ObjectiveTo establish an animal model of atrial fibrillation（AF） that accurately reflects the phlegm-heat and blood stasis（TRYZ） pathogenesis in traditional Chinese medicine. MethodsForty SPF-grade SD rats were randomly assigned using a random number table to the following groups：the control group， the TRYZ+AF group，the AF group and the TRYZ group， with ten rats in each group. The TRYZ+AF and TRYZ groups underwent a high-fat diet combined with intraperitoneal lipopolysaccharide（LPS） injection to simulate the pathological alterations of TRYZ syndrome. Groups TRYZ+AF and AF were induced with acetylcholine-calcium chloride（Ach-CaCl₂） via caudal vein injection to induce AF. The control group received no intervention and was maintained under normal conditions. The modeling period lasted 3 weeks. Electrocardiography was used to assess AF episodes and duration， echocardiography evaluated left atrial dimensions and cardiac function， fully automated biochemical analyzer measured the levels of total cholesterol（TC）， triglycerides（TG）， high-density lipoprotein cholesterol（HDL-C） and low-density lipoprotein cholesterol（LDL-C）， hemoreometer analyzed the whole blood viscosity， plasma viscosity， and whole blood reduced viscosity， a coagulation analyzer assessed prothrombin time（PT）， activated partial thromboplastin time（APTT）， thrombin time（TT）， and fibrinogen（FIB）， enzyme-linked immunosorbent assay（ELISA） was used to determine the levels of C-reactive protein（CRP）， interleukin（IL）-1β， IL-6， IL-17， tumour necrosis factor（TNF）-α， matrix metalloproteinase-9（MMP-9）， galectin-3（Gal-3）， Collagen Ⅰ， and α-smooth muscle actin（α-SMA）. Hematoxylin-eosin（HE） staining and Masson's trichrome staining were used to analyze pathological changes in atrial myocardium， Western blot was employed to detect MMP-9， Collagen Ⅰ and α-SMA protein expression in myocardial tissue， real-time quantitative polymerase chain reaction（Real-time PCR） evaluated fibrous factor gene expression levels. Changes in the TRYZ syndrome were assessed via body weight， tongue color［red（R）， green（G）， and blue（B）］， and rectal temperature. Ultra-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry（UPLC-Q-TOF-MS） was employed to detect differential metabolites between the control group and the TRYZ+AF group. ResultsFollowing three weeks of sustained modeling， compared with the control group， rats in the TRYZ+AF and the TRYZ groups exhibited reduced body weight， dry faeces， elevated rectal temperature， dark red tongue， decreased RGB values on the tongue surface， and markedly elevated TC and LDL-C levels（P<0.05， P<0.01）. The TRYZ+AF， TRYZ， and AF groups exhibited significantly decreased TT， APTT and PT， along with markedly elevated whole blood viscosity and FIB（P<0.05， P<0.01）. Rats in the TRYZ+AF and AF groups exhibited AF rhythm， markedly decreased heart rate， prolonged RR intervals， enlarged left atrium， and significantly reduced ejection fraction and shortening fraction（P<0.05， P<0.01）. Serum levels of CRP， IL-1β， IL-6， IL-17， TNF-α， MMP-9， Gal-3， Collagen Ⅰ， and α-SMA were elevated in rats from the TRYZ+AF， TRYZ， and AF groups compared to the control group， with the most pronounced increase observed in the TRYZ+AF group（P<0.05， P<0.01）. Histopathology revealed that the collagen fiber deposition in the atrial of rats in the TRYZ+AF， TRYZ and AF groups was higher than that in the control group（P<0.05， P<0.01）. Western blot and Real-time PCR results further demonstrated that the protein and mRNA expression levels of MMP-9， Collagen Ⅰ and α-SMA in the myocardial tissue of the TRYZ+AF group were higher than those in the other three groups（P<0.05， P<0.01）. Metabolomic analysis revealed 173 differentially expressed metabolites in the TRYZ+AF group and the control group， primarily enriched in pathways such as glycerophospholipid metabolism and glycolysis/gluconeogenesis. ConclusionThis study successfully establishes a rat model of AF integrated with the TRYZ syndrome， demonstrating the pathological process where the interactions of phlegm， heat and stasis jointly trigger tremor， this provides a reliable experimental tool for in-depth research into the biological basis of this disease syndrome.

ObjectiveTo investigate the present situation of input, output, outcome and impact of all registered community-based rehabilitation stations in Inner Mongolia in China, and analyze how the input predict the output, outcome and impact. MethodsFrom March 1st to April 30th, 2025, a questionnaire survey was conducted on all registered community-based rehabilitation stations in Inner Mongolia, covering four dimensions: input, output, outcome and impact. A total of 1 365 questionnaires were distributed. The input included four items: laws and policies, human resources, equipment and facilities, and rehabilitation information management. The output included two items: technical paths and benefits/effectiveness. The outcome included three items: coverage rates, rehabilitation interventions and functional results. The impact included two items: health and sustainability. Each item contained several questions, all of which were described in a positive way. Each question was scored from one to five. A lower score indicated that the situation of the community-based rehabilitation station was more in line with the content described in the question. Regression analysis was performed using the total score of each item of input dimension as independent variables, and the total scores of the output, outcome and impact dimensions as dependent variables. ResultsA total of 1 262 valid questionnaires were collected. The mean values of input, output, outcome and impact of community-based rehabilitation stations were 1.827 to 1.904, with coefficient of variation of 45.892% to 49.239%. The regression analysis showed that, rehabilitation information management, human resources, and laws and policies significantly predicted the output dimension (R² = 0.910, P < 0.001). Meanwhile, all four items in the input dimension predicted both the outcome (R² = 0.850, P < 0.001) and impact dimensions (R² = 0.833, P < 0.001). ConclusionInput, output, outcome and impact of the community-based rehabilitation stations in Inner Mongolia were generally in line with the content of the questions, although some imbalances were observed. Additionally, the input of community-based rehabilitation stations could significantly predict their output, outcome and impact.

Background Per- and polyfluoroalkyl substances (PFAS) are a class of persistent organic pollutants widely used in various products, leading to population exposure and long-term accumulation. At present, there is a lack of research on the relationships between pre-pregnancy PFAS and menstrual characteristics among women undergoing assisted reproductive technology (ART) in China. Objective To explore the relationships between pre-pregnancy PFAS exposure among women undergoing ART and menstrual characteristics prior to assisted reproductive treatment. Methods This study employed a cross-sectional research design, recruiting women undergoing ART treatment at the Reproductive Clinic of the International Peace Maternity & Child Health Hospital, School of Medicine, Shanghai Jiao Tong University, from 2017 to 2020 as study participants. Ultra-high-performance liquid chromatography-tandem mass spectrometry was used to detect 42 types of PFAS in pre-pregnancy serum samples. Questionnaires were administered to collect information on demographic characteristics, lifestyle habits, and menstrual characteristics (average menstrual cycle length, average menstrual period length, menstrual irregularities, and menstrual bleeding volume) of women undergoing ART. Multiple linear regression, binary logistic regression, and multinomial logistic regression analyses were performed to investigate the relationships between individual PFAS exposure before pregnancy and menstrual characteristics among ART women. Additionally, weighted quantile sum (WQS) model was applied to analyze the association between PFAS mixtures and menstrual characteristics. Results In the pre-pregnancy serum samples of the study population, 15 PFAS were detected in more than 60% of the samples, including perfluoroheptanoic acid (PFHpA), perfluorooctanoic acid (PFOA), perfluorononanoic acid (PFNA), perfluorodecanoic acid (PFDA), perfluoroundecanoic acid (PFUnDA), perfluorododecanoic acid (PFDoDA), perfluorobutanesulfonic acid (PFBS), perfluorohexanesulfonic acid (PFHxS), perfluoroheptanesulfonic acid (PFHpS), perfluorooctanesulfonic acid (PFOS), 6:2 chlorinated polyfluorinated ether sulfonate (6:2 Cl-PFESA), 8:2 chlorinated polyfluorinated ether sulfonate (8:2 Cl-PFESA), perfluoro-2-propoxypropanoic acid (HFPO-DA), perfluoro-2-methoxyacetic acid (PFMOAA), and perfluoro-(3,5,7,9,11-pentaoxadodecanoic) acid (PFO5DoDA). Among them, PFOA had the highest median concentration of 9.160 ng·mL⁻¹. The single PFAS exposure analysis revealed a positive correlation between PFAS and irregular menstrual cycles. Specifically, for every natural-log unit (e) increase in PFOA, PFBS, or PFHxS level, the incidence of irregular menstrual cycles increased by 57%, 42%, or 39%, respectively. Most PFAS were positively correlated with the average number of menstrual cycle days, such as PFHpA (b=1.08, 95%CI: 0.11, 2.05), PFOA (b=1.69, 95%CI: 0.39, 3.00), PFBS (b=1.23, 95%CI: 0.25, 2.22), PFHxS (b=1.47, 95%CI: 0.61, 2.32), PFHpS (b=1.48, 95%CI: 0.35, 2.61), and 6:2 Cl-PFESA (b=0.90, 95%CI: 0.08, 1.72). Furthermore, levels of PFHpA (OR=1.39, 95%CI: 1.06, 1.82), PFOA (OR=1.58, 95%CI: 1.09, 2.30), PFBS (OR=1.37, 95%CI: 1.04, 1.80), PFHxS (OR=1.34, 95%CI: 1.05, 1.71), PFHpS (OR=1.53, 95%CI: 1.10, 2.14), and 6:2 Cl-PFESA (OR=1.34, 95%CI: 1.06, 1.70) were positively correlated with low menstrual blood volume, while PFOA (OR=0.40, 95%CI: 0.23, 0.71), PFHpS (OR=0.45, 95%CI: 0.29, 0.71), and HFPO-DA (OR=0.68, 95%CI: 0.48, 0.97) were negatively correlated with high menstrual blood volume. The mixed exposure model showed that PFAS mixtures were positively correlated with the average number of menstrual cycle days (b=1.60, 95%CI: 0.49, 2.71), irregular menstrual cycles (OR=1.77, 95%CI: 1.19, 2.63), and low menstrual blood volume (OR=1.59, 95%CI: 1.08, 2.35), but negatively correlated with high menstrual blood volume (OR=0.40, 95%CI: 0.22, 0.73). Conclusion Women undergoing ART in Shanghai are widely exposed to PFAS prior to conception. Exposure to PFAS before pregnancy may be related to menstrual characteristics among women seeking ART before undergoing fertility treatments, but additional data from larger populations are required to validate the findings of this study.

This paper summarizes Professor WANG Xiuxia's clinical experience in treating hyperprolactinemia using the liver soothing therapy. Professor WANG identifies liver qi stagnation and rebellious chong qi （冲气） as the core pathomechanisms of hyperprolactinemia. Furthermore， liver qi stagnation may transform into fire or lead to pathological changes such as spleen deficiency with phlegm obstruction or kidney deficiency with essence depletion. The treatment strategy centers on soothing the liver， with a modified version of Qinggan Jieyu Decoction （清肝解郁汤） as the base formula. Depending on different syndrome patterns such as liver stagnation transforming into fire， liver stagnation with spleen deficiency， or liver stagnation with kidney deficiency， heat clearing， spleen strengthening， or kidney tonifying herbs are added accordingly. In addition， three paired herb combinations are commonly used for symptom specific treatment， Danggui （Angelica sinensis） with Chuanxiong （Ligusticum chuanxiong）， Zelan （Lycopus lucidus） with Yimucao （Leonurus japonicus） ， and Jiegeng （Platycodon grandiflorus） with Zisu （Perilla frutescens）.

Based on the "sweat pore-qi and liquid-collaterals" theory， it is considered that the core pathogenesis of pediatric infectious mononucleosis lies in the obstruction of sweat pores， the failure of qi and liquid to disperse， and damage to the collaterals due to pathogenic toxins. Accordingly， the treatment principles proposed include unblocking the sweat pores， regulating qi and liquid， and smoothing the collaterals. In clinical practice， treatment is differentiated according to stages： initial， acute， and late stages. In the initial stage， invasion of warm pathogenic toxins into the lung defense leads to obstruction of the sweat pores， which should be treated by unblocking the sweat pores and expelling pathogens outward. In the acute stage， the obstruction of the sweat pores worsens， leading to the failure of qi and liquid dispersal， resulting in intense heat toxins with accumulation of dampness， phlegm， and blood stasis， which should be treated by promoting qi movement， resolving dampness and phlegm， clearing heat， detoxifying， and dispersing stasis to regulate qi and liquid. In the late stage， residual pathogens remain， with qi and yin deficiency and unsmooth collaterals， which should be treated by unblocking the collaterals， dissipating nodules， tonifying qi， and nourishing yin to smooth the collaterals. This approach may provide new insights for the clinical treatment of pediatric infectious mononucleosis.

Objective To compare the cost-effectiveness between sodium valproate and levetiracetam in the treatment of childhood epilepsy and provide an economic basis for clinical medication choices. Methods A cost-effectiveness analysis was conducted using a decision tree model to compare the effectiveness and drug costs of sodium valproate and levetiracetam in treating childhood epilepsy. Single-factor sensitivity analysis and probabilistic sensitivity analysis were used to assess the impact of parameter variations on the study results. Results The treatment cost of levetiracetam was significantly higher than that of sodium valproate. The incremental cost-effectiveness ratio （ICER） of levetiracetam compared to sodium valproate was ¥8 628.43. Sensitivity analysis results were consistent with the base-case analysis. The probabilistic sensitivity analysis showed that, over a 6-month treatment period, levetiracetam became a more cost-effective option when the willingness-to-pay （WTP） threshold was ¥9,000 or higher. One-way sensitivity analysis revealed that the price of levetiracetam was the most influential factor affecting the ICER. Conclusion When the WTP per effective pediatric epilepsy case is ¥9,000 or higher, levetiracetam demonstrates a cost-effectiveness advantage.

ObjectiveTo investigate the influence of empagliflozin combined with donafenib or lenvatinib on the pharmacokinetic parameters of each drug， and to provide a reference for combined medication in clinical practice. MethodsA total of 48 healthy male Sprague-Dawley rats were divided into 8 groups： empagliflozin group 1 and 2， donafenib group， lenvatinib group， donafenib pretreatment+empagliflozin group， lenvatinib pretreatment + empagliflozin group， empagliflozin pretreatment+donafenib group， and empagliflozin pretreatment+lenvatinib group， with 6 rats in each group. The doses of empagliflozin， donafenib， and lenvatinib were 2.5 mg/kg， 40 mg/kg， and 1.2 mg/kg， respectively. The rats in the empagliflozin group， donafenib group， and lenvatinib group were given a blank solvent by gavage for 7 consecutive days， followed by a single dose of empagliflozin， donafenib， or lenvatinib on day 7 after the administration of the blank solvent； the rats in the pretreatment groups were given the pretreatment drug by gavage for 7 consecutive days， followed by a single dose of drug combination on day 7 after administration of the pretreatment drug. Blood samples were collected at different time points， and plasma was separated to measure the concentration of each drug. A validated ultra-performance liquid chromatography-tandem mass spectrometry method was used to measure the plasma concentrations of donafenib， lenvatinib， and empagliflozin， and a non-compartmental model was used to calculate the main pharmacokinetic parameters of each drug （area under the plasma concentration-time curve ［AUC］， time to peak ［T_max］， peak concentration ［C_max］， and half-life time ［t_1/2］）. The independent-samples t test was used for comparison of normally distributed continuous data between two groups， and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two groups. ResultsCompared with the empagliflozin group， the donafenib pretreatment+empagliflozin group had significant increases in the AUC_0-t and AUC_0-∞ of empagliflozin （P=0.011 and 0.008）， while the lenvatinib pretreatment+empagliflozin group had no significant change in the AUC of empagliflozin， with a slightly shorter T_max （P=0.019）. Compared with the donafenib group， the empagliflozin pretreatment+donafenib group had significant increases in the AUC_0-t and AUC_0-∞ of donafenib （P=0.027 and 0.025）， as well as a significant increase in C_max （P=0.015） and significant reductions in CLz/F and Vz/F （P=0.005 and 0.004）； compared with the lenvatinib group， the empagliflozin pretreatment+lenvatinib group had a reduction in the t_1/2 of lenvatinib by approximately 5 hours （P=0.002）， with a trend of reduction in AUC_0-t （P0.05）. ConclusionEmpagliflozin combined with donafenib may alter the pharmacokinetic parameters of both drugs， leading to a significant increase in the exposure levels of both drugs， and efficacy and adverse reactions should be monitored during co-administration. There are no significant changes in the exposure levels of empagliflozin and lenvatinib during co-administration.

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.