Hepatitis B virus （HBV） infection is the primary cause of viral hepatitis and represents a substantial disease burden in China. However， effective and safe agents capable of completely eliminating HBV DNA are still lacking. In modern medicine， anti-HBV strategies mainly target covalently closed circular DNA （cccDNA）， among other mechanisms， and multiple novel drugs are currently under clinical investigation. Traditional medicine has been shown to exert anti-HBV effects through direct pathways， such as blocking viral entry， as well as indirect pathways， including the regulation of programmed cell death. Studies have confirmed that the integration of traditional Chinese medicine （TCM） and Western medicine in treating HBV infection and its related complications offers complementary advantages， particularly in enhancing HBV clearance rates， improving liver function， preventing various complications， and delaying the progression from hepatic fibrosis to hepatocellular carcinoma. This review focuses on advances in anti-HBV research involving TCM， Western medicine， and their integrated application， aiming to provide a basis for integrated HBV therapy and new drug development.

Background/Aims: Non-pharmacological treatments are crucial for managing irritable bowel syndrome (IBS), yet patient engagement remains a challenge. Understanding patients' knowledge, attitudes, and practices regarding these treatments is essential for improving care. Methods: A cross-sectional study was conducted across 5 hospitals, from October 2023 to February 2024. A self-designed knowledge, attitudes, and practices questionnaire along with the IBS quality of life and IBS severity scoring system was administered, and 496 valid responses were analyzed. Statistical analyses included correlation tests, multivariate linear regression, and mediation effect analysis. Results: The median scores for knowledge, attitude, and practice were 28, 25.5, and 21, respectively. Significant positive correlations were found between knowledge-attitude (r = 0.195), knowledge-practice (r = 0.364), and attitude-practice (r = 0.151). The multivariate linear regression analysis further indicated that knowledge (β = 0.399, P < 0.001) and attitude (β = 0.219, P = 0.022) positively correlated with the practical performance. SEM revealed that knowledge had a significant direct effect on both attitude (β = 0.186, P = 0.013) and practice (β = 0.356, P = 0.006). However, the direct effect of attitude on practice was not significant, and attitude did not mediate the relationship between knowledge and practice. Conclusions IBS patients exhibit a significant gap between their positive attitudes and their actual practices concerning non-pharmacological treatments. Knowledge is a direct driver of practice, but positive attitudes alone are insufficient to translate into behavior. Healthcare providers must move beyond simply fostering positive attitudes and focus on targeted educational interventions that provide actionable knowledge and skills to improve patient outcomes.

Background and aims The mechanism of cholestatic liver injury (CLI) is unclear, and effective therapies are lacking. While peroxisome proliferator-activated receptor alpha (PPARα) agonists show potential hepatoprotective effect and pyroptosis is implicated in hepatocellular damage, how PPARα activation mitigates lithocholic acid (LCA)-induced pyroptosis remains unknown. Methods The hepatoprotective effect of PPARα agonists was evaluated in a mouse model of intrahepatic cholestasis induced by LCA. Liver injury was assessed via serum biochemistry, hematoxylin and eosin and TUNEL staining, and electron microscopy. Pyroptosis pathways were analyzed using real-time quantitative polymerase chain reaction, Western blot, and co-immunoprecipitation. Results Combined morphological, histopathological, and biochemical analyses confirmed that PPARα activation protects against CLI. Compared with LCA treatment alone, PPARα activation significantly attenuated the elevation of serum lactate dehydrogenase (LDH), the increased TUNEL-positive cells, and the formation of hepatocyte membrane pores. Mechanistically, PPARα activation suppressed both NOD-like receptor protein 3 (NLRP3) inflammasome-mediated pyroptosis and apoptosis protease-activating factor-1 (APAF-1)/CASPASE-3/GSDME-mediated pyroptosis. Furthermore, PPARα agonist pretreatment inhibited activation of the nuclear factor-kappa B (NF-κB) and forkhead box O1 (FOXO1) signaling pathways. Conclusions PPARα protects against LCA-induced CLI by inhibiting both NLRP3 inflammasome-mediated pyroptosis associated with NF-κB and APAF-1/CASPASE-3/GSDME-mediated pyroptosis associated with the FOXO1 signaling pathway.

Sleep is an instinctive behavior alternating awakening state, sleep entails many active processes occurring at the cellular, circuit and organismal levels. The function of sleep is to restore cellular energy, enhance immunity, promote growth and development, consolidate learning and memory to ensure normal life activities. However, with the increasing of social pressure involved in work and life, the incidence of sleep disorders (SD) is increasing year by year. In the short term, sleep disorders lead to impaired memory and attention; in the longer term, it produces neurological dysfunction or even death. There are many ways to directly or indirectly contribute to sleep disorder and keep the hormones, including pharmacological alternative treatments, light therapy and stimulus control therapy. Exercise is also an effective and healthy therapeutic strategy for improving sleep. The intensities, time periods, and different types of exercise have different health benefits for sleep, which can be found through indicators such as sleep quality, sleep efficiency and total sleep time. So it is more and more important to analyze the mechanism and find effective regulation targets during sleep disorder through exercise. Dopamine (DA) is an important neurotransmitter in the nervous system, which not only participates in action initiation, movement regulation and emotion regulation, but also plays a key role in the steady-state remodeling of sleep-awakening state transition. Appreciable evidence shows that sleep disorder on humans and rodents evokes anomalies in the dopaminergic signaling, which are also implicated in the development of psychiatric illnesses such as schizophrenia or substance abuse. Experiments have shown that DA in different neural pathways plays different regulatory roles in sleep behavior, we found that increasing evidence from rodent studies revealed a role for ventral tegmental area DA neurons in regulating sleep-wake patterns. DA signal transduction and neurotransmitter release patterns have complex interactions with behavioral regulation. In addition, experiments have shown that exercise causes changes in DA homeostasis in the brain, which may regulate sleep through different mechanisms, including cAMP response element binding protein signal transduction, changes in the circadian rhythm of biological clock genes, and interactions with endogenous substances such as adenosine, which affect neuronal structure and play a neuroprotective role. This review aims to introduce the regulatory effects of exercise on sleep disorder, especially the regulatory mechanism of DA in this process. The analysis of intracerebral DA signals also requires support from neurophysiological and chemical techniques. Our laboratory has established and developed an in vivo brain neurochemical analysis platform, which provides support for future research on the regulation of sleep-wake cycles by movement. We hope it can provide theoretical reference for the formulation of exercise prescription for clinical sleep disorder and give some advice to the combined intervention of drugs and exercise.

Objective:To screen bile acid-related characteristic genes in IgA nephropathy (IgAN) based on the feature gene selection algorithm in the machine learning method, aiming to exploring the molecular biological mechanisms and biomarkers of IgAN.Methods:The gene expression data and sample grouping information of GSE93798, GSE116626 and GSE35487 were downloaded from the Gene Expression Omnibus (GEO). Bile acid-related gene sequences were obtained from the Molecular Signatures Database (MSigDB). R language was used to identify differentially expressed genes between IgAN samples and healthy control samples. Candidate genes were obtained by intersecting differentially expressed genes and bile acid-related genes. The least absolute shrinkage and selection operator (LASSO) algorithm in machine learning was used to screen the feature genes in the candidate genes as biomarkers, and the feature genes in the training set and validation set were analyzed by the rate of change index. Receiver operating characteristic curve (ROC) method was used to evaluate the diagnostic value of identified bile acid related characteristic genes for IgAN. Gene set enrichment analysis (GSEA) was used to analyze the Spearman correlation between the characteristic genes and all other genes and their related metabolic pathways. The expression of disease-characteristic genes in the kidney tissues of IgAN rats was validated by real-time PCR.Results:Gene expression information from kidney tissue samples of 20 IgAN cases and 22 healthy controls were obtained from GEO database. A total of 204 bile acid-related genes including 24 pathways were obtained from MSigDB. The results of gene differential expression analysis showed that 333 genes in the kidney tissues of IgAN patients were differentially expressed compared with those of healthy controls, including 102 up-regulated genes and 231 down-regulated genes, among which 12 differentially expressed genes were related to bile acid genes, as follows: NR1H4,SLC23A1, ALDH8A1, FABP1, ALB, SLC27A2, DIO1, CYP8B1, BBOX1, PIPOX, AKR1C1 and SLC10A2. Five characteristic genes ( NR1H4, SLC23A1, FABP1, ALB and AKR1C1) were screened by LASSO regression algorithm.ROC analysis results showed that in GSE93798 cohort genes, the AUC of NR1H4, SLC23A1, FABP1 and ALB genes with differential expression was >0.95 respectively in diagnosing IgAN, and that of AKR1C1 genes with differential expression was >0.85 in diagnosing IgAN. The gene expression data of SLC23A1 in GSE35487 cohort was missing. ROC analysis results of other four genes showed that the AUC of differential expression of ALB gene for IgAN was >0.95 respectively, that of NR1H4 gene was >0.70, and that of both FABP1 and AKR1C1 gene was >0.60. In the GSE116626 cohort genes, the AUC of five disease characteristic genes ( NR1H4, SLC23A1, FABP1, ALB, AKR1C1) for diagnosing IgAN was >0.60, respectively. These results suggested that 5 characteristic genes have certain distinguishing ability between IgAN group and control group. GSEA results were displayed that the characteristic genes were related to butyric acid metabolism, propionic acid metabolism, arginine and proline metabolism, valine leucine and isoleucine degradation, fatty acid metabolism, etc. These results suggested that five characteristic genes might be related to IgAN through the above metabolic mechanisms. The verification results of five bile acid characteristic genes in the rat model of IgAN in the kidney tissue showed that the expressions of four genes, NR1H4, SLC23A1, FABP1 and ALB, were higher than those of the control group, and there was no statistical significance in the expression of AKR1C1 gene between the two groups. Conclusions:The expression of bile acid-related characteristic genes is abnormal in the kidney tissue of IgAN patients. Four bile acid-related differentially expressed genes, NR1H4, SLC23A1, FABP1 and ALB, are expected to be biomarkers for non-invasive diagnosis and therapeutic targets .

Objective:To develop a predictive model for adverse pregnancy outcomes in patients with pregnancy-related acute kidney injury (Pr-AKI) using machine learning methods.Methods:This study was a single-center retrospective study. Patients with Pr-AKI in the First Affiliated Hospital of Xinjiang Medical University from January 2013 to December 2020 were included. Demographic characteristics, laboratory parameters, and fetal outcomes for comparative analysis between adverse pregnancy outcome group and favorable pregnancy outcome group were collected. Adverse pregnancy outcomes were defined as the occurrence of any one or more of the following events: stillbirth, perinatal death, preterm birth (reaching 28 weeks but less than 37 weeks), and low birth weight (< 2.5 kg). Conversely, an ideal pregnancy outcome was defined as the absence of any adverse pregnancy outcome events. The dataset was randomly divided into a training set (70%) and a validation set (30%). Logistic regression, decision tree, random forest, K-nearest neighbor, support vector machine, and lightweight gradient boosting algorithms were employed on the training set to develop predictive models for adverse pregnancy outcomes in patients with Pr-AKI. Receiver operating characteristic curves were plotted, and the area under the curves ( AUC) were calculated. Recall, precision, accuracy, and F1 scores were used to evaluate the predictive performance of each model. The optimal machine learning model was selected for subsequent analysis. Predictive model variables were screened and compressed by visualizing SHAP (SHapley additive exPlanations) with recursive feature regression. Furthermore, the efficacy of each model was evaluated through calibration curves and clinical decision curves. The optimal predictive model was selected for internal validation using the validation set, and data of in-hospital Pr-AKI patients (72 cases) in the hospital from January 2021 to June 2023 were collected for validation (time series validation set). Results:A total of 458 pregnancies in 441 patients were included in the present analysis, among which 277 cases (60.5%) resulted in adverse pregnancy outcomes. Utilizing the training set, 21 feature variables were selected for model construction. Among the 6 models, the random forest model performed the best ( AUC=0.860, recall=0.784, precision=0.813, F1-score=0.790, accuracy=0.806). With subsequent feature refinement proceeding, a total of 12 clinical indicators were selected to construct the model. Among them, proteinuria, systolic blood pressure, and the highest serum creatinine were the top three related factors, and the other related factors included: severe preeclampsia, baseline serum creatinine, serum albumin, diastolic blood pressure, aspartate aminotransferase, blood uric acid, white blood cell count, serum cystatin C, and cholesterol. Among various machine learning models, the random forest model demonstrated optimal net benefits and the widest clinical utility range, showing robust performance in both internal validation set ( AUC=0.80) and the time series validation set ( AUC=0.72). Conclusions:In this study, different machine learning algorithms are successfully applied to develop predictive models for adverse pregnancy outcomes in patients with Pr-AKI. The random forest model is translated into a clinically applicable tool, providing a reference for the convenient and rapid identification of adverse pregnancy outcomes in Pr-AKI patients.

Objective:To study and analyze radiation doses to the eye of the lens dose in interventional radiology staff of Guandong medical institutions from 2019 to 2023.Methods:Employing a convenience sampling method, the lens dose and chest dose was monitored with TLD dosimeters in 34 level A tertiary medical institutions. The monitoring data were analyzed on the basis of a summary, and the relationship between the two was explored.Results:A total of 1 033 interventional radiology staff were monitored. The ocular lens doses were in the range of (

Objective:To investigate the dose characteristics of the Zeiss INTRABEAM system in air and water, providing dose reference for electronic brachytherapy.Methods:A Monte Carlo program was used to establish a three-dimensional model of a miniature X-ray source vacuum drift tube and a 4 cm spherical applicator. The process of electron beam bombardment on a gold target to generate X-rays was simulated, and parameters such as photon fluence spectrum, percentage depth dose, and half-value layer were calculated. Additionally, the radial dose uniformity in water was measured.Results:The average energy of X-rays at 3 cm in air was 20.8 keV, with a half-value layer of 0.08 mm Al. Under the influence of the applicator, the spectrum becomes hardened, with axial and radial average energies of 28.7 and 29.0 keV, respectively. In water, the percentage depth dose (PDD) curve follows an inverse cubic decay with depth, indicating strong dose concentration and rapid fall-off in near-field irradiation. The radial dose uniformity in water exceeded 99.5%.Conclusions:The INTRABEAM device emits low-energy X-rays characterized by shallow penetration depth, and concentrated dose delivery. Its highly uniform dose distribution ensures comprehensive coverage of the target area, making it particularly suitable for treating superficial tumors and for intraoperative radiotherapy at close range.

Objectives:This study aims to investigate the expression changes of transient receptor potential vanilloid type 1 (TRPV1) channel and inflammatory factors in the peripheral blood of patients with schizophrenia, and to evaluate their potential value for diagnostic prediction.Methods:This cross-sectional study was conducted at Renmin Hospital of Wuhan University from September 2023 to June 2024. A total of 35 patients with schizophrenia (patient group) from the outpatient/inpatient departments and 35 age-and sex-matched healthy individuals (control group) were recruited. Psychiatric symptoms and cognitive function were evaluated using the Positive and Negative Syndrome Scale (PANSS) and the Brief Assessment of Cognition in Schizophrenia (BACS), respectively. The between-group comparisons of the total scores of these two instruments were calculated using independent samples t-tests. Fasting peripheral blood samples were collected from all participants. Plasma and peripheral blood mononuclear cells (PBMCs) were isolated for subsequent analysis. TRPV1 protein expression was quantified by Western blotting, while inflammatory cytokines, including tumor necrosis factor-α (TNF-α), interleukin-2 (IL-2), interleukin-4 (IL-4), interleukin-6 (IL-6), and interleukin-10 (IL-10), were measured using enzyme-linked immunosorbent assay (ELISA). The between-group differences in TRPV1 and inflammatory cytokines were analyzed using the analysis of covariance (ANCOVA), controlling for age and sex. Pearson correlation analysis was employed to examine relationships between continuous variables, controlling for years of education, age, and sex. The diagnostic performance of TRPV1 and inflammatory cytokines for schizophrenia was assessed using receiver operating characteristic (ROC) curve analysis. Results:Significant between-group differences were observed in BACS total and subscale scores ( t=2.57-9.72, all P<0.01). Compared with the control group, the patient group exhibits significantly decreased expression of TRPV1, IL-4, and IL-10 ( t=6.78, 2.75, 2.53, all P<0.01), increased expression of TNF-α, IL-2, and IL-6 ( t=4.08, 2.64, 2.63, all P<0.01), and an increased IL-6/IL-10 ratio ( t=3.18, P<0.01). Correlation analyses revealed that in the patient group, the TRPV1 expression level was negatively correlated with levels of TNF-α and IL-6, and positively correlated with levels of IL-4 and IL-10 ( r=-0.589, -0.234, 0.341, 0.293, all P<0.05). In the patient group, the TRPV1 expression level was negatively correlated with the negative symptom score of PANSS ( r=-0.299, P<0.05), and the IL-6 level was positively correlated with the negative symptom score, the general pathology score, and the total score of PANSS ( r=0.387, 0.356, 0.321, all P<0.05). The TRPV1 level was positively correlated with the total score of BACS in both the control group and the patient group ( r=0.144, 0.828, all P<0.01). The IL-6/IL-10 ratio was positively correlated with the total score of PANSS and negatively correlated with the total score of BACS in the patient group ( r=0.623, -0.333, all P<0.05). The area under the ROC curve for the combination of TRPV1 level and IL-6/IL-10 ratio was 0.98 (95% confidence interval=0.96 to 1.00). Conclusions:Patients with schizophrenia exhibit reduced expression levels of TRPV1 along with an imbalanced inflammatory response. The combined assessment of TRPV1 level and IL-6/IL-10 ratio has demonstrated a high predictive and diagnostic value for schizophrenia.

Objective To explore limb coordination patterns and energy flow strategies during the sit-to-stand(STS)transition in individuals with patellofemoral pain(PFP),so as to provide a theoretical evidence for the pathogenesis of PFP and subsequent formulation of treatment and rehabilitation strategies for PFP patients.Methods A totoal of 36 participants was recruited for the STS test.They were divided into the unilateral PFP group(unilateral group),bilateral PFP group(bilateral group),and control group,based on the number of limbs affected by PFP.An infrared motion capture system and a three-dimensioanl force plate were used for motion capture.Visual 3D and Matlab software were used to calculate the trunk and pelvis angles,angular velocities,linear velocities,and proximal and distal joint forces.Additionally,the angles,torques,and joint forces of the hip,knee,and ankle joints,along with the angular and linear velocities of the thigh and shank,were computed.Coupling angles was used to represent coordination patterns via vector coding;the segmental net energy integration method was used to calculate energy flow within segments at each stage.Results For the coordination pattern at frontal plane,the proximal coordination mode frequency of the pelvis-hip coordination in the flexion momentum phase(FMP)was higher in unilateral group than that in bilateral group(P=0.024).In the momentum transfer phase(MTP),the frequency of in-phase coordination in the trunk-pelvis coordination was higher in unilateral group than that in bilateral group(P=0.023),while the frequency of distal coordination was higher in control group than in that in unilateral group(P=0.032).For the knee-ankle coordination pattern,the frequency of distal coordination in control group was lower than that in unilateral and bilateral groups(P=0.025,P=0.005).In segmental energy flow,during the FMP,the energy output from the pelvis during extension phase(MP)was higher in bilateral group than that in control group(P=0.021).Conclusions PFP affects energy flow patterns and coordination patterns at frontal plane during the STS transition.Individuals in unilateral group may engage in lateral pelvic and ankle movements as a dynamic compensation for patellofemoral joint pressure,whereas individuals in bilateral group appear to increase pelvic region energy output and employ a more complex whole-body coordination pattern to compensate for functional deficits in the knee caused by PFP.