To thoroughly implement the strategic deployment outlined in the Opinions of the Central Committee of the Communist Party of China and the State Council on Promoting the Inheritance and Innovative Development of Traditional Chinese Medicine regarding research on dominant diseases of traditional Chinese medicine and to uphold the development philosophy of equal emphasis on traditional Chinese medicine and western medicine，the China Association of Chinese Medicine has fully played a leading academic role by systematically organizing and conducting a series of academic youth salons on clinical dominant diseases of traditional Chinese medicine. On September 13，2024，the 36^th Youth Salon on Clinical Dominant Diseases was successfully held in Nanjing，focusing on the advantages of traditional Chinese medicine and the integrative traditional Chinese medicine and western medicine in the diagnosis and treatment of erectile dysfunction （ED）. The conference brought together leading experts from traditional Chinese medicine，western medicine，and interdisciplinary fields，facilitating in-depth multidisciplinary discussions that led to key consensus on optimizing traditional Chinese medicine treatment protocols for ED，researching and developing new drugs of traditional Chinese medicine，and advancing interdisciplinary development in traditional Chinese medicine. This salon systematically sorted out the clinical strengths and distinctive features of traditional Chinese medicine in the diagnosis and treatment of ED. Based on current research foundations and clinical needs，it identified key directions for future scientific layout and scientific research tackling： （1） Standardization of syndrome differentiation system of traditional Chinese medicine for ED. （2） Optimization and standardization of intervention methods of integrated traditional Chinese medicine and western medicine. （3） High-quality clinical research guided by evidence-based medicine. （4） In-depth analysis of the pharmacological mechanisms of traditional Chinese medicine in the treatment of ED. （5） Clinical translation and application promotion of new drugs of traditional Chinese medicine. （6） Interdisciplinary integration and innovation in traditional Chinese medicine. For each research direction，key focus areas，expected objectives，and clinical value were further refined，along with the establishment of a scientifically sound priority funding level evaluation system. Therefore，building on the series of salons on the ED-focused dominant diseases of traditional Chinese medicine，this paper provides standardized guidance for clinical practice of traditional Chinese medicine in ED management，effectively contributing to the high-quality development of traditional Chinese medicine. It serves as a valuable reference for national scientific and technological strategic layout， research and development decision-making in new drugs of traditional Chinese medicine，research topic planning，and clinical guideline formulation.

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.

ObjectiveTo analyze the epidemiological characteristics of latent tuberculosis infection (LTBI) among newly detained populations in eastern China, to identify high-risk groups, and to provide a scientific basis for formulating tuberculosis prevention and control strategies in the prison system. MethodsA cross-sectional study was conducted among the newly admitted detainees in two prisons in eastern China in 2022. Data on demographic characteristics, behavioral risk factors and previous disease history of the research subjects were collected through a structured questionnaire survey. The LTBI status of the detainees was determined using the QuantiFERON-TB Gold In-Tube (QFT-GIT) method. Lasso regression was used to screen variables, followed by multivariate logistic regression analysis to investigate the influencing factors of LTBI. ResultsA total of 305 detainees were included in the study. The median age of detainees was 35 (31, 43) years. The study population was predominantly male (67.21%), of Han ethnicity (95.41%), had a junior or senior high school education (59.34%), and was unemployed (31.80%). A history of smoking was reported by 52.79% of participants, while 57.70% reported no alcohol consumption. The majority had no history of hypertension (85.90%), diabetes mellitus (93.77%), human immunodeficiency virus (HIV) infection (97.38%), familial genetic diseases (95.08%), surgery or trauma (73.77%), drug use (92.79%), or hepatitis (93.77%). The LTBI rate was 14.75%. After comparing the demographic characteristics of LTBI and non-infected groups, it was found that smoking history (χ²=7.40, P=0.025), drug use history (χ²=5.49, P=0.019), and HIV infection (χ²=8.12, P=0.004) were statistically correlated with LTBI infection. The results of multivariate logistic regression analyses showed that smoking [adjusted odds ratio (aOR)=4.08, 95%CI: 1.60‒10.42, P=0.003], HIV infection (aOR=11.57, 95%CI: 2.50‒53.51, P=0.002) and drug use (aOR=3.04, 95%CI: 1.02‒9.09, P=0.046) were risk factors for LTBI. ConclusionThe LTBI rate among newly detainees in two prisons in eastern China is slightly lower than that among long-term detainees. Early screening and intervention should be implemented for newly detainees, with particular attention focused on high-risk groups such as those with a history of smoking, HIV infection, or drug use.

Multidrug-resistant (MDR) bacterial infections have emerged as a serious challenge of global public health crisis. The overuse and misuse of conventional antibiotics have dramatically accelerated the emergence, evolution and worldwide spread of drug-resistant bacterial strains, necessitating urgent exploration of novel antibacterial strategies. Bacteriophages serve as natural bacterial predators offering distinct advantages including high host specificity, autonomous self-replication capabilities and cost-effective large-scale production. However, wild-type phages present significant clinical limitations due to their narrow host ranges, susceptibility to rapid immune clearance and poor penetration of bacterial biofilms, which severely restrict their therapeutic applications. The convergence of synthetic biology, nanotechnology and advanced gene editing technologies has accelerated the development of engineered bacteriophage platforms, providing programmable, scalable and clinically translatable pathways to overcome these inherent biological constraints. Here, we systematically delineate four fundamental strategies for engineered bacteriophage development. Chemical modification utilizes reactive functional groups such as amino, carboxyl and thiol moieties on capsid proteins through esterification, amidation or click chemistry reactions to achieve precise drug conjugation and surface functionalization. In vivo editing encompasses ultraviolet or chemical mutagenesis for random mutation induction, homologous recombination for targeted genetic alterations, recombineering methodologies including electroporation-mediated bacteriophage recombination engineering, and CRISPR-Cas systems for precise genome editing to enable exact genetic reconstruction and host range reprogramming. In vitro synthesis leverages genome engineering platforms where intact phage genomes are transferred into yeast or host bacteria to facilitate highly efficient homologous recombination, enabling large DNA fragment assembly and cross-gene host range expansion without bacterial toxicity constraints. Directed evolution combines artificial selection through mutation library screening with rational design approaches involving chimeric receptor binding protein construction or site-specific mutagenesis, effectively balancing the discovery of unknown adaptive pathways with targeted host specificity modification. Moreover, we comprehensively discuss therapeutic applications across diverse clinical scenarios. Engineered bacteriophage effectively disrupt bacterial biofilms through sophisticated functionalized delivery platforms including nanozyme-conjugated phages, phage-liposome nanoconjugates and bio-responsive hydrogels, demonstrating significantly enhanced bactericidal efficiency compared to unmodified free phages. These bioengineered vectors attenuate bacterial virulence and resensitize pathogens to antibiotics by delivering CRISPR-Cas systems or base editors to disrupt critical virulence factors such as pili, capsule synthesis machineries and quorum sensing systems, or by inactivating antibiotic resistance determinants including beta-lactamase genes. As an intelligent nanomedicine delivery platform, engineered bacteriophage enable precise pathogen elimination an through photocatalytic reactive oxygen species generation, immunomodulatory interventions, or controlled release of antibacterial drugs. Furthermore, oral administration of engineered bacteriophage facilitates microbiota modulation, which selectively eliminate intestinal pathogens while preserve beneficial commensal microbiota, thereby restoring microbial community balance and preventing complications associated with dysbiosis. Finally, we critically analyze persistent challenges including host strain matching complexity, evolution of bacterial resistance mechanisms, pharmacokinetic optimization requirements, optimal administration route selection, large-scale production quality control standards and clinical dosing determination protocols. Through multidisciplinary integration of synthetic biology, infectious disease medicine and immunology, future translational medicine studies of bacteriophage should establish comprehensive technical platforms encompassing rapid phage screening, intelligent rational design, rigorous in vivo evaluation and standardized clinical validation processes, ultimately advancing engineered bacteriophage from laboratory innovations to clinically approved therapeutics for effectively combating MDR bacterial infections.

Objective To explore the characteristics and correlation between perivascular spaces (PVS) and diffusion tensor image analysis along perivascular spaces (DTI-ALPS) index in patients with amnestic mild cognitive impairment (aMCI). Methods A retrospective study was conducted on a total of 118 participants, including cognitive normal (CN) healthy controls and aMCI patients, recruited from the Department of Neurology, Zhongshan Hospital, Fudan University from September 2020 to September 2022. All participants underwent structural magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI). An automatic segmentation algorithm was used to quantify PVS metrics in the brain, and DTI-ALPS index was calculated based on DTI. Differences in DTI-ALPS index and PVS metrics between the CN and aMCI groups were compared. Multivariate logistic regression was used to identify independent factors influencing aMCI. Correlation analysis was performed to assess relationships among DTI-ALPS index, PVS metrics, and cognitive scores. Results A total of 80 CN healthy controls and 38 aMCI patients were included. The DTI-ALPS index was significantly lower in the aMCI group compared with the CN group (1.28±0.18 vs 1.37±0.21, P＝0.018), while differences in PVS metrics between groups were not statistically significant. Multivariate logistic regression analysis indicated that DTI-ALPS index was an independent factor affecting aMCI (OR＝0.097, 95%CI 0.011–0.833, P＝0.033). Correlation analysis revealed a positive relationship between DTI-ALPS index and MMSE score (r＝0.210, P＝0.023) as well as PVS length in the centrum semiovale (r＝0.216, P＝0.019). Conclusions The DTI-ALPS index may serve as an imaging biomarker for identifying early cognitive impairment, and patients with aMCI exhibit abnormal DTI-ALPS indices, suggesting that brain glymphatic system dysfunction may occur prior to morphological changes.

Background::The increasing incidence of inflammatory bowel disease (IBD) presents significant medical and societal challenges. A well-designed IBD database is crucial for both epidemiological studies and clinical management. However, inconsistencies between regional databases hinder cross-institutional and international research, especially between Eastern and Western societies.Methods::We developed a new IBD database, the 301 IBD database, integrating the IBD clinical characteristics from the Penn IBD database (USA) and the latest IBD guidelines and consensus and clinical practices of the Chinese PLA General Hospital (PLAGH). We applied this database to analyze clinical data of IBD inpatients at PLAGH from 2008 to 2023.Results::The 301 IBD database contains 490 items in 6 sections including demographic characteristics, personal history, clinical phenotype, disease activity, laboratory tests and examinations, and treatment. Features of the 301 IBD database include inpatient focus, biochemical indicators and opportunistic infection focus, and more about ulcerative colitis (UC)-associated complications. Single-center analysis revealed an increasing hospitalization trend, from 2.35% in 2008 to 3.94% in 2023. We found that the clinical characteristics of our UC inpatients are predominantly male (62.5%), extensive lesions (55.1%), low usage of biologics (4.1%), and a high incidence of UC-CRC (3.0%). The clinical characteristics of CD inpatients included male predominance (68.39%), early onset age (35.43 ± 14.75-year-old), and high rate of surgery (25.81%).Conclusion::The 301 IBD database, integrating Eastern and Western clinical data, provides a valuable tool for IBD clinical research. Future international, multicenter collaborations are expected to further enhance its utility.

Objective To investigate the clinical and imaging features of alveolar soft part sarcoma(ASPS).Methods A retro-spective analysis was conducted on the clinical and imaging data of 41 patients with pathologically confirmed ASPS.Results The primary clinical manifestation of 41 patients with ASPS was progressive tumour enlargement.The tumors were located in the but-tocks(14 cases),thighs(11 cases),lower legs(5 cases),forearms(3 cases),upper arms(2 cases),psoas major muscles(2 cases),and one case each in the paracervical region,shoulder,axilla,and plantar regions.Pulmonary metastasis were observed in 30 patients,and 7 patients had metastases to other sites,including 2 cases of intracranial metastasis,1 case of lymph node metastasis,and 4 cases of bone and soft tissue metastasis.Five patients experienced postoperative local recurrence or metastasis.MR was performed in 34 patients,and CT was performed in 32 patients.The tumors were oval or irregular in shape.On CT,the tumors appeared as soft tissue density shadow,with calcification in 8 cases and 68％(17/25)showed marked enhancement with peripheral vascular plexus.On MR,the tumors exhibited isointense T1 and long T2 signals,67％(23/34)showed flow-void vessels within the tumor and 94％(32/34)showed tortuous vascular plexus at the tumor margins.Conclusion ASPS predominantly occurs in the muscles of buttocks and thigh and is prone to lung metastasis.Enhanced CT and MR can reveal vessels within and at the margins of the tumor,which is diagnosti-cally significant for ASPS.

Objective To establish a stable liquid chromatography-tandem mass spectrometry(LC-MS/MS)method for detecting gamma-aminobutyric acid(GABA)in plasma,and to evaluate the value of GABA detection in the diagnosis of sleep disorders.Methods GABA was detected using a UPLC Xevo TQs system.The method was pre-validated and its performance was verified to establish a reference range for healthy individuals.The difference in plasma GABA levels between apparently healthy individuals and patients with sleep disorders was compared.Results We employed deuterated compounds as isotopic internal standards and utilized an Amide chromatographic column for separation.The mobile phase was 0.050%formic acid in water and 90%acetonitrile in water containing 0.175%formic acid and 5 mmol/L ammonium acetate with gradient elution in the column temperature of 35℃.The linear range for the detection of GABA by LC-MS/MS was 0.05-10.00 μmol/L,with a lower limit of quantification of 0.02 μmol/L,the inter-day CV<3.00%and intra assay CV<4.00%,respectively,and the recovery rate was 101.06%-109.02%.The reference ranges for plasma GABA were established by analyzing 300 healthy controls stratified by age:18-34 years(0.08-0.15 μmol/L),35-49 years(0.10-0.20 μmol/L),and≥50 years(0.12-0.23 μmol/L).Then plasma GABA was used as a biomarker for auxiliary diagnosis of sleep disorders in analyzing 221 patients and 300 healthy controls,which revealed that AUC values were 0.510(P=0.850),0.686(P=0.002),and 0.890(P<0.001)in the groups of 18-34 years,35-49 years,and≥50 years,respectively,with optimal cut-off values of 0.09,0.10 and 0.11 μmol/L.Conclusion A reliable LC-MS/MS method for detecting GABA has been established,which can detect plasma GABA levels sensitively and accurately and can be used in assisting the clinical diagnosis of sleep disorders.

Objective To investigate the changes in oral microbiota of db/db mice and provide an experimental basis for exploring the relationship between type 2 diabetes mellitus and oral microecology.Methods Eight 10-week-old male db/db mice were designated as the diabetes experimental group(db/db group),while eight 10-week-old male db/m mice were assigned as the normal control group(db/m group).After a 5-day adaptive feeding period,tail venous blood samples were collected on the 6th and 37th days,and fasting blood glucose(FBG)levels and oral glucose tolerance test(OGTT)were performed for both groups to verify the reliability of the diabetes model.On the 15th day of feeding with the same diet,oral microbiota samples were collected from the buccal mucosa,dorsal and ventral tongue surfaces,oral floor mucosa,hard palate mucosa,and the gingival areas of both the upper and lower jaws of the two groups.Genomic DNA from the oral microbiota was extracted,and the V3-V4 regions of the 16S ribosomal RNA(16S rRNA)gene were amplified using a GeneAmp 9700 thermocycler.The composition of the oral microbiota was evaluated through double-labelled amplification and sequencing on the Illumina MiSeq platform,followed by bioinformatics analysis using QI I ME software(version 1.6.0).Results The FBG levels and OGTT results on the 6th and 37th days after the start of the experiment indicated that db/db mice exhibited more pronounced symptoms of type 2 diabetes compared to db/m mice.Alpha diversity(αdiversity)analysis showed no significant difference in the diversity of oral microbiota between the two groups(P＞0.05);however,there was a significant difference in richness(P＜0.05).Principal coordinate analysis(PCoA)revealed differences in the oral microbiota composition between the db/db group and db/m group(P＜0.05).Species composition analysis and LEfSe analysis demonstrated that the relative abundance of oral microbiota in db/db group mice,predominantly composed of p_Proteobacteria,increased significantly at the phylum level(P＜0.05).At the genus level,the relative abundances of g_Proteus and g_Enterococcus showed a significant increase(P＜0.001).Conclusion The composition and diversity of oral microbiota in db/db mice with type 2 diabetes mellitus significantly differed from those without the disease.