Objective The aim of this study was to investigate the correlation between the interaction of uric acid and inflammatory factors and hyperuricemia in overweight/obese patients. Methods The personnel with hyperuricemia who underwent physical examination in our hospital from September 2021 to September 2022 were selected as the study subjects, and they were divided into 100 cases of overweight group and 90 cases of obese group according to the BMI index; 120 cases of healthy and non-hyperuricemic personnel were randomly selected as the control group; venous blood of the three groups was collected in 5 mL after 8 h of fasting, and were tested respectively for serum uric acid, lipid indexes and inflammatory factors: IL-6, IL-2, IFN-γ, TNF-α, IL-4, IL-10. Results Glucose, triglycerides, total cholesterol, and LDL were significantly higher in the obese group versus the overweight group (P<0.001), while HDL was significantly lower than the control group (P<0.001), and these changes were more pronounced in the obese group (P<0.001).The Pearson correlation coefficient pointed out that the levels of serum uric acid in patients with hyperuricosuric acid were significantly associated with the pro-inflammatory factors IL- 6, IL-2, IFN-γ, and TNF-α were significantly positively correlated (P<0.001), whereas they were significantly negatively correlated with the anti-inflammatory factors IL-4, IL-10 (P<0.001). Conclusion High uric acid levels in overweight/obese patients can cause enhanced inflammatory responses and reduced expression levels of anti-inflammatory factors, and the interaction between uric acid and pro-inflammatory factors aggravates the condition of patients with hyperuricemia.

Objective: To investigate the characteristics and potential risk factors associated with HIV infection among newly reported HIV positive male student cases in Jiangsu Province from 2023 to 2024, so as to provide evidence for targeted intervention strategies. Methods: Data were obtained from the China CDC Surveillance System on newly reported HIV positive male student cases from 2023 to 2024. A survey was conducted to collect information on demographic characteristics, knowledge of AIDS prevention, education and training history, HIV testing history, behavioral and substance use patterns, and other relevant factors prior to HIV diagnosis among 343 newly reported HIV positive male student cases in Jiangsu Province. Multivariate Logistic regression analysis was used to assess the risk factors of HIV infection among male students. Results: Among the HIV positive male student cases, homosexual behavior accounted for 93.88% of transmission routes, while 10.20% involved heterosexual contact, as well as 4.08% for two sexual hehaviors. Awareness of HIV prevention knowledge was 97.08%, and 66.76% had previously undergone HIV testing. Among the respondents, 10.50% had used rush poppers as enhancers, and 72.30% had received HIV prevention education within the past year. Among students cases with homosexual behavior, the median time from first homosexual contact to HIV diagnosis was ≤2 years, with 54.66% of cases falling into this category; the most common way of finding same sex partners was through social software, accounting for 88.20% of cases, while the proportion of those via "Blued" app reached 87.07% ; the proportion of using condoms every time during sexual activity in the past six months was 12.27%. Among the student cases with homosexual behavior, the results of multiple Logistic regression analysis showed that student cases aged 18 to 24 ( OR =4.52) and >24 ( OR = 19.23 ), without receiving education on HIV prevention in the past year ( OR =1.86), having consistent condom use ( OR =2.73) and not using condoms ( OR =2.12) during the last sexual activity were more likely to had the first same sex sexual activity for more than 3 years before being diagnosed as HIV positive cases (all P <0.05). Student cases who were uncertain about their partner s sexual identity ( OR =0.33), and who primarily identified same sex partners through "other" means ( OR = 0.23 ) were more likely to avoid HIV testing; in contrast, student cases with consistent condom use during the last homosexual encounter ( OR =7.20) was significantly associated with increased likelihood of HIV testing (all P <0.05). Conclusions Newly reported HIV positive male student cases in Jiangsu Province exhibit serious discrepancies between knowledge and practice regarding HIV prevention. Measures are needed to accelerate the optimization of campus based HIV prevention education content and delivery methods. Simultaneously, enhanced management of extracurricular male populations is essential to effectively control the spread of HIV.

ObjectiveThe essence of syndrome manifestation recognition in traditional Chinese medicine (TCM) is to infer the body’s latent pathogenesis state from clinical observational information, rather than to perform simple label matching. However, previous studies have largely modeled this task as syndrome pattern classification within a fixed label space, which does not adequately reflect the cognition process of TCM syndrome differentiation centered on pathogenesis reasoning, and is also insufficient to capture the openness, semantic variability, and cross-disease reusability of syndrome manifestation expression. This study aimed to investigate whether introducing pathogenesis reasoning chain-of-thought (PR-CoT) supervision into large language models (LLMs) could improve the quality and cognitive consistency of syndrome manifestation recognition and support cross-disease transfer. MethodsSyndrome manifestation recognition was formulated as a conditional generation task under the framework of clinical observational information (X)→pathogenesis structure (Z)→syndrome pattern output (Y), where Z serves as an explicit intermediate structural variable linking the clinical evidence and syndrome judgment. Within this framework, a PR-CoT-supervised dataset for syndrome manifestation recognition was constructed based on medical case records of spleen-stomach disorders. After preprocessing, information extraction, manual proofreading, and data cleaning, the dataset comprised 4 800 training cases, 400 development cases, and 400 test cases. Each sample was annotated with a structured PR-CoT consisting of three progressive levels: clinical information summarization, comprehensive pathogenesis analysis, and syndrome pattern output. Supervised fine-tuning was conducted on open-source LLMs, with an end-to-end model serving as the baseline. Qwen3-32B was used as the primary experimental model, and Qwen3-14B as the scale comparison model. A progressive multidimensional evaluation framework was further established, comprising a structural parsing level, a semantic similarity level, and an expert blind review level. At the structural parsing level, syndrome pattern expressions were decomposed into structural elements and evaluated using Precision, Recall, F1 score, and Jaccard similarity. At the semantic similarity level, independent LLMs scored the theoretical proximity between predicted and reference syndrome patterns. At the expert blind review level, three TCM experts independently evaluated model outputs on two dimensions: syndrome differentiation consistency and terminology standardization of syndrome patterns. In addition, zero-shot cross-disease transfer evaluation was conducted on gynecological and heart-system disorder test sets. ResultsAt the structural parsing level, PR-CoT supervision did not lead to a stable improvement in the element-wise overlap of syndrome pattern structural components. Compared with the corresponding baselines, neither Qwen3-32B nor Qwen3-14B showed consistent advantages in structural matching metrics after the introduction of PR-CoT supervision. In contrast, at the semantic similarity level, PR-CoT supervision produced stable positive gains across different model scales and evaluation systems. The average semantic score of Qwen3-32B increased from 6.425 8 in the baseline model to 6.585 0 after PR-CoT supervision, and that of Qwen3-14B increased from 5.870 0 to 5.964 2. At the expert blind review level, the overall score of Qwen3-32B (PR-CoT) was 7.026 0±0.107 7, higher than 6.416 3±0.288 9 for its baseline. In zero-shot cross-disease testing, the PR-CoT model still showed advantages in semantic evaluation and expert evaluation on both gynecological and heart-system disorder test sets, indicating a certain degree of transferability. ConclusionThe benefits of PR-CoT supervision are mainly reflected in TCM semantic consistency and clinical plausibility, rather than in improved hard matching of structural elements. These findings support understanding syndrome manifestation recognition as a process of generating and expressing latent pathogenesis structures, rather than as a classification task within a traditional fixed label space. By introducing pathogenesis reasoning as an explicit intermediate structure into the modeling process and combining it with a progressive multidimensional evaluation framework, this study provides a methodological pathway for intelligent TCM syndrome differentiation that integrates theoretical alignment, interpretability, and multi-level evaluation.

ObjectiveThe essence of syndrome manifestation recognition in traditional Chinese medicine (TCM) is to infer the body’s latent pathogenesis state from clinical observational information, rather than to perform simple label matching. However, previous studies have largely modeled this task as syndrome pattern classification within a fixed label space, which does not adequately reflect the cognition process of TCM syndrome differentiation centered on pathogenesis reasoning, and is also insufficient to capture the openness, semantic variability, and cross-disease reusability of syndrome manifestation expression. This study aimed to investigate whether introducing pathogenesis reasoning chain-of-thought (PR-CoT) supervision into large language models (LLMs) could improve the quality and cognitive consistency of syndrome manifestation recognition and support cross-disease transfer. MethodsSyndrome manifestation recognition was formulated as a conditional generation task under the framework of clinical observational information (X)→pathogenesis structure (Z)→syndrome pattern output (Y), where Z serves as an explicit intermediate structural variable linking the clinical evidence and syndrome judgment. Within this framework, a PR-CoT-supervised dataset for syndrome manifestation recognition was constructed based on medical case records of spleen-stomach disorders. After preprocessing, information extraction, manual proofreading, and data cleaning, the dataset comprised 4 800 training cases, 400 development cases, and 400 test cases. Each sample was annotated with a structured PR-CoT consisting of three progressive levels: clinical information summarization, comprehensive pathogenesis analysis, and syndrome pattern output. Supervised fine-tuning was conducted on open-source LLMs, with an end-to-end model serving as the baseline. Qwen3-32B was used as the primary experimental model, and Qwen3-14B as the scale comparison model. A progressive multidimensional evaluation framework was further established, comprising a structural parsing level, a semantic similarity level, and an expert blind review level. At the structural parsing level, syndrome pattern expressions were decomposed into structural elements and evaluated using Precision, Recall, F1 score, and Jaccard similarity. At the semantic similarity level, independent LLMs scored the theoretical proximity between predicted and reference syndrome patterns. At the expert blind review level, three TCM experts independently evaluated model outputs on two dimensions: syndrome differentiation consistency and terminology standardization of syndrome patterns. In addition, zero-shot cross-disease transfer evaluation was conducted on gynecological and heart-system disorder test sets. ResultsAt the structural parsing level, PR-CoT supervision did not lead to a stable improvement in the element-wise overlap of syndrome pattern structural components. Compared with the corresponding baselines, neither Qwen3-32B nor Qwen3-14B showed consistent advantages in structural matching metrics after the introduction of PR-CoT supervision. In contrast, at the semantic similarity level, PR-CoT supervision produced stable positive gains across different model scales and evaluation systems. The average semantic score of Qwen3-32B increased from 6.425 8 in the baseline model to 6.585 0 after PR-CoT supervision, and that of Qwen3-14B increased from 5.870 0 to 5.964 2. At the expert blind review level, the overall score of Qwen3-32B (PR-CoT) was 7.026 0±0.107 7, higher than 6.416 3±0.288 9 for its baseline. In zero-shot cross-disease testing, the PR-CoT model still showed advantages in semantic evaluation and expert evaluation on both gynecological and heart-system disorder test sets, indicating a certain degree of transferability. ConclusionThe benefits of PR-CoT supervision are mainly reflected in TCM semantic consistency and clinical plausibility, rather than in improved hard matching of structural elements. These findings support understanding syndrome manifestation recognition as a process of generating and expressing latent pathogenesis structures, rather than as a classification task within a traditional fixed label space. By introducing pathogenesis reasoning as an explicit intermediate structure into the modeling process and combining it with a progressive multidimensional evaluation framework, this study provides a methodological pathway for intelligent TCM syndrome differentiation that integrates theoretical alignment, interpretability, and multi-level evaluation.

Background: and Purpose This study aimed to investigate the association between residual inflammatory risk (RIR) and vulnerable plaques using high-resolution magnetic resonance imaging (HRMRI) in symptomatic intracranial atherosclerotic stenosis (ICAS). Methods: This retrospective study included 70%–99% symptomatic ICAS patients hospitalized from January 2016 to December 2022. Patients were classified into four groups based on high-sensitivity C-reactive protein (hs-CRP) and low-density lipoprotein cholesterol (LDL-C): residual cholesterol inflammatory risk (RCIR, hs-CRP ≥3 mg/L and LDL-C ≥2.6 mmol/L), RIR (hs-CRP ≥3 mg/L and LDL-C <2.6 mmol/L), residual cholesterol risk (RCR, hs-CRP <3 mg/L and LDL-C ≥2.6 mmol/L), and no residual risk (NRR, hs-CRP <3 mg/L and LDL-C <2.6 mmol/L). Vulnerable plaque features on HRMRI included positive remodeling, diffuse distribution, intraplaque hemorrhage, and strong enhancement. Results: Among 336 included patients, 21, 60, 58, and 197 were assigned to the RCIR, RIR, RCR, and NRR groups, respectively. Patients with RCIR (adjusted odds ratio [aOR], 3.606; 95% confidence interval [CI], 1.346–9.662; P=0.011) and RIR (aOR, 3.361; 95% CI, 1.774–6.368, P<0.001) had higher risks of strong enhancement than those with NRR. Additionally, patients with RCIR (aOR, 2.965; 95% CI, 1.060–8.297; P=0.038) were more likely to have intraplaque hemorrhage compared with those with NRR. In the sensitivity analysis, RCR (aOR, 2.595; 95% CI, 1.201–5.608; P=0.015) exhibited an additional correlation with an increased risk of intraplaque hemorrhage. Conclusion In patients with symptomatic ICAS, RIR is associated with a higher risk of intraplaque hemorrhage and strong enhancement, indicating an increased vulnerability to atherosclerotic plaques.

Purpose To investigate the change of network topology attribute of brain structure in obese adolescents using graph theory analysis.Materials and Methods A total of 86 obese adolescents in Children's Hospital of Nanjing Medical University from January 2023 to April 2024 were prospectively collected,including 60 patients in the simple obesity group(OB group),26 patients in the obese group with metabolic syndrome(MS group).Meanwhile,24 healthy volunteers were recruited as the control group.Diffusion tensor imaging scan of the head,anthropological characteristics examination and blood test were performed.The differences of global and local topology properties among the three groups were compared.Global or node attributes with statistical differences were correlated with clinical indicators.Results There were significant differences in body height,body weight,body mass index,waist circumference,diastolic blood pressure,systolic blood pressure and high density lipoprotein cholesterol among the three groups(χ2/F=3.208-5.085,all P<0.05).Compared with the control group,there were significant differences in total body fat,triglyceride,total cholesterol,alanine amino-transferase,aspartate aminotransferase and fasting insulin between the OB group and the MS group(all P<0.05).No statistically significant differences were observed in the small world attribute,shortest path length and global efficiency among the three groups(all P>0.05).A statistically significant difference was observed in the clustering coefficient and local efficiency among the three groups(F=2.534,3.012,both P<0.05),with the values of clustering coefficient and local efficiency of OB group were significantly lower than those of the control group(P<0.05).The node attribute differences occurred in the left frontal lobe,right insula,right anterior central gyrus,left anterior cingulate gyrus,left anterior cuneus and bilateral occipital lobes.The connection value between module Association and Limbic in control group was significantly lower smaller than those of the OB group(P=0.033).A negative correlation was observed between local efficiency and age(r=-0.239),body weight(r=-0.254),body mass index(r=-0.230)and waist circumference(r=-0.263,all P<0.05).The modularity was negatively correlated with fasting insulin(r=-0.325,P<0.05).Conclusion Adolescent obesity leads to the abnormal topological properties of structural network in some brain regions,which may be associated with the abnormal cognitive function and could provide neuroimaging evidence for clinical intervention.

Objective:To summarize the current situation and shortcomings of China's health technology innovation policies,and provide reference for policy formulation and improvement.Methods:Text mining was used to sort out 24 policy documents related to health technology innovation issued by the national and provincial levels since the 13th Five Year Plan period.A PMC index evaluation model for health technology innovation policies was established,and a quantitative analysis of health technology innovation policies was conducted through 9 primary indicators and 43 secondary indicators.Results:Among the 24 policies,2 were rated as perfect,8 were rated as excellent,and 14 were rated as acceptable.Conclusions and Suggestions:China's policies on health and medical science and technology innovation have been basically improved.They can be further refined by focusing on core and key technologies,emphasizing clinical research and transformation,and advancing digital and intelligent strategies.

Objective To explore the relationship of metabolic comorbidities and insulin resistance(IR)with chronic kidney disease(CKD)among elderly individuals undergoing health exam.Methods A cross-sectional observational study was conducted on 8358 older adults who took health exam in Chinese PLA General Hospital between December 2009 and May 2021.According to the guidelines for CKD diagnostic criteria,they were divided into CKD group(983 cases)and non-CKD(7375 cases).Clinical data was collected,and the eGDR was calculated.Quasi-Bayesian method was used for causal mediation analysis.Results The prevalence of metabolic comorbidi-ties including hypertension,CHD,DM,hyperlipidemia,and hyperuricemia was significantly higher in the CKD group than the non-CKD group(P＜0.01).The eGDR was obviously lower in the CKD group than the non-CKD group[6.88±2.09 mg/(kg·min)vs 8.41±2.12 mg/(kg·min),P＜0.01].Logistic regression analysis revealed that,without adjusting covariates,each 1-unit increase in eGDR was associated with a 29％reduction in the risk of developing CKD(OR=0.714,95％CI:0.691-0.738,P＜0.01),and after adjusting covariates,eGDR remained signifi-cantly negatively association with the risk of CKD(P＜0.01).Mediation analysis indicated that DM and brachial-ankle pulse wave velocity accounted for the highest proportions of the mediating effect in the relationship between eGDR and CKD(14.2％and 12.5％,respectively).Conclusion In the elderly population undergoing health exam,reduced insulin sensitivity is significantly asso-ciated with the development of CKD.Diabetes and arteriosclerosis exert mediating effect in this association.

Objective:To investigate the feasibility of varicocele ligation with mobile phone microscope.Methods:The high-performance mobile phone and mobile phone stand were combined to act as a mobile phone microscope.And the varicocele ligation was performed under the mobile phone microscope.Results:All five patients successfully underwent varicocelectomy under the guidance of a mobile phone microscope.The average operation time was(112.8±52.2)with ranged from 74.0 to 195.0 minutes.Three pa-tients completed the follow-up after the operation with the proportion of improved sperm quality reaching 100.0％(3/3).Conclusion:High-performance mobile phone microscope can be used for varicocele ligation.

Objective To construct a diagnostic model for phlegm-dampness syndrome in hypertension based on multimodal feature fusion.Methods Clinical text information(physiological/lifestyle data,symptoms,pulse characteristics)and tongue image data were collected from 261 hypertension patients.For clinical text data,statistical analyses,including ANOVA,Mann-Whitney U test,and Chi-square test,were performed to identify significant features(P<0.05),which were incorporated into a clinical text-based diagnosis model(CTDM)using a multilayer perceptron algorithm.For tongue images,a tongue image-based diagnosis model(TIDM)was constructed based on channel attention mechanisms and residual networks.A multimodal diagnostic model(MDM)was built by fusing clinical text and tongue image features using a feature concatenation method.The diagnostic performance of each model was evaluated using five-fold cross-validation with the area under the receiver operating characteristic curve(AUC),accuracy,specificity,and sensitivity.Results Seven clinical text features,including physiological/lifestyle factors(disease duration,body mass index),symptoms(chest tightness,loss of appetite,excessive phlegm),and pulse characteristics(slippery pulse,damp pulse),were identified as risk factors for phlegm-dampness syndrome in hypertension.The AUC of the CTDM was 0.831±0.021,the AUC of the TIDM was 0.878±0.035,and the MDM achieved an AUC of 0.972±0.015.Conclusion The multimodal diagnostic model that integrates clinical text and tongue image features demonstrates high diagnostic accuracy and provides valuable guidance for AI-assisted diagnosis of phlegm-dampness syndrome in hypertension.