Medical sciences (Basel, Switzerland)最新文献

Background: COVID-19, caused by SARS-CoV-2, exhibits highly variable severity, from mild symptoms to respiratory failure and multiorgan dysfunction. Traditional risk factors incompletely explain this heterogeneity, highlighting the potential role of gut microbiota and host metabolomics in modulating immune responses. Methods: Thus, this study investigates how gut microbiota variations are associated with plasma metabolite profiles in COVID-19, exploring relationships between microbial and metabolic signatures and disease severity and potential therapeutic targets. In a prospective cohort of 55 patients, stool and plasma samples were analyzed using 16S rRNA sequencing and untargeted LC-HRMS metabolomics. Results: Severe COVID-19 was associated with reduced microbial diversity and enrichment of pro-inflammatory taxa, including Prevotella, Alistipes, Dialister, and Lachnoclostridium, whereas mild cases showed higher abundance of protective commensals such as Bacteroides, Faecalibacterium, and Blautia. Metabolomic profiling revealed alterations in bile acids, unsaturated fatty acids, tryptophan, and inositol phosphate pathways. Notably, linoleate levels were elevated in severe cases, showing correlations with pro-inflammatory microbes, while acylcarnitines and inositol derivatives were enriched in mild disease. Predictive functional analysis suggested that severe-associated microbes showed enhanced amino acid catabolism, oxidative glucose metabolism, and xenobiotic degradation, which may be linked to host inflammation. Conclusions: These findings highlight associations between gut microbiota composition, microbial metabolism, and circulating metabolites in COVID-19 severity. Identified microbial and metabolomic signatures may represent potential candidates to be considered biomarkers and therapeutic targets to modulate disease progression.

Background: Gastrointestinal bleeding (GIB) is a common and serious complication in patients with left ventricular assist devices (LVADs), contributing to significant morbidity, prolonged hospitalization, and increased healthcare costs. We evaluated national trends, demographic disparities, and outcomes of GIB in hospitalized LVAD patients. Methods: We analyzed adult (≥18 years) LVAD hospitalizations in the National Inpatient Sample (2016-2021), identifying internal LVADs using ICD-10-PCS code 02HA0QZ. GIB was defined using ICD-10-CM codes and classified into upper (UGIB) and lower (LGIB) sources. Survey-weighted logistic and linear regression models assessed associations with mortality, length of stay (LOS), and total charges. Subgroup analyses explored sex and racial disparities. Results: Among 20,785 weighted adult LVAD admissions, 9.8% had GIB. Of these, 72.3% had LGIB and 31.0% had UGIB. Patients with GIB were older (59.2 vs. 54.8 years) and more likely to be female (43% vs. 40%) and Black (9.2% vs. 7.8%). GIB was associated with longer LOS (+15.3 days, 95% CI: 12.0-18.5), higher charges (+$316,031, 95% CI: $212,435-$419,627), and greater in-hospital mortality (OR 1.69, 95% CI: 1.25-2.29; p < 0.001). Female patients with GIB had higher odds of mortality (OR 1.37) and increased LOS (+5.6 days), though this was not statistically significant. Racial disparities were evident: Black patients with GIB had longer LOS (+8.9 days), while Asian/Pacific Islander patients had shorter LOS (-23.3 days, p < 0.001). From 2016 to 2021, GIB prevalence rose modestly (from 9.4% to 10.7%, p = 0.33), with no significant change in mortality trends (p = 0.13). Conclusions: GIB complicates nearly 1 in 10 LVAD hospitalizations, with lower GI bleeds being most common. GIB is independently associated with higher mortality, LOS, and costs. Persistent gender and racial disparities highlight the need for targeted strategies to improve outcomes in this high-risk population.

Background/Objectives: Forest bathing (Shinrin-yoku) is a nature-based approach with potential preventive health relevance. This review summarizes evidence on its effects on immune function, stress physiology, and neuroprotective pathways. Methods: A narrative review of peer-reviewed studies was conducted using major scientific databases, including observational and interventional research assessing physiological or neurocognitive outcomes following forest exposure. Results: Forest bathing is associated with enhanced natural killer (NK) cell activity, modulation of inflammatory cytokine profiles, reductions in cortisol levels, and shifts toward parasympathetic autonomic dominance. Evidence also suggests a contributory role of tree-derived biogenic volatile organic compounds and phytoncides in immune and stress-regulatory effects. Emerging findings indicate potential benefits for cognitive restoration, emotional regulation, and neurotrophic signaling; however, substantial heterogeneity in study design, exposure characteristics, and outcome measures limits direct comparability and causal inference. Conclusions: Current evidence supports forest bathing as a promising, low-risk strategy for supporting immune resilience, stress regulation, and neurocognitive well-being within a preventive health framework. Preliminary findings also suggest potential benefits in chronic neurological conditions, supporting its neuroprotective role within multimodal neurorehabilitation strategies. Standardized intervention protocols, mechanistic biomarkers, and longitudinal studies are required to strengthen clinical relevance and guide evidence-based integration into public health and lifestyle medicine.

Background/objective: Anxiety symptoms in preschool children represent early indicators of potential mental health vulnerabilities. Maternal psychological, sociodemographic, lifestyle and dietary factors may be associated with child emotional development; however, evidence regarding their independent contributions to distinct dimensions of child anxiety (trait vs. state) remains limited. This study aimed to examine maternal factors associated with preschool children's trait and state anxiety.

Methods: In this cross-sectional study conducted in Greece, 200 preschool-aged children and their mothers were assessed. Maternal demographic, socioeconomic, anthropometric, lifestyle, dietary, and psychosocial characteristics were evaluated using validated instruments, including the Mediterranean Diet Score (MedDietScore), Beck Depression Inventory-II (BDI-II), and the State-Trait Anxiety Inventory short form (STAI-6). Children's trait and state anxiety were assessed using the State-Trait Anxiety Inventory for Children (STAI-CH). Bivariate analyses were conducted, followed by separate multivariable linear regression models for trait and state anxiety, with covariate selection guided by a directed acyclic graph (DAG).

Results: Maternal anxiety was positively associated with children's state anxiety (B = 1.508, SE = 0.566, β = 0.196, t = 2.666, p = 0.008; 95% CI [0.43, 2.66]). Higher maternal educational attainment demonstrated a weak positive association with child state anxiety (B = 1.061, SE = 0.509, β = 0.145, t = 2.086, p = 0.038; 95% CI [0.08, 2.09]), which may reflect greater awareness or reporting of child symptoms by more-educated mothers or other unmeasured factors. For trait anxiety, maternal depressive symptomatology exhibited the strongest association (B = 3.578, SE = 0.918, β = 0.276, t = 3.897, p < 0.001; 95% CI [1.77, 5.39]), while maternal anxiety was also independently associated with higher trait anxiety (B = 2.088, SE = 0.744, β = 0.194, t = 2.807, p = 0.006; 95% CI [0.62, 3.56]). The models explained a modest proportion of variance (R² < 0.15), indicating that most variation in child anxiety does not seem to be fully explained by the specific measured maternal factors.

Conclusions: Maternal psychological distress was modestly associated with preschool children's state and trait anxiety, exhibiting differential patterns across anxiety dimensions. These findings should be interpreted as correlational, with unmeasured contributors such as paternal mental health, family functioning, genetics, and school/peer influences likely playing important roles. Early screening and interventions addressing maternal mental health may support children's emotional well-being, but further multi-informant and longitudinal research is needed to clarify temporal and causal pathways.

Objective: This study provides the first systematic synthesis of the burden of Group B Streptococcus (GBS) colonization and invasive disease in Nigeria, with emphasis on prevalence, serotypes, and sequence types (STs). Method: This systematic review and meta-analysis were conducted in accordance with the PRISMA guidelines and was registered on PROSPERO (CRD420251155310). Searches were conducted across multiple databases, including Scopus, ScienceDirect, Web of Science, PubMed, Dimensions, and African Journals Online, as well as in Google Scholar and Google to identify relevant articles. In total, 426 records were retrieved, of which 43 studies met the inclusion criteria. A random-effects model was applied to estimate the pooled prevalence. Result: The pooled prevalence of GBS colonization in Nigeria was 12.0% (95% CI: 9.0-15.0%). Higher colonization rates were observed in Southern Nigeria (13.0%) than in Northern Nigeria (9.0%). The neonatal colonization rate was 16.0%. Colonization rates were 13.0% in pregnant women and 8.0% in non-pregnant individuals. Human immunodeficiency virus status showed no significant association with GBS colonization among pregnant women (OR = 1.47, p = 0.17). Invasive GBS disease was uncommon (3.0%) and occurred only in neonates. Across included studies, serotypes V and II were the most frequently reported, with ST19, ST182, and ST28 being the predominant STs. Conclusions: GBS colonization is common in Nigeria, with marked regional variation and heightened neonatal vulnerability to invasive GBS infections. Notably, nineteen states lacked surveillance data, highlighting substantial gaps in national monitoring. These findings highlight the importance of strengthening prevention strategies, expanding surveillance coverage, and implementing maternal screening and immunization programs to mitigate the burden of GBS.

Venous thromboembolism (VTE), including pulmonary embolism (PE) and deep vein thrombosis (DVT), remains a major cause of morbidity and mortality worldwide, with significant clinical challenges in diagnosis and risk stratification. Traditional diagnostic tools, including clinical prediction scores, D-dimer testing, and imaging, are limited by suboptimal specificity or sensitivity. In this context, proteomics-based approaches have emerged as powerful tools to elucidate the molecular mechanisms of VTE and to identify novel diagnostic and prognostic biomarkers. This review synthesizes recent advances in proteomic research relevant to VTE. We searched four databases (PubMed, ScienceDirect, Springer Nature, and Wiley) using the keywords "acute pulmonary embolism", "acute venous thromboembolism", and "proteomics". Thirty proteomic studies investigating VTE were examined. Across these studies, proteomic profiling consistently revealed alterations in pathways related to coagulation, inflammation, platelet activation, endothelial dysfunction, and fibrin clot structure. Multiple protein classes, including acute-phase reactants, complement components, coagulation factors, and platelet-derived proteins, have demonstrated potential value in improving diagnostic accuracy and refining prognostic stratification. Proteomic analyses have also revealed distinct molecular signatures between isolated PE and isolated DVT, supporting the concept of biologically heterogeneous VTE phenotypes. Furthermore, emerging evidence from COVID-19-associated thrombosis, cancer-associated VTE, and non-invasive sources such as exhaled breath condensate underscores the expanding clinical relevance of proteomic approaches. Although technical limitations and heterogeneity across studies remain challenges, the integration of proteomic data with clinical and genetic information holds promise for advancing precision medicine in VTE.

Background/Objectives: Accurate preoperative characterization of ovarian masses is essential for appropriate clinical management, particularly for borderline ovarian tumors (BOTs), which are less common and often difficult to distinguish from benign or malignant lesions on ultrasound. Although expert subjective ultrasound assessment achieves high diagnostic accuracy, limited availability of highly trained sonologists restricts its widespread application. Artificial intelligence-based approaches offer a potential solution; however, the low prevalence of BOTs restricts the development of robust deep learning models due to severe class imbalance. This study aimed to develop a Convolutional Neural Network (CNN)-based classifier enhanced with Generative Adversarial Networks (GANs) to improve the discrimination of ovarian masses as benign, malignant, or BOT using ultrasound images. Methods: A total of 3816 ultrasound images from 636 ovarian masses were retrospectively analyzed, including 390 benign lesions, 202 malignant tumors, and 44 BOTs. To address class imbalance, a Deep Convolutional GAN (DCGAN) was used to generate 2000 synthetic BOT images for data augmentation. A three-class ensemble CNN model integrating VGG16, ResNet50, and InceptionNetV3 architectures was developed. Performance was assessed on an independent test set and compared with a baseline model trained without DCGAN augmentation. Results: The incorporation of DCGAN-generated BOT images significantly enhanced classification performance. The BOT F1-score increased from 68.4% to 86.5%, while overall accuracy improved from 84.7% to 91.5%. For BOT identification, the final model achieved a sensitivity of 88.2% and specificity of 85.1%. Class-specific AUCs were 0.96 for benign lesions, 0.94 for malignant tumors, and 0.91 for BOTs. Conclusions: DCGAN-based augmentation effectively expands limited ultrasound datasets and improves CNN performance, particularly for BOT detection. This approach demonstrates potential as a decision support tool for preoperative assessment of ovarian masses.

Background: Transrectal ultrasound-guided prostate biopsy remains the gold standard in diagnosing prostate cancer, but is associated with infectious and non-infectious complications. Increasing fluoroquinolone resistance and regulatory restrictions have prompted evaluation of alternative prophylactic strategies, including fluoroquinolone-sparing agents and targeted prophylaxis. This study compared ciprofloxacin and fosfomycin as empirical prophylactic agents, focusing on microbiological concordance, clinical outcomes, and patient-reported outcomes. Methods: In this prospective observational study, 265 men undergoing transrectal ultrasound-guided prostate biopsy received empirical antibiotic prophylaxis with either ciprofloxacin (n = 146) or fosfomycin trometamol (n = 119). Rectal swabs were obtained prior to biopsy, and antimicrobial susceptibility was analyzed post hoc. Infectious and non-infectious complications were recorded. Lower urinary tract symptoms (IPSS), erectile function (IIEF-5), and patient-reported quality of life were assessed before and after biopsy. Results: Microbiological concordance between administered prophylaxis and rectal flora susceptibility was higher in the ciprofloxacin group than in the fosfomycin group (80.1% vs. 65.0%, p = 0.007), while resistance rates were similar (10.9% vs. 10.2%). Post-biopsy fever occurred in 5.3% of patients, and hospitalization was required in 3.1%, with no significant differences between prophylaxis groups. IPSS increased significantly after biopsy (p < 0.001), while IIEF-5 scores remained unchanged. Patients with microbiological concordance reported significantly better post-biopsy quality of life (p = 0.006). Conclusions: Ciprofloxacin and fosfomycin showed similar safety profiles as empirical prophylaxis before transrectal prostate biopsy. Although ciprofloxacin achieved higher microbiological concordance, fosfomycin remains a viable alternative. The link between microbial concordance and improved patient-reported quality of life underscores the importance of targeted prophylaxis and supports antimicrobial stewardship in prostate cancer diagnostics.

The vertebrate respiratory system arose under evolutionary pressures that linked increasing atmospheric oxygen levels to the metabolic demands of mitochondria. This transition-from ancestral gill-based exchange to the highly alveolated mammalian lung-was accompanied by the emergence of a hormonal regulatory axis centered on the glucocorticoid receptor alpha (GRα). Over time, GRα became deeply integrated into the architecture and function of the respiratory system, aligning pulmonary performance with organismal homeostasis across different developmental stages, environmental challenges, and disease states. This review combines evolutionary, embryological, and molecular evidence to explain how GRα shapes respiratory structure and function. We trace the evolution from ancient oxygen-sensing systems to mammalian alveoli and endothelial adaptations, demonstrating how conserved developmental pathways (including WNT, FGF, BMP, and SHH) are repurposed during both organogenesis and repair. Genetic models show that GRα is essential for preparing the lung for postnatal life, coordinating the reciprocal signaling between mesenchyme and epithelium that drives branching, septation, extracellular matrix organization, and the development of functional alveolar units. In the mature lung, GRα maintains the stability of the alveolar-capillary interface and coordinates immune, vascular, and metabolic functions to support efficient gas exchange. Its actions also extend to red blood cell biology and the regulation of stress erythropoiesis, linking pulmonary oxygen management with systemic oxygen delivery. Mechanistically, GRα interacts with circadian and hypoxia pathways and activates mitochondrial programs that enhance energy production and redox homeostasis during stress. By integrating these regulatory layers across developmental and physiological contexts, this review reframes GRα not simply as a stress-response receptor but as a non-redundant system-level integrator of respiratory homeostasis. Understanding this layered control not only explains the benefits of antenatal corticosteroids but also highlights the therapeutic value of phase-specific, precision modulation of the GC-GRα axis-along with strategies that support GC-GR signaling-to reestablishing and maintaining homeostasis in acute and chronic pulmonary disorders.

Background: Sleep is a complex physiological process, crucial for cognitive functioning, emotional regulation, and overall health. Recent advances in genomics and neuroimaging have illuminated the intricate relationship between genetics, sleep architecture, and brain changes. This study investigated the association between sleep duration genetics, through a Sleep Duration Polygenic Index (Sleep PGI), and brain changes (total cortical thickness, white matter volume, gray matter volume, white matter hyperintensities volume) in cognitively healthy adults aged 20-80 years old.

Methods: Using longitudinal data from the Reference Ability Neural Network (RANN) and Cognitive Reserve (CR) studies, we examined the impact of Sleep PGI on brain measures (total cortical thickness, gray matter volume, white matter volume, WMH volume) over time. Generalized Estimated Equations were used for the statistical analysis. Analysis was performed in the total sample (n = 94) and in three age-groups (young, middle, old).

Results: Across age, higher Sleep PGI was associated with higher temporal WMH volumes over time. In models considering an interaction of age between Sleep PGI and time in study, age emerged as a significant moderator for outcomes of hippocampal volume, cortical white matter volume, and WMH volume (total, parietal) as outcomes.

Conclusions: Sleep duration polygenic score was associated with changes in the brain in cognitively healthy adults. Genetic predisposition for longer sleep duration was associated with more favorable longitudinal trajectories against brain decline, a result mostly driven by younger adults. These findings underscore the importance of maintaining optimal sleep duration and the potential for personalized interventions to improve sleep and brain health.