The adverse effects of fine particulate matter (PM 2.5) on human health have become a major global public health concern. Pregnant women and fetuses, as susceptible populations, are more vulnerable to the threat of PM 2.5 pollution. Increasing studies indicate that PM 2.5 exposure is an important risk factor of fetal growth restriction (FGR), and oxidative stress, inflammatory response, endocrine disorders, epigenetic modifications, autophagic abnormalities, and gut microbiota dysbiosis may be the biological mechanisms underlying PM 2.5-induced FGR. This study offers insights for the development of targeted preventive and therapeutic methods for FGR caused by PM 2.5.

Objective:To investigate the diagnostic and surgical strategies in managing patients with coexisting thyroid carcinoma and cervical vagal schwannoma.Methods:We retrospectively analyzed three cases treated at Guangzhou First People’s Hospital between Jun. 2019 and Dec. 2024.Results:All patients presented with neck masses or thyroid nodules. Ultrasonography identified suspicious malignant thyroid nodules and lateral neck lesions—interpreted as metastatic lymphadenopathy in two cases and as a possible nerve sheath tumor in one. Fine-needle aspiration cytology (FNAC) of thyroid nodules yielded Bethesda VI results in all cases. FNAC of the lateral neck lesions revealed no evidence of malignancy in all cases; in one case, a core needle biopsy confirmed a vagal schwannoma. Two patients underwent MRI, which supported the diagnosis of vagal schwannoma. Surgical management included single-stage resection in two patients and staged surgery in one. Postoperative histopathology confirmed papillary thyroid carcinoma and schwannoma in all cases. Transient postoperative hoarseness occurred in two patients, with recovery within 3-6 months.Conclusions:When thyroid carcinoma is complicated by cervical vagal schwannoma, the schwannoma may be misdiagnosed as metastatic cervical lymph nodes, potentially leading to iatrogenic vagus nerve injury during neck dissection. Although cervical vagal schwannoma can be diagnosed preoperatively, simultaneous surgical treatment of both conditions may increase the risk of vocal cord paralysis, and in severe cases, result in airway compromise. Therefore, comprehensive preoperative evaluation is important. It is recommended to classify cases based on the anatomical locations of the thyroid carcinoma and vagal schwannoma to guide surgical planning, and to use intraoperative nerve monitoring to enhance surgical safety and avoid serious complications.

With the rapid advancement of artificial intelligence (AI) technology, particularly breakthroughs in large models, AI applications in healthcare are becoming increasingly widespread.Ophthalmology, as a critical branch of medicine, has emerged as a clinical specialty with comprehensive AI research and applications, especially in the AI-driven analysis of ophthalmic imaging.Currently, AI in ophthalmology is undergoing profound transformation driven by large model technology.AI large models, with their robust data comprehension and multimodal interaction capabilities, offer new possibilities for the diagnosis, treatment, and health education of ophthalmic diseases, powerfully propelling the evolution of current AI paradigms in ophthalmology.This article explores the novel opportunities brought by the extensive application of AI large models in ophthalmic research and practice, and provides recommendations for ophthalmologists and insights for industry development.

In recent years, generative artificial intelligence (AI) technologies have achieved remarkable progress in the early screening, risk prediction, disease progression assessment, and clinical trial design of glaucoma.Using advanced algorithms, such as generative adversarial networks, variational autoencoders, and diffusion models, researchers have synthesized high-quality structural images of the optic disc, macular region, and retinal nerve fiber layer, which effectively alleviates the limitations of scarce clinical imaging data and label imbalance.These methods have substantially improved the accuracy and generalization of deep learning models in visual field defect prediction, structure-function mapping, and longitudinal disease progression simulation.Meanwhile, multimodal generative approaches that integrate imaging data, visual field tests, and clinical features have facilitated individualized prediction of glaucoma progression.In addition, large language models have shown preliminary potential in ophthalmic image interpretation, clinical text information extraction, and decision support, providing new insights into intelligent ophthalmic diagnosis and treatment.However, the clinical implementation of generative AI in glaucoma faces challenges.The pathological authenticity and cross-device consistency of generated images require further validation, which may affect the reliability of early glaucoma detection.The heterogeneous characteristics of different glaucoma subtypes, such as open-angle and angle-closure glaucoma, also limit the generalization of synthetic data.Moreover, issues related to model interpretability (" black-box" nature), artifact generation, data privacy, and ethical governance remain key barriers to clinical translation.In the future, it is expected that establishing large-scale training frameworks that incorporate multicenter, multimodal, and multiethnic datasets will enhance model robustness and clinical applicability.Furthermore, generative AI may contribute to remote ophthalmic care and personalized precision therapy by enhancing low-quality image, reconstructing missing data, and simulating dynamic disease courses.This article reviews the current applications, core technologies, and challenges of generative AI in glaucoma diagnosis and management, and discusses its future directions and translational potential in clinical ophthalmology.

Metformin has been demonstrated to attenuate hyperglycaemia by modulating the gut microbiota. However, the mechanisms through which the microbiome mediates metformin monotherapy failure (MMF) are unclear. Herein, in a prospective clinical cohort study of newly diagnosed type 2 diabetes mellitus (T2DM) patients treated with metformin monotherapy, metagenomic sequencing of faecal samples revealed that Phocaeicola vulgatus abundance was approximately 12 times higher in nonresponders than in responders. P. vulgatus rapidly hydrolysed taurine-conjugated bile acids, leading to ceramide accumulation and reversing the improvements in glucose intolerance conferred by metformin in high-fat diet-fed mice. Interestingly, C22:0 ceramide bound to mitochondrial fission factor to induce mitochondrial fragmentation and impair hepatic oxidative phosphorylation in P. vulgatus-colonized hyperglycaemic mice, which could be exacerbated by metformin. This work suggests that metformin may be unsuitable for P. vulgatus-rich T2DM patients and that clinicians should be aware of metformin toxicity to mitochondria. Suppressing P. vulgatus growth with cefaclor or improving mitochondrial function using adenosylcobalamin may represent simple, safe, effective therapeutic strategies for addressing MMF.

With the growing emphasis on maternal and child oral health, the significance of managing oral health across preconception, pregnancy, and infancy stages has become increasingly apparent. Oral health challenges extend beyond affecting maternal well-being, exerting profound influences on fetal and neonatal oral development as well as immune system maturation. This expert consensus paper, developed using a modified Delphi method, reviews current research and provides recommendations on maternal and child oral health management. It underscores the critical role of comprehensive oral assessments prior to conception, diligent oral health management throughout pregnancy, and meticulous oral hygiene practices during infancy. Effective strategies should be seamlessly integrated across the life course, encompassing preconception oral assessments, systematic dental care during pregnancy, and routine infant oral hygiene. Collaborative efforts among pediatric dentists, maternal and child health workers, and obstetricians are crucial to improving outcomes and fostering clinical research, contributing to evidence-based health management strategies.
Humans ; Pregnancy ; Female ; Infant ; Consensus ; Mouth Diseases/therapy* ; Pregnancy Complications/therapy* ; Oral Health ; Infant, Newborn ; Delphi Technique ; Oral Hygiene

OBJECTIVE: To explore the relationship between the geriatric nutritional risk index (GNRI) and cognitive function. METHODS: A cross-sectional study method was conducted. People aged ≥ 60 years from the National Health and Nutrition Examination Survey (NHANES) databases from 1999 to 2002 and 2011 to 2014 were included as study subjects. The participants were divided into three groups based on their GNRI scores: a medium-high risk group (82 ≤ GNRI < 92), a low risk group (92 ≤ GNRI < 98), and a no-risk group (GNRI ≥ 98). Demographic characteristics (gender, age, race, education), chronic diseases [chronic bronchitis, emphysema, thyroid problems, coronary heart disease, angina pectoris, stroke, hypertension, diabetes mellitus, and depression score on the patient health questionnaire (PHQ-9)], lifestyle habits (history of smoking, hours of sleep), etc., were collected. Cognitive function was assessed using the consortium to establish a registry for Alzheimer's disease word learning subtest (CERAD-WL), animal fluency test (AFT), and digit symbol substitution test (DSST) for the 2011-2014 data, while only the DSST was used for the 1999-2002 data. Differences in the above information among the GNRI cohorts were compared. Factors affecting cognitive function in the population were analyzed using multifactorial Logistic regression. RESULTS: 2 653 participants from 2011 to 2014 and 2 380 participants from 1999 to 2002 were enrolled, with a total of 5 033 participants in the study. There were statistically significant differences in age, stroke, diabetes mellitus, DSST score, AFT score, CERAD score test 1 recall (Cst1), and CERAD score test 2 recall (Cst2) among the GNRI groups. Multifactorial Logistic regression analysis of data from 2011 to 2014 showed that in model 3 (DSST score, age, gender, race, marriage, education, hours of sleep, history of smoking, emphysema, thyroid problems, chronic bronchitis, coronary heart disease, angina pectoris, hypertension, diabetes mellitus, depression score on the PHQ-9, and stroke) adjusted for all covariates, GNRI was a protective factor for DSST [odds ratio (OR) = 1.03, 95% confidence interval (95%CI) was 1.00 to 1.05, P = 0.03]; Logistic regression analyse for 1999 to 2002 and 2011 to 2014 showed a significant association even after adjustment for covariates (OR = 1.02, 95%CI was 1.00 to 1.03, P = 0.02). Subgroup Logistic regression analyses of the total population from 2011 to 2014 showed a significant association between GNRI and DSST scores (OR = 1.02, 95%CI was 1.01 to 1.03, P < 0.001), with significant associations in the age subgroups of 60 to 64 years old, across gender, non-Hispanic Whites and Blacks, by education, and by marital status associations were significant (all P < 0.05). Subgroup Logistic regression analyse of the total populations from 1999 to 2002 and 2011 to 2014 showed a significant association between the GNRI and DSST score (OR = 1.01, 95%CI was 1.01 to 1.02, P < 0.001), but did not show a significant year difference (interaction P = 0.503), and the newly found in the smoking population the association was also more significant (P < 0.01). CONCLUSION The GNRI correlates with the presence of cognitive functions related to processing speed, sustained attention, and executive function, and may be able to serve as an indicator for the assessment or prediction of related cognitive functions.
Humans ; Cross-Sectional Studies ; Aged ; Middle Aged ; Nutrition Surveys ; Cognition ; Female ; Male ; Nutritional Status ; Risk Factors ; Geriatric Assessment

Objective:To explore the effectiveness of the"full-chain"integrated medical and elderly care service model in addressing key issues in medical-nursing services such as weak medical support capacity and insufficient provision of community-and home-based medical-nursing services.Methods:The development pathway for the"full-chain"integrated medical-elderly care service standardization system,encompassing core components such as operational mechanisms,smart platforms,policy documents,and quality control systems was systematically outlined.Effectiveness based on dimensions including service coverage,quality improvement,talent development,and social benefits was evaluated.With standardization as the core driver,the'1234567'management model was innovatively implemented.Results:The model leveraged the downward allocation of high-quality resources from tertiary general hospitals to strengthen subdistrict community health service centers.By collaborating with subdistrict elderly-care service centers,it established"subdistrict medical-elderly care and wellness service centers".These centers enhanced the capabilities of"community-embedded elderly-care complexes",including community daytime care centers,established two-way referral channels between medical and elderly care services,aligned with healthcare demands to provide elderly individuals with reliable medical support.It reduced the burden on families and society,stimulated market vitality,boosted domestic demand,promoted the development of integrated medical-elderly care and wellness initiatives,thereby advancing the silver economy.With provincial government endorsement,the model had been applied to 203 communities across 37 counties by the end of 2024.Conclusion:The established"full-chain"integrated medical-elderly care service model facilitates regional high-quality development in integrated care by consolidating healthcare group resources and seamlessly connecting the service chain across hospitals,nursing homes,community institutions,and home-based settings,thereby creating a practical paradigm for comprehensive elderly care service delivery.

Objective To explore the expression pattern and molecular function of ubiquitin-like containing PHD and RING finger domains 1(UHRF1)gene in soft tissue sarcoma(STS),as well as its correlation with clinical characteristics and prognosis of STS.Methods RNA data and related clinical data of 263 STS tissues were obtained from Cancer Genome Atlas(TCGA).Wilcoxon rank-sum test was used to analyze correlation between two groups of data;Spearman correlation coefficient analyzed the top 35 co-expressed genes positively and negatively correlated with UHRF1 expression in STS database,ggplot2 statistical package displayed co-expressed gene heatmap,Pearson correlation coefficient showed correlation between UHRF1 expression and expression of the top 10 genes in the heatmap;different UHRF1 gene expression groups in STS were analyzed using DESeq2 package,ggplot2 package was used to draw volcano plots,gene ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analyzed differentially expressed genes(DEGs)and protein functions,ggplot2 package for visualization,and cluster Profiler package for statistical analysis;STRING web was used to establish PPI network of DEGs,and the MCC algorithm in CytoHubba of Cytoscape was used to analyze hub genes.Results In STS,UHRF1 gene was significantly correlated with its histological type(liposarcoma 22.2％,synovial sarcoma 3.8％,leiomyosarcoma 40.7％,malignant peripheral nerve sheath tumor 3.8％,myxofibrosarcoma 9.6％,pleomorphic sarcoma 19.9％,P=0.001),tumor necrosis(none 38.8％,focal necrosis 20.8％,moderate necrosis 33.8％,extensive necrosis 6.6％,P=0.010),and tumor metastasis(no metastasis 67％,metastasis 33％,P＜0.001).In different clinical subgroups(age,gender,histological type,residual tumor,tumor necrosis,tumor depth,margin status,tumor multifocality,radiotherapy),high expression of UHRF1 led to poor prognosis of overall survival(OS),disease-specific survival(DSS),and progression-free interval(PFI);Three prognostic factors above were simultaneously shortened in the following five subgroups:namely residual tumor R0 and R1,tumor necrosis extensive,focal and moderate,tumor depth deep,positive margin status,tumor without multifocality.Analysis of the top 10 co-expressed genes associated with UHRF1 expression revealed that the associated positive genes were PAGE5,LINC01425,LCEP3,SERPINB7,AC074031.1,LCE3A,LCE2A,PAGE2B,MYF5,and AC037486.1(P＜0.05);the associated negative genes were CDH19,CSN1S1,TAC3,AC103563.7,SAA1,CHST8,PRLHR,MIR202HG,IGHV1-24,and ART4(P＜0.05).A total of 3 029 DEGs of UHRF1 in STS were obtained with a threshold of|log2 fold-change(FC)|＞1.0 and adjusted P value＜0.05,in which 1 228 genes were up-regulated and 1 801 genes were down-regulated;GO enrichment analyed primary biological processes(BP),original cellular components(CC),and original molecular functions(MF),and KEGG enrichment analyed signaling pathways.A total of 343 DEGs including 133 up-regulated genes and 210 down-regulated genes,were obtained with a threshold of|log2 fold-change(FC)|＞2.0 and adjusted P value＜0.05.The top 10 hub genes were analyzed.The top 3 hub genes were GCG,SST and SHH,respectively.Conclusion UHRF1 is significantly correlated with histological type,tumor necrosis,metastasis,OS,DSS,and PFI events in STS.In co expressed genes model and molecular functions of related positive and negative genes involved in multiple biological processes;The network of differentially expressed genes and protein product interactions involved in mechanisms of occurrence and development of the disease,and provided new ideas for in-depth researches on STS.

The adverse effects of fine particulate matter (PM 2.5) on human health have become a major global public health concern. Pregnant women and fetuses, as susceptible populations, are more vulnerable to the threat of PM 2.5 pollution. Increasing studies indicate that PM 2.5 exposure is an important risk factor of fetal growth restriction (FGR), and oxidative stress, inflammatory response, endocrine disorders, epigenetic modifications, autophagic abnormalities, and gut microbiota dysbiosis may be the biological mechanisms underlying PM 2.5-induced FGR. This study offers insights for the development of targeted preventive and therapeutic methods for FGR caused by PM 2.5.