Objective To investigate the effects of remimazolam(REM)on cerebral ischemia-reperfusion injury(CIRI)rats and the AMP-activated protein kinase(AMPK)/NOD-like receptor protein 3(NLRP3)signaling pathway.Methods One hundred rats were selected to construct the CIRI rat model(Mod)and stochastically separated into a Mod group,low,medium,and high dose remifentanil groups(REM-L,REM-M,REM-H),and high dose remifentanil+pathway inhibitor Compound C group(REM-H+Compound C),with 20 rats in each group.Another 20 healthy rats were included as the control(Ctrl)group.All rats were subjected to neurobehavioral scoring.The water content,infarct area,and oxidative stress indicators of brain tissue were detected.The morphology and apoptosis of brain tissue were observed by HE and TUNEL staining.Western blotting was applied to detect protein expression related to the AMPK/NLRP3 signaling pathway.Results Compared with the Mod group,with the increase of REM dose,the movement disorders in rats were alleviated,the overall structure of brain tissue gradually recovered,pathological damage was reduced,the area of cerebral infarction,brain water content,and apoptosis rate of brain tissue cells decreased,reactive oxygen species(ROS)level,malondialdehyde(MDA)content,and NLRP3 and Caspase-1 protein expression levels decreased,superoxide dismutase the(SOD)content and AMPK protein expression level increased(P＜0.05).Compared with the REM-H group,the REM-H+Compound C group showed aggravated motor disorders,and more severe pathological damage to brain tissue,the area of cerebral infarction,cerebral water content and apoptosis rate of brain tissue cells increased,the ROS level,MDA content and the protein expression of NLRP3 and Caspase-1 increased,while the content of SOD and the protein expression decreased(P＜0.05).Conclusion Remimazolam can enhance the antioxidant function of the body,reduce brain cell apoptosis,alleviate brain tissue injury,and thus have a certain protective effect on ischemia-reperfusion brain injury in rats,the mechanism of which may be related to the activation of the AMPK/NLRP3 signaling pathway.

Objective To analyze the risk factors for meconium-stained amniotic fluid(MSAF)in preterm infants and the clinical outcome and prognosis of preterm infants.Methods Preterm infants with gestational age＜37 weeks delivered in Zhangjiajie People's Hospital from January 2022 to December 2023 were used as the study subjects,31 cases with MSAF were in MSAF group,and 31 cases of preterm infants hospitalized during the same period without MSAF were randomly paired in the ratio of 1∶1 to select with gestational age-body mass matching as non-MSAF group.Retrospective collection and analysis of pregnancy and perinatal conditions of mothers of preterm infants in two groups,comparing the differences of related factors between two groups of children;Logistic regression analysis of risk factors related to MSAF in preterm infants;comparing the complications and clinical outcomes of preterm infants in two groups.Results A total of 387 preterm infants with gestational age＜37 weeks were collected during the study period,including 31 preterm infants with comorbid MSAF,and the prevalence of MSAF in preterm infants was 8.0％.MSAF group had a higher incidence of advanced maternal age,premature rupture of membranes＞18 hours,antepartum fever,and cholestasis during pregnancy than non-MSAF group.Logistic regression analysis suggested that combined cholestasis during pregnancy and white blood cell count ≥ 30× 109/L within 6 hours after birth increased the incidence of MSAF in preterm infants.There was no statistically significant difference in the results of postnatal umbilical artery blood gas analysis between two groups of preterm infants.The proportion of leukocyte count ≥30×109/L,ultrasensitive C-reactive protein＞0.8 mg/L,and interleukin 6＞6 pg/L in MSAF group was higher than that of non-MSAF group in the 6 hours after birth.MSAF group had a higher incidence of intrauterine infectious pneumonia,feeding intolerance,and necrotizing small bowel colitis in neonates than non-MSAF group.Conclusion Advanced maternal age,intrauterine infections,and combined intrahepatic cholestasis during pregnancy may be the major risk factors for MSAF in preterm infants.MSAF preterm infants have a higher prevalence of intrauterine infectious pneumonitis,feeding intolerance,and necrotizing small bowel colitis in newborns,as well as longer hospital stays.

As a physical treatment technique, modified electro-convulsive therapy (MECT) is used to treat mental and certain neurological disorders by causing seizures with short, suitable electrical currents applied to the brain while the patient is under general anesthesia and muscle relaxants. MECT is recognized for its therapeutic efficacy and clinical safety, rendering it one of the most prevalent interventions in psychiatric care. To enhance clinical outcomes and minimize adverse effects, this consensus document delineates the indications, therapeutic parameters, therapeutic procedures, potential adverse effects, and associated management strategies for MECT. These guidelines are informed by the latest clinical research and expert consensus, integrating evidence-based medicine methodologies. The objective is to furnish clinicians with precise operational guidelines and to advance the standardization of MECT practices in clinical settings.

OBJECTIVE: The present study evaluated the effects of deep acupuncture at Weizhong acupoint (BL40) on bladder function and brain activity in a rat model of overactive bladder (OAB), and investigated the possible mechanisms around the acupuncture area that initiate the effects of acupuncture. METHODS: Adult female Sprague-Dawley rats were randomly divided into six groups, comprising a control group, model group, group treated with deep acupuncture at BL40, group treated with shallow acupuncture at BL40, group treated with acupuncture at non-acupoint next to BL40, and group treated with acupuncture at Xuanzhong (GB39). Urodynamic evaluation was used to observe the urination, and functional magnetic resonance imaging was used to observe the brain activation. The mechanism of acupuncture at BL40 in regulating bladder function was explored by toluidine blue staining and enzyme-linked immunosorbent assay, and the mechanism was verified by stabilizing mast cells (MCs) or blocking tibial nerve. RESULTS: Deep acupuncture at BL40 significantly increased the intercontraction interval in OAB rats and enhanced the mean amplitude of low frequency fluctuation of primary motor cortex (M1), periaquaductal gray matter (PAG), and pontine micturition center (PMC). It also increased the zero-lag functional connectivity between M1 and PAG and between PAG and PMC. Shallow acupuncture at BL40 and acupuncture at non-acupoint or GB39 had no effect on these indexes. Further studies suggested that deep acupuncture at BL40 increased the number and degranulation rate of MCs as well as the contents of 5-hydroxytryptamine, substance P, and histamine in the tissues around BL40. Blocking the tibial nerve by lidocaine injection or inhibiting MC degranulation by sodium cromoglycate injection obstructed the effects of acupuncture on restoring urinary function and modulating brain activation in OAB rats. CONCLUSION Deep acupuncture at BL40 may be more effective for inhibiting OAB by promoting degranulation of MCs around the acupoint and stimulating tibial nerve, thereby regulating the activation of the brain area that controls the lower urinary tract. Please cite this article as: Liu X, Zhang CY, Du XY, Li SS, Wang YQ, Zheng Y, Deng HZ, Fang XQ, Li JY, Wang ZQ, Xu SF, Mi YQ. Acupuncture at Weizhong (BL40) attenuates acetic acid-induced overactive bladder in rats by regulating brain neural activity through the modulation of mast cells and tibial nerves. J Integr Med. 2025; 23(1): 46-55.
Animals ; Urinary Bladder, Overactive/physiopathology* ; Mast Cells/physiology* ; Rats, Sprague-Dawley ; Female ; Acupuncture Therapy ; Acupuncture Points ; Rats ; Brain/physiopathology* ; Tibial Nerve/physiopathology* ; Acetic Acid ; Urinary Bladder/physiopathology*

Cardiovascular disease (CVD), chronic kidney disease (CKD), and metabolic disorders are the 3 major chronic diseases threatening human health, which are closely related and often coexist, significantly increasing the difficulty of disease management. In response, the American Heart Association (AHA) proposed a novel disease concept of “cardiovascular-kidney-metabolic (CKM) syndrome” in October 2023, which has triggered widespread concern about the co-treatment of heart and kidney diseases and the prevention and treatment of metabolic disorders around the world. This review posits that effectively managing CKM syndrome requires a new and multidimensional paradigm for diagnosis and risk prediction that integrates biological insights, advanced technology and social determinants of health (SDoH). We argue that the core pathological driver is a “metabolic toxic environment”, fueled by adipose tissue dysfunction and characterized by a vicious cycle of systemic inflammation and oxidative stress, which forms a common pathway to multi-organ injury. The at-risk population is defined not only by biological characteristics but also significantly impacted by adverse SDoH, which can elevate the risk of advanced CKM by a factor of 1.18 to 3.50, underscoring the critical need for equity in screening and care strategies. This review systematically charts the progression of diagnostic technologies. In diagnostics, we highlight a crucial shift from single-marker assessments to comprehensive multi-marker panels. The synergistic application of traditional biomarkers like NT-proBNP (reflecting cardiac stress) and UACR (indicating kidney damage) with emerging indicators such as systemic immune-inflammation index (SII) and Klotho protein facilitates a holistic evaluation of multi-organ health. Furthermore, this paper explores the pivotal role of non-invasive monitoring technologies in detecting subclinical disease. Techniques like multi-wavelength photoplethysmography (PPG) and impedance cardiography (ICG) provide a real-time window into microcirculatory and hemodynamic status, enabling the identification of early, often asymptomatic, functional abnormalities that precede overt organ failure. In imaging, progress is marked by a move towards precise, quantitative evaluation, exemplified by artificial intelligence-powered quantitative computed tomography (AI-QCT). By integrating AI-QCT with clinical risk factors, the predictive accuracy for cardiovascular events within 6 months significantly improves, with the area under the curve (AUC) increasing from 0.637 to 0.688, demonstrating its potential for reclassifying risk in CKM stage 3. In the domain of risk prediction, we trace the evolution from traditional statistical tools to next-generation models. The new PREVENT equation represents a major advancement by incorporating key kidney function markers (eGFR, UACR), which can enhance the detection rate of CKD in primary care by 20%-30%. However, we contend that the future lies in dynamic, machine learning-based models. Algorithms such as XGBoost have achieved an AUC of 0.82 for predicting 365-day cardiovascular events, while deep learning models like KFDeep have demonstrated exceptional performance in predicting kidney failure risk with an AUC of 0.946. Unlike static calculators, these AI-driven tools can process complex, multimodal data and continuously update risk profiles, paving the way for truly personalized and proactive medicine. In conclusion, this review advocates for a paradigm shift toward a holistic and technologically advanced framework for CKM management. Future efforts must focus on the deep integration of multimodal data, the development of novel AI-driven biomarkers, the implementation of refined SDoH-informed interventions, and the promotion of interdisciplinary collaboration to construct an efficient, equitable, and effective system for CKM screening and intervention.

This study explored the drying kinetics of Salviae Miltiorrhizae Radix et Rhizoma(SM), established the suitable models simulating the drying kinetics, and then analyzed the dynamic changes of active components during the drying processes with different methods, aiming to provide a basis for the establishment of suitable drying methods and the quality control of SM. The drying kinetics were studied based on the drying curve, drying rate, moisture effective diffusion coefficient, and drying activation energy, and the appropriate drying kinetics model of SM was established. The drying performance of different methods, such as hot air drying, infrared drying, and microwave drying of SM was evaluated, and the changes in the content of 10 salvianolic acids and 6 tanshinones during drying were analyzed by UPLC-TQ-MS. The Technique for Order Preference by Similarity to an Ideal Solution(TOPSIS) was employed to evaluate the quality of SM dried with different methods. The results showed that the drying rate and moisture effective diffusion coefficient of SM increased with the rise in drying temperature, and the maximum drying rates of different methods were in the order of microwave drying > infrared drying > hot air drying, slice > whole root. The drying rate decreased with the rise in temperature and the extension of drying time. The activation energy of hot air drying was higher than that of infrared drying in SM. The most suitable model for simulating the drying process of SM was the Page model. The TOPSIS results suggested infrared drying at 50 ℃ was the optimal drying method for SM. During the drying process, the content of salvianolic acids increased in different degrees with the loss of moisture, among which salvianolic acid B showed the largest increase of 44 times compared with that in the fresh medicinal material. Tanshinones also existed in the fresh herb of SM, and the content of tanshinone Ⅱ_A increased by 3 times after drying. The results provided a basis for the establishment of suitable drying methods and the quality control of SM.
Salvia miltiorrhiza/chemistry* ; Desiccation/methods* ; Drugs, Chinese Herbal/chemistry* ; Rhizome/chemistry* ; Kinetics ; Quality Control ; Abietanes

Atractylodes lancea is a perennial herbaceous plant of Asteraceae, with rhizomes for medical use. However, A. lancea plants from different habitats have great variability, and the germplasm resources of A. lancea are unclear and mixed during production. Therefore, it is urgent to protect new varieties of A. lancea. The distinctness, uniformity, and stability(DUS) testing of new plant varieties is the foundation of plant variety protection, and the DUS testing guidelines are the technical basis for variety approval agencies to conduct DUS testing. In this study, the phenotypic traits of 94 germplasm accessions of A. lancea were investigated considering the breeding and variety characteristics of A. lancea in China. The traits were classified and described, and 24 traits were preliminarily determined, including 20 basic traits that must be tested and four traits selected to be tested. The 20 basic traits included 3 quality traits, 5 false quality traits, and 12 quantitative traits, corresponding to 1 plant traits, 2 stem traits, 8 leaf traits, 6 flower traits, and 3 seed traits. The measurement ranges and coefficients of variation of eight quantitative traits were determined, on the basis of which the grading criteria and codes of the traits were determined and assigned. The guidelines has guiding significance for the trait evaluation, utilization, and breeding of new varieties of A. lancea.
Atractylodes/growth & development* ; China ; Phenotype ; Guidelines as Topic ; Plant Breeding

OBJECTIVE: To investigate the clinical characteristics and prognosis of primary pulmonary lymphoma (PPL). METHODS: The clinical data of 17 patients with PPL admitted to Gansu Provincial Hospital from January 2013 to June 2023 were collected, and their clinical characteristics and prognosis were retrospectively analyzed and summarized. RESULTS: The median age of the 17 patients was 56 (29-73) years old. There were 8 males and 9 females. According to Ann Arbor staging system, there were 9 patients with stage I-II and 8 patients with stage III-IV. There were 14 patients with IPI score of 0-2 and 3 patients with IPI score of 3-4. All 17 patients had symptoms at the initial diagnosis, most of the first symptoms were cough, and 6 patients had B symptoms.Among the 17 patients, there were 8 cases of diffuse large B-cell lymphoma (DLBCL), 5 cases of mucosa-associated lymphoid tissue (MALT) lymphoma, 1 case of gray zone lymphoma (GZL), and 3 cases of Hodgkin's lymphoma (HL). 15 patients received chemotherapy, of which 3 cases received autologous hematopoietic stem cell transplantation(ASCT) and 3 cases received radiotherapy; 2 patients did not receive treatment. The median number of chemotherapy courses was 6(2-8). The short-term efficacy was evaluated, 12 patients achieved complete remission (CR) and 3 patients achieved partial remission (PR). The age, pathological subtype, sex, Ann Arbor stage, β₂-microglobulin(β₂-MG) level, lactate dehydrogenase(LDH) level were not correlated with CR rate (P >0.05), while IPI score was correlated with recent CR rate (P < 0.05 ). The median follow-up time was 31(2-102) months. One of the 12 CR patients died of COVID-19, and the rest survived. Among the 3 patients who did not reach CR, 1 died after disease progression, while the other 2 survived. One of the 2 untreated patients died one year after diagnosis. Both the median progression-free survival (PFS) time and overall survival (OS) time of the 17 patients were both 31 (2-102) months. CONCLUSION The incidence of PPL is low, and the disease has no specific clinical manifestations, which is easily missed and misdiagnosed. The pathological subtypes are mainly MALT lymphoma and DLBCL, and the treatment is mainly combined chemotherapy. The IPI score is related to the treatment efficacy.
Humans ; Middle Aged ; Male ; Female ; Adult ; Prognosis ; Aged ; Lung Neoplasms/therapy* ; Retrospective Studies ; Neoplasm Staging ; Lymphoma/therapy* ; Lymphoma, Large B-Cell, Diffuse

Infant formula milk powder(infant formula)contains a variety of fatty acids that require hydrolysis and derivation,and the calibration methods are complex and variable,affecting the accuracy of quantification.Using the gas chromatography with flame ionization detector(GC-FID)under internal standard and external standard calibration methods,the effects of using fatty acid methyl esters(FAMEs)and triacylglycerol(TAGs)as calibration solutions on determination of 19 kinds of fatty acids content in infant formula were compared in this work.Additionally,the differences in determination between the acetyl chloride methanol method and the hydrolysis extraction method using FAMEs as the calibration solution under internal standard method were also compared.The quantitative results of TAGs external standard quantitative method were significantly higher than those of FAMEs external standard quantitative method and FAMEs calibrator derived by methylation,and the deviation of quantitative results were 7%-20%and 2%-10%,respectively.The quantitative results of FAMEs calibrator added FAME internal standard were significantly higher than those of FAMEs calibrator added FAME internal standard derived from TAG methylation and FAMEs calibrator added TAG internal standard with methyl esterification,and the deviation of quantitative results were about 15%and 2%-5%,respectively.The results indicated that both the two methods of internal standard calibration using FAMEs as the calibration solution and external standard calibration using TAGs as the calibration solution could effectively eliminate the bias in the determination,with simple operation and accurate comparation of the results.However,the results were significantly lower under the external standard calibration using FAMEs as calibration solution.

Objective To investigate the efficacy of an interpretable integrated learning model combining clinical indicators,CT image features and radiomics features for the differential diagnosis of lung squamous cell carcinoma and adenocarcinoma,so as to provide references for clincal treatment decisions.Methods A retrospective analysis was conducted on clinical and imaging data from 220 patients(231 lesions)with primary non-small cell lung cancer at Jiangjin Central Hospital of Chongqing(Center 1)and 83 patients(84 lesions)at Chongqing General Hospital(Center 2).In Center 1,the squamous cell carcinoma group consisted of 60 patients(60 lesions),while the adenocarcinoma group included 160 patients(171 lesions).In Center 2,the squamous cell carcinoma group comprised 18 patients(18 lesions),and the adenocarcinoma group involved 65 patients(66 lesions).The patients were categorized into squamous cell carcinoma and adenocarcinoma groups based on pathological findings.Center 1 was randomly partitioned into a training set and a validation set at a 7∶3 ratio,while Center 2 served as the independent test set.Firstly,a deep learning model,VB-Net,was used to automatically segment the tumor region on the lung window image;secondly,the SMOTE(synthetic minority oversampling technique)method was used to balance the categories in the training set and standardize the extracted features with Z-scores;thirdly,the least absolute shrinkage and selection operator(LASSO)were used to select the optimal radiomics features and calculate the radiomics score(Radscore),and univariate and multivariate logistic regression was used to screen clinical indicators and independent clinical factors for differentiating lung squamous cell carcinoma and adenocarcinoma in CT image features;finally,three ensemble learning algorithms(AdaBoost,Bagging decision tree and XGBoost)were used to combine independent clinical factors and Radscore to construct the model.The receiver operating characteristic(ROC)curve was used to evaluate the diagnostic performance of the models.SHAP technique was used to analyze the feature contribution and model decision-making process.Results Among the evaluated ensemble models,AdaBoost and Bagging decision trees demonstrated overfitting tendencies.In contrast,the XGBoost model showed the best performance,achieving AUC values of 0.939,0.887 and 0.853 in the training,validation and independent test sets,respectively.SHAP indicated that Radscore was the most important feature affecting the performance of the model.The decision diagram enabled the visualization of the diagnostic process of the model.Conclusion The interpretable integrated learning model based on clinical indicators,CT image and radiomics features is expected to non-invasively diagnose lung squamous cell carcinoma and adenocarcinoma before treatment and assist clinicians make treatment decisions as early as possible.[Chinese Medical Equipment Journal,2025,46(7):12-20]