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.

Metastasis serves as an indicator of malignancy and is a biological characteristic of carcinomas. Epithelial-mesenchymal transition (EMT) plays a key role in the promotion of tumor invasion and metastasis and in the enhancement of tumor cell aggressiveness. Prostaglandin E synthase 3 (p23) is a cochaperone for heat shock protein 90 (HSP90). Our previous study showed that p23 is an HSP90-independent transcription factor in cancer-associated inflammation. The effect and mechanism of action of p23 on lung cancer metastasis are tested in this study. By utilizing cell models in vitro and mouse tail vein metastasis models in vivo, the results provide solid evidence that p23 is critical for promoting lung cancer metastases by regulating downstream CXCL1 expression. Rather than acting independently, p23 forms a complex with RNA-binding motif protein 14 (RBM14) to facilitate EMT progression in lung cancer. Therefore, our study provides evidence for the potential role of the RBM14-p23-CXCL1-EMT axis in the metastasis of lung cancer.

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.

Qingzao Jiufeitang is a famous classical formula for treating lung injury caused by warm and dryness， included in the Catalogue of Ancient Famous Classical Formulas（The First Batch）. By systematically organizing ancient and modern literature on this formula， this study analyzed and verified the origin， medicinal composition， original plants and processing， dosage and decoction method， efficacy and application of this formula. According to the research， Qingzao Jiufeitang was first recorded in Yimen Falyu in the Qing dynasty， and its creation was mainly inspired by the Ming dynasty physician MIAO Xiyong's idea of the moisturizing drugs with sweet flavour and cold nature. Based on the 2020 edition of the Pharmacopoeia of the People's Republic of China（hereinafter referred to as the Chinese Pharmacopoeia） and the textual research results of modern scholars on traditional Chinese herbal medicines， the botanical sources and processing methods of the herbs in this formula are basically clarified. Among them， Mori Folium， Gypsum Fibrosum， Ginseng Radix et Rhizoma， Sesami Semen Nigrum， Asini Corii Colla， Ophiopogonis Radix and Eriobotryae Folium are consistent with the 2020 edition of the Chinese Pharmacopoeia. The primary source of Glycyrrhizae Radix et Rhizoma is the dried roots and rhizomes of Glycyrrhiza uralensis， family Leguminosae， while the primary source of Armeniacae Semen Amarum is the dried mature seeds of Prunus armeniaca， family Rosaceae. It is recommended to use Gypsum Ustum， stir-fried Sesami Semen Nigrum， stir-fried Armeniacae Semen Amarum， Asini Corii Colla bead， and honey-fried Eriobotryae Folium， and the rest of the raw products. According to the conversion of ancient and modern doses， the recommended dosages are 11.19 g for Mori Folium， 9.33 g for Gypsum Fibrosum， 3.73 g for Glycyrrhizae Radix et Rhizoma， 2.61 g for Ginseng Radix et Rhizoma， 3.73 g for Sesami Semen Nigrum， 4.48 g for Ophiopogonis Radix， 2.61 g for Armeniacae Semen Amarum， 3.73 g for Eriobotryae Folium. The decoction method is to add 300 mL of water， decoct it down to 180 mL， remove the residue， and then add 2.98 g of Asini Corii Colla into the decoction. Take it warm after meals， two to three times a day. Qingzao Jiufeitang has the effects of clearing dryness and moistening the lungs， nourishing Yin and invigorating Qi. In ancient times， it was mainly used to treat stagnation and depression of various Qi， as well as paralysis， asthma and vomiting. In modern clinical practice， it is mostly used to treat diseases in respiratory system， otolaryngology， skin system and digestive system caused by warm-dry impairing lung， deficiency of both Qi and Yin. The above research results can provide a reference for the later development of Qingzao Jiufeitang.

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

Long-term exposure to particulate matter has been increasingly implicated in the progression of chronic kidney disease (CKD). However, its impact on IgA nephropathy (IgAN), a leading cause of end-stage renal disease (ESRD), remains unclear. A total of 1768 IgAN patients, confirmed by renal biopsy were included in this cohort study. Long-term exposure to PM_2.5 and PM₁₀ was assessed using high-resolution satellite-based data from the China High Air Pollutants (CHAP) dataset. Cox proportional hazards models were used to estimate the associations between PM_2.5 or PM₁₀ and ESRD risk, adjusting for demographic, clinical, and biochemical covariates. Over a median follow-up of 3.63 years, 209 participants progressed to ESRD. Higher exposure to both PM_2.5 and PM₁₀ was significantly associated with an increased risk, with hazard ratios of 1.62 and 1.36 per 10 µg/m³ increase, respectively. A nonlinear dose-response relationship was observed, with risk increasing markedly beyond threshold levels. Trajectory modeling of prebaseline exposure identified a subgroup with persistently high and fluctuating particulate matter exposure that showed the highest risk. This study provides strong evidence that prolonged exposure to ambient particulate matter contributes to renal disease progression in individuals with IgAN.
Humans ; Glomerulonephritis, IGA/pathology* ; Particulate Matter/adverse effects* ; Male ; Female ; Kidney Failure, Chronic/epidemiology* ; Adult ; China/epidemiology* ; Disease Progression ; Environmental Exposure/adverse effects* ; Middle Aged ; Proportional Hazards Models ; Risk Factors ; Air Pollutants/adverse effects* ; Cohort Studies

Glioma is the most common primary malignant tumor of the central nervous system in adults. Despite the standard treatment of surgery combined with radiotherapy and chemotherapy, the prognosis for high-grade glioma patients remains poor, highlighting the urgent need to further explore its pathogenesis and develop new therapeutic strategies. This article reviews the research progress in the field of glioma in China in 2024, covering tumorigenesis mechanisms, tumor immune microenvironment composition, advances in imaging techniques and novel imaging agents, improvements in surgical approaches, mechanisms of radio- and chemoresistance, and explorations of new therapeutic modalities. These studies provide a solid theoretical foundation for advancing clinical diagnosis and treatment of gliomas and may offer new opportunities to improve patient outcomes.

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.