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.

Human non-histone lysine crotonylation plays crucial roles in biological activities.However,traditional wet-lab experiments are time-consuming and labor-intensive,making computational prediction methods increasingly popular in recent years.Despite the biological importance of lysine crotonylation,there are relatively few studies on human non-histone proteins.In this study,we developed an ensemble deep learning predictor named iHNHC-RsFPN by constructing a Residual Pyramid Network(RsFPN).First,three feature extraction methods were employed to encode sequence samples.Next,weak classifi-ers based on RsFPN were individually trained for different feature types.Finally,these weak classifiers were integrated to build a robust final predictor.Independent test results demonstrated that iHNHC-RsF-PN achieved outstanding performance across four key metrics:sensitivity(Sn=0.8580),specificity(Sp=0.7463),accuracy(Acc=0.7798),and Matthews correlation coefficient(MCC=0.5586).Comparative experiments revealed that iHNHC-RsFPN significantly improved prediction accuracy for hu-man non-histone crotonylation sites over existing methods.Additionally,we established a user-friendly web server(http://www.lzzzlab.top/ihnc/)that provides straightforward prediction services without complex calculations,facilitating further research for experts in related fields.

Objective:To observe the early efficacy of intense pulsed light(IPL)combined with non-ablative fractional laser(NAFL)in preventing postoperative pathological scar formation and intervention of inflammatory factors.Methods:93 patients with postoperative pathological scar formation who were admitted to our hospital from March 2022 to September 2024 were selected,they were divided into control group A(silicone gel treatment,n=31),control group B(NAFL on the basis of control group A,n=31)and study group(IPL on the basis of control group B,n=31)using the random number table method.The clinical efficacy,simple quality of life scale(SF-36),vancouver scar scale(VSS),inflammatory factors[interleukin-6(IL-6),tumor necrosis factor-α(TNF-α),C-reactive protein(CRP)],and adverse reactions among three groups were compared.Results:The clinical total effective rate in the study group were higher than those in the control group A and control group B(P＜0.05).SF-36 increased sequentially and VSS decreased sequentially in control group A,control group B,and study group after treatment(P＜0.05).CRP,IL-6,and TNF-α decreased sequentially in control group A,control group B,and study group after treatment(P＜0.05).There was no significant difference in the incidence of adverse reactions among the three groups(P＞0.05).Conclusion:IPL combined with NAFL in preventing postoperative pathological scar formation,can effectively reduce scar formation,reduce inflammatory factors levels,improve patients' quality of life,and be safe and reliable.

Human non-histone lysine crotonylation plays crucial roles in biological activities.However,traditional wet-lab experiments are time-consuming and labor-intensive,making computational prediction methods increasingly popular in recent years.Despite the biological importance of lysine crotonylation,there are relatively few studies on human non-histone proteins.In this study,we developed an ensemble deep learning predictor named iHNHC-RsFPN by constructing a Residual Pyramid Network(RsFPN).First,three feature extraction methods were employed to encode sequence samples.Next,weak classifi-ers based on RsFPN were individually trained for different feature types.Finally,these weak classifiers were integrated to build a robust final predictor.Independent test results demonstrated that iHNHC-RsF-PN achieved outstanding performance across four key metrics:sensitivity(Sn=0.8580),specificity(Sp=0.7463),accuracy(Acc=0.7798),and Matthews correlation coefficient(MCC=0.5586).Comparative experiments revealed that iHNHC-RsFPN significantly improved prediction accuracy for hu-man non-histone crotonylation sites over existing methods.Additionally,we established a user-friendly web server(http://www.lzzzlab.top/ihnc/)that provides straightforward prediction services without complex calculations,facilitating further research for experts in related fields.

The clinical data and genetic characteristics of one child with mental retardation-56 (MRD56) diagnosed at the Department of Neonatology, Foshan Fosun Chancheng Hospital in October 2021 were retrospectively analyzed.The patient was admitted to the hospital with " 34 + 2 weeks of preterm birth, shortness of breath, and dyspnea for 0.5 hours". In the neonatal period, the patient had special facial features, hypotonia, weaning and feeding difficulties, laryngeal stridor.In infancy, the patient showed global psychomotor development delay, intellectual disability, epilepsy, etc.Magnetic resonance imaging of the brain showed delayed myelination and dysplasia of the cerebellum and corpus callosum.Whole-exome sequencing showed that the CLTC gene had a new missense mutation c.3334T>C (p.Trp1112Arg), and MRD56 was confirmed.A total of 32 cases of MRD56 were reported worldwide, with special facial features, intellectual disability, and psychomotor retardation as the main clinical manifestations.The cause is a mutation in the CLTC gene, which leads to abnormality in the structure of the clathrin encoded, thus affecting neurotransmitter transmission.This is the first report of MRD56 caused by the CLTC gene mutation in China, and a new clinical phenotype has been discovered.The finding enriches the phenotypic spectrum of the disease and provides a basis for clinicians to understand and study the disease.

Objective:To observe the early clinical efficacy of 3D-printed modular supporting prosthesis for reconstruction of lacunar bone defect caused by giant cell tumor of the distal femur.Methods:From May 2018 to July 2023, a total of 9 patients with giant cell tumor of the distal femur were treated with 3D-printed modular supporting prosthesis to reconstruct lacunar bone defects in the Department of Orthopedics, West China Hospital, Sichuan University. There were 4 males and 5 females, aged 30.8±6.1 years (range, 24-44 years), 5 cases on the left side, 4 cases on the right side, 2 cases of Campanacci grade I, 7 cases of Campanacci grade II. The anteroposterior and lateral X-ray films and T-SMART tomosynthesis imaging of the knee joint were taken to observe the bone graft healing and osseointegration after operation. Musculoskeletal Tumor Society (MSTS)-93 was used to evaluate knee function, and visual analogue scale (VAS) was used to evaluate knee pain.Results:All patients were successfully operated and followed up for an average of 30.8±7.5 months (range, 18-42 months). The operation time was 124.2±23.6 min, and the intraoperative blood loss was 105.6±17.4 ml. All autografts showed bony union at the graft-host junction, and the healing time was 3.3±0.4 months (range, 3.0-4.0 months). At 6 months after surgery, T-SMART tomosynthesis imaging showed that the gap between the prosthesis-bone interface was less than 1 mm in all patients. At the last follow-up, the thickness of residual subchondral bone was 5.7±1.3 mm, which was greater than that before operation 2.2±0.8 mm, and the difference was statistically significant ( t=10.823, P<0.001). At the last follow-up, the score of MSTS-93 was 26.7±2.4, which was higher than that before operation 18.8±3.7, and the difference was statistically significant ( t=5.367, P<0.001). At the last follow-up, the range of motion of the knee joint was 122.8°±9.1°, which was higher than that before operation 108.3°±6.1°, and the difference was statistically significant ( t=3.970, P<0.001). All patients were able to walk normally, go up and down stairs and other daily activities, and 7 patients were able to complete squats. At the last follow-up, there was no local tumor recurrence, distant metastasis, death, joint infection, pain (VAS score was 0), delayed wound healing, joint degeneration, prosthesis loosening or articular surface collapse. Conclusion:Reconstruction of lacunar bone defect caused by giant cell tumor of distal femur with 3D-printed modular supporting prosthesis can effectively improve knee joint function and osseointegration, and the short-term clinical results are satisfactory.

Objective:To explore the early and mid-term efficacy of three-dimensional printed customized porous prosthesis with preserved articular in the reconstruction of ultra-long segmental bone defect around the metaphysis of peri-knee.Methods:A retrospective analysis was conducted on the data of 24 patients who underwent reconstruction of ultra-long segmental bone defect around the metaphysis of peri-knee using 3D-printed customized porous prostheses at West China Hospital of Sichuan University from June 2015 to June 2021. There were 14 female cases and 10 male cases, with an average age of 28.9±16.5 years (range, 12-61 years), 12 cases at the distal end of the femur and 12 cases at the proximal end of the tibia. Tumor types: 16 cases of osteosarcoma, 4 cases of Ewing's sarcoma, 2 cases of chondrosarcoma, and 2 case of parosteal osteosarcoma. All patients were classified as Enneking stage IIB. Record the oncology results of the patients, the length of tumor segment resection, and the remaining bone length at the distal femur or proximal tibia, as well as complications, systemic metastasis and imaging changes. The bone integration at the prosthesis-bone interface was evaluated by tomosynthesis-shimadzu metal artifact reduction technology (T-SMART). Limb function was evaluated using the Musculoskeletal Tumor Society (MSTS)-93 score and knee range of motion assessment.Results:All 24 patients successfully completed the surgery and were followed up, with an average follow-up time of 51.8±12.7 months (range, 32-99 months). The length of femoral osteotomy was 241.1±66.2 mm (range, 150.6-333.4 mm), and the length of tibial osteotomy was 198.6±35.6 mm (range, 156.6-287.6 mm). The remaining bone length at the epiphyseal end around the knee joint (from the knee joint plane to the osteotomy plane of the distal femur or proximal tibia) was 52.6±11.0 mm (range, 31.1-77.5 mm). At the last follow-up, 23 patients survived tumor-free, while one patient died due to lung metastasis 54 months after the operation. One patient had prosthesis fracture 75 months after the operation, two patients had aseptic loosening 6 and 8 months after the operation, and the T-SMART of the remaining 20 patients showed that the implanted prostheses all achieved good osseointegration. At the last follow-up, the range of motion of the knee joint was 126.2°±7.5° (range, 110.0°-140.0°), and the MSTS-93 score was 26.7±1.8 points (range, 23-30 points). Among them, the MSTS-93 score of the femoral prosthesis was 26.7±1.6 points (range, 24-29 points), and the MSTS-93 score of the tibial prosthesis was 26.9±1.9 points (range, 23-30 points). The average knee range of motion was 126.2°±7.5° (range, 110°-140°), and the MSTS-93 functional score was 26.7±1.8 points (range, 23-30 points) at the last follow-up. The femoral component had an average score of 26.7±1.6 points (range, 24-29 points), while the tibial component had an average score of 26.9±1.9 points (range, 23-30 points).Conclusion:The application three-dimensional printed customized porous prosthesis with preserved articular in the reconstruction of ultra-long segmental bone defect around the metaphysis of peri-knee can preserve the joint, restore limb function well, and have a low incidence of prosthesis complications, with good clinical efficacy in the early and middle stages.

Objective:To conduct a scoping review on the application of telemedicine in patients with breast cancer-related lymphedema (BCRL), to generalize and summarize the intervention methods, application forms, outcome indicators and effects of telemedicine, so as to provide a reference for healthcare professionals to implement interventions.Methods:Computerized searches of PubMed, Web of Science, Embase, Cochrane Library, CINAHL, China National Knowledge Infrastructure, Wanfang Data, China Biology Medicine disc, and VIP were performed with a search period from their establishment to June 1, 2024. The included articles were screened, summarized and analyzed.Results:A total of 14 papers were included. Telemedicine intervention methods included tele-education, tele-exercise, tele-monitoring, tele-consultation, tele-psychological interventions, tele-visits, and tele-evaluation. Application forms involved web-based cloud platforms, social network service systems, telemedicine APPs, and remote portable monitoring devices. Outcome indicators included physical indicators, psychological indicators, quality of life, incidence of lymphedema, degree of lymphedema symptoms, and feasibility indicators.Conclusions:Telemedicine relies on web-based platforms and social network service software to conduct tele-education, tele-consultation, and tele-exercise for BCRL patients, and its feasibility and effectiveness have been proven. In the future, it is necessary to accelerate the establishment of breast cancer telemedicine centers, optimize the telemedicine service team, and increase the investment in the development of portable lymphedema telemonitoring equipment, so as to build a comprehensive and perfect breast cancer telemedicine system and improve the effectiveness of the prevention and treatment of BCRL.

Objective:To observe the early efficacy of intense pulsed light(IPL)combined with non-ablative fractional laser(NAFL)in preventing postoperative pathological scar formation and intervention of inflammatory factors.Methods:93 patients with postoperative pathological scar formation who were admitted to our hospital from March 2022 to September 2024 were selected,they were divided into control group A(silicone gel treatment,n=31),control group B(NAFL on the basis of control group A,n=31)and study group(IPL on the basis of control group B,n=31)using the random number table method.The clinical efficacy,simple quality of life scale(SF-36),vancouver scar scale(VSS),inflammatory factors[interleukin-6(IL-6),tumor necrosis factor-α(TNF-α),C-reactive protein(CRP)],and adverse reactions among three groups were compared.Results:The clinical total effective rate in the study group were higher than those in the control group A and control group B(P＜0.05).SF-36 increased sequentially and VSS decreased sequentially in control group A,control group B,and study group after treatment(P＜0.05).CRP,IL-6,and TNF-α decreased sequentially in control group A,control group B,and study group after treatment(P＜0.05).There was no significant difference in the incidence of adverse reactions among the three groups(P＞0.05).Conclusion:IPL combined with NAFL in preventing postoperative pathological scar formation,can effectively reduce scar formation,reduce inflammatory factors levels,improve patients' quality of life,and be safe and reliable.