Triclosan (TCS) and triclocarban (TCC) are widely used synthetic broad-spectrum antibacterial agents that can enter the human body through the skin, gastrointestinal tract, and other pathways. More and more studies have found that exposure to TCS and TCC can affect human health, but currently, review reports on the health effects of human exposure to TCS and TCC are limited. Therefore, this study reviewed population studies on the relationship between TCS and TCC exposure and health effects by searching the PubMed database, summarized the associated health outcomes, and elucidated the biological mechanisms. A total of 56 studies were retrieved, among which cross-sectional studies (25 studies, 44.64%) and cohort studies (25 studies, 44.64%) accounted for a relatively large proportion, while case-control studies (6 studies, 10.72%) were relatively few. Studies on TCS exposure (48 studies, 85.71%) were far more prevalent than those on TCC exposure (2 studies, 3.57%). The remaining 6 studies involved both TCS and TCC exposure. The research results revealed that TCS exposure was associated with male and female abnormal reproductive functions, fetal growth restriction, abnormal behavior development in children, obesity, gestational diabetes mellitus (GDM), and immune-related diseases. Although the results of different studies show significant differences, they have indicated that exposure to TCS is a potential risk factor for these health problems. Due to the limited number of studies, the evidence for the relationship between TCC exposure and most of the aforementioned health effects is insufficient. Population studies and in vitro and in vivo studies have shown that exposure to TCS and TCC can interfere with the microbial homeostasis, the endocrine system, oxidative stress and immune function of the body, which are potential mechanisms causing adverse health effects. In the future, large-scale prospective cohort studies, as well as in vivo and in vitro studies, are still needed to further clarify the associations between TCS and TCC exposure and health effects, and to deeply explore its mechanism of action. These efforts will provide references for clarifying the human health hazards of TCS and TCC exposure and formulating targeted prevention and control strategies.

Objective:To examine the distribution of pathogens that cause postoperative nosocomial infections in patients with rectal cancer(RC)and to construct a predictive nomogram for nosocomial infection.Methods:The clinical data of 1537 RC patients admitted to Sir Run Run Shaw Hospital between January 2021 and December 2022 were collected.Patients were assigned 1∶1 by propensity score matching(PSM)to the infection group(n=83)and control group(n=83)based on the occurrence of nosocomial infection.The dis-tribution and drug resistance of bacteria in patients with nosocomial infection were analyzed.Risk factors for postoperative nosocomial infection were identified by least absolute shrinkage and selection operator(LASSO)regression,and a predictive nomogram was con-structed using multivariate logistics regression.The predictive performance of the model was evaluated by receiver operating character-istic(ROC)curve,calibration curve,and decision curve analysis(DCA).Results:A total of 93 strains of pathogens were isolated from the 83 infected patients,including 62 strains of Gram-negative bacteria(66.67%;predominantly Escherichia coli and Pseudomonas ae-ruginosa),25 strains of Gram-positive bacteria(26.88%;mainly Enterococcus faecalis),and 6 strains of fungi(6.45%;all Candida albicans).LASSO and multivariate logistics regression showed that smoking(odds ratio[OR]=3.97,95%CI=1.27-12.43),the dwelling time of drainage tube(OR=1.19,95%CI=1.08-1.30),difference in preoperative and postoperative neutrophil counts(OR=1.23,95%CI=1.01-1.49),and difference between preoperative and postoperative C-reactive protein levels(OR=1.05,95%CI=1.03-1.07)were inde-pendent risk factors for postoperative nosocomial infection in RC patients.The area under the ROC curve of the nomogram constructed based on the above factors was 0.933(95%CI=0.896-0.969).The calibration curve showed that the predicted risk was in good agree-ment with the actual observed risk of infection.In addition,DCA demonstrated that the nomogram has good clinical utility and high net clinical benefits in predicting nosocomial infection.Conclusion:The nomogram constructed in this study has a good predictive perfor-mance in postoperative nosocomial infection in RC patients.

Targeted protein degradation via nanoparticle-based universal strategy modifies nanoparticles with antibodies and ingeniously utilizes its cellular transport characteristics. This strategy achieved targeted degradation of extracellular proteins without complex design.Image 1.

Objective: To construct a scientific and perfect evaluation index system of infectious disease prevention and control ability in colleges and universities, so as to provide reference tools for colleges and universities to effectively respond to infectious disease. Methods: The initial framework of the evaluation index system of infectious disease prevention and control ability in colleges and universities was constructed by using literature analysis method. Experts familiar with infectious disease prevention and control or school health work were selected to conduct two rounds( n =16，18) of Delphi expert consultation for determining the evaluation index system. Analytical hierarchy process was used to calculate the index weights and combined weights. About 198 prevention and control personnel were conveniently selected from 3 universities in Inner Mongolia Autonomous Region to comprehensively evaluate the evaluation indicators by using fuzzy comprehensive evaluation method. Results: After two rounds of Delphi consultation questionnaire, the effective recovery rates were 80.0% and 90.0%, the expert authority levels were 0.89 and 0.86, the expert harmony coefficients for Kendall W were 0.166 and 0.310, and the variation coefficient of each index was <0.25. Finally, the evaluation index system of infectious disease prevention and control ability of colleges and universities included 4 first level indicators, 14 second level indicators and 75 third level indicators. The weights of prevention and monitoring and early warning, organizational system guarantee, emergency management, rehabilitation and summary were 0.176, 0.476, 0.268 and 0.080, respectively. The top 3 weights of the secondary indexes were 0.623 for infectious disease surveillance and early warning, 0.595 for loss assessment and 0.370 for emergency response. The score of fuzzy comprehensive evaluation of the index system of infectious disease prevention and control ability in colleges and universities was 79.148, suggesting a high level. Conclusion The established evaluation index system of infectious disease prevention and control ability in colleges and universities is scientific and reasonable, which is conducive to provide tool reference for the evaluation of infectious disease prevention and control ability in colleges and universities.

To investigate the awareness of cognitive impairment disorders among residents of the Xizang Autonomous Region and its influencing factors, thereby providing a basis for targeted prevention and treatment efforts.

Objective Exploring the clinical diagnosis and treatment status of epilepsy patients at the epilepsy specialty clinic in a single-center comprehensive hospital in the Lhasa area of the Tibetan Plateau.Methods Epilepsy patients who visited the epilepsy specialty clinic of the Department of Neurology at the Tibet Autonomous Region People's Hospital from September 2021 to June 2023 were continuously enrolled.Data such as clinical characteristics and diagnosis and treatment conditions of the enrolled patients was analyzed.Results A total of 121 patients were enrolled in this study,with 33.9%(41/121 cases)being new patients at our hospital and 6.6%(8/121 cases)being referred to our hospital.Non-adherence to treatment,with patients self-reducing or stopping medication without medical advice,accounted for 8.3%(10/121 cases)of the cases.The majority of epilepsy patients were in the young and middle-aged group,with 51.2%(62/121 cases)being between 18 and 44 years old.There were significant differences in the distribution of epilepsy patients across different age groups(P<0.001),while there was no significant difference in gender distribution(49.6%male vs.50.4%female,P>0.05).Generalized seizures were the predominant type of seizure(75.2%,91/121 cases),and 73.6%(89/121 cases)of the patients had an unknown etiology for their epilepsy,with symptomatic epilepsy accounting for 26.4%(32/121 cases)and structural causes being the most common at 24.8%(30/121 cases).Monotherapy was the main treatment for epilepsy(55.4%,67/121 cases),with sodium valproate being the most frequently prescribed drug for monotherapy at 22.3%(27/121 cases).Conclusion In the epilepsy specialty clinic in the plateau region,newly diagnosed patients account for about one-third,and over one-tenth of revisiting patients have not been receiving standardized treatment.The majority of our epilepsy patients are young to middle-aged adults.Generalized seizures are the predominant type.The etiology is unknown in the majority of cases,with structural causes being a common etiology in symptomatic epilepsy.Sodium valproate is the most frequently used antiseizure medication(ASM)in monotherapy in the plateau area.

Objective To investigate the predictive value of changes in various indicators of routine blood tests for the severity of brain damage in patients with acute cerebral hemorrhage(ACH)in high-altitude regions.Methods A retrospective analysis was conducted using data from 249 inpatients diagnosed with ACH at a hospital in Xizang.Patient data,including demographic information and results of routine blood tests,were collected.Based on their Glasgow Coma Scale(GCS)scores,the patients were divided into 2 groups,a mild brain damage group(GCS≥13 points)and a moderate-to-severe brain damage group(GCS≤12 points).Demographic information and laboratory test results were compared between the two groups.Binary logistic regression analysis was performed to examine the relationship between indicators of routine blood tests and the severity of brain damage,and key indicators were identified.The receiver operating characteristic(ROC)curve analysis was used to evaluate the predictive performance of key indicators in various combinations for the severity of brain injury in ACH patients.Results The moderate-to-severe group had a higher proportion of high-altitude residents,as well as elevated levels of white blood cells(WBC),neutrophils(N),neutrophil-to-lymphocyte ratio(NLR),systemic inflammatory index(SII),neutrophil-to-platelet ratio(NPR),and C-reactive protein(CRP)-to-lymphocyte ratio(CLR),compared to the mild group.On the other hand,the levels of lymphocytes(L),platelets(PLT),and platelet-to-albumin ratio(PAR)in the moderate-to-severe group were lower than those in the mild group.Binary logistic regression analysis showed that WBC(OR=1.221,95%CI:1.127-1.322),CRP(OR=1.019,95%CI:1.004-1.033),CRP-to-albumin ratio(CAR)(OR=1.845,95%CI:1.137-2.996),and CLR(OR=1.018,95%CI:1.005-1.030)were positively associated with moderate-to-severe brain damage,and that their elevated levels were associated with an increase in risk by the corresponding folds.PAR(OR=0.845,95%CI:0.721-0.990)was negatively correlated with moderate-to-severe brain damage,with an increase resulting in a reduction of risk by 0.845 times.ROC curve analysis showed that,in the mild group,the combined AUC for WBC+CRP was 0.689(optimal cutoff value 0.19,specificity 0.776,95%CI:0.624-0.755);the PAR+CAR+CLR combination(CAR was not significant,P>0.05)had an AUC of 0.675(optimal cutoff value 0.19,specificity 0.760,95%CI:0.609-0.741);the key indicator combination of WBC+PAR+CLR(CRP was not significant,P>0.05)demonstrating the strong predictive performance moderate-to-severe brain damage,yielding an AUC of 0.737(optimal cutoff value 0.08,specificity 0.624,95%CI:0.676-0.798).Conclusion The indicator combinations of WBC+CRP,PAR+CLR,and WBC+PAR+CLR exhibit significant value for predicting the severity of brain injury in ACH patients and may serve as potential predictive tools for the severity of brain damage in patients with acute cerebral hemorrhage in high-altitude regions.

Objective To observe the value of machine learning model based on MR T2WI and diffusion weighted imaging(DWI)radiomics for predicting perineural invasion(PNI)of rectal cancer.Methods Totally 343 patients with rectal cancer were retrospectively collected and divided into training set(n=275,92 PNI[+]and 183 PNI[-])and test set(n=68,23 PNI[+]and 45 PNI[-])at the ratio of 8∶2.Univariate and multivariate logistic regression(LR)were used to analyze clinical data and screen the independent predictors of PNI in rectal cancer,so as to construct a clinical model.The best radiomics features were extracted and screened based on preoperative T2WI and DWI.Then extremely randomized trees,multilayer perceptron,light gradient boosting machine,extreme gradient boosting,support vector machine(SVM),LR,K-nearest neighbor and random forest algorithms were used to construct ML models,respectively,and the optimal ML model was selected to establish a clinical-radiomics ML model combined with clinical relevant independent predictors.The predictive efficacy and clinical value of each model were evaluated.Results Patients' age was the independent predictor of PNI of rectal cancer(OR=0.988,P＜0.001),and the area under the curve(AUC)of the clinical model constructed based on it was 0.435 and 0.458 in training and test sets,respectively.SVM model was the best one among 8 ML models,with AUC in training and test set of 0.887 and 0.854,respectively.The AUC of clinical-radiomics ML model in training and test sets was 0.887 and 0.860,respectively,not different with AUC of SVM model(both P＞0.05).Decision curve analysis showed that when the threshold value was 0.20-0.45,clinical net benefit of SVM model was higher than that of other models.Conclusion SVM model based on T2WI and DWI radiomics could effectively predict PNI of rectal cancer.