Esophageal cancer is a prevalent malignant tumor of the digestive tract in China, and radical surgery remains the cornerstone of its comprehensive treatment. However, multifactorial challenges such as postoperative gastrointestinal tract reconstruction, traumatic stress, and tumor-related metabolic disturbances render esophageal cancer patients highly susceptible to malnutrition. Perioperative nutritional support therapy plays a crucial role in enhancing surgical safety, improving clinical outcomes, and elevating patients' quality of life by regulating metabolic homeostasis, preserving organ function, and optimizing the immune microenvironment. This article reviews the mechanisms underlying malnutrition in esophageal cancer, methods for nutritional status assessment, and precision intervention pathways based on multi-omics evaluations. The aim is to strengthen clinicians' awareness of standardized perioperative nutritional management for esophageal cancer patients and promote its clinical implementation, thereby facilitating postoperative recovery and improving long-term quality of life.

Background: Sex-based differences often influence the therapeutic efficacy and safety of medications. Semen Cuscutae is a traditional tonic botanical drug with sex-specific characteristics, traditionally indicated for conditions such as impotence (exclusive to males) and restless fetus (exclusive to pregnant females). However, most existing studies have focused on a single sex. Objective: To evaluate the sex-specific biological effects of Semen Cuscutae in rats and explore its molecular mechanisms, with the aim of uncovering its pharmacological characteristics through a multiomics approach. Methods: A traditional aqueous extract of Semen Cuscutae (SCA) was used as the experimental material. Forty adult Sprague-Dawley rats (equal numbers of males and females) were randomly divided into 4 groups: male control, male SCA treatment (240 mg/kg), female control, and female SCA treatment (240 mg/kg), with 10 rats in each group. The biological effects were comprehensively evaluated using a combination of open field test, biochemical analyses, proteomics, and gut microbiota profiling. Results: As a tonic botanical drug, SCA appeared to directly affect the mental and behavioral state of rats. It significantly altered the time spent by rats in the center area during the open field test, showing a sex-dependent reversal of behaviors. Proteomic analysis of brain tissue identified 624 differentially expressed proteins across the groups, with 10 key differentially expressed proteins related to sex differences, including fibroblast growth factor receptor 3, transcription elongation factor A protein-like 1, 40S ribosomal protein S25, neural cell adhesion molecule, and anion exchange protein 2 (SLC4A2). Enrichment analysis revealed that in male rats, SCA upregulated proteins involved in biological processes such as ribosome function and energy derivation, supporting protein synthesis and enhancing energy supply, showing an overall gain effect. In contrast, in female rats, SCA downregulated proteins associated with processes such as positive regulation of target of rapamycin (TOR) signaling and vesicle transport, suggesting suppression of neuronal signaling and material transport, indicative of a shift toward a more restrained physiological state. Furthermore, SCA reduced gut microbiota diversity in female rats but increased it in males, including the abundance of Akkermansia, which may serve as a crucial mediator. Conclusion: Overall, the biological effects of SCA differ significantly between male and female rats, with evidence suggesting greater health benefits in males. These findings help elucidate the scientific basis of its traditional applications and provide guidance for the precise application of SCA as a functional health food.

ObjectiveTo enhance teaching in postoperative cancer rehabilitation, this study developed an integrative Chinese-Western medicine postoperative oncology rehabilitation system, termed the medical oncology generative pre-trained transformer (MedOncoGPT). By introducing MedOncoGPT as an intelligent assistant, an integrated teaching model combining Chinese and Western medicine was established. The study evaluated its impact on students’ integrative clinical reasoning and practical abilities, providing support for instructional reform in related courses. MethodsUsing teaching resources as the knowledge base, MedOncoGPT was built upon the open-source ChatGLM model and incorporated Low-Rank Adaptation (LoRA) fine-tuning and retrieval-augmented generation (RAG) techniques to address postoperative integrative oncology scenarios. The system was applied in courses and clinical clerkships related to integrative oncology. In alignment with course objectives, a five-stage instructional process—pre-class preparation, in-class inquiry, simulated multidisciplinary consultation, clinical reinforcement, and teaching reflection—was designed to guide students in completing syndrome differentiation, comprehensive assessment, and follow-up planning within real or simulated case contexts. Comparative analyses of student engagement, syndrome differentiation thinking, evidence-based awareness, and interdisciplinary integration skills before and after the teaching reform were conducted using questionnaires, course assessments, classroom observations, and semi-structured interviews. ResultsFollowing the implementation of MedOncoGPT, students demonstrated improved performance in case analysis, prescription formulation, and integrative Chinese-Western medical evaluation compared with those receiving traditional instruction. Classroom participation and the relevance of student inquiries also increased. Self-assessment results indicated high levels of satisfaction with respect to clarity of integrative clinical reasoning, ability to retrieve and apply guideline-based evidence, and awareness of appropriate use of intelligent tools in clinical decision-making. More than 92% of students reported that the system facilitated understanding of abstract theoretical concepts presented in textbooks. Instructors noted that the system helped reduce lesson preparation time, enriched typical case materials and discussion scenarios, and promoted the translation of research findings into classroom teaching. Pilot data showed that, with MedOncoGPT assistance, the mean time for initial syndrome differentiation decreased from 18.4 min to 12.1 min, and the agreement rate increased from 68.3% to 82.5%. In the teaching pilot, the experimental group achieved a higher mean score on the final case analysis assessment than the control group (82.6 vs. 74.3). ConclusionThe integration of MedOncoGPT into teaching on postoperative integrative cancer rehabilitation enabled the establishment of a stable instructional process within existing curricula and enhanced students’ integrative clinical reasoning and evidence-based practice capabilities. The approach demonstrates positive potential for advancing the integration of research, clinical practice, and education and represents a valuable exploratory strategy for instructional reform in courses on integrative Chinese-Western medicine.

ObjectiveTo enhance teaching in postoperative cancer rehabilitation, this study developed an integrative Chinese-Western medicine postoperative oncology rehabilitation system, termed the medical oncology generative pre-trained transformer (MedOncoGPT). By introducing MedOncoGPT as an intelligent assistant, an integrated teaching model combining Chinese and Western medicine was established. The study evaluated its impact on students’ integrative clinical reasoning and practical abilities, providing support for instructional reform in related courses. MethodsUsing teaching resources as the knowledge base, MedOncoGPT was built upon the open-source ChatGLM model and incorporated Low-Rank Adaptation (LoRA) fine-tuning and retrieval-augmented generation (RAG) techniques to address postoperative integrative oncology scenarios. The system was applied in courses and clinical clerkships related to integrative oncology. In alignment with course objectives, a five-stage instructional process—pre-class preparation, in-class inquiry, simulated multidisciplinary consultation, clinical reinforcement, and teaching reflection—was designed to guide students in completing syndrome differentiation, comprehensive assessment, and follow-up planning within real or simulated case contexts. Comparative analyses of student engagement, syndrome differentiation thinking, evidence-based awareness, and interdisciplinary integration skills before and after the teaching reform were conducted using questionnaires, course assessments, classroom observations, and semi-structured interviews. ResultsFollowing the implementation of MedOncoGPT, students demonstrated improved performance in case analysis, prescription formulation, and integrative Chinese-Western medical evaluation compared with those receiving traditional instruction. Classroom participation and the relevance of student inquiries also increased. Self-assessment results indicated high levels of satisfaction with respect to clarity of integrative clinical reasoning, ability to retrieve and apply guideline-based evidence, and awareness of appropriate use of intelligent tools in clinical decision-making. More than 92% of students reported that the system facilitated understanding of abstract theoretical concepts presented in textbooks. Instructors noted that the system helped reduce lesson preparation time, enriched typical case materials and discussion scenarios, and promoted the translation of research findings into classroom teaching. Pilot data showed that, with MedOncoGPT assistance, the mean time for initial syndrome differentiation decreased from 18.4 min to 12.1 min, and the agreement rate increased from 68.3% to 82.5%. In the teaching pilot, the experimental group achieved a higher mean score on the final case analysis assessment than the control group (82.6 vs. 74.3). ConclusionThe integration of MedOncoGPT into teaching on postoperative integrative cancer rehabilitation enabled the establishment of a stable instructional process within existing curricula and enhanced students’ integrative clinical reasoning and evidence-based practice capabilities. The approach demonstrates positive potential for advancing the integration of research, clinical practice, and education and represents a valuable exploratory strategy for instructional reform in courses on integrative Chinese-Western medicine.

Objective To explore the optimal warning threshold of motor evoked potentials(MEP)in decompression surgery for ossification of the posterior longitudinal ligament(OPLL)at cervical and thoracic segments,and the predictive role of different MEP parameters on postoperative lower extremity motor function.Methods A retrospective analysis was conducted on the clinical data of 227 patients diagnosed with cervical or thoracic OPLL and underwent decompression surgery from January 2022 to January 2024 in the hospital.There were 131 males and 96 females,with an average age of(60±10)years.All patients underwent continuous neuro-physiological monitoring during the operation,and the minimum ratio of MEP amplitude change to the baseline at the beginning of the operation(Dmax)and the ratio of MEP terminal amplitude change to the baseline at the end of the operation(Dend)were recorded.The correlations between these two ratios and the lower extremity motor func-tion immediately after the operation and at 1 year were compared.According to the Medical Research Council muscle strength score(MRC)standard,a postoperative score increase of≥1 point compared to preoperative was defined as postoperative motor dysfunction.Pearson correlation coefficients were used to evaluate the correlations between Dmax and Dend and the lower extremity motor function immediately after the operation and at 1 year.Receiver operating characteristic(ROC)curves were drawn to predict postoperative lower extremity motor dysfunc-tion using Dmax and Dend.Results Among the 227 patients,186 had cervical OPLL and 41 had thoracic OPLL.The incidence of lower extremity motor dysfunction immediately after the operation and at 1 year was 7 cases(3.76%)and 2 cases(1.08%)in the cervical group,and 9 cases(21.95%)and 3 cases(7.32%)in the thoracic group,respectively.The incidence of lower extremity motor dysfunction in the thoracic group was higher than that in the cervical group(P<0.001).The baseline induction rate of bilateral lower extremity MEPs was 98.92%(368/372)in the cervical group and 96.34%(79/82)in the thoracic group.The Pearson correlation coefficients of Dend with the bilateral lower extremity motor function immediately after the operation in the cervical and thoracic groups were both greater than those of Dmax,and the differences were statistically significant(cervical group:r=0.669,0.517,P=0.001 2;thoracic group:r=0.882,0.727,P=0.003 6),while the differences in the Pearson corre-lation coefficients of Dend and Dmax with the bilateral lower extremity motor function at 1 year were not statistically significant(cervical group:r=0.457,0.352,P=0.088;thoracic group:r=0.760,0.625,P=0.098).The cut-off values of Dend for the cervical group were 0.853 immediately after the operation and at 1 year,and the cut-off values of Dmax were 0.881 and 0.978,respectively.For the thoracic group,the cut-off values of Dend were 0.532 immediately after the operation and 0.639 at 1 year,and the cut-off values of Dmax were 0.532 and 0.640,respec-tively.Conclusions In OPLL surgery,the MEP monitoring strategy should be adjusted according to the surgical segment.For the cervical segment,Dmax should be emphasized to balance high sensitivity and specificity,while for the thoracic segment,Dmax or Dend can be flexibly selected.Higher MEP warning thresholds are required for cervical OPLL surgery(Dmax:0.881 immediately after the operation and 0.978 at 1 year;Dend:0.853),while significantly lower thresholds are needed for thoracic OPLL(Dmax/Dend:0.532 immediately after the operation and 0.640 at 1 year).

Objective:To investigate the value of biparametric-MRI (bpMRI) based peritumoral radiomics for preoperative prediction of extraprostatic extension (EPE) in prostate cancer (PCa).Methods:In this cross-sectional study, consecutive bpMRI of patients undergoing prostatectomy for PCa were retrospectively collected from the First Medical Center (center 1) and the Third Medical Center (center 2) of Chinese PLA General Hospital. A total of 274 patients were finally enrolled. Patients at center 1 from January 2020 to December 2022 were randomly divided into a training set (149 cases) and an internal validation set (63 cases) by stratified random sampling. Patients at center 2 from January 2023 to March 2024 were assigned to the external test set (62 cases). Patients were categorized into EPE-positive group and EPE-negative group according to pathological assessment postoperatively. In the training set, there were 49 cases in EPE-positive group and 100 cases in EPE-negative group. In the internal validation set, there were 26 cases in EPE-positive group and 37 cases in EPE-negative group. In the external test set, there were 22 cases in EPE-positive group and 40 cases in EPE-negative group. Axial T 2WI and apparent diffusion coefficient (ADC) images were manually annotated to obtain index lesion regions of interest (ROIs), with the peritumoral ROIs subsequently delineated by semi-automatic segmentation technique. Radiomics features were extracted from intra-tumoral, peri-tumoral, and intra-tumoral plus peri-tumoral ROIs. The training set data was employed to select and optimize features to build the radiomics models. The logistic regression analysis was used to develop radiomics, clinical, and integrated models. The predictive performance was assessed by the area under the receiver operating characteristic curve (AUC) in the external test set, and compared by the DeLong test. The sensitivity and specificity were compared by the exact McNemar test. Results:In the external test set, the peri-tumoral radiomics model based on bpMRI showed the highest performance in evaluating EPE, with an AUC of 0.739 (95% CI 0.611-0.842), which was identified as the optimal radiomics model. EPE grade ( OR=6.151, 95% CI 3.371-11.226, P<0.001) was incorporated into the clinical model, with an AUC of 0.780 (95% CI 0.657-0.875) in the external test set. The integrated model had an AUC of 0.817 (95% CI 0.698-0.904) in the external test set. There was no statistically significant difference in comparisons of AUCs among the three models (all P>0.05). The sensitivity of the integrated model (68.2%) showed no significant difference from those of the clinical model and the optimal radiomics model (77.3% and 86.4%, respectively; P=0.500 and P=0.289). However, the specificity of the integrated model (85.0%) was significantly higher than those of the clinical model (67.5%, P=0.016) and the optimal radiomics model (50.0%, P<0.001). Conclusion:A bpMRI-based peritumoral radiomics integrating clinical model demonstrates high performance for preoperative prediction of EPE in PCa.

Objective:To analyze the influencing factors of postoperative pulmonary embolism (PE) in patients undergoing hepatectomy.Methods:Clinical data of 171 patients undergoing hepatectomy at the Department of Hepatobiliary and Pancreatic Surgery, the Second Affiliated Hospital of Kunming Medical University from January 2018 to November 2024 were retrospectively analyzed, including 95 males and 76 females, aged (52.0±12.6) years. The pathology of patients included hepatolithiasis, hepatic hemangioma, liver abscess, focal nodular hyperplasia of liver, hepatocellular carcinoma, intrahepatic cholangiocarcinoma, etc. According to whether PE occurred after hepatectomy, patients were divided into PE group ( n=64) and control group ( n=107). Univariate and multivariate logistic regression analysis were used to analyze the influencing factors of PE after hepatectomy. The receiver operating characteristic (ROC) curve was used to analyze the effect of each index on predicting PE after hepatectomy. Results:Multivariate logistic regression analysis showed that red blood cell volume distribution width ( OR=1.399, 95% CI: 1.223-1.601) and systemic inflammation response index (SIRI) on postoperative day (POD) 3 ( OR=1.317, 95% CI: 1.124-1.544) and D-dimer on POD1 ( OR=1.208, 95% CI: 1.026-1.421) were associated with a higher risk of PE after hepatectomy (all P<0.05). The area under the ROC curve of SIRI on POD3, D-dimer on POD1, and red blood cell volume distribution width on POD3 on predicting PE after hepatectomy was 0.763 (95% CI: 0.689-0.838), 0.744 (95% CI: 0.668-0.820) and 0.796 (95% CI: 0.727-0.864), respectively. Conclusion:Red blood cell volume distribution width on POD3, SIRI on POD3 and D-dimer on POD1 are the risk factors of PE after hepatectomy. These three indicators have certain predictive value for PE after hepatectomy.

Aim To explore the mechanism of the syn-ergistic effect of the ferroptosis inducer erastin com-bined with shikonin in promoting ferroptosis in human hypertrophic scar fibroblasts(HSFBs).Methods Hypertrophic scar tissues provided by the General Hos-pital of Ningxia Medical University were collected,and HSFBs were extracted.HSFBs were identified by HE staining and immunofluorescence.The inhibitory rates of Era and SHK on HSFBs at different concentrations were detected by CCK-8 assay,and the IC50 value was calculated.CompuSyn software was used to calculate the co-use index(CI).Control group,Erastin(Era)group,shikonin(SHK)group and Era+SHK group were set up,and the number and morphological chan-ges of cells were observed after 24 hours of interven-tion.The ability of cell migration and invasion was de-tected by scratch test and Transwell test.The changes of malondialdehyde(MDA),total iron ion and reactive oxygen species(ROS)were detected by corresponding biochemical kits.The expressions of collagen I,α-SMA and GOT1,SLC7A11,GPX4 and FTH1 were detected by Western blot.Results The IC50 value of Era and SHK of primary HSFBs was 2.22 μmol·L-1 and 3.94μmol·L-1 respectively,which was used as the single drug concentration for subsequent experiments.The CompuSyn software was employed to calculate the CI value when the two drugs were used in combination,and the concentrations corresponding to CI=0.39597(Era:1.2 μmol·L-1+SHK:1.5 μmol·L-1)were selected as subsequent combination concentrations(Because when CI was equal to 0.395 97,the concen-tration of each drug was lower than the concentration of single drug,and the inhibition rate of combined drug was greater than 50％).Compared with the monother-apy group,the number of HSFBs in the SHK+Era group was significantly reduced,cell membrane showed breakage and vesiculation,cell wrinkling became smal-ler,and cytoplasm was concentrated.The migration and invasion ability of HSFBs in the SHK+Era group were obviously weakened(P＜0.05),and the expres-sion of fibrosis-related proteins collagen Ⅰ and α-SMA was reduced(P＜0.05);the contents of MDA,total i-ron ions,and ROS in HSFBs of the SHK+Era group increased(P＜0.05),and the protein expression lev-els of SLC7A11,GOT1,GPX4,and FTH1 further de-creased(P＜0.05).Conclusions Erastin in combi-nation with shikonin can synergistically inhibit the pro-liferation,migration and fibrosis levels of HSFBs.The mechanism may be that erastin enhances the inhibition of shikotin on GOT1,increases the levels of cellular i-ron ions,ROS,and lipid peroxides,thereby promoting ferroptosis in HSFBs.

Background: Salvia miltiorrhiza Bunge, commonly known as “Danshen” in China due to the distinctive red color of its roots, is one of the most widely used traditional Chinese medicines. It is cultivated in various regions across China, and environmental differences among these regions can affect the secondary metabolites of plants, thereby influencing the quality of S. miltiorrhiza. In recent years, increasing demand for S. miltiorrhiza has exacerbated the problem of origin fraud. Therefore, ensuring the authenticity of its geographical origin is crucial for the sustainable development of the industry. Objective: The red coloration of S. miltiorrhiza is closely associated with the content of its primary active compounds, particularly tanshinones. Therefore, both its internal chemical composition and external color characteristics serve as key indicators for quality assessment. This study utilized hyperspectral imaging technology to evaluate its potential in classifying the geographical origin of S. miltiorrhiza. Methods: Spectral data reflecting the internal chemical properties of S. miltiorrhiza were integrated with color information representing its external features through 3 levels of data fusion. These fused datasets were then combined with deep learning algorithms to achieve accurate origin classification. Results: The results demonstrated that the Transformer model combined with soft-voting decision-level fusion achieved the highest classification accuracy of 98.72% by integrating image color and short-wave infrared spectral data. Conclusion: This study demonstrates that integrating hyperspectral imaging spectral data with color information provides a reliable and innovative approach for verifying the authenticity and traceability of S. miltiorrhiza.

Objective:To investigate the value of biparametric-MRI (bpMRI) based peritumoral radiomics for preoperative prediction of extraprostatic extension (EPE) in prostate cancer (PCa).Methods:In this cross-sectional study, consecutive bpMRI of patients undergoing prostatectomy for PCa were retrospectively collected from the First Medical Center (center 1) and the Third Medical Center (center 2) of Chinese PLA General Hospital. A total of 274 patients were finally enrolled. Patients at center 1 from January 2020 to December 2022 were randomly divided into a training set (149 cases) and an internal validation set (63 cases) by stratified random sampling. Patients at center 2 from January 2023 to March 2024 were assigned to the external test set (62 cases). Patients were categorized into EPE-positive group and EPE-negative group according to pathological assessment postoperatively. In the training set, there were 49 cases in EPE-positive group and 100 cases in EPE-negative group. In the internal validation set, there were 26 cases in EPE-positive group and 37 cases in EPE-negative group. In the external test set, there were 22 cases in EPE-positive group and 40 cases in EPE-negative group. Axial T 2WI and apparent diffusion coefficient (ADC) images were manually annotated to obtain index lesion regions of interest (ROIs), with the peritumoral ROIs subsequently delineated by semi-automatic segmentation technique. Radiomics features were extracted from intra-tumoral, peri-tumoral, and intra-tumoral plus peri-tumoral ROIs. The training set data was employed to select and optimize features to build the radiomics models. The logistic regression analysis was used to develop radiomics, clinical, and integrated models. The predictive performance was assessed by the area under the receiver operating characteristic curve (AUC) in the external test set, and compared by the DeLong test. The sensitivity and specificity were compared by the exact McNemar test. Results:In the external test set, the peri-tumoral radiomics model based on bpMRI showed the highest performance in evaluating EPE, with an AUC of 0.739 (95% CI 0.611-0.842), which was identified as the optimal radiomics model. EPE grade ( OR=6.151, 95% CI 3.371-11.226, P<0.001) was incorporated into the clinical model, with an AUC of 0.780 (95% CI 0.657-0.875) in the external test set. The integrated model had an AUC of 0.817 (95% CI 0.698-0.904) in the external test set. There was no statistically significant difference in comparisons of AUCs among the three models (all P>0.05). The sensitivity of the integrated model (68.2%) showed no significant difference from those of the clinical model and the optimal radiomics model (77.3% and 86.4%, respectively; P=0.500 and P=0.289). However, the specificity of the integrated model (85.0%) was significantly higher than those of the clinical model (67.5%, P=0.016) and the optimal radiomics model (50.0%, P<0.001). Conclusion:A bpMRI-based peritumoral radiomics integrating clinical model demonstrates high performance for preoperative prediction of EPE in PCa.