To explore the advantages of traditional Chinese medicine （TCM） and integrative TCM-Western medicine approaches in the treatment of diabetic microvascular complications （DMC）， refine key pathophysiological insights and treatment principles， and promote academic innovation and strategic research planning in the prevention and treatment of DMC. The 38th session of the Expert Salon on Diseases Responding Specifically to Traditional Chinese Medicine， hosted by the China Association of Chinese Medicine， was held in Beijing， 2024. Experts in TCM， Western medicine， and interdisciplinary fields convened to conduct a systematic discussion on the pathogenesis， diagnostic and treatment challenges， and mechanism research related to DMC， ultimately forming a consensus on key directions. Four major research recommendations were proposed. The first is addressing clinical bottlenecks in the prevention and control of DMC by optimizing TCM-based evidence evaluation systems. The second is refining TCM core pathogenesis across DMC stages and establishing corresponding "disease-pattern-time" framework. The third is innovating mechanism research strategies to facilitate a shift from holistic regulation to targeted intervention in TCM. The fourth is advancing interdisciplinary collaboration to enhance the role of TCM in new drug development， research prioritization， and guideline formulation. TCM and integrative approaches offer distinct advantages in managing DMC. With a focus on the diseases responding specifically to TCM， strengthening evidence-based support and mechanism interpretation and promoting the integration of clinical care and research innovation will provide strong momentum for the modernization of TCM and the advancement of national health strategies.

OBJECTIVE To construct a predictive model for evaluating the efficacy of a triple antiemetic regimen （neurokinin- 1 receptor antagonist+5-hydroxytryptamine 3 receptor antagonist+dexamethasone） for preventing nausea and vomiting induced by highly emetogenic chemotherapy （HEC） based on interpretable deep learning algorithms. METHODS Clinical data of cancer patients who received HEC and were treated with the standard triple antiemetic regimen in the oncology department of Tianjin Medical University General Hospital from January 2018 to December 2022 were collected retrospectively. Demographic， clinical and metabolism-related variables were integrated. After data pre-processing， two deep learning algorithms （deep random forest and dense neural network） and four machine learning algorithms （support vector machine， categorical boosting， random forest and decision tree） were used to build predictive models. Subsequently， model performance evaluation and model interpretability analysis were conducted. RESULTS Among the six candidate models， the deep random forest model demonstrated the best predictive performance on the test set， with an area under the receiver operating characteristic curve of 0.850， an accuracy of 0.911， a precision of 0.805， a recall of 0.783， an F1 score of 0.793， and a Brier score of 0.075. Interpretability analysis revealed that creatinine clearance rate （Ccr） was the key predictive factor， and low Ccr levels， female gender， younger age， highly emetogenic drugs （particularly cisplatin-containing chemotherapy regimens）， and anticipatory nausea and vomiting were positively correlated with the risk of HEC-related nausea and vomiting. CONCLUSIONS The deep random forest model exhibits the best performance in predicting the efficacy of triple antiemetic regimen for preventing HEC-related nausea and vomiting. The key predictors in this model primarily include Ccr，anticipatory nausea and vomiting， gender， age， and highly emetogenic drugs.

Background: s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated. Methods: In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs. Results: Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment. Conclusions We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective To investigate the probability and dosimetric risk factors of lung injury after sequential immune checkpoint inhibitors (ICIs) and thoracic radiotherapy. Methods A retrospective analysis was conducted on 139 patients who received sequential ICIs and thoracic radiotherapy in Xuzhou Cancer Hospital and Affiliated Hospital of Xuzhou Medical University between February 2020 and February 2024. The relationships of clinical factors and lung and heart volume dose parameters with grade ≥ 2 acute lung injury (ALI) in patients with thoracic tumors were studied using univariable (χ² test, t test, nonparametric test) and multivariable (binary logistic regression analysis) methods. The thresholds of dosimetric risk factors were determined using the receiver operating characteristic curves. Clinical factors included age, gender, smoking history, type of ICIs, cycle of ICI application, and the interval between ICI application and thoracic radiotherapy. Dose parameters included total radiotherapy dose, single dose, planning target volume, maximum dose of planning target volume, average dose of planning target volume, total lung volume, heart volume, and the V₅, V₁₀, V₁₅, V₂₀, V₂₅, V₃₀, V₃₅, and V₄₀ of lung and heart. Results The incidence of grade ≥ 2 ALI in the included cases was 36% (50/139). The χ² test did not find any statistically significant clinical factors. In the univariable and binary Logistic regression analysis, lung V₁₅ and V₂₀, heart V₁₅ and V₂₀, and lung volume were independent risk factors for the occurrence of grade ≥ 2 ALI in sequential ICIs and thoracic radiotherapy. The thresholds were 18.51% for lung V₁₅, 14.43% for lung V₂₀, 32.41% for heart V₁₅, and 17.74% for heart V₂₀. Conclusion For patients who are going to receive thoracic radiotherapy after ICIs, the thresholds of lung V₁₅ and V₂₀ and heart V₁₅ and V₂₀ in the radiotherapy plan are recommended to be less than 18.51%, 14.43%, 32.41%, and 17.74%, respectively, which can effectively reduce the occurrence of grade ≥ 2 ALI.

Objective: To analyze the temporal variation patterns of sickness absenteeism among primary and secondary school students in Shanghai, so as to explore models suitable for predicting peaks and intensity of absenteeism rates. Methods: The seasonal and trend decomposition using loess (STL) method was used to analyze the seasonal and long term trend changes in sickness absenteeism among primary and secondary school students from September 1 in 2010 to June 30 in 2018, in Shanghai. A hierarchical clustering method based on Dynamic Time Warping (DTW) was employed to classify absenteeism symptoms with similar temporal patterns. Based on historical data, the study constructed and evaluated different time series algorithms and machine learning models to optimize the accuracy of predicting the trend of sickness absenteeism. Results: During the research period, the average new absenteeism rate due to illness was 16.86 per 10 000 person day for every academic year, and the trend of sickness absenteeism exhibited both seasonality and a long term upward trend, reaching its highest point in the 2017 academic year (22.47 per 10 000 person day). The symptoms of absenteeism were divided into three categories: high incidence in winter and spring (respiratory symptoms, fever and general discomfort, etc.), high incidence in summer (eye symptoms, nosebleeds, etc.) and those without obvious seasonality (skin symptoms, accidental injuries, etc.).The constructed time series models effectively predicted the trend of absenteeism due to illness, although the accuracy of predicting peak intensity was relatively low. Among them, the multi layer perceptron (MLP) model performed the best, with an root mean squared error (RMSE) of 8.96 and an mean absolute error (MAE) of 4.37, reducing 36.51% and 39.02% compared to the baseline model. Conclusion Time series models and machine learning algorithms could effectively predict the trend of sickness absenteeism, and corresponding prevention and control measures can be taken for absenteeism caused by different symptoms during peak periods.

Sleep， skin， and health are closely interconnected. Clinically， insomnia has a high incidence and is often accompanied by or secondary to skin aging. The two conditions exhibit "different diseases with the same syndrome"， significantly affecting the physical and mental health of the Chinese population. Preventing and treating skin aging by improving insomnia is an important strategy， with the principle of "treating different diseases with the same approach" serving as a crucial therapeutic guideline. However， effective clinical prevention and treatment methods for both conditions remain lacking. Traditional Chinese medicine （TCM） has a profound theoretical foundation and notable efficacy in the concurrent treatment of insomnia and skin aging， yet there are few reports on the etiology， pathogenesis， therapeutic principles， and treatment methods of their shared treatment， warranting further exploration. Based on holistic view and syndrome differentiation and treatment in TCM， this study systematically investigates the theoretical origins of the shared manifestations of insomnia and skin aging from multiple dimensions， including etiology， pathological location， pathogenesis， disease nature， and prevention and treatment strategies. As early as Huangdi's Internal Classic （Huangdi Neijing）， it was recognized that mental clarity during the day， sound sleep at night， and firm， healthy skin are key indicators of external health， whereas daytime lethargy， poor sleep quality， and dry， withered skin are prominent signs of aging. Maintaining mental clarity during the day and restful sleep at night is essential for skin integrity and healthy aging. Later medical scholars proposed that the common etiology of insomnia and skin aging lies in "internal-external interactions"， with the pathological location involving "the five organ systems". The primary pathogenesis includes "deficiency， fire， stagnation， phlegm， and blood stasis"， while the disease nature is often characterized by "a combination of deficiency and excess". Treatment should be guided by syndrome differentiation， following the principle of balancing Yin and Yang. This theoretical exploration enriches and advances TCM understanding of disease onset and prevention， providing theoretical guidance for the clinical prevention and treatment of insomnia-associated skin aging and contributing to the realization of the "Healthy China" initiative.

ObjectiveTo explore the molecular mechanism by which gypenoside L （Gyp-L） promotes apoptosis and inhibits ovarian cancer （OC） through the FK506-binding protein （FKBP） prolyl isomerase 8 （FKBP8）/B-cell lymphoma-2 （Bcl-2） axis， with the piR-hsa-2804461 pathway as a breakthrough point. MethodsThe effects of different concentrations of Gyp-L and cis-platinum on the proliferation of OVCAR3 cells were determined by the cell count kit-8 method to identify the appropriate intervention concentration for subsequent experiments. OVCAR3 cells were allocated into blank， low-dose Gyp-L （Gyp-L-L， 50 µmol·L^-1）， high-dose Gyp-L （Gyp-L-H， 100 µmol·L^-1）， and cis-platinum （15 µmol·L^-1） groups. The migration， colony formation， and apoptosis of OVCAR3 cells were detected by the cell scratch assay， colony formation assay， and flow cytometry， respectively. The mRNA levels of piR-hsa-2804461 and FKBP8/Bcl-2 axis-related genes in OVCAR3 cells were determined by Real-time PCR， and the expression levels of FKBP8/Bcl-2 axis-related proteins were determined by simple Western blot. Further， an OVCAR3 cell model with piR-hsa-2804461 knocked out was constructed. The cells were allocated into blank， NC-inhibitor， inhibitor， NC-inhibitor+Gyp-L， and inhibitor+Gyp-L groups. The colony formation of OVCAR3 cells was detected by the colony formation assay. The mRNA levels of piR-hsa-2804461 and FKBP8/Bcl-2 axis-related genes and the expression levels of FKBP8/Bcl-2 axis-related proteins were determined by Real-time PCR and simple Western blotting， respectively. ResultsGyp-L inhibited the migration and proliferation （P<0.01）， promoted the apoptosis （P<0.05）， up-regulated the mRNA level of piR-hsa-2804461 （P<0.05）， and down-regulated the mRNA and protein levels of FKBP8 and Bcl-2 （P<0.05） in OVCAR3 cells. Furthermore， Gyp-L increased the mRNA and protein levels of Bcl-2-associated X protein （Bax）， cysteinyl aspartate-specific proteinase （Caspase）-3， and Caspase-9， which are related to the FKBP8/Bcl-2 axis （P<0.05）. ConclusionGyp-L may promote apoptosis by regulating the piR-hsa-2804461/FKBP8/Bcl-2 axis， thus affecting the occurrence of ovarian cancer.

ObjectiveTo explore the molecular mechanism of gypenoside L （Gyp-L） in the treatment of ovarian cancer （OC） by taking the glycolytic pathway of OC as the key point. MethodsThe proliferation activity of OVCAR3 cells was measured by the cell counting kit-8 （CCK-8） assay to determine the appropriate intervention concentration for subsequent experiments. The cell clone formation assay and the scratch healing assay were employed to assess the proliferation and migration capabilities of OVCAR3 cells. OVCAR3 cells were divided into a blank group， a Gyp-L-L group （low concentration of Gyp-L， 50 µmol·L^-1）， a Gyp-L-H group （high concentration of Gyp-L， 100 µmol·L^-1）， and a cisplatin （15 µmol·L^-1） group. The glucose consumption in OC cells was determined using a kit， and the expression levels of related mRNAs in OVCAR3 cells were detected by real-time fluorescence quantitative polymerase chain reaction （Real-time PCR）. The expressions of related proteins were detected by Wes automatic Western blot quantitative analysis. ResultsValidated by the cell scratch assay， the scratch healing rate of OVCAR3 cells was decreased after Gyp-L intervention， reflecting that Gyp-L could significantly inhibit the migration of OVCAR3 cells （P<0.05）. According to the clone formation assay， the cell colony formation ability of the Gyp-L-L group， Gyp-L-H group， and cisplatin group was significantly lower than that of the control group （P<0.05）. In OVCAR3 cells， compared with those in the control group， the levels of glucose consumption and lactate generation in the Gyp-L-L group and Gyp-L-H group were significantly reduced （P<0.05）， indicating that Gyp-L could effectively inhibit the glycolysis level of OC cells. Meanwhile， Gyp-L could suppress the expression levels of glucokinase （GCK）， phosphofructokinase liver （PFKL）， signal transducer and activator of transcription 3 （STAT3）， lactate dehydrogenase D （LDHD）， phosphoglycerate mutase 1 （PGAM1）， mRNAs， and proteins related to the glycolytic pathway in OC cells. ConclusionGyp-L may inhibit the occurrence and development of OC by influencing the GCK-mediated glycolytic pathway.

ObjectiveTo evaluate the effectiveness of stone needle thermocompression and massage compared to flurbiprofen gel patch in relieving chronic musculoskeletal pain in the shoulder and back， and to explore the potential mediating mechanism through muscle elasticity. MethodsA total of 120 patients with chronic musculoskeletal pain in the shoulder and back were randomly assigned to either stone needle group or flurbiprofen group， with 60 patients in each. The stone needle group received stone needle thermocompression and massage for 30 minutes， three times per week； the flurbiprofen group received flurbiprofen gel patch twice daily. Both groups were treated for 2 weeks. Pain improvement， as the primary outcome， was assessed using the Global Pain Scale （GPS） at baseline， after 2 weeks of treatment， and again 2 weeks post-treatment. To explore potential mechanisms， a mediator analysis was conducted by measuring changes in superficial and deep muscle elasticity using musculoskeletal ultrasound at baseline and after the 2-week treatment period. ResultsThe stone needle group showed significantly greater pain relief than the flurbiprofen group 2 weeks post-treatment. After adjusting for confounders related to pain duration， the between-group mean difference was -8.8 ［95% CI （-18.2， -0.7）， P＜0.05］. Part of the therapeutic effect was mediated by changes in deep muscle elasticity， with a mediation effect size of -1.5 ［95% CI （-2.0， -0.9）， P = 0.024］， accounting for 17.9% of the total effect. ConclusionStone needle thermocompression and massage can effectively relieve chronic musculoskeletal pain in the shoulder and back， partly through a mediating effect of improved deep muscle elasticity.