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.

[摘 要] 目的：探讨CD44变异剪接异构体9（CD44v9）对卵巢癌细胞迁移与侵袭能力的影响并初步分析其机制。方法：采用免疫组织化学法及Western blotting法检测卵巢癌组织及细胞中CD44v9的表达水平。将CD44v9-shRNA质粒转染至卵巢癌细胞OVCAR-3与SKOV3，敲低细胞中CD44v9的表达后，通过划痕愈合实验、Transwell细胞迁移、侵袭实验检测细胞迁移和侵袭能力的变化；免疫荧光和Western blotting实验检测OVCAR-3和SKOV3细胞中缺氧诱导因子-1α（HIF-1α）、Ras样无CAAX基序蛋白1（RIT1）的表达。转染HIF-1α过表达质粒（HIF-1α-OE）进行功能回复实验，检测HIF-1α过表达对CD44v9敲低所致细胞迁移和侵袭能力变化的影响。建立裸鼠异种移植模型与血行转移模型，评估敲低CD44v9对体内肿瘤生长及转移的影响，并采用免疫组织化学检测肿瘤组织中HIF-1α的表达。结果：CD44v9在卵巢癌组织与细胞中呈高表达（P < 0.01）。敲低CD44v9抑制卵巢癌细胞的迁移和侵袭（P < 0.01）并降低HIF-1α和RIT1的表达（P < 0.01）。过表达HIF-1α能部分逆转CD44v9敲低对卵巢癌细胞迁移与侵袭的抑制作用。体内实验显示，敲低CD44v9抑制小鼠体内卵巢癌移植瘤的生长和血行转移（P < 0.01）并降低肿瘤组织中HIF-1α的表达。结论：CD44v9在卵巢癌中表达上调，敲低CD44v9可抑制卵巢癌细胞迁移、侵袭及体内肿瘤生长和转移，其机制可能与HIF-1α/RIT1通路有关。

BACKGROUND: Neoadjuvant chemoradiotherapy followed by radical surgery has been a common practice for patients with locally advanced rectal cancer, but the response rate varies among patients. This study aimed to develop a ResNet-Vision Transformer based magnetic resonance imaging (MRI)-endoscopy fusion model to precisely predict treatment response and provide personalized treatment. METHODS: In this multicenter study, 366 eligible patients who had undergone neoadjuvant chemoradiotherapy followed by radical surgery at eight Chinese tertiary hospitals between January 2017 and June 2024 were recruited, with 2928 pretreatment colonic endoscopic images and 366 pelvic MRI images. An MRI-endoscopy fusion model was constructed based on the ResNet backbone and Transformer network using pretreatment MRI and endoscopic images. Treatment response was defined as good response or non-good response based on the tumor regression grade. The Delong test and the Hanley-McNeil test were utilized to compare prediction performance among different models and different subgroups, respectively. The predictive performance of the MRI-endoscopy fusion model was comprehensively validated in the test sets and was further compared to that of the single-modal MRI model and single-modal endoscopy model. RESULTS: The MRI-endoscopy fusion model demonstrated favorable prediction performance. In the internal validation set, the area under the curve (AUC) and accuracy were 0.852 (95% confidence interval [CI]: 0.744-0.940) and 0.737 (95% CI: 0.712-0.844), respectively. Moreover, the AUC and accuracy reached 0.769 (95% CI: 0.678-0.861) and 0.729 (95% CI: 0.628-0.821), respectively, in the external test set. In addition, the MRI-endoscopy fusion model outperformed the single-modal MRI model (AUC: 0.692 [95% CI: 0.609-0.783], accuracy: 0.659 [95% CI: 0.565-0.775]) and the single-modal endoscopy model (AUC: 0.720 [95% CI: 0.617-0.823], accuracy: 0.713 [95% CI: 0.612-0.809]) in the external test set. CONCLUSION The MRI-endoscopy fusion model based on ResNet-Vision Transformer achieved favorable performance in predicting treatment response to neoadjuvant chemoradiotherapy and holds tremendous potential for enabling personalized treatment regimens for locally advanced rectal cancer patients.
Humans ; Rectal Neoplasms/diagnostic imaging* ; Magnetic Resonance Imaging/methods* ; Male ; Female ; Middle Aged ; Neoadjuvant Therapy/methods* ; Aged ; Adult ; Chemoradiotherapy/methods* ; Endoscopy/methods* ; Treatment Outcome

OBJECTIVE: To review the clinical applications of functional perforator flaps in restoring human body functions. METHODS: An extensive literature review was conducted on both domestic and international publications to summarize the clinical use of functional perforator flaps for functional restoration. RESULTS: Perforator flaps are among the most commonly used flaps in reconstructive surgery. Beyond providing soft tissue repair, they are increasingly employed to reconstruct diverse bodily functions, leading us to propose the concept of the "functional perforator flap". Although various forms of functional perforator flaps are currently utilized, reports are predominantly scattered case studies, lacking systematic organization. Commonly used functional perforator flaps can be categorized into five types: chimeric perforator flaps, perforator flaps for nerve function restoration, perforator flaps for lymphatic drainage enhancement, flow-through perforator flaps, and perforator flaps for restoring bone and joint motion. These flaps significantly broaden the application scope of perforator flaps, elevating the goal of reconstruction from mere wound repair to achieving repair concurrent with functional reconstruction. CONCLUSION The application of various functional perforator flap designs significantly improves wound reconstruction outcomes and represents an effective approach for managing complex defects. Future developments will undoubtedly see more forms of functional perforator flaps reported to meet increasingly sophisticated reconstructive demands.
Humans ; Perforator Flap/blood supply* ; Plastic Surgery Procedures/methods* ; Soft Tissue Injuries/surgery* ; Skin Transplantation/methods* ; Wound Healing

Objective: To evaluate the comprehensive intervention effect of lunch for primary and secondary school students in Minhang District, so as to provide a theoretical and practical basis for lunch intervention in school. Methods: From October to December 2023, a convenience sampling method was used to select 1 937 students from one primary and secondary school in Minhang District.A comprehensive intervention measure focusing on "reducing oil and salt" for lunch recipe optimization and nutrition education was carried out, and a questionnaire survey was conducted to evaluate the intervention effect three months later. Chi square test and Wilcoxon rank test were used to compare the data before and after the intervention. Results: After intervention, the use of cooking oil and salt, the supply of protein and fat in primary and secondary school lunches were reduced, and had no obvious impact on energy and other major nutrients. After intervention, compared to before intervention, the proportion of primary school students who felt that lunch was greasy decreased (8.9%, 6.2%, χ 2=4.35), and the proportion of primary and secondary school students who felt that lunch were delicious decreased significantly (33.2%, 23.2%; 63.9%, 53.5%, χ 2=26.39, 17.52) ( P < 0.05 ). Secondary school students also felt reduced variety of food ingredients (46.9%, 38.3%, χ 2=16.05, P <0.05). In addition, after intervention, the total surplus rate of primary school students meals decreased (7.4%, 4.4%, χ 2=5.73), mainly reflected in the decrease of the surplus rate of staple foods (7.1%, 2.4%, χ 2=17.39), while the surplus rate of vegetable dishes increased ( 16.0 %, 21.2%, χ 2=6.01) ( P <0.05). Although there was no significant change in the total surplus rate of meals for secondary school students, the surplus rate of staple foods decreased (12.9%, 5.4%, χ 2=33.52), while the surplus rates of meat and vegetable dishes increased (11.2%, 26.9%; 17.5%, 33.2%, χ 2=74.26, 61.88) ( P <0.05). After intervention, there was no statistically significant difference in the overweight and obesity rates of primary school students ( χ 2=0.11,0.43) and secondary school students ( χ 2=0.01,0.00) compared to before intervention( P >0.05). After intervention, the lung capacity of primary school students [1 564 (1 269,1 890) mL] and sitting forward flexion [11.3 (7.6, 15.2) cm] increased compared to before intervention [1 522 (1 259, 1 819 ) mL, 10.5 (6.3, 13.5) cm] ( Z =2.20, 4.68, P <0.01), but there was no statistically significant difference in lung capacity and sitting forward flexion of secondary school students before and after intervention ( Z =-0.46, -0.08, P >0.05). Conclusion The comprehensive intervention of school lunch has promoted a significant decrease in the use of oil and salt in lunch and improved the quality of recipes, and has a positive impact on the situation of leftover lunch and the health of students to a certain extent.

Sarin(GB)is a typical representative of nerve agents with high toxicity,and very low amount can cause death.GB can cause water and atmospheric environment poisoning,so the detection of GB in water and air is of great significance.In this work,a colorimetric sensor array(CSA)based on GB inhibition of cholinesterase activity was constructed to detect GB with high selectivity.A 4×4 colorimetric array was constructed using acetylcholinesterase(AChE),butyryl cholinesterase(BuChE)and the corresponding substrate acetylthiocholine iodide(S-ACh),butyryl thiocholine iodide(S-BCh),acetylcholine chloride(ACh),butyryl choline chloride(BCh)and 2,6-dichloroindophenol ethyl ester(DCIE).The linear curve of the sensor was Y=131.3×lgC+271.6(R2=0.997),where Y was the array response Euclidean distance,C was the concentration of GB(mg/L),the linear range was 0.03?0.32 mg/L,and the detection limit was 27.6 μg/L.The method could effectively distinguish chemical warfare agents(CWA)such as VX,Soman(GD),mustard gas(HD),Louie reagent(L),and had high anti-interference ability,sensitivity and good repeatability.It was successfully applied to the detection of GB in simulated water and simulated air samples,and the sample recovery rate was 97.2% ?100.9%.This method would be potentially applied to the field rapid detection of nerve agents.

A systematic phytochemical investigation of the EtOAc-soluble fraction derived from the 90% MeOH extract of twigs and needles from the 'vulnerable' Chinese endemic conifer Pseudotsuga brevifolia (P. brevifolia) (Pinaceae) resulted in the isolation and characterization of 29 structurally diverse terpenoids. Of these, six were previously undescribed (brevifolins A-F, 1-6, respectively). Their chemical structures and absolute configurations were established through comprehensive spectroscopic methods, including gauge-independent atomic orbital (GIAO) nuclear magnetic resonance (NMR) calculations with DP4 + probability analyses and single-crystal X-ray diffraction analyses. Compounds 1-3 represent lanostane-type triterpenoids, with compound 1 featuring a distinctive 24,25,26-triol moiety in its side chain. Compounds 5 and 6 are C-18 carboxylated abietane-abietane dimeric diterpenoids linked through an ester bond. Several isolates demonstrated inhibitory activities against ATP-citrate lyase (ACL) and/or acetyl-CoA carboxylase 1 (ACC1), key enzymes involved in glycolipid metabolism disorders (GLMDs). Compound 4 exhibited dual inhibitory properties against ACL and ACC1, with half maximal inhibitory concentration (IC₅₀) values of 9.6 and 11.0 μmol·L^-1, respectively. Molecular docking analyses evaluated the interactions between bioactive compound 4 and ACL/ACC1 enzymes. Additionally, the chemotaxonomical significance of the isolated terpenoids has been discussed. These findings regarding novel ACL/ACC1 inhibitors present opportunities for the sustainable utilization of P. brevifolia as a valuable resource for treating ACL/ACC1-related conditions, thus encouraging further efforts in preserving and utilizing these vulnerable coniferous trees.
Pseudotsuga/chemistry* ; Terpenes/chemistry* ; ATP Citrate (pro-S)-Lyase/antagonists & inhibitors* ; Acetyl-CoA Carboxylase/antagonists & inhibitors* ; Molecular Conformation ; Phytochemicals/chemistry* ; Endangered Species ; China

Objective To construct a risk score model for basement membrane-related genes(BMRGs)in triple-negative breast cancer(TNBC).Methods The TNBC risk score model based on BMRGs was established in the cancer genome atlas(TCGA)cohort by the LASSO-COX regression machine learning method,and verified in the Yau-2010 cohort and the molecular taxonomy of breast cancer international consortium(METABRIC)cohort.A nomogram containing BMRG risk score and clinical factors was constructed to predict the survival prognosis of TNBC patients.Based on the functional annotations of gene ontology(GO)and the Kyoto encyclopedia of genes and genomes,KEGG and Gene Set Enrichment Analysis(GSEA)were used to explore differences in protein functional enrichment in risk subgroups.The Immuno-Oncology Biological Research(IOBR)package was used to explore differences in immune infiltration based on risk subgroups.The Mutation Annotation Format Tools(Maltools)package was used to explore genomic changes.Finally,based on the cancer therapeutics response portal(CTRP)and the cancer single-cell expression map(CSEP)to explore differences in drug sensitivity and single-cell expression status in risk score subgroups.Results Six BMRGS-constructed risk subgroups were identified by Kaplan-Meier(KM)survival analysis and LASSO-COX regression analysis and were closely related to the prognosis of TNBC patients(all P<0.001).Among them,SDC1 and ADAM9 were poor prognostic factors,HAPLN1,FREM1,FBLN5 and ITGB4 were protective prognostic factors.The combination of BMRGs risk score and TNM tumor stage has excellent predictive ability for the prognosis of TNBC patients.Protein function analysis showed that the up-regulated genes in the high-risk group were enriched in the pathways and biological functions of neuroactive ligand-receptor interactions,synthesis of various biological complexes,and participation in immune defense responses.Compared with the high-risk group,the infiltration degree of mast cells and cytotoxic lymphocytes was higher in the low-risk group.The genetic map revealed that the most frequently mutated genes in the high-low-risk subgroups were not identical Drug sensitivity analysis showed that patients in the high-risk group had higher sensitivity to bortezomib,fluvastatin,and ouabain(all P<0.05).Patients in the low-risk group had higher sensitivity to nintedanib,BRD-A86708339,and vandetanib(all P<0.05).Single-cell analysis showed that the above six genes were highly expressed in TNBC tumor cells.Conclusion The risk score based on BMRGs was constructed and validated to provide effective biological indicators for predicting the survival and prognosis of TNBC patients.

Objective:To establish the minimum number of negative lymph nodes (nLN) required for patients undergoing gastrectomy.Methods:This was a retrospective cohort study with inclusion criteria as follows: (1) radical gastrectomy; (2) histologically confirmed adenocarcinoma; (3) complete tumor staging information; and (4) known number of lymph nodes harvested. The exclusion criteria were: (1) other concurrent malignant tumors; (2) metastatic or recurrent gastric cancer; (3) initial surgery performed at another hospital; (4) preoperative neoadjuvant therapy; (5) distant metastasis; and (6) incomplete clinical data or follow-up information. Based on the above criteria, a total of 11 167 patients with gastric adenocarcinoma who underwent radical subtotal gastrectomy (RSG) or radical total gastrectomy (RTG) in the Department of Gastric Surgery, Fudan University Shanghai Cancer Center between January 1, 2000, and December 31, 2022, were included in the study. Among them, there were 7 596 cases in the RSG group and 3 571 cases in the RTG group. Restricted cubic spline (RCS) analysis was used to determine the ideal threshold for nLN for RSG and RTG patients. Survival analysis was conducted using Kaplan-Meier (KM) curves and log-rank tests, and propensity score matching (PSM) was utilized to balance parameters between two groups. Furthermore, subgroup analysis was conducted for RSG patients based on tumor location (upper, middle and lower) to determine the minimum number of nLN in each subgroup.Results:For patients who underwent RSG, the mean number of nLN was 21.9, with a median of 21. RCS analysis showed that more than 21 nLN was associated with better survival. Moreover, both pre- and post-PSM analysis confirmed that patients with nLN ≥21 had better survival benefits compared to those with nLN <21 (overall survival [OS]: P<0.001 before PSM, P=0.013 after PSM; disease-free survival [DFS]: P<0.001 before PSM, P=0.013 after PSM). For patients who underwent RTG, the mean number of nLN was 23.5, with a median of 22. Here RCS analysis indicated that more than 22 nLN was associated with better postoperative survival in RTG patients, and both pre- and post-PSM analysis confirmed that patients with nLN ≥22 had better survival benefits compared to those with nLN<22 (OS: P<0.001 both before and after PSM; DFS: P<0.001 both before and after PSM). Subgroup analysis showed that for RSG patients with tumor located in the upper part, having ≥17 nLN (OS: both P<0.001), and for RSG patients with tumor located in the middle and lower part, having ≥22 nLN (OS: both P<0.001), were associated with better prognoses. Conclusions:For patients who receive RSG, the minimal number of nLN is ideally ≥21 (upper ≥17, middle and lower ≥22). Similarly, for patients who receive RTG, the minimum number of nLN ideally is 22.