profiles that complicate treatment decisions and alter risk-benefit considerations. Emerging evidence suggests that age at diagnosis is a major determinant of prognosis, with younger-onset cases showing higher lifetime risks of vascular complications. However, the prognostic implications of diabetes first diagnosed at older ages remain insufficiently characterised, particularly within Mediterranean populations. We investigated cardiovascular and mortality risks associated with type 2 diabetes diagnosed at older ages in Catalonia, Spain. We conducted a retrospective, population-based study using electronic health records from primary care centres in Catalonia, Northeast Spain. Data were collected from 1 January 2010 to 30 June 2023. We included adult participants with newly recorded type 2 diabetes between 1 January 2010 and 31 December 2021 and excluded individuals with other types of diabetes or sustained insulin monotherapy during the first year after diagnosis. Individuals with type 2 diabetes were stratified by age at diagnosis (<65 vs ≥65 years), with follow-up for up to 10 years. Sex- and birth year-matched individuals without diabetes were included at a 1:3 ratio. Outcomes were cardiovascular events and all-cause mortality. Cox regression models were used to estimate hazard ratios and relative hazard ratios (RHRs), with sex-stratified analyses. Among 481,709 individuals with type 2 diabetes, 241,472 were diagnosed between ages 18 and 64 years and 240,237 at age ≥65 years. These individuals were matched with 1,398,836 individuals without diabetes. At 10 years, individuals diagnosed before age 65 had higher diabetes-associated excess risk of heart failure than those diagnosed at age ≥65 years (RHR 1.18, 95% CI: 1.10-1.26). Within the older-onset population, individuals diagnosed at age 65-74 years had higher 10-year diabetes-associated excess risks than those diagnosed at age ≥75 years for ischaemic heart disease (RHR 1.14, 95% CI: 1.07-1.20), heart failure (RHR 1.20, 95% CI: 1.14-1.26), and all-cause mortality (RHR 1.16, 95% CI: 1.11-1.20). Diabetes-associated relative excess risks for cardiovascular outcomes and mortality differed by age at first recorded type 2 diabetes diagnosis, with lower relative excess risks among those diagnosed at older ages. However, absolute cardiovascular and mortality burdens remained substantial in older adults. These findings should be interpreted as prognostic associations based on routine clinical recognition of diabetes rather than biological onset, and they support age-informed, but individualised, cardiovascular prevention rather than treatment decisions based on chronological age alone. Future research should clarify the mechanisms underlying age-specific differences in diabetes-associated cardiovascular and mortality risk, and determine how these findings can inform individualised prevention strategies for older adults. This research received financial support from the Instituto de Salud Carlos III, Ministry of Health, and by the Catalan Agency for Management of University and Research Grants (AGAUR, Generalitat de Catalunya), under the consolidated research group DAP.cat.group. This research was also supported by the Consorcio Centro de Investigación Biomédica en Red (CIBER), Instituto de Salud Carlos III, Ministerio de Ciencia e Innovación and Unión Europea-European Regional Development Fund.
Cardiovascular diseases are the leading cause of mortality worldwide, with a particularly high burden in low- and middle-income countries such as Mexico. Cardiometabolic risk factors are strongly associated with increased mortality. Although exercise is well established as protective against mortality, evidence on its joint associations with these risk factors in high-risk populations remains limited. This study aimed to examine the joint associations of exercise and classical cardiometabolic risk factors with all-cause, premature, and cardiovascular mortality among Mexican adults. This prospective cohort study analyzed data from 155156 adults (mean age, 52.3 years; 67.1% women) from the Mexico City Prospective Study. Exercise behavior and cardiometabolic risk factors (hypertension, diabetes, obesity, and smoking) were assessed at baseline. Mortality outcomes (all-cause, premature <75 years, and cardiovascular mortality) were tracked over a median follow-up of 18.26 years. Cox proportional hazards models, adjusted for sociodemographic characteristics and additional risk factors, were used to estimate associations. Joint exposure categories combining exercise with each cardiometabolic risk factor were analyzed. During follow-up, 27510 deaths were recorded, including 13970 premature and 9192 cardiovascular deaths. Individuals who exercised had significantly lower mortality risk compared to non-exercisers. Exercise was associated with a 12-16% reduction in all-cause mortality, 16-20% reduction in premature mortality, and 10-15% reduction in cardiovascular mortality, even in the presence of cardiometabolic risk factors. The joint associations, combining absence of the cardiometabolic risk factor and exercise, showed the greatest risk reduction (HRs ranging from 0.20 to 0.43). Regular exercise is consistently associated with reduced risk of all-cause, premature, and cardiovascular mortality, regardless of the presence of major cardiometabolic risk factors. These findings highlight exercise as a powerful and broadly applicable strategy for reducing mortality risk and support its integration into clinical and public health interventions, particularly in populations with high cardiometabolic burden.
Cardiovascular disease (CVD) remains the leading cause of mortality globally. Emerging evidence indicates that cardiovascular risk in women is frequently underestimated, underscoring the importance of recognizing sex-specific contributors. Endometriosis is a chronic inflammatory disorder affecting 5%-10% of reproductive-aged women. However, previous syntheses evaluating its cardiovascular implications have yielded inconsistent results or were narrow in scope. A systematic literature search was conducted across databases, adhering to PRISMA guidelines. Studies comparing cardiovascular outcomes in women with versus without endometriosis were included. Primary outcomes were overall CVD and major adverse cardiovascular events (MACE). Secondary outcomes included ischemic heart disease (IHD), coronary artery disease (CAD), heart failure (HF), arrhythmias, coronary revascularization, and a composite of angina/acute myocardial infarction (Angina-AMI). Random-effects models with inverse variance weighting were used to calculate risk ratios (RRs) and 95% confidence intervals (CIs). Women with endometriosis exhibited a significantly higher risk of primary outcomes, including overall CVD (RR 1.21; 95% CI 1.09-1.35; p = 0.004) and MACE (RR 1.23; 95% CI 1.10-1.38; p = 0.01). Regarding secondary outcomes, endometriosis was significantly associated with elevated risks of IHD (RR 1.57; 95% CI 1.14-2.17; p = 0.01), CAD (RR 1.36; 95% CI 1.32-1.41; p < 0.0001), and Angina-AMI (RR 1.62; 95% CI 1.18-2.21; p = 0.002). Moderate-to-high statistical heterogeneity was observed across most secondary endpoints, except for CAD. Endometriosis is significantly associated with an increased risk of overall CVD, MACE, and ischemic coronary complications. These findings suggest that endometriosis should be recognized as an important sex-specific modifier of cardiovascular risk.
Endogenous sex steroid hormones are involved in numerous regulatory mechanisms of the cardiovascular system and their imbalances are frequently observed in patients with established cardiovascular disease (CVD). However, their prognostic significance for mortality remains unclear. This study aims to systematically synthesize existing research and quantify the association between endogenous sex steroid hormones, sex hormone binding globulin (SHBG), and the risk of all-cause and cardiovascular mortality in individuals with established CVD. Six bibliographic databases were systematically searched. Pooled hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated using a random-effects model, comparing the highest versus lowest levels of sex hormones/SHBG. The risk of bias was evaluated using the ROBINS-E tool (Risk Of Bias In Non-randomized Studies - of Exposures). Twelve studies with a total of 5,981 patients with established CVD were included. No significant association was found between endogenous total testosterone and risk of all-cause ((HR (95%CI): 0.78 (0.56 to 1.09), n= 5 studies) or CVD (HR (95%CI): 1.30 (0.28 to 6.01), n= 3) mortality in men. Most studies (seven out of twelve studies) were classified as having a high risk of bias, particularly due to confounding. We found no evidence for an association between endogenous sex hormones and mortality outcomes in patients with CVD. This study underscored the lack of sufficient evidence on this topic, especially concerning women. https://www.crd.york.ac.uk/PROSPERO/view/CRD42022329605, identifier CRD42022329605.
This study aimed to examine the relationship between the prognostic nutritional index (PNI) and both all-cause and cardiovascular mortality among individuals diagnosed with insomnia. A total of 3161 participants from the NHANES database were analyzed, stratified by the severity of insomnia (mild, moderate, severe). Weighted Cox regression models were employed to evaluate the associations between PNI and mortality, while subgroup and interaction analyses were conducted to assess consistency across various demographic groups. Kaplan-Meier survival curves were utilized to compare survival rates across PNI quartiles, and Receiver Operating Characteristic (ROC) curves were used to evaluate the predictive accuracy of PNI. Additionally, Restricted Cubic Spline (RCS) analysis was performed to identify safety thresholds for PNI. Among the participants, 16% were classified as having severe insomnia. A higher PNI, within a specific range, was found to be protective against cardiovascular mortality (Hazard Ratio [HR] = 0.24, 95% Confidence Interval [CI]: 0.14-0.41, p < 0.05) and all-cause mortality (HR = 0.37, 95% CI: 0.27-0.50, p < 0.001), after adjusting for confounding factors such as age, sex, race, and education. The RCS analysis revealed a nonlinear relationship, indicating that a PNI below 51.9 was associated with an increased risk of cardiovascular mortality. An elevated PNI, within a defined range, is associated with reduced mortality risks in patients with insomnia, whereas PNI levels below 53.35 for all-cause mortality and 51.9 for cardiovascular mortality are associated with heightened risk. PNI may serve as a valuable prognostic tool in this population. NA.
Manually tracking research trends in extensive conference programs is challenging, so we used a natural language processing approach to automatically extract trending topics from PDF-formatted programs of the Japanese Circulation Society (JCS). Programs from JCS2023 to JCS2026 were analyzed by GiNZA and Latent Dirichlet Allocation. Among the 42,400 extracted text blocks, there were 8 primary research themes, including sustained interests in coronary artery syndrome and heart failure, an increase in interprofessional collaboration and emerging clusters in arrhythmia and valvular intervention. The automated workflow successfully visualized evolving academic trends, providing a robust tool for comprehensive research exploration.
Perivascular spaces (PVS) are markers of cerebral small vessel disease (cSVD). While some vascular risk factors are known, broader determinants of regional PVS burden and progression remain unclear. This study aimed to identify exposome-wide determinants of cross-sectional regional PVS burden in the basal ganglia (BG) and centrum semiovale (CSO) and examine associations of identified exposures with PVS progression. We analysed 44,938 UK Biobank participants (4,568 with repeat imaging after 2.6 ± 1.0 years). Of 3,767 candidate exposures across eight domains, 1,289 were retained after preprocessing. The cross-sectional Exposome-Wide Association Study (ExWAS) used negative binomial regression with false discovery rate (FDR) correction. Surviving exposures were further examined with weighted quantile sum (WQS) regression to assess relative importance, Conway-Maxwell-Poisson longitudinal models, and structural equation modelling (SEM) linking exposures to cognition via PVS. ExWAS identified 80 exposures for BG-PVS and 89 for CSO-PVS (PFDR-corrected < 0.01). Higher diastolic blood pressure (BG: Incident rate ratio (IRR)=1.04, 95% CI: 1.03-1.05; CSO: IRR=1.07, 1.05-1.08) and greater left ventricular (LV) myocardial mass (BG: IRR=1.05, 1.04-1.07; CSO: IRR=1.09, 1.06-1.11) were associated with greater burden. WQS weights were dominated by cardiovascular exposures in BG (54.5%) but were more broadly distributed in CSO, including cardiovascular (31.9%), sociodemographic (20.9%) and environmental (12.7%). Longitudinally, cardiovascular and adiposity exposures were nominally associated with faster BG-PVS progression, with stronger effects in females. SEM demonstrated cardiovascular exposures linked to cognition through BG-PVS, but not CSO-PVS. Determinants of PVS burden and progression showed regional heterogeneity: BG-PVS is more strongly associated with cardiovascular exposures and cognition, while CSO-PVS shows a broader, more heterogeneous pattern. These findings support the importance of regional PVS assessment and suggest cardiovascular risk management may be particularly relevant to BG-PVS-related cSVD.
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Cardiac fibrosis is a pathological process accompanied by the development of cardiovascular diseases, which is mainly manifested as excessive deposition of extracellular matrix (ECM) of the heart muscle. Recent studies indicate that metabolic reprogramming significantly influences fibroblast activation, collagen deposition, and the fibrotic process by reshaping glycolytic, lipid, and amino acid metabolic pathways. This paper systematically reviews the mechanism of metabolic reprogramming in cardiac fibrosis and puts forward potential intervention strategies from a critical perspective. Although metabolic reprogramming shows potential in regulating cardiac fibrosis, its practical application still faces major challenges. Future research should strive to build a comprehensive research framework and promote metabolic reprogramming research to open a new way of precise intervention for the prevention and treatment of cardiac fibrosis through cross-technological innovation and precise regulation.
Stroke remains one of the clinical conditions with the highest global disease burden, yet whose underlying risk factors and pathogenetic mechanisms are increasingly well understood. Nevertheless, the prevailing terminology for stroke-particularly the terms "cerebrovascular" and the broader "cardiovascular"-semantically foregrounds the target-organ manifestation of the disease rather than its etiological center. This article aims to reassess the alignment of stroke terminology with the pathogenetic hierarchy and to analyze the conceptual limitations of organ-centered naming. At the intersection of psycholinguistics, cognitive framing theory, translational stroke research, pan-vascular medicine, and multi-organ disease models, the article proposes the concept of "cerebrocentric bias." According to this model, the semantic dominance of the organ component in the term "cerebrovascular" may shift clinical reasoning and research priorities from the etiological root toward the phenotypic outcome. The analysis reveals a two-tiered problem with organ-centered terminology: at the macro level, the term "cardiovascular" places the heart at the semantic center, casting stroke into the shadow within the broader spectrum; at the micro level, the term "cerebrovascular" foregrounds the brain, pushing blood composition changes, systemic arterial pathology, and hemodynamic mediation to the background. On this basis, the article advances the hemovascular paradigm as an alternative conceptual framework. This paradigm explains the disease through a three-stage model: the primary stage-blood composition changes and systemic arterial pathology; the secondary stage-hemodynamic disturbances; and the tertiary stage-multi-organ clinical phenotypes. Under this approach, stroke is interpreted not as an isolated event but as the cerebral phenotype of the hemovascular spectrum. The authors regard this proposal not as one that invalidates existing clinical diagnoses but rather as an evolutionary recentering that unifies them etiologically.
The gut microbiome influences host health, affecting gastrointestinal, metabolic, immune, cardiovascular, and neurological functions. A balanced microbiome is associated with favorable health outcomes. However, excessive antibiotic use and dietary habits can disrupt this ecosystem, leading to dysbiosis and affecting body homeostasis. This first comprehensive metagenomic analysis of the gut microbiome in a healthy Romanian cohort, a population underrepresented in microbiome studies and characterized by high antibiotic consumption, addresses a gap in current microbiome research. We report an enrichment of Enterobacteriaceae although overall composition is more comparable to other European than non-European cohorts. Community configurations align with established enterotype patterns, and our analysis provides insight into their relationship with within-phylum diversity. The analysis of antimicrobial resistance provides insight into the prevalence of resistance genes within this reservoir. We specifically report the presence of cfr(E), a Clostridioides difficile gene, and tet(X5), a variant from the ubiquitous tet family, genes not previously reported in healthy European populations. Integration with data from the European Centre for Disease Prevention and Control links the overall prevalence of resistance genes in this reservoir to antibiotic classes with higher community consumption in this population, notably beta-lactams and quinolones, highlighting potential targets for antibiotic stewardship programs. Finally, we investigate the relationship between the microbial profile and the systemic immune responses, inferred from correlations with in vitro cytokine production. Notably, we identify potential immune-priming roles for Collinsella, Flavonifractor, and Bifidobacterium species.IMPORTANCEThis first comprehensive study of the healthy gut microbiome in a Romanian cohort addresses a gap in current microbiome research, dominated by data sets from a limited number of regions. It sets a baseline for the microbiome and resistome composition of this population, and, while definitions of "healthy" microbiomes, or baseline resistomes, remain lacking, such study helps contextualize future studies and support the monitoring of dynamics. The Enterobacteriaceae abundance suggests a microbiome composition potentially influenced by antimicrobial consumption, a relevant pattern in a region with a high burden of nosocomial infections. In addition, the prevalence of antimicrobial resistance genes and the concordance with commonly used antibiotics in the community reinforce the need to address antibiotic use in public health strategies. Although gut microbiome-immunity relationships remain incompletely understood, our findings support a role for microbiome composition in immune-related traits and provide a valuable resource for future studies.
Individuals with cardiometabolic disease (CMD) often exhibit decreased microbial alpha diversity and/or differences in beta diversity indices than those without CMD. However, it is unclear if these compositional changes in the gut microbiome are a cause or a consequence of CMD. Research suggests individual bacterial species act as drivers of disease, inducing shifts in microbial community and host metabolism. During this process, large-scale compositional changes can develop secondarily, obscuring the original microbial drivers. This study aimed to characterize the gut microbiota of healthy individuals compared to those with early risk factors for CMD to determine whether specific microbial taxa and community associations exist with early stages of hypertension, vascular dysfunction, dyslipidemia, and overweight/obesity. Baseline anthropometric, physiological, and gut microbiome data from three clinical studies previously conducted by our research groups were compiled and re-analyzed. No differences in alpha and/or beta diversity were observed across CMD parameters. Through a consensus-based differential abundance analysis, we observed that several health-related taxa decreased as CMD levels increased, including Akkermansia, Bacteroides, Bifidobacterium, Blautia, Eubacterium, Lachnospiraceae, Oscillospiraceae, Prevotella, Roseburia, and Ruminococcus. Furthermore, co-occurrence networks of individuals with elevated cardiometabolic parameters showed lower clustering coefficients, higher path lengths, lower degrees, higher modularity, and higher negative cohesion than those with normal parameters. The loss of health-associated gut microbiota, along with decreased network connectivity and increased network fragmentation, may play a role in the progression of CMD.
Post-traumatic stress disorder (PTSD) is associated with poor health behaviors and risk for cardiovascular disease, and PTSD may impair cardiovascular disease recovery. Whether PTSD severity is a barrier to cardiac rehabilitation (CR) use following a new myocardial infarction (MI) or revascularization (percutaneous coronary intervention or coronary artery bypass grafting) is uncertain. Eligible patients were identified from Veterans Health Administration historical medical record data. Patients (N = 5170) had 1 or more PTSD diagnoses and ≥1 PTSD Checklist score between October 1, 2011, and September 30, 2022. Modified Poisson models with robust error variance were computed before and after adjusting for covariates to measure the association between PTSD severity and any CR use in the 12 months after MI/revascularization. Among those who used CR, we determined if PTSD severity was linked to receiving 9 or more sessions. The sample was an average 62.1 ± 11.0 years of age, 95% male, and 77% identified as White race. During the 12-month follow-up period, 8% of the sample had any CR, and among those who did, 66% had ≥9 visits. The severity of PTSD was not significantly associated with any CR use nor with receipt of 9 or more encounters. Participation in CR was low regardless of PTSD severity. Although it is encouraging that higher PTSD severity is not a barrier to CR participation, increasing engagement of veterans in CR after MI/revascularization will be important for reducing their risk of recurrent events and mortality.
This study explores the perceptions, understanding, and behaviors regarding health-related risk issues reported in interviews with 21 Hispanic female agricultural workers living and working in central Florida. Results reveal that these farmworkers are aware of many health risk issues facing women in their communities, and realize the relevance and impact of them on their health, safety, and well-being (affective learning). They also actively seek information about these risks and pursue support to both treat and prevent them (behavioral learning). However, results also reveal learning gaps in terms of unintelligible health information (cognitive learning) and pursuing expert medical support regarding physical and mental illnesses, as well as abuse (behavioral learning). Finally, this study extends the IDEA model theoretical framework in two important ways. First, it employs the model as both theory and method. In doing so, it confirms the utility of the IDEA model for both collecting and examining interview data provided by underrepresented populations regarding health risk issues. Second, it employs the model effectively as a pre-assessment tool to identify internal and external learning gaps in affective learning perceptions, cognitive learning comprehension, and behavioral learning actions regarding health-related risk issues. As such, it provides a foundation upon which future research may construct and implement authentic learner- and learning-centered strategic instructional health risk communication interventions directly targeting identified gaps in what female agricultural workers currently believe, know, and do. Finally, the study also identifies recommendations for future research focused on health-risk communication as it may inform strategic instructional interventions.
Premature ovarian insufficiency (POI) is a chronic condition affecting approximately 1.1-3.7% of women worldwide. Beyond its primary impact on fertility, POI poses significant long-term health risks, including cardiovascular disease, osteoporosis, and neurocognitive decline. Current clinical interventions, largely limited to hormone replacement therapy, are primarily palliative and do not address the underlying depletion of ovarian reserve. Recent research has identified a potential link between gut microbiota and POI pathogenesis, suggesting that gut-ovary axis dysbiosis may play a pivotal role. Systemic depletion of butyrate-producing microbiota has been shown to induce oxidative stress and granulosa cell apoptosis. In this review, we propose the gut-butyrate-SIRT1-FoxO1 axis as a central theoretical framework. This model advances beyond the conventional "leaky gut-LPS inflammation" model to demonstrate that gut-derived butyrate functions as a trans-organ "metabolic messenger." Through epigenetic-metabolic coupling, butyrate orchestrates SIRT1-FoxO1 activation. This pathway may mitigate reactive oxygen species (ROS)-induced calcium overload, restore mitochondrial quality control, and preserve granulosa cell homeostasis. Recent preclinical studies have demonstrated that butyrate supplementation can rescue ovarian function in POI models by enhancing SIRT1-mediated FoxO1 deacetylation, This mechanism may suppress pro-apoptotic signaling and promote follicular survival. Furthermore, fecal microbiota transplantation (FMT) from healthy donors has been shown to mitigate ovarian senescence in mice with dysbiotic intestinal microbiota, further substantiating the therapeutic potential of this axis. This review delineates the pleiotropic effects of butyrate across multiple organ systems and provides a robust biological foundation for future microbiota-based interventions. Although substantial experimental validation remains necessary, a deeper understanding of this signaling axis has the potential to transform POI clinical management. Future approaches may shift from palliative, symptomatic treatment to precise disease-modifying therapy.
Categorical criteria for diagnosing metabolic syndrome often fail to capture the continuous nature of metabolic risk and underlying patient heterogeneity. This narrative review evaluates the methodological evolution of quantitative severity assessment, focusing on the transition from conventional statistical scoring to advanced machine learning applications. Initial statistical models established the foundation for continuous risk evaluation by mathematically weighting core diagnostic components. Supervised machine learning approaches subsequently enhanced predictive precision by processing multidimensional datasets, with high-performing models frequently achieving area under the curve values exceeding 0.88. Concurrently, unsupervised clustering algorithms provide a data-driven method to identify distinct clinical endotypes linked to specific prognostic outcomes. Current research advances the field by integrating routine clinical data with multi-omics profiles, medical imaging, and wearable sensor inputs to construct dynamic metabolic phenotypes. However, clinical translation demands rigorous validation against hard cardiovascular endpoints, algorithmic transparency via explainable artificial intelligence, and strict adherence to standardized reporting guidelines. Future implementation must prioritize prospective trials, harmonize endotype definitions, and embed these validated algorithms within electronic health record systems to realize precision metabolic healthcare.
Despite evolution in decompression algorithms, decompression illness is still an issue. Reducing vascular gas emboli (VGE) production by varying decompression procedures is very common among divers. Several methods have been tried, either mechanical, cardiovascular, desaturation-aimed or biochemical, with encouraging results. In this study, we tested two different decompression methods: one called DEEP, where the decompression starts deeper, the other one SHALLOW, where shallower stops were planned, for the same dive and decompression time. In total, 18 healthy, non-smoking divers participated [1 female, 17 males; mean age 44.94 ± 5.74 years; body mass index (BMI) 27.3 ± 5.9 kg/m2]. Each diver performed two standardized Open Circuit trimix (21/35) dives, decompression mix EAN50. The deep profile used stops at 21, 18, 15, 12, 9, 6, and 3 meters. The shallow profile used stops at 9, 6, 3, with the same total bottom and decompression times for both groups. All dives were done in a pool (Y-40, Montegrotto, Italy) at a depth of 40 m for 40 min of bottom time and 80 minutes of total runtime. VGE counts were recorded every 15 min from 0 (0-5 min) to 90 min by echocardiography. Vascular gas emboli were significantly reduced after the deep stops decompression procedure (DEEP: 6.7 ± 7.2 VGE per heartbeat vs. shallow: 10.7 ± 11.6 VGE per heartbeat, p = 0.0006). Three DCS cases were recorded after the "shallow" stop procedure (p = 0.24 Fisher's exact test). There are significant differences between the two tested decompression procedures. The DEEP procedure resulted in a lower production of bubbles compared to the SHALLOW procedure.
Anemia in chronic kidney disease (CKD) is associated with increased cardiovascular risk, impaired quality of life, and reduced survival. Roxadustat, a hypoxia-inducible factor prolyl hydroxylase inhibitor (HIF-PHI), has demonstrated non-inferior efficacy to erythropoiesis-stimulating agents (ESAs) for anemia correction in CKD. Gut microbiota modulate the intestinal HIF-iron metabolism axis, thereby regulating intestinal iron absorption. This cross-sectional study investigated the association between gut microbiome composition and iron-metabolism response to roxadustat, and developed a logistic regression model to identify factors associated with iron metabolism non-response in anemic patients undergoing peritoneal dialysis (PD). Demographic and clinical data were collected at study enrollment, and fecal samples underwent 16S rRNA gene sequencing. Microbial taxa associated with the iron-metabolism response to roxadustat were identified using linear discriminant analysis effect size (LEfSe), differential abundance analysis with DESeq2, and Spearman's rank correlation analysis. Key microbial features were further selected using random forest analysis. Multivariable logistic regression models were constructed using R software (version 4.2.3). Variable selection was performed through stepwise selection based on the Akaike information criterion. Model performance was evaluated with the area under the receiver operating characteristic curve, calibration curves, and decision curve analysis. Internal validation was performed using 10-fold cross-validation and bootstrapping with 1,000 iterations. The overall iron-metabolism response rate to roxadustat was 39% among the enrolled participants. Random forest analysis identified microbial features associated with the iron-metabolism response to roxadustat. The final multivariable model included Clostridium perfringens, Propionibacterium acnes, Bacilli, Paraeggerthella hongkongensis, compound α-ketoacid tablets, and antihypertensive medication. The final model achieved an AUC exceeding 0.8, with favorable calibration and clinical utility, and showed good discriminative performance for iron metabolism non-response to roxadustat in PD patients. Distinct gut microbiome signatures are associated with the iron metabolism response to roxadustat in anemic PD patients.
This study examined the longitudinal associations between self-reported residual hearing and loneliness, and whether associations differed by age and sex. Using comprehensive cohort data from the Canadian Longitudinal Study on Aging (CLSA; n = 30,097 at baseline), cross-lagged path models (CLPMs) assessed associations across three timepoints (Baseline, Follow-Up 1 [FU1], and FU2). Among females 45-64 years, we observed statistically significant bi-directional associations (hearing to loneliness β = .018, p = .027; loneliness to hearing β = .015, p = .026). For males 65+ years, associations from self-reported residual hearing to loneliness were statistically significant (β = .02, p = .038). After adjustment for cardiovascular covariates, bi-directional associations remained significant only among females aged 45-64 years. Overall, the findings provide evidence of small sub-group-specific associations between hearing and loneliness and highlight the importance of including demographic and broader health-related factors when examining hearing and psychosocial well-being in the aging population.