Background Platelet parameters are important indicators of cardiovascular risk, and environmental pollutants such as polychlorinated biphenyls (PCBs) may impair platelet function through oxidative stress. Objective To investigate the differential effects of single and mixed exposure to PCBs on platelet parameters among individuals with normal glucose tolerance (NGT), impaired fasting glucose (IFG), and type 2 diabetes mellitus (T2DM), and to evaluate the potential modifying role of a healthy lifestyle. Methods This study included 2249 participants (including 707 with NGT, 759 with IFG, and 783 with T2DM). Plasma PCB concentrations were measured using triple quadrupole gaschromatography-tandem mass spectrometry. Generalized linear regression was used to assess the associations between individual PCB congeners and platelet parameters. Quantile g-computation (QGC) and Bayesian kernel machine regression (BKMR) models were used to evaluate the overall effects of PCBs mixture exposure on platelet parameters across different glycemic states, as well as its interaction with healthy lifestyle score (HLS). Results Generalized linear regression analyses showed significant differences in the effects of PCBs on platelet parameters across different glycemic states (P<0.05). After adjusting for confounders, PCBs mixture exposure was significantly associated with lower platelet counts (PLT) in individuals with NGT (b=−10.60, 95%CI: −16.48, −4.71) and IFG (b=−12.91, 95%CI: −18.90, −6.92), whereas no significant association was observed in individuals with T2DM (P=0.051). Mean platelet volume (MPV) and platelet-large cell ratio (P-LCR) increased significantly with higher PCBs exposure levels across all three groups (P<0.05). BKMR analysis showed a positive association between PCBs mixture exposure and P-LCR, with the strongest association observed in the NGT group. Furthermore, a significant interaction was observed between HLS and PCBs mixture exposure, and a higher HLS attenuated the effects of PCBs on P-LCR. Conclusion Glycemic glycemic states may modify the effects of PCBs on platelets. Individuals with NGT appear more sensitive to PCBs exposure, whereas the T2DM state may attenuate this effect. Moreover, healthy lifestyles, including not smoking, moderate alcohol consumption, maintaining moderate-to-high physical activity, a healthy diet, and an appropriate body mass index (BMI), may mitigate the adverse effects of most PCBs on platelet parameters.

Background Platelet parameters are important indicators of cardiovascular risk, and environmental pollutants such as polychlorinated biphenyls (PCBs) may impair platelet function through oxidative stress. Objective To investigate the differential effects of single and mixed exposure to PCBs on platelet parameters among individuals with normal glucose tolerance (NGT), impaired fasting glucose (IFG), and type 2 diabetes mellitus (T2DM), and to evaluate the potential modifying role of a healthy lifestyle. Methods This study included 2249 participants (including 707 with NGT, 759 with IFG, and 783 with T2DM). Plasma PCB concentrations were measured using triple quadrupole gaschromatography-tandem mass spectrometry. Generalized linear regression was used to assess the associations between individual PCB congeners and platelet parameters. Quantile g-computation (QGC) and Bayesian kernel machine regression (BKMR) models were used to evaluate the overall effects of PCBs mixture exposure on platelet parameters across different glycemic states, as well as its interaction with healthy lifestyle score (HLS). Results Generalized linear regression analyses showed significant differences in the effects of PCBs on platelet parameters across different glycemic states (P<0.05). After adjusting for confounders, PCBs mixture exposure was significantly associated with lower platelet counts (PLT) in individuals with NGT (b=−10.60, 95%CI: −16.48, −4.71) and IFG (b=−12.91, 95%CI: −18.90, −6.92), whereas no significant association was observed in individuals with T2DM (P=0.051). Mean platelet volume (MPV) and platelet-large cell ratio (P-LCR) increased significantly with higher PCBs exposure levels across all three groups (P<0.05). BKMR analysis showed a positive association between PCBs mixture exposure and P-LCR, with the strongest association observed in the NGT group. Furthermore, a significant interaction was observed between HLS and PCBs mixture exposure, and a higher HLS attenuated the effects of PCBs on P-LCR. Conclusion Glycemic glycemic states may modify the effects of PCBs on platelets. Individuals with NGT appear more sensitive to PCBs exposure, whereas the T2DM state may attenuate this effect. Moreover, healthy lifestyles, including not smoking, moderate alcohol consumption, maintaining moderate-to-high physical activity, a healthy diet, and an appropriate body mass index (BMI), may mitigate the adverse effects of most PCBs on platelet parameters.

Background: Nasopharyngeal carcinoma (NPC) is characterized by high programmed death-ligand 1 (PD-L1) expression and abundant infiltration of non-malignant lymphocytes, which renders patients potentially suitable candidates for immune checkpoint blockade therapies. Palate, lung, and nasal epithelium clone (PLUNC) inhibit the growth of NPC cells and enhance cellular apoptosis and differentiation. Currently, the relationship between PLUNC (as a tumor-suppressor) and PD-L1 in NPC is unclear. Methods: We collected clinical samples of NPC to verify the relationship between PLUNC and PD-L1. PLUNC plasmid was transfected into NPC cells, and the variation of PD-L1 was verified by western blot and immunofluorescence. In NPC cells, we verified the relationship of PD-L1, activating transcription factor 3 (ATF3), and β-catenin by western blot and immunofluorescence. Later, we further verified that PLUNC regulates PD-L1 through β-catenin. Finally, the effect of PLUNC on β-catenin was verified by co-immunoprecipitation (Co-IP). Results: We found that PLUNC expression was lower in NPC tissues than in paracancer tissues. PD-L1 expression was opposite to that of PLUNC. Western blot and immunofluorescence showed that β-catenin could upregulate ATF3 and PD-L1, while PLUNC could downregulate ATF3/PD-L1 by inhibiting the expression of β-catenin. PLUNC inhibits the entry of β-catenin into the nucleus. Co-IP experiments demonstrated that PLUNC inhibited the interaction of DEAD-box helicase 17 (DDX17) and β-catenin. Conclusions PLUNC downregulates the expression of PD-L1 by inhibiting the interaction of DDX17/β-catenin in NPC.

Objective To investigate the pathogenesis of high-altitude cerebral edema(HACE)and develop new therapeutic strategies.Methods Male Sprague-Dawley(SD)rats of 6 weeks old were selected and placed in a hypobaric chamber.The rats were exposed to the high-altitude environment of 7000 m above sea level for 3 days for HACE modeling.Whether the HACE model was successfully established in the rats was evaluated by measuring brain water content,the degree of disruption to the blood-brain barrier(BBB),and brain tissue Nissl staining.The experimental animals were divided into four groups,with 28 rats in each group.The blank control group was exposed to a normobaric and normoxic environment simulating the conditions at 500 m above sea level for 3 d.The other groups,including a model group(the HACE group),a bumetanide group(the positive control group),and a XH-6003 treatment group,were placed at an altitude of 7 000 m above sea level and were injected with normal saline,bumetanide,and XH-6003,a new type of Na-K-2C1 cotransporter 1(NKCC1)inhibitor,via the tail vein,respectively,twice daily for 3 d.The experimental animals were taken out of the hypobaric chamber for testing after 3 d.The primary outcome measures included brain water content,BBB permeability,changes in brain tissue morphology,and the expression levels of aquaporin-4(AQP4)and NKCC1.The secondary outcome measures included behavioral changes,apoptosis,and oxidative stress markers.Results The HACE rat model was successfully established.The model group exhibited increased brain water content(P＜0.0001),BBB disruption(P＜0.0001),impairment in learning skills and memory(P＜0.001),and anxiety/depression-like behaviors(P＜0.01).qPCR results showed significantly increased expression of NKCC1 and AQP4 in the brain tissue of the model group(P＜0.01).Pathology examination revealed neuronal and glial cell damage in the hippocampus of the model group(P＜0.01).Treatment with XH-6003,the NKCC1 inhibitor,reversed brain water content,BBB disruption,and neuronal and glial cell damage to a certain degree(P＜0.05),decreased the expression of NKCC1 and AQP4 in the brain tissue(P＜0.01),and inhibited apoptosis-related proteins.Among the oxidative stress indices,only glutathione(GSH)showed improvement(P＜0.001).Rats treated with XH-6003 showed functional improvement only in the time spent exploring novel objects,while other behavioral outcomes remained unchanged.Conclusion HACE is associated with the activation of the NKCC1/AQP4 pathway.Inhibition of this pathway alleviates brain edema,BBB disruption,and neuronal and glial cell damage.These findings suggest that XH-6003 holds potential as a therapeutic strategy for HACE at the cellular and molecular levels,but its effects in improving HACE-related behavioral disorders warrant further investigation.

Purpose: Human epidermal growth factor receptor 2 (HER2)-low breast cancer has the potential to emerge as a distinct subtype. Several studies have compared the differences between HER2-low and HER2-0 breast cancers, but no consensus has been reached.Additionally, a biomarker to predict pathological complete response (pCR) rates in patients with HER2-low breast cancer remains to be identified. Methods: We collected data from 777 patients across three centers, stratifying them into HER2-low and HER2-0 groups. We compared differences in survival and pCR rates between the two groups and investigated potential biomarkers that could reliably predict pCR. Results: The study found that patients with HER2-0 breast cancer had higher pCR rates compared to patients with HER2-low tumors (289 patients [30.1%] vs. 475 patients [18.1%], p < 0.0001). Survival analysis showed no significant advantage for HER2-low tumors over HER2-0 breast cancers. Binary logistic analysis revealed that androgen receptor (AR) expression predicts poorer pCR rates in both the overall patient group and the HER2-0 breast cancer group (overall patients: odds ratio [OR], 0.479; 95% confidence interval [CI], 0.250–0.917; p = 0.026 and HER2-0 patients: OR, 0.267; 95% CI, 0.080–0.892; p = 0.032). In contrast, programmed death ligand 1 (PD-L1) expression was associated with more favorable pCR rates in the overall patient group (OR, 3.199; 95% CI, 1.020–10.037; p = 0.046). Conclusion There is currently insufficient evidence to classify HER2-low breast cancer as a distinct subtype. Our study revealed that AR expression, along with negative PD-L1 expression, contributes to lower pCR rates.

OBJECTIVE: To explore the rules of acupoint selection and compatibility of acupuncture and moxibustion in treatment of chronic cough using data mining. METHODS: The ancient and modern medical record cloud platform, and the databases, i.e. CNKI, Wanfang, VIP, EMbase, Web of Science and PubMed, were searched to screen the ancient and modern literature on acupuncture and moxibustion treatment of chronic cough. The prescription database was established for acupuncture and moxibustion treatment of chronic cough, and the analysis conducted on the frequency and use percentage in the aspects of intervention measures, acupoint selection, acupoint distribution, meridian tropism, special points and acupoint combination, as well as the association rules and clustering rules of acupoint selection. The subgroup analysis was performed in accordance with the etiology of chronic cough and intervention measures. RESULTS: A total of 106 articles were included and 158 prescriptions were extracted. The intervention measures were acupuncture, moxibustion, herbal medication and the combination of several measures. The high-frequency acupoints included Feishu (BL13), Zusanli (ST36), Dazhui (GV14), Pishu (BL20), Danzhong (CV17), Shenshu (BL23), Lieque (LU7), Dingchuan (EX-B1), Tiantu (CV22), and Fenglong (ST40). These acupoints are mainly distributed on the back, lumbar region, chest and abdomen. The involved meridians were bladder meridian of foot-taiyang, conception vessel, and lung meridian of hand-taiyin. The special points covered back-shu points, crossing points and five-shu point. Regarding the compatibility of acupoints, the combination of upper and lower points, and the combination of front and back points were predominant in treatment. The analysis of association rules found that the support of Feishu (BL13)→Zusanli (ST36) was the highest; the cluster analysis obtained 8 clusters of acupoints. The acupoint compatibility and overall rules were similar when cough variant asthma (CVA) or the mixed reasons were involved, and the local treatment approach was adopted if the etiology of disease was related to upper airway cough syndrome (UACS) and gastroesophageal reflux cough (GERC). The acupoint selection was similar among different intervention measures. When two kinds of measures were combined in treatment, Feishu (BL13), Pishu (BL20) and Zusanli (ST36) were the most common. CONCLUSION In treatment with acupuncture and moxibustion for chronic cough, the acupoints are selected on the affected local area, depending on syndrome differentiation, and focusing on back-shu points. The main acupoints are Feishu (BL13), Zusanli (ST36), Dazhui (GV14), Pishu (BL20), Danzhong (CV17) and Shenshu (BL23). The combined therapy is dominant with acupuncture, moxibustion and herbal medicine involved.
Acupuncture Points ; Moxibustion/history* ; Humans ; Cough/history* ; Acupuncture Therapy/history* ; Chronic Disease/therapy* ; Data Mining ; History, Ancient ; Meridians ; Chronic Cough

Based on the etiology and clinical diagnostic criteria of type 2 diabetes mellitus （T2DM）， identification and typing of treatment from the perspective of traditional Chinese and western medicine， the criteria for evaluating the clinical compatibility of traditional Chinese and western medicine in animal models of T2DM were set up. The literature was reviewed to sort out and analyze the existing commonly used modeling methods， summarize the mechanism， compare the advantages and disadvantages， and calculate the consistency between the animal model and the clinical symptoms， syndromes， and indicators from the perspective of traditional Chinese and western medicine. The authors found that spontaneous animal models and high-fat diets combined with multiple low-dose streptozotocin （STZ） induction models were more in line with modern medical pathogenesis of T2DM. However， it fails to form some special syndromes required for traditional Chinese medicine （TCM） research. In addition， there are many methods of combining the etiology and pathogenesis of TCM， which can be divided into three categories： intervention carried out by drug administration， behavioral stimulation， or environmental changes according to TCM， or use of hormones according to clinical evidence and combination of the two methods mentioned above. All of them can successfully establish different types of animal models. However， different methods of establishing syndrome models have their own advantages and disadvantages， and there is no unified standard for the stability and evaluation of syndrome models. As for the clinical consistency criteria of traditional Chinese and western medicine established in this paper， the animal model with 100% consistency has not been calculated due to the conditions of incomplete symptoms and syndromes described in the studies and different selection indicators. Consequently， the establishment of a simple， easy-to-use， and affordable T2DM animal model with both traditional Chinese and western medicine disease characteristics and the improvement of the Chinese and western medicine evaluation system for different evidence types are of great significance for the future development of TCM research on T2DM.

Based on the etiology and clinical diagnostic criteria of type 2 diabetes mellitus （T2DM）， identification and typing of treatment from the perspective of traditional Chinese and western medicine， the criteria for evaluating the clinical compatibility of traditional Chinese and western medicine in animal models of T2DM were set up. The literature was reviewed to sort out and analyze the existing commonly used modeling methods， summarize the mechanism， compare the advantages and disadvantages， and calculate the consistency between the animal model and the clinical symptoms， syndromes， and indicators from the perspective of traditional Chinese and western medicine. The authors found that spontaneous animal models and high-fat diets combined with multiple low-dose streptozotocin （STZ） induction models were more in line with modern medical pathogenesis of T2DM. However， it fails to form some special syndromes required for traditional Chinese medicine （TCM） research. In addition， there are many methods of combining the etiology and pathogenesis of TCM， which can be divided into three categories： intervention carried out by drug administration， behavioral stimulation， or environmental changes according to TCM， or use of hormones according to clinical evidence and combination of the two methods mentioned above. All of them can successfully establish different types of animal models. However， different methods of establishing syndrome models have their own advantages and disadvantages， and there is no unified standard for the stability and evaluation of syndrome models. As for the clinical consistency criteria of traditional Chinese and western medicine established in this paper， the animal model with 100% consistency has not been calculated due to the conditions of incomplete symptoms and syndromes described in the studies and different selection indicators. Consequently， the establishment of a simple， easy-to-use， and affordable T2DM animal model with both traditional Chinese and western medicine disease characteristics and the improvement of the Chinese and western medicine evaluation system for different evidence types are of great significance for the future development of TCM research on T2DM.

Objective: To comprehensively evaluate and analyze the transfusion outcomes of patients with acute upper gastrointestinal bleeding (UGIB). Methods: The transfusion management system and hospital information system (HIS) were used to retrospectively collect clinical data of 230 patients with UGIB admitted to Zhejiang Provincial People's Hospital and its branches from June 2018 to June 2021. 101 cases were screened and categorized into transfusion group (n=56) and non-transfusion group (n=45) based on transfusion outcomes. The cohort comprised 68 males and 33 females. A univariate model based on the AIMS65 score, a logistic multiple regression model, and multivariate transfusion models using machine learning methods (including Random Forest, Support Vector Machine, and Artificial Neural Network) were established. The sensitivity, specificity, accuracy, and receiver operating characteristic (ROC) curves of each model were compared. Results: For the univariate model based on the AIMS65 scoring, the optimal threshold was 1.5. This model demonstrated a sensitivity of 0.446, a specificity of 0.822, an AUC of 0.67, an accuracy (ACC) of 0.614, a Kappa value of 0.256, and an F1-score of 0.655. For logistics regression model (optimal critical probability: 0.459), the sensitivity was 0.929, specificity was 0.889, AUC was 0.96, ACC was 0.911, Kappa was 0.819, and F1-score was 0.899. For the Random Forest model (optimal critical probability: 0.458), the sensitivity was 0.964, specificity was 0.956, AUC was 0.99, ACC was 0.960, Kappa was 0.920, and F1-score was 0.956. For the Support Vector Machine model (optimal critical probability: 0.474), the sensitivity was 0.875, specificity was 0.933, AUC was 0.94, ACC was 0.901, Kappa was 0.801, and F1-score was 0.894. For the Artificial Neural Network model (optimal critical probability: 0.797), the sensitivity was 0.804, specificity was 0.956, AUC was 0.96, ACC was 0.871, Kappa was 0.745, and F1-score was 0.869. Ten-fold cross validation also confirmed the reliability of the results. Conclusion: Based on integrated various clinical test indicators of patients, we could establish logistic regression model and multiple machine learning models. These models hold significant value for predicting the need for blood transfusion in patients, indicating a promising application prospect for machine learning algorithms in transfusion prediction.

Objective:To investigate the influencing factors for dysphagia in the elderly,to construct a predictive model for dysphagia,and to provide a theoretical basis for clinical practice.Methods:In this case-control study,the patients with dysphagia who attended Department of Geriatrics in the first affiliated hospital of Chongqing Medical University from March 2016 to June 2023 were enrolled as case group,and the patients without dysphagia who attended the same department during the same period of time were enrolled as con-trol group.The correlation analysis,least absolute shrinkage and selection operator(LASSO)regression,and multivariate logistic re-gression analysis were used to investigate the influencing factors for dysphagia;the 10-fold cross-validation Extreme Gradient Boosting(XGBoost)model was used to predict dysphagia,and the SHapley additive exPlanations(SHAP)method was used for model visualiza-tion.Results:There were 1009 cases in the case group and 2125 cases in the control group.The correlation analysis and LASSO re-gression analysis identified 12 factors for the multivariate logistic re-gression analysis,and the results showed that sarcopenia,increasing age,children or caretakers as caregivers,frail health,poor oral health,poor self-care ability,depression,and cognitive impairment were risk factors for dysphagia(odds ratio[OR]>1,P<0.05),and fe-male sex and participation in community activities were protective factors against dysphagia(OR<1,P<0.05).The XGBoost model had a good predictive efficacy,with an accuracy rate of 0.795,a preci-sion rate of 0.711,a sensitivity of 0.613,a specificity of 0.881,an F1 value of 0.661,and an area under the ROC curve of 0.855.The SHAP plot showed that the top five important characteristics were caregiver,oral score,frail health condition,activities of daily living,and cognitive function.Conclusion:There are various influencing factors for dysphagia in the elderly,and the elderly patients with poor oral health,frailty,dependence on others for daily life,and cognitive impairment should be taken seriously in clinical practice.The XGBoost model has a good performance in predicting dysphagia in the elderly,which can provide a reference for clinical practice.