Objective: To investigate the regional differences in the incidence of urothelial carcinoma among kidney transplant recipients between northern and southern China，so as to provide reference for early diagnosis of this disease. Methods: A comprehensive search was conducted across multiple databases，including CNKI，Wanfang，CBM，and PubMed，using the keywords “kidney transplantation” and “tumor” to collect clinical data from qualified kidney transplant centers.The latest and most complete literature data published by 17 transplant centers in northern China and 14 in southern China were included.Statistical analyses were performed to compare the incidence of post-transplant urothelial carcinoma and non-urothelial malignancies. Results: A total of 37 475 kidney transplant recipients were included，among whom 837 (2.23%) developed post-transplant malignancies，including urothelial carcinoma (366/837，43.73%)，non-urothelial carcinoma (444/837，53.05%)，and malignancies with unspecified pathology (27/837，3.23%).The incidence of malignancies was significantly higher in northern China than in southern China [(2.82±1.39)% vs. (1.67±0.83)%，P=0.011]，with a particularly pronounced difference in the incidence of urothelial carcinoma [(1.68±1.12)% vs. (0.32±0.32)%，P<0.001].No significant difference was observed in the incidence of non-urothelial carcinoma between the two regions [(1.11±0.56)% vs. (1.35±0.65)%，P=0.279].Additionally，female transplant recipients exhibited a higher incidence of malignancies than males in both regions (southern China：2.38% vs. 1.80%; northern China：8.93% vs. 2.52%). Conclusion: The incidence of urothelial carcinoma following kidney transplantation is significantly higher in northern China than in southern China，underscoring the importance of implementing regular tumor screening for kidney transplant recipients，particularly for female patients in northern China，to facilitate early diagnosis and timely intervention.

Schizophrenia (SZ) stands as a severe psychiatric disorder. This study applied diffusion tensor imaging (DTI) data in conjunction with graph neural networks to distinguish SZ patients from normal controls (NCs) and showcases the superior performance of a graph neural network integrating combined fractional anisotropy and fiber number brain network features, achieving an accuracy of 73.79% in distinguishing SZ patients from NCs. Beyond mere discrimination, our study delved deeper into the advantages of utilizing white matter brain network features for identifying SZ patients through interpretable model analysis and gene expression analysis. These analyses uncovered intricate interrelationships between brain imaging markers and genetic biomarkers, providing novel insights into the neuropathological basis of SZ. In summary, our findings underscore the potential of graph neural networks applied to multimodal DTI data for enhancing SZ detection through an integrated analysis of neuroimaging and genetic features.
Humans ; Schizophrenia/pathology* ; Diffusion Tensor Imaging/methods* ; Male ; Female ; Adult ; Brain/metabolism* ; Young Adult ; Middle Aged ; White Matter/pathology* ; Gene Expression ; Nerve Net/diagnostic imaging* ; Graph Neural Networks

Aim To discover the potential active compounds and possible mechanisms in rheumatoid arthritis (RA) treatment with Zhi-Huang-Zhi-Tong powder (ZHZTP) by using network pharmacology and in vitro study. Methods The active ingredient targets and disease targets of Zhihuang Zhitong Powder were searched and screened by database; they intersected to get a common target; and the "drug-component-target" relationship network diagram was constructed for GO and KEGG enrichment analysis of the overlapping genes; then the core components were docked with the core targets. Finally, based on the inflammation model of HUVECs in vitro, the efficacy and mechanism of Zhihuang Zhitong powder were verified by MTT method, plate scratch test and Western blot. Results Active compounds involved in RA treatment were screened in the present study, and the top two were ursolic acid and emodin, all playing crucial roles in RA treatment with ZHZTP. Additionally, the key target was AKTA, TNF and IL-6. GO and KEGG enrichment analysis revealed that ZHZTP regulated BP, MF and CC, and also focused on regulating AKTA, TNF and IL-6 signaling pathway. Molecular docking showed that interactions between key active compounds and key targets were stable. In vitro ZHZTP significantly inhibited cell viability and migration of TNF-a-stimulated HUVECs, and the involved mechanism may be associated with PI3K/AKT/m-TOR signaling. Conclusions The present study reveals that the potential active compounds of ZHZTP are ursolic acid and emodin, and moreover, the involved mechanisms of ZHZTP for RA treatment are associated with PI3 K/AKT/m-TOR signaling.

Chronic pelvic inflammatory disease(CPID)is a common chronic inflammatory disease in women,and has a long course and is easy to relapse.Danggui Shaoyao Powder is from Jin Gui Yao Lve(Synopsis of the Golden Chamber),which was a commonly-used formula for the treatment of women's abdominal pain in ancient medical records.It is now often used in the treatment of CPID and has achieved satisfactory therapeutic effect.The article summarizes and analyzes the achievements in the clinical research and experimental study of Danggui Shaoyao Powder in the treatment of CPID over the past 10 years,and invesigates the clinical efficacy of Danggui Shaoyao Powder in the treatment of CPID and its therapeutic mechanism.In the field of clinical studies,Danggui Shaoyao Powder for the treatment of CPID was used by modification,or alone,or in combination with antibiotics and Chinese medicine external treatment,and its combined use was effective on significantly improving the indicators of inflammatory response and immune function,alleviating the clinical signs and symptoms such as pain,and did not increase the incidence of adverse reactions compared with the application of western medicines alone.In the field of experimental studies,Danggui Shaoyao Powder played the therapeutic role in CPID by decreasing the adhesion of endothelial cells,regulating the degradation of extracellular matrix,improving the level of inflammatory factors,and down-regulating the expression of proteins related to the nuclear factor κB(NF-κB)pathway.

Objective: To construct a prognostic model for unsuccessful removal of nasogastric tube (NGT) was the aim of our study. Methods: This study examined patients with swallowing disorders receiving NGT feeding due to stroke or traumatic brain injury in a regional hospital. Clinical data was collected, such as age, sex, body mass index (BMI), level of activities of daily living (ADLs) dependence. Additionally, gather information regarding the enhancement in Functional Oral Intake Scale (FOIS) levels and the increase in food types according to the International Dysphagia Diet Standardization Initiative (IDDSI) after one month of swallowing training. A stepwise logistic regression analysis model was employed to predict NGT removal failure using these parameters. Results: Out of 203 patients, 53 patients (26.1%) had experienced a failed removal of NGT after six months of follow-up. The strongest predictors for failed removal were age over 60 years, underweight BMI, total dependence in ADLs, and ischemic stroke. The admission prediction model categorized patients into high, moderate, and low-risk groups for removal failure. The failure rate of NGT removal was high not only in the high-risk group but also in the moderate-risk groups when there was no improvement in FOIS levels and IDDSI food types. Conclusion Our predictive model categorizes patients with brain insults into risk groups for swallowing disorders, enabling advanced interventions such as percutaneous endoscopic gastrostomy for high-risk patients struggling with NGT removal, while follow-up assessments using FOIS and IDDSI aid in guiding rehabilitation decisions for those at moderate risk.

Background/Aims: Despite the high efficacy of direct-acting antivirals (DAAs), approximately 1–3% of hepatitis C virus (HCV) patients fail to achieve a sustained virological response. We conducted a nationwide study to investigate risk factors associated with DAA treatment failure. Machine-learning algorithms have been applied to discriminate subjects who may fail to respond to DAA therapy. Methods: We analyzed the Taiwan HCV Registry Program database to explore predictors of DAA failure in HCV patients. Fifty-five host and virological features were assessed using multivariate logistic regression, decision tree, random forest, eXtreme Gradient Boosting (XGBoost), and artificial neural network. The primary outcome was undetectable HCV RNA at 12 weeks after the end of treatment. Results: The training (n=23,955) and validation (n=10,346) datasets had similar baseline demographics, with an overall DAA failure rate of 1.6% (n=538). Multivariate logistic regression analysis revealed that liver cirrhosis, hepatocellular carcinoma, poor DAA adherence, and higher hemoglobin A1c were significantly associated with virological failure. XGBoost outperformed the other algorithms and logistic regression models, with an area under the receiver operating characteristic curve of 1.000 in the training dataset and 0.803 in the validation dataset. The top five predictors of treatment failure were HCV RNA, body mass index, α-fetoprotein, platelets, and FIB-4 index. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the XGBoost model (cutoff value=0.5) were 99.5%, 69.7%, 99.9%, 97.4%, and 99.5%, respectively, for the entire dataset. Conclusions Machine learning algorithms effectively provide risk stratification for DAA failure and additional information on the factors associated with DAA failure.

Background/Aims: Chronic hepatitis C (CHC) patients who failed antiviral therapy are at increased risk for hepatocellular carcinoma (HCC). This study assessed the potential role of metformin and statins, medications for diabetes mellitus (DM) and hyperlipidemia (HLP), in reducing HCC risk among these patients. Methods: We included CHC patients from the T-COACH study who failed antiviral therapy. We tracked the onset of HCC 1.5 years post-therapy by linking to Taiwan’s cancer registry data from 2003 to 2019. We accounted for death and liver transplantation as competing risks and employed Gray’s cumulative incidence and Cox subdistribution hazards models to analyze HCC development. Results: Out of 2,779 patients, 480 (17.3%) developed HCC post-therapy. DM patients not using metformin had a 51% increased risk of HCC compared to non-DM patients, while HLP patients on statins had a 50% reduced risk compared to those without HLP. The 5-year HCC incidence was significantly higher for metformin non-users (16.5%) versus non-DM patients (11.3%; adjusted sub-distribution hazard ratio [aSHR]=1.51; P=0.007) and metformin users (3.1%; aSHR=1.59; P=0.022). Statin use in HLP patients correlated with a lower HCC risk (3.8%) compared to non-HLP patients (12.5%; aSHR=0.50; P<0.001). Notably, the increased HCC risk associated with non-use of metformin was primarily seen in non-cirrhotic patients, whereas statins decreased HCC risk in both cirrhotic and non-cirrhotic patients. Conclusions Metformin and statins may have a chemopreventive effect against HCC in CHC patients who failed antiviral therapy. These results support the need for personalized preventive strategies in managing HCC risk.

Humans ; Blast Crisis/genetics* ; Leukemia, Promyelocytic, Acute/genetics* ; Oncogene Proteins, Fusion/genetics* ; Tretinoin

A crucial lesson gained through the pandemic preparedness and response to COVID-19 is that all measures for epidemic control must be law-based. The legal system is related not only to public health emergency management per se but also to all aspects of the institutional supporting system throughout the lifecycle. Based on the lifecycle emergency management model, this article analyses the problems of the current legal system and the potential solutions. It is suggested that the lifecycle emergency management model shall be followed to establish a more comprehensive public health legal system and to gather the intelligence and consensus of experts with different expertise, including epidemiologists, sociologists, economists, jurist and others, which will collaboratively promote the science-based legislation in the field of epidemic preparedness and response for the establishment of a comprehensive legal system for public health emergency management and with Chinese characteristics.
Humans ; China ; Pandemics/prevention & control* ; Public Health ; Emergencies ; Disaster Planning

AIM: To explore the optimal concentration of endoplasmic reticulum stress immunohistochemical(IHC)staining antibody in mouse retinitis pigmentosa(RP)model, which provides the corresponding index detection method for studying the pathogenesis and intervention measures of RP.METHODS: Clean male C57BL/6J mice were intraperitoneally injected with N-methyl-N-nitrosourea(MNU, 60mg/kg)to prepare RP mouse model. Electroretinogram(ERG)and hematoxylin-eosin(HE)staining were performed on 7d after modeling to verify the successful modeling. The expression of endoplasmic reticulum stress-related proteins(IRE1, ATF6, PERK, GRP78, Caspase-12)was detected by IHC staining.RESULTS: The following proteins, including IRE1, ATF6, PERK, GRP78 and Caspase-12, were positively expressed in retina of RP mouse. The optimal concentrations of the above proteins were as follows: IRE1 antibody concentration was 1:1000, ATF6 antibody concentration was 1:500 and 1:1000(with no difference in positive expression, P>0.05), PERK antibody concentration was 1:1500, GRP78 antibody concentration was 1:200 and Caspase-12 antibody concentration was 1:100, the proteins were well expressed at the above concentrations, and the positive expressions of corresponding proteins were different from those of other antibody concentrations(P<0.05).CONCLUSION: The optimal concentrations for IHC staining in different proteins of mouse RP models were as follows: the concentrations of endoplasmic reticulum stress-related protein antibodies were 1:1000 in IRE1, 1:500 and 1:1000 in ATF6, 1:1500 in PERK, 1:200 in GRP78, and 1:100 in Caspase-12.