BACKGROUND:Pulmonary arterial hypertension is a destructive cardiopulmonary disease for which there is no cure.An association between plasma proteins and pulmonary arterial hypertension has been suggested,but the causal relationship has not been specifically elucidated.OBJECTIVE:To elucidate the causal relationship between plasma proteome and pulmonary arterial hypertension using a two-sample Mendelian randomization method,thereby searching for potential therapeutic targets for pulmonary arterial hypertension.METHODS:Plasma Protein Gene-Wide Association Analysis Statistics for 4 907 Aptamer Measurements in 35 559 Icelanders from the Icelandic Database;Genome-wide association analysis statistics for pulmonary arterial hypertension were obtained from the Finn Gen database,version R9,including 234 cases and 265 626 controls.Analyses were performed using Mendelian randomization and Bayesian co-localization analysis,the findings were examined using sensitivity analyses,and protein-protein interaction network maps were constructed to explore the causal relationship between plasma proteins and pulmonary arterial hypertension.RESULTS AND CONCLUSION:(1)The results of inverse variance weighting,maximum likelihood and Wald ratio methods showed 19 proteins causally associated with pulmonary arterial hypertension(P＜0.05).Among them,10 plasma proteins,including Beta-1,3-N-acetylglucosaminyltransferase manic fringe(odds ratio[OR]=0.12,95％confidence interval[CI]0.02-0.61,P=0.01)and interferon alpha/beta receptor 1(OR=0.45,95％CI 0.24-0.84,P=0.012),might be associated with a reduced risk of pulmonary arterial hypertension.In contrast,nine plasma proteins,such as glucoside xylosyltransferase 1(OR=3.48,95％CI 1.51-8.00,P=0.003)and plasminogen(OR=42.78,95％CI 2.49-734.31,P=0.01),might be associated with an increased risk of pulmonary arterial hypertension.After the false discovery rate was corrected,19 proteins remained significantly associated with pulmonary arterial hypertension.(2)Multiple sensitivity analyses such as the MR-Egger intercept test and leave-one-out method showed no horizontal multiplicity or heterogeneity in the results of the study,indicating the stability of the study's results.(3)Bayesian co-localization analysis showed that six plasma proteins,including plasminogen(PPH4=1.0)and glucoside xylosyltransferase 1(PPH4=0.94),had PPH4＞0.8,suggesting that plasma proteins and the genome-wide association study of pulmonary arterial hypertension had similar causal variance in terms of genetic association.(4)By constructing a protein-protein interaction network map,plasminogen,Annexin A1,fibrinogen gamma chain and matrix metalloproteinase 7 were found to be core proteins.(5)The article used Mendelian randomization analysis to reveal a potential causal association between 4 907 plasma proteins and pulmonary arterial hypertension,suggesting that plasma proteins may be potential therapeutic targets for pulmonary arterial hypertension.The core proteins identified in the study also provide a theoretical basis for further in-depth study of the pathophysiological mechanisms of pulmonary arterial hypertension.Secondly,analyses using the large-scale international databases of Iceland and FinnGen provide new research directions and treatment ideas for pulmonary arterial hypertension in specific populations and environments,as well as ideas and methods that can be used to prevent and treat pulmonary arterial hypertension in China.

Objective To explore the prevalence of depressive symptoms in postoperative patients with ovarian cancer and to analyze its influencing factors from multiple dimensions, including clinical characteristics, psychological factors, and laboratory indicators. Methods A cross-sectional study was conducted, which enrolled 235 postoperative patients with ovarian cancer. Depressive status was assessed using the patient health questionnaire, and the demographic, pathological, and medical record data of the patients were collected using the generalized anxiety disorder scale, Pittsburgh sleep quality index, European organization for research and treatment of cancer quality of life questionnaire core 30, and ECOG performance status score. Peripheral blood tumor marker (CA125), routine blood test, lymphocyte subsets, and serum cytokine levels were measured. Univariate and multivariate binary logistic regression analysis were used for statistical analysis. Results The prevalence of depression in postoperative patients with ovarian cancer was 39.15% (92/235). Univariate analysis showed that ECOG score ≥ 2 points, pain, anxiety, poor sleep quality, low quality of life, low life satisfaction, tumor recurrence, six or more cycles of chemotherapy, as well as higher levels of CA125, NLR, and NAR, and lower hemoglobin levels were significantly associated with depression (all P<0.05). Multivariate binary Logistic regression analysis showed that anxiety (OR=1.975, 95%CI: 1.231-3.170), sleep efficiency (OR=4.181, 95%CI: 1.211-14.43), sleep latency (OR=34.806, 95%CI: 4.258-284.542), ECOG performance status score, cognitive function (OR=0.918, 95%CI: 0.868-0.97), and life satisfaction were independent risk factors for depression (all P<0.05). Laboratory indicators were not independent influencing factors in the multivariate Logistic regression model. Conclusion Depression in postoperative patients with ovarian cancer is influenced by physiological, psychological, and social factors. Clinical management should focus on patients with anxiety, sleep disorders, poor physical condition, and low life satisfaction, and a comprehensive prevention and treatment strategy centered on psychological intervention and taking into account symptom management and social support should be implemented.

Hygroscopicity research has long been a key focus and hot topic in Chinese materia medica（CMM）. Elucidating hygroscopic mechanisms plays a vital role in formulation design， process optimization， and storage condition selection. Hygroscopic models serve as essential tools for characterizing CMM hygroscopic mechanisms， with various types available. The double exponential model is a kinetic mathematical model constructed based on the law of conservation of energy and Fick's first law of diffusion， tailored to the physical properties of CMM extracts. In recent years， this model has been extensively applied to simulate the dynamic moisture absorption behavior of CMM extracts and solid dosage forms under varying humidity conditions. It has revealed the correlation between moisture absorption kinetic parameters and material properties， offering a new perspective for characterizing the moisture uptake behavior of CMM. This paper systematically reviews the application progress of this model in the field of CMM， analyzes its advantages， disadvantages， and challenges in this domain， and explores its potential application trends in other fields. It aims to provide references for elucidating the moisture absorption mechanisms of CMM and researching moisture-proofing technologies， while also offering insights for its broader application in food and polymer materials.

Epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) block downstream signaling pathways by inhibiting receptor tyrosine kinase activity, consequently suppressing proliferation, invasion and metastasis of tumor cells. EGFR-TKIs have been proven to be highly effective in patients with late non-small cell lung cancer (NSCLC) harboring EGFR sensitive mutations, significantly better than chemotherapy. Third-generation EGFR-TKIs, such as osimertinib, have emerged as the first-line treatment for advanced NSCLC patients with sensitive EGFR mutations. However, there are still some patients who exhibit primary resistance upon initial treatment with EGFR-TKIs. The exact mechanism of primary resistance remains unknown, and may be related to factors such as the structure of EGFR mutation subtypes, concurrent mutations, BIM deletion polymorphism, and high expression of programmed cell death-ligand 1. This review summarizes the molecular mechanisms of primary resistance to EGFR-TKIs and discusses potential therapeutic strategies, with the goal of optimizing precision targeted therapy for NSCLC patients.

ObjectiveCleft palate (CP) is a common congenital deformity often associated with velopharyngeal insufficiency (VPI), which disrupts the physiological coupling between respiration and speech. Conventional clinical assessments, such as nasometry and spirometry, provide limited static data and fail to visualize the dynamic spatiotemporal distribution of lung ventilation during phonation. This study introduces spatiotemporal electrical impedance tomography (ST-EIT) to evaluate speech-respiratory functional features in CP patients compared to normal controls (NC). The aim is to characterize multi-domain respiratory patterns and to validate an interpretable machine learning framework for providing objective, quantitative evidence for clinical assessment. MethodsSeventy-five participants were enrolled in this study, comprising 37 patients with surgically repaired CP and 38 healthy volunteers matched for age, gender, and body mass index (BMI). All subjects performed standardized sustained phonation tasks while undergoing synchronous monitoring with a 16-electrode EIT system and a pneumotachograph. A comprehensive feature engineering pipeline was developed to extract physiological parameters across 3 complementary domains. (1) Temporal domain: including inspiratory/expiratory phase duration (tPhase), time constants (Tau), and inspiratory-to-expiratory time ratios (TI/TE); (2) airflow domain: comprising mean flow, peak flow, and instantaneous flow at 25%, 50%, and 75% of tidal volume; and (3) spatial domain: quantifying global and regional tidal impedance variation (TIV), global inhomogeneity (GI), and center of ventilation (CoV). Extreme Gradient Boosting (XGBoost) classifiers were trained using 5 distinct data sources (Spirometry, Nasometry, Inspiratory-EIT, Expiratory-EIT, and fused ST-EIT). Model performance was rigorously evaluated via stratified 5-fold cross-validation, and Shapley additive explanations (SHAP) were employed to quantify global and local feature contributions. ResultsThe CP group exhibited a distinct respiratory phenotype compared to controls. In the temporal domain, CP patients showed significantly shorter inspiratory (1.60 s vs.1.85 s, P<0.001) and expiratory phase durations (2.45 s vs. 3.95 s, P<0.001), indicating a rapid, shallow breathing rhythm. In the airflow domain, while inspiratory flows were comparable, the CP group demonstrated significantly elevated mean and peak flows during the expiratory phase (P<0.001), reflecting compensatory respiratory effort. Spatially, CP patients presented significant ventilation redistribution, characterized by higher regional TIV in the right-anterior (ROI1) and left-posterior (ROI4) quadrants, but lower TIV in the left-anterior (ROI2) quadrant. In terms of diagnostic accuracy, the multi-modal ST-EIT model achieved the highest performance (AUC: 0.915±0.012, Accuracy: 0.843±0.019, F1-score: 0.872±0.017), substantially outperforming models based on spirometry (AUC: 0.721) or nasometry (AUC: 0.625) alone. Interpretability analysis revealed that spatial domain features were the most critical, contributing 53.4% to the model’s decision-making, followed by temporal (25.0%) and airflow (21.6%) features. ConclusionST-EIT successfully captures the temporal, airflow, and spatial deviations in CP speech respiration that are undetectable by conventional methods—specifically, rapid phase transitions, hyperdynamic expiratory airflow, and regional ventilation heterogeneity. This study validates ST-EIT as a robust, non-invasive, and radiation-free tool for characterizing speech-respiratory dysfunction, offering high clinical value for bedside screening, rehabilitation planning, and longitudinal monitoring of patients with cleft palate.

ObjectiveCleft palate (CP) is a common congenital deformity often associated with velopharyngeal insufficiency (VPI), which disrupts the physiological coupling between respiration and speech. Conventional clinical assessments, such as nasometry and spirometry, provide limited static data and fail to visualize the dynamic spatiotemporal distribution of lung ventilation during phonation. This study introduces spatiotemporal electrical impedance tomography (ST-EIT) to evaluate speech-respiratory functional features in CP patients compared to normal controls (NC). The aim is to characterize multi-domain respiratory patterns and to validate an interpretable machine learning framework for providing objective, quantitative evidence for clinical assessment. MethodsSeventy-five participants were enrolled in this study, comprising 37 patients with surgically repaired CP and 38 healthy volunteers matched for age, gender, and body mass index (BMI). All subjects performed standardized sustained phonation tasks while undergoing synchronous monitoring with a 16-electrode EIT system and a pneumotachograph. A comprehensive feature engineering pipeline was developed to extract physiological parameters across 3 complementary domains. (1) Temporal domain: including inspiratory/expiratory phase duration (tPhase), time constants (Tau), and inspiratory-to-expiratory time ratios (TI/TE); (2) airflow domain: comprising mean flow, peak flow, and instantaneous flow at 25%, 50%, and 75% of tidal volume; and (3) spatial domain: quantifying global and regional tidal impedance variation (TIV), global inhomogeneity (GI), and center of ventilation (CoV). Extreme Gradient Boosting (XGBoost) classifiers were trained using 5 distinct data sources (Spirometry, Nasometry, Inspiratory-EIT, Expiratory-EIT, and fused ST-EIT). Model performance was rigorously evaluated via stratified 5-fold cross-validation, and Shapley additive explanations (SHAP) were employed to quantify global and local feature contributions. ResultsThe CP group exhibited a distinct respiratory phenotype compared to controls. In the temporal domain, CP patients showed significantly shorter inspiratory (1.60 s vs.1.85 s, P<0.001) and expiratory phase durations (2.45 s vs. 3.95 s, P<0.001), indicating a rapid, shallow breathing rhythm. In the airflow domain, while inspiratory flows were comparable, the CP group demonstrated significantly elevated mean and peak flows during the expiratory phase (P<0.001), reflecting compensatory respiratory effort. Spatially, CP patients presented significant ventilation redistribution, characterized by higher regional TIV in the right-anterior (ROI1) and left-posterior (ROI4) quadrants, but lower TIV in the left-anterior (ROI2) quadrant. In terms of diagnostic accuracy, the multi-modal ST-EIT model achieved the highest performance (AUC: 0.915±0.012, Accuracy: 0.843±0.019, F1-score: 0.872±0.017), substantially outperforming models based on spirometry (AUC: 0.721) or nasometry (AUC: 0.625) alone. Interpretability analysis revealed that spatial domain features were the most critical, contributing 53.4% to the model’s decision-making, followed by temporal (25.0%) and airflow (21.6%) features. ConclusionST-EIT successfully captures the temporal, airflow, and spatial deviations in CP speech respiration that are undetectable by conventional methods—specifically, rapid phase transitions, hyperdynamic expiratory airflow, and regional ventilation heterogeneity. This study validates ST-EIT as a robust, non-invasive, and radiation-free tool for characterizing speech-respiratory dysfunction, offering high clinical value for bedside screening, rehabilitation planning, and longitudinal monitoring of patients with cleft palate.

BACKGROUND:Pulmonary arterial hypertension is a destructive cardiopulmonary disease for which there is no cure.An association between plasma proteins and pulmonary arterial hypertension has been suggested,but the causal relationship has not been specifically elucidated.OBJECTIVE:To elucidate the causal relationship between plasma proteome and pulmonary arterial hypertension using a two-sample Mendelian randomization method,thereby searching for potential therapeutic targets for pulmonary arterial hypertension.METHODS:Plasma Protein Gene-Wide Association Analysis Statistics for 4 907 Aptamer Measurements in 35 559 Icelanders from the Icelandic Database;Genome-wide association analysis statistics for pulmonary arterial hypertension were obtained from the Finn Gen database,version R9,including 234 cases and 265 626 controls.Analyses were performed using Mendelian randomization and Bayesian co-localization analysis,the findings were examined using sensitivity analyses,and protein-protein interaction network maps were constructed to explore the causal relationship between plasma proteins and pulmonary arterial hypertension.RESULTS AND CONCLUSION:(1)The results of inverse variance weighting,maximum likelihood and Wald ratio methods showed 19 proteins causally associated with pulmonary arterial hypertension(P＜0.05).Among them,10 plasma proteins,including Beta-1,3-N-acetylglucosaminyltransferase manic fringe(odds ratio[OR]=0.12,95％confidence interval[CI]0.02-0.61,P=0.01)and interferon alpha/beta receptor 1(OR=0.45,95％CI 0.24-0.84,P=0.012),might be associated with a reduced risk of pulmonary arterial hypertension.In contrast,nine plasma proteins,such as glucoside xylosyltransferase 1(OR=3.48,95％CI 1.51-8.00,P=0.003)and plasminogen(OR=42.78,95％CI 2.49-734.31,P=0.01),might be associated with an increased risk of pulmonary arterial hypertension.After the false discovery rate was corrected,19 proteins remained significantly associated with pulmonary arterial hypertension.(2)Multiple sensitivity analyses such as the MR-Egger intercept test and leave-one-out method showed no horizontal multiplicity or heterogeneity in the results of the study,indicating the stability of the study's results.(3)Bayesian co-localization analysis showed that six plasma proteins,including plasminogen(PPH4=1.0)and glucoside xylosyltransferase 1(PPH4=0.94),had PPH4＞0.8,suggesting that plasma proteins and the genome-wide association study of pulmonary arterial hypertension had similar causal variance in terms of genetic association.(4)By constructing a protein-protein interaction network map,plasminogen,Annexin A1,fibrinogen gamma chain and matrix metalloproteinase 7 were found to be core proteins.(5)The article used Mendelian randomization analysis to reveal a potential causal association between 4 907 plasma proteins and pulmonary arterial hypertension,suggesting that plasma proteins may be potential therapeutic targets for pulmonary arterial hypertension.The core proteins identified in the study also provide a theoretical basis for further in-depth study of the pathophysiological mechanisms of pulmonary arterial hypertension.Secondly,analyses using the large-scale international databases of Iceland and FinnGen provide new research directions and treatment ideas for pulmonary arterial hypertension in specific populations and environments,as well as ideas and methods that can be used to prevent and treat pulmonary arterial hypertension in China.

Objective This study reports on the obligatory parasitism of water mites Arrenurus sp. on Anopheles messeae at the Manzhouli Port, Inner Mongolia, China. Methods Duing July 2024, a survey on the mosquito diversity was conducted at the Manzhouli Port. Captured mosquitoes and their ectoparasites were identified to species level. Results A total of 1840 adult mosquitoes were collected, representing species from three genera: Culex(Cx. modestus, Cx. pipiens pallens), Aedes(Ae. dorsalis, Ae. flavidorsalis, Ae. flavescens), and Anopheles (An. messeae). Among all the mosqutioes specimens,3 out of 150 captured An. messeae were found to carry ectoparasitic mites, with number of 2,4,27 mites separately. Morphological and molecular identification reached the same result as water mites(Hydrachnidiae, Hydracrina). COI gene sequence showed 94% similarity with the closest species Arrenurus truncatellus. Conlusions Literature review suggests water mites are host-specific parasitism of mosquito species and herein with the first record of Arrenurus sp. parasiting on An. Messeae in the most high-latitude region globally.

ObjectiveTo investigate the status and influencing factors of latent tuberculosis infection (LTBI) among close contacts of patients with bacteriologically confirmed pulmonary tuberculosis in Jing’an District, Shanghai, and to provide scientific evidence for the development of tuberculosis infection testing and preventive intervention strategies for close contacts of bacteriologically positive patients. MethodsFrom October 2022 to October 2023, patients with bacteriological confirmed pulmonary tuberculosis registered in Jing’an District, Shanghai, and their close contacts were enrolled as the research subjects. The close contacts were screened for tuberculosis infection using the interferon-γ release assay (IGRA). The chi-square test and binary logistic regression model were used to analyze factors influencing LTBI. ResultsA total of 112 close contacts were included, of whom 30 (26.79%) were male and 82 (73.21%) were female. The age ranged from 1 to 86 years, with a median (25th, 75th percentiles) of 47.50 (32.25, 61.00) years. The infection rate of LTBI was 21.43% (24/112), and the incidence of active pulmonary tuberculosis was 2.68% (3/112). Univariate analyses showed that a positive sputum smear of the index case, being a direct relative of the index case, co-living, and not wearing a mask were significantly associated with LTBI (all P<0.05). Multivariate logistic regression analyses showed that the risk of latent infection in close contacts of the index case with a positive sputum smear was 6.50 times higher than in those with a negative sputum smear (95%CI: 1.82‒23.25, P=0.004). ConclusionThe infection rate of LTBI in close contacts of patients with bacteriologically confirmed pulmonary tuberculosis in Jing’an District, Shanghai, is relatively high, and close contacts of sputum smear-positive patients face an even higher risk of infection. Therefore, tuberculosis infection screening and follow-up management should be strengthened for this population.

The struggle between healthy qi and pathogenic factors runs through the whole process of the formation and development of diabetic cardiomyopathy(DCM),and autophagy is the main regulator of cardiac homeostasis and function.Based on the theory of healthy qi and pathogenic factors,the autophagy state of DCM was understood.In the early stage of DCM,it is mainly characterized by deficiency of healthy qi and supplemented by pathogenic excess.In the middle stage,it is characterized by deficiency of healthy qi and pathogenic excess.In the late stage,it is mainly characterized by pathogenic excess and supplemented by deficiency of healthy qi.TCM clinical practice adheres to the principle of"strengthening the healthy qi and eliminating pathogenic factors",which aims to restore the dynamic balance of autophagy in the body by adjusting the balance between healthy qi and pathogenic factors,and ultimately improve the prognosis of DCM.This article took the theory of healthy qi and pathogenic factors as the starting point,and elaborated on the role of autophagy in the development of DCM from macro and micro perspectives.It explored Chinese materia medica intervention plans for different stages of DCM,providing theoretical reference for the regulation of autophagy in DCM by TCM.