Functional constipation （FC） is a common functional disorder of the intestines， mainly characterized by reduced bowel movement frequency， difficulty in defecation， a sensation of incomplete evacuation， and hard stools， which severely affect patients’ quality of life. Research indicates that the pathogenesis of FC is closely related to gut microbiota dysbiosis and abnormal bile acid secretion. Bile acids， as endogenous natural laxatives， promote bowel movements by enhancing colonic secretion and regulating intestinal motility； meanwhile， gut microbiota influence colonic transit function by regulating the enteric nervous system， immune system， and their metabolic products. Based on an overview of the relationship between gut microbiota and bile acid metabolism， this article systematically reviews the current research status on the mechanisms of traditional Chinese medicine （TCM） in treating FC by regulating the balance of the gut microbiota-bile acid axis. It is found that single Chinese medicinal herbs （such as Atractylodes macrocephala）， isolated compounds （such as Platycodon grandiflorum polysaccharides）， herbal formulas （such as Shanger huang pill）， acupuncture， and moxibustion can up-regulate the abundance of beneficial bacteria， reshape the microbial structure， correct bile acid metabolism， and activate the Takeda G-protein receptor 5/farnesoid X receptor pathway to treat FC.

low transit constipation （STC） is a common functional intestinal disorder caused by impaired colonic transit function， characterized by reduced bowel movement frequency， hard stools， and difficulty in defecation. The mitogen-activated protein kinase （MAPK） signaling pathway， which mainly includes extracellular signal-regulated kinase （ERK）， c-Jun N-terminal kinase （JNK）， and p38 subtypes， plays a critical regulatory role in the occurrence and development of STC. This paper systematically reviews the multiple pathogenic mechanisms of the MAPK signaling pathway in STC and the research progress of traditional Chinese medicine （TCM） intervention.At the mechanistic level， the MAPK signaling pathway promotes the progression of STC through the following links：（1） Activation of p38 upregulates the expression of aquaporin 3 （AQP3）/AQP4 in the colon， leading to excessive reabsorption of water in the intestinal lumen； （2） It forms a positive feedback loop with nuclear factor-κB （NF-κB） to maintain low-grade intestinal inflammation， releases inflammatory factors such as tumor necrosis factor-α （TNF-α） and interleukin-1β （IL-1β）， and inhibits smooth muscle contraction； （3） Overactivation of p38 downregulates the expression of occludin and mucin 2 while upregulates the expression of claudin-2， thereby disrupting the mucosal barrier； （4） The JNK/p38 signaling pathway activates the caspase cascade to induce apoptosis of intestinal epithelial cells， neurons， and interstitial cells of Cajal； （5） Abnormal ERK signaling and excessive activation of p38/JNK inhibit intestinal smooth muscle contraction and reduce 5-hydroxytryptamine secretion， ultimately resulting in impaired colonic transit function.At the intervention level， TCM compound formulas and single herbs have been proven to improve STC by regulating the MAPK signaling pathway. Their effects are syndrome type-dependent：yin-nourishing formulas （Zengye Chengqi Tang， Tongbian Tang） mainly regulate the ERK/AQP axis； yang-warming formulas （Jichuan Jian） target both ERK/JNK and anti-apoptosis； heat-clearing formulas （Sanren Tang） focus on p38/NF-κB anti-inflammation. A single drug can simultaneously cover multiple aspects including water metabolism， inflammation， barrier function， apoptosis， and intestinal motility.Current relevant studies still have limitations such as mechanisms mostly remaining at the correlational level and a lack of disease-syndrome integrated research models. Future studies should combine specific inhibitors or gene knockout to identify core targets， establish disease-syndrome integrated STC models， and use network pharmacology and molecular docking techniques to deeply analyze the fine mechanism of “component-target-phenotype”， so as to provide high-quality evidence for the precise regulation of the MAPK signaling pathway by TCM in the intervention of STC.

ObjectiveAs a common lifestyle habit, alcohol consumption has a controversial association with the onset of Parkinson’s disease (PD). To demonstrate the correlation between alcohol consumption and PD and to identify associated genes, we integrated findings from clinical surveys, genomics, transcriptomics, and animal experiments. MethodsWe investigated the alcohol consumption rates (including both before and after disease onset) among 244 PD patients in China and 177 PD patients from the U.S. NHANES database. Mendelian randomization (MR) analysis was performed using genome-wide association study (GWAS) data for three alcohol-related traits and seven PD-related datasets from the MRC IEU OpenGWAS database. Transcriptomic data from the substantia nigra of PD patients were obtained from three GEO datasets (GSE7621, GSE20141, and GSE49036) to analyze RIT2 gene transcription. Finally, three groups of animal experiments (water/20% ethanol/20% liquor, with 4 C57BL/6J mice per group) were conducted to examine changes in brain RIT2 gene expression and transcriptomic profiles following alcohol consumption. ResultsThe alcohol consumption rates among PD patients in China and the U.S. (9%-18.87%) were significantly lower than the general population rates of 15%-45% in their respective regions (P<0.001), suggesting a possible negative association between alcohol consumption and PD. Subsequently, in 21 bidirectional MR analyses using 3 alcohol-related GWAS datasets and 7 PD-related GWAS datasets, the forward MR analyses (alcohol intake as exposure, PD as outcome) yielded 12 negative associations (OR_IVW<1) and 9 positive associations (OR_IVW>1). Among these, only two negative associations reached statistical significance: alcohol intake frequency (OR_IVW=0.75, 95% CI: 0.60-0.93, P=0.010) and alcohol consumption (OR_IVW=0.20, 95% CI: 0.05-0.83, P=0.026). The forward MR analysis (alcohol intake→PD) identified 235 SNPs, annotated to 316 genes, while the reverse MR analyses (PD→alcohol intake) identified 37 SNPs, annotated to 53 genes. Notably, only the RIT2 gene appeared in both the forward and reverse MR analyses (alcohol intake→PD: rs28597806, rs8083110; PD→alcohol intake: rs4588066). RIT2 is selectively expressed in the human brain (FPKM: 5.259±2.103), with low or no expression in peripheral tissues (FPKM: <1). Analysis of three human substantia nigra transcriptomic datasets revealed a decreasing trend in RIT2 gene expression in PD patients (GSE20141 array signal: 3.49±1.23 vs. 2.33±0.87, P=0.044). Animal experiments demonstrated that administration of 20% ethanol or 20% liquor (approximately 8% ethanol) stimulated a >2-fold upregulation of RIT2 gene expression in the mouse brain. Furthermore, transcriptomic sequencing revealed that the two alcohol-treated groups exhibited 96 (20% ethanol vs. water control) and 4 (20% liquor vs. water control) differentially expressed genes, respectively, indicating that low-dose alcohol consumption can achieve RIT2 upregulation while minimizing impact on other brain genes. In addition to its anti-infective effects, low-dose alcohol consumption primarily influences signaling pathways related to neurodegenerative diseases such as PD and Prion diseases. ConclusionAlcohol consumption is generally considered as a harmful lifestyle habit. However, some studies have also shown a lower risk of mortality among individuals who consume low doses of alcohol (100 g/week of ethanol) or drink occasionally. Currently, one of the research focuses on alcohol consumption is whether the human body can benefit from low-dose alcohol intake. This study provides new evidence supporting a negative association between alcohol consumption and PD, and for the first time, through MR analysis, identifies the RIT2 gene as a potential mediator of the effect of alcohol consumption on PD. RIT2 is selectively expressed in the human brain. Building upon existing evidence indicating downregulated RIT2 gene expression in PD pathogenesis, our experiments confirm that low-dose alcohol consumption can upregulate RIT2 expression in the brain. In brief, alcohol consumption may suppress the pathogenesis of PD by upregulating RIT2 expression in the substantia nigra. China is facing a serious problem of population aging. This study offers important insights for long-term PD prevention and treatment strategies, with the aim of benefiting more potential PD patients through lifestyle modifications, thereby improving the quality of life of the aging population and reducing the economic burden on healthcare.

OBJECTIVE To investigate the mechanism by which Shenfukang capsule （SFK） ameliorates renal interstitial fibrosis （RIF） by regulating macrophage-fibroblast crosstalk via the signal transducer and activator of transcription 3 （STAT3）/Yes-associated protein （YAP） pathway. METHODS RAW264.7 macrophages were induced to polarize with transforming growth factor-β 1 （TGF-β 1 ）. Subsequently， a non-contact co-culture system of macrophages with renal fibroblasts NRK-49F， as well as a non-contact co-culture system of macrophages with YAP-knockdown renal fibroblasts， were established. Cells were treated with low， medium， and high concentrations （4， 8， 16 μg/mL） of SFK， as well as a STAT3 inhibitor （STAT3-I，1.64 μg/mL） and losartan potassium tablets （positive control， 0.28 μg/mL）， for 48 h. After intervention， the protein and mRNA expression levels of CD86， CD163， and STAT3 in macrophages， as well as CD86， F4/80， and STAT3 mRNA， were detected. In co-cultured renal fibroblasts， the protein and mRNA expression levels of α -smooth muscle actin （ α -SMA）， Vimentin， collagen type Ⅰ （Col-Ⅰ）， matrix metalloproteinase-1 （MMP-1）， and YAP were detected. In co-cultured YAP-knockdown renal fibroblasts， the protein and mRNA expression levels of α -SMA， Vimentin， and MMP-1 were also detected. RESULTS Following TGF-β 1 induction， the protein expression levels of CD86， CD163， and STAT3， as well as the mRNA expression levels of CD86， F4/80， and STAT3 in macrophages were significantly increased （ P ＜0.05）. The conditioned medium from polarized macrophages activated renal fibroblasts， as evidenced by significantly increased protein and mRNA expression levels of α -SMA， Vimentin， Col-Ⅰ， and YAP， and significantly decreased protein and mRNA expression levels of MMP-1 in renal fibroblasts （ P ＜0.05）. Treatment with SFK and STAT3-I reversed the changes in the above indicators， with the medium concentration SFK group showing stronge r effects on some indicators than the low and high concentration groups. In the non-contact co-culture experiment of macrophages and YAP-knockdown renal fibroblasts， there were no statistically significant differences in the protein and mRNA expression of α-SMA， Vimentin， and MMP-1 among the groups. CONCLUSIONS SFK can inhibit macrophage-renal fibroblast crosstalk by blocking the STAT3/YAP pathway， thereby delaying the progression of RIF.

Objective To evaluate the feasibility of intravesical instillation of urokinase and heparin sodium in the treatment of bladder clot irrigation.Methods This report discusses the diagnosis and treatment of three patients with bladder blood clot tamponade confirmed by abdominal and pelvic computed tomography(CT)scans enrolled from our hospital during Jun. to Sep. 2024, and discuss the relevant literature.Results A solution containing urokinase(20 000 IU)and heparin sodium(125 000 U)was instilled through a three-way catheter and retained for 30 minutes before drainage. Complete clot dissolution was achieved in all cases, with immediate relief of hypogastric distension and pain. Post-procedural CT showed restored bladder lumen patency. Hemoglobin levels decreased by 2-5 g/L without complications.Conclusion This preliminary trial demonstrated that intravesical instillation of urokinase-heparin provides a safe and effective minimally invasive alternative for bladder clot in irrigation cases.

OBJECTIVE To explore the influencing factors of Shenfukang capsule in the treatment of chronic kidney disease （CKD） and construct a nomogram prediction model for evaluating its therapeutic efficacy. METHODS CKD patients who were hospitalized from July 2019 to August 2022 in the First Affiliated Hospital of Guangxi Medical University and treated with Shenfukang capsule were selected as study subjects. Clinical data of the patients were collected from the hospital’s electronic medical record system， and they were divided into an effective group and an ineffective group based on treatment outcomes. Lasso-Logistic multivariate regression analysis was used to screen the influencing factors of the efficacy of Shenfukang capsule. Using the effectiveness of Shenfukang capsule treatment as the prediction outcome and the screened influencing factors as predictor variables， a nomogram prediction model was constructed using R software. All patients were randomly divided into a training cohort and a validation cohort. The discriminative ability， calibration， and clinical net benefit of the model were evaluated using the receiver operating characteristic （ROC） curve， calibration curve， and decision curve analysis， respectively. RESULTS Lasso-Logistic regression analysis revealed that concurrent diabetes mellitus， decreased levels of blood urea nitrogen， triglycerides， and serum phosphorus， as well as prolonged prothrombin time and elevated apolipoprotein AⅠ levels， were influencing factors for reduced efficacy of Shenfukang capsule in CKD treatment. The evaluation results of the nomogram prediction model showed that the area under curve values were 0.745 and 0.797 in the training and validation cohorts， respectively， which were close and both exceeded 0.70， indicating stable predictive performance. The calibration curves demonstrated good agreement in both datasets， suggesting satisfactory calibration performance. The clinical decision curves were positioned above the two extreme reference lines， indicating high clinical benefit of the model. CONCLUSIONS Diabetes mellitus， blood urea nitrogen， triglycerides， apolipoprotein AⅠ， serum phosphorus， and prothrombin time were factors associated with the efficacy of Shenfukang capsule in CKD patients. The nomogram prediction model established in this study may provide a basis for rational clinical application of Shenfukang capsule and for improving its therapeutic efficacy in CKD.

OBJECTIVE To explore the influencing factors of Shenfukang capsule in the treatment of chronic kidney disease （CKD） and construct a nomogram prediction model for evaluating its therapeutic efficacy. METHODS CKD patients who were hospitalized from July 2019 to August 2022 in the First Affiliated Hospital of Guangxi Medical University and treated with Shenfukang capsule were selected as study subjects. Clinical data of the patients were collected from the hospital’s electronic medical record system， and they were divided into an effective group and an ineffective group based on treatment outcomes. Lasso-Logistic multivariate regression analysis was used to screen the influencing factors of the efficacy of Shenfukang capsule. Using the effectiveness of Shenfukang capsule treatment as the prediction outcome and the screened influencing factors as predictor variables， a nomogram prediction model was constructed using R software. All patients were randomly divided into a training cohort and a validation cohort. The discriminative ability， calibration， and clinical net benefit of the model were evaluated using the receiver operating characteristic （ROC） curve， calibration curve， and decision curve analysis， respectively. RESULTS Lasso-Logistic regression analysis revealed that concurrent diabetes mellitus， decreased levels of blood urea nitrogen， triglycerides， and serum phosphorus， as well as prolonged prothrombin time and elevated apolipoprotein AⅠ levels， were influencing factors for reduced efficacy of Shenfukang capsule in CKD treatment. The evaluation results of the nomogram prediction model showed that the area under curve values were 0.745 and 0.797 in the training and validation cohorts， respectively， which were close and both exceeded 0.70， indicating stable predictive performance. The calibration curves demonstrated good agreement in both datasets， suggesting satisfactory calibration performance. The clinical decision curves were positioned above the two extreme reference lines， indicating high clinical benefit of the model. CONCLUSIONS Diabetes mellitus， blood urea nitrogen， triglycerides， apolipoprotein AⅠ， serum phosphorus， and prothrombin time were factors associated with the efficacy of Shenfukang capsule in CKD patients. The nomogram prediction model established in this study may provide a basis for rational clinical application of Shenfukang capsule and for improving its therapeutic efficacy in CKD.

Objective: To evaluate the radiation dose, operational standardization, and image quality of computed tomography (CT) Ningbo City Medical Imaging Cloud Platform, so as to provide references for optimizing the quality of CT examinations. Methods: Six CT devices were randomly selected from the Ningbo City Medical Imaging Cloud Platform. Digital Imaging and Communication in Medicine (DICOM) image data from CT examinations of the head, neck, chest, and abdomen in males aged 36 to 60 years were collected from January 2023 to December 2024. The radiation dose levels were evaluated using the volume CT dose index (CTDIvol) and dose length product (DLP). The coefficient of variation (CV) of CTDIvol and scan length were calculated to assess scan stability. Operational standardization was evaluated using the redundancy rate of scan length and protocol matching degree. Imaging quality was assessed using the signal to noise ratio (SNR) and contrast to noise ratio (CNR). Results: A total of 28 897 DICOM images were collected, including 6 730 axial scans of the skull, 2 778 plain scans of the neck, 15 496 plain scans of the chest, and 3 893 plain scans of the abdomen. The typical values of CTDIvol and DLP radiation doses for the head, neck, and chest were all lower than the diagnostic reference levels. The maximum typical values of CTDIvol and DLP for the abdomen were 22.49 mGy and 941.45 mGy·cm, respectively, which were higher than the diagnostic reference levels. The CV values of CTDIvol and scan length ranged from 14.59% to 37.88% and from 8.27% to 44.96%, respectively. The scan stability of head CT was relatively poor, with CV values ranging from 21.74% to 37.88% and from 12.66% to 44.96%, respectively. The redundancy rate of scan length ranged from 6.02% to 74.40%, and the protocol matching degree ranged from 79.80% to 100.00%. The operational standardization of neck CT was relatively poor, with redundancy rates ranging from 45.70% to 74.40% and protocol matching degrees ranging from 79.80% to 95.36%. The mean SNR and mean CNR of the pulmonary arteries in the chest were relatively high, ranging from 15.81 to 17.65 and from 6.33 to 7.41, respectively. Conclusions The radiation doses from abdominal CT examinations on some CT devices exceed the diagnostic reference levels. The scan stability of head CT examinations and the operational standardization of neck CT examinations represent weak points in quality control. It is recommended to carry out targeted quality control training to enhance the overall quality level of CT examinations.

Objective To construct 5 machine-learning models and compare their performance in predicting the associations between pre-pregnancy socio-psycho-behavioral exposures of both spouses and preconception outcomes.Methods Based on Chongqing Preconception Reproductive Health and Birth Outcome Cohort of volunteers recruited from Chongqing Health Center for Women and Children during January 2019 and March 2022,5 447 couples were recruited and surveyed through interviewer-interview for the demographic and social-psychological-behavioral data of both spouses(221 variables).According to the inclusion and exclusion criteria,4 097 couples were finally included,and randomly assigned into a training set(n=2 867 spouses)and a validation set(n=1 230 spouses)at a ratio of 7∶3.Feature analysis and collinear screening were applied to select the potential exposure factors.In consideration of difficulty to carry out semen parameters analysis in primary healthcare institutions,feature Set 1 including sperm parameters and feature Set 2 excluding semen parameters were constructed by including or excluding sperm quality simultaneously in the training set and the validation set.Five algorithms,that is,Logistic Regression,Naive Bayes,Random Forest,Gradient Boosting Machine,and Support Vector Machine,were used to construct preconception outcome prediction models,and the parameters of each model were optimized using random search combined with grid search.The predictive performance of each model was compared using precision,recall,F1 score,area under the receiver operating characteristic curve(AUC),and calibration curve.The optimal model was then selected by comparing the changes in the predictive ability of the questionnaire data for fertility outcomes with or without semen parameters.Results There were 24 variables screened out in feature Set 1,and 16 variables in feature Set 2.In feature Set 1,the gradient boosting machine performed better,with a relatively higher AUC value(0.651)and better F1 score(0.61).The logistic regression model performed stably(AUC value=0.647)and was suitable as the reference model.The random forest(AUC value=0.641),Naive Bayes(AUC value=0.641),and support vector machine(AUC value=0.634)performed second-best.By utilizing the gradient boosting machine,comparable results were found between the predictions from feature sets with or without semen parameters,as in feature Set 1,the AUC value of its validation set was 0.651(95%CI:0.629～0.681),the prediction accuracy was 0.63,the recall rate was 0.65,and the average precision value F1 was 0.61;and in feature Set 2,the AUC value of its validation set was 0.649(95%CI:0.624～0.663),and both the calibration curves were close to the ideal curve.The prediction results indicated that in feature Set 1,the features highly negatively correlated with preconception outcomes were female age,male age,and no pregnancy within 1 year without contraception,while the features highly positively correlated with preconception outcomes were female pregnancy history,total sperm vitality,and use of contraceptive measures before enrollment.Conclusion Among the 5 machine-learning algorithms performed in this cohort data,the gradient boosting machine shows slightly better performance.There are 24 factors being associated with preconception outcomes in both spouses,and the performance of the simplified model excluding semen parameters is not significantly declined.It is feasible to use machine-learning methods to predict human preconception outcomes through social-psychological-behavioral questionnaires.

Breast cancer is one of the most common malignant tumors among women worldwide, with an increasing incidence rate year by year, making it a significant public health concern. With the continuous advancement of tumor biology research, N 6-methyladenosine (m 6A) modification, as an important form of RNA modification, has attracted growing attention. The m 6A modification, the most prevalent RNA modification in eukaryotes, occurs in almost all types of RNA and plays a critical role in the occurrence, progression, and metastasis of breast cancer. It influences cell proliferation, apoptosis, and alterations in the tumor microenvironment, though the specific mechanisms underlying these effects require further in-depth investigation. Moreover, the specific patterns of m 6A modification demonstrate its potential as a novel biomarker for breast cancer, which could provide new directions for early diagnosis and prognosis evaluation.