Background Methicillin-resistant Staphylococcus aureus (MRSA) is an important pathogen for both human bloodstream infections and mastitis in cows. However, little attention has been paid to the cross-host transmission of MRSA from cows to high-risk groups in China. Objective To determine the MRSA colonization rates among dairy cows and dairy farm workers in Xinjiang, identify the antibiotic resistance profiles and molecular characteristics of the isolates, and provide scientific evidence for the formulation of targeted infection control strategies. Method A cross-sectional survey combined with laboratory pathogen analysis was conducted. From June to August 2024, large-scale dairy farms in Xinjiang region were selected as study sites. Nasal swabs (n=96) and skin swabs (n=39) were collected from workers, and bovine nasal swab samples (n=109) were collected simultaneously. All samples were subjected to MRSA isolation, cultivation, and identification, followed by antibiotic susceptibility testing to characterize resistance phenotypes. Staphylococcus aureus protein A (Spa) typing was performed to determine strain genotypes and elucidate MRSA colonization rates and molecular epidemiological patterns. Results A total of 35 MRSA strains was successfully isolated from 244 samples. The MRSA colonization rates among dairy farm workers and dairy cows were 20.83% (20/96) and 12.84% (14/109), respectively, with an overall isolation rate of 14.34% (35/244). Among the workers, the nasal colonization rate was 16.67% (16/96), and the skin colonization rate was 12.82% (5/39). One worker exhibited MRSA colonization at multiple body sites. All MRSA strains were resistant to cefoxitin (100%, 35/35). The resistance rates to erythromycin and clindamycin were 42.86% (15/35) and 34.29% (12/35), respectively. Thirteen strains showed a multidrug-resistant phenotype, whereas all strains were susceptible to vancomycin. The MRSA isolates exhibited high genetic diversity, with 13 Spa types identified, among which t441 was the most prevalent (8 strains). Both t441 and t034 types were detected in samples from both the dairy cows and their handlers. These two Spa types also carried and stably inherited specific resistance combinations, including erythromycin–clindamycin–cefoxitin and ciprofloxacin–erythromycin–clindamycin–gentamicin–cefoxitin–tetracycline, and a statistically significant association was also observed between the two resistance profiles and the bacterial types (P < 0.001). In addition, one novel Spa type strain was identified. Conclusion MRSA colonization rates among dairy cows and dairy farm workers in Xinjiang are relatively high, with evidence of multi-site colonization. The isolates exhibit high levels of multidrug resistance and genetic diversity, indicating a potential risk of cross-host transmission.

Climate change is a significant environmental concern in the 21^st century. It can directly and indirectly affect public health, making it a major public health problem. This review focused on the relationship between meteorological factors and health-related behaviors such as physical activity, sleep, dietary behavior, and social contact behavior. The results indicated that meteorological factors such as temperature, relative humidity, wind speed, atmospheric pressure, and rainfall are associated with the four health behaviors. Physical activity levels are negatively associated with temperature, relative humidity, and rainfall. Sleep quality tends to decrease under extreme temperatures and extreme weather events. Dietary behavior is influenced by high and low temperatures, low pressure, and daylight duration, which in turn affects appetite and food intake. Social contact frequency decreases in response to extreme temperatures, increased rainfall, and extreme weather events. However, there are differences in the strength and direction of the associations between meteorological factors and health-related behaviors in various studies. Research on the combined effects of multiple meteorological factors exposure on health-related behaviors is rare, and the mechanisms underlying the associations are unclear. Therefore, there is a need for more multi-center, large-scale studies to explore the biological and behavioral mechanisms behind these associations, which will help clarify the complex effects of meteorological factors on human health behaviors and provide scientific evidence for policy-making, thereby mitigating the negative impact of climate change on public health.

Bacterial infection is a major threat to global public health, and can cause serious diseases such as bacterial skin infection and foodborne diseases. It is essential to develop a new method to rapidly diagnose clinical multiple bacterial infections and monitor food microbial contamination in production sites in real-time. In this work, we developed a 4-mercaptophenylboronic acid gold nanoparticles (4-MPBA-AuNPs)-functionalized hydrogel microneedle (MPBA-H-MN) for bacteria detection in skin interstitial fluid. MPBA-H-MN could conveniently capture and enrich a variety of bacteria within 5 min. Surface enhanced Raman spectroscopy (SERS) detection was then performed and combined with machine learning technology to distinguish and identify a variety of bacteria. Overall, the capture efficiency of this method exceeded 50%. In the concentration range of 1 × 10⁷ to 1 × 10¹⁰ colony-forming units/mL (CFU/mL), the corresponding SERS intensity showed a certain linear relationship with the bacterial concentration. Using random forest (RF)-based machine learning, bacteria were effectively distinguished with an accuracy of 97.87%. In addition, the harmless disposal of used MNs by photothermal ablation was convenient, environmentally friendly, and inexpensive. This technique provided a potential method for rapid and real-time diagnosis of multiple clinical bacterial infections and for monitoring microbial contamination of food in production sites.

Given the increasing concern regarding antibacterial resistance, the antimicrobial properties of naphthoquinones have recently attracted significant attention. While 1,4-naphthoquinone and its derivatives have been extensively studied, the antibacterial properties of 5,8-dihydroxy-1,4-naphthoquinone derivatives remain relatively unexplored. This study presents a comprehensive in vitro and in vivo analysis of the antibacterial activity of 35 naturally sourced and chemically synthesized derivatives of 5,8-dihydroxy-1,4-naphthoquinone. Kirby-Bauer antibiotic testing identified three compounds with activity against methicillin-resistant Staphylococcus aureus (MRSA), with one compound (PNP-02) demonstrating activity comparable to vancomycin in minimum inhibitory concentration, minimum bactericidal concentration (MBC), and time-kill assays. Microscopic and biochemical analyses revealed that PNP-02 adversely affects the cell wall and cell membrane of MRSA. Mechanistic investigations, including proteomic sequencing analyses, Western blotting, and RT-qPCR assays, indicated that PNP-02 compromises cell membrane integrity by inhibiting arginine biosynthesis and pyrimidine metabolism pathways, thereby increasing membrane permeability and inducing bacterial death. In an in vivo mouse model of skin wound healing, PNP-02 exhibited antibacterial efficacy similar to vancomycin. The compound demonstrated low toxicity to cultured human cells and in hemolysis assays and remained stable during serum incubation. These findings suggest that PNP-02 possesses promising bioactivity against MRSA and represents a potential novel antibacterial agent.
Methicillin-Resistant Staphylococcus aureus/genetics* ; Anti-Bacterial Agents/chemistry* ; Naphthoquinones/administration & dosage* ; Animals ; Microbial Sensitivity Tests ; Mice ; Humans ; Staphylococcal Infections/microbiology* ; Molecular Structure

Objective:To develop a nomogram model for predicting the risk of ventilator-associated pneumonia (VAP) in patients with mechanical ventilation (MV) and to validate the stability of the prediction performance of the model.Methods:The patients with MV admitted to the Department of Critical Care Medicine of General Hospital of Ningxia Medical University from January 2019 to December 2022 were retrospectively selected according to the order of admission. The patients with MV were divided into the non-VAP group and the VAP group according to whether VAP occurred. The clinical data of the two groups, including general information, disease, medication, condition, and operation-related indicators were collected as candidate predictors of the model for comparison. Multivariate logistic stepwise forward regression analysis was used to screen the predictors that finally entered the model, and a nomogram model was constructed. The model discrimination was evaluated by the area under the receiver operating characteristic curve (AUC), the diagnostic test results of the model at the predicted threshold were calculated, the Hosmer-Lemeshow test was used to evaluate the model fit, and the Bootstrap resampling was used 1 000 times for internal validation, and model calibration and clinical applicability were evaluated by calibration curve and decision analysis curve, respectively.Results:A total of 1 250 patients with MV were included, including 1 102 patients in the non-VAP group and 148 patients in the VAP group, and the prevalence of VAP was 11.8%. The detection of multidrug-resistant organisms, chronic kidney disease, brain injury, oxygenation index, the place of tracheal intubation, reintubation, use of bronchoscopy, use of antibiotics, and MV duration were model predictors of VAP. The AUC of the nomogram model was 0.917 (95% CI: 0.895-0.939), the maximum Youden index of 0.697 corresponded to a prediction threshold of 0.096. The model accuracy, sensitivity and specificity were 0.836, 0.865, and 0.832, respectively. The positive predictive value and the negative predictive value were 0.409 and 0.979, respectively. The Hosmer- Lemeshow test indicated that the model fit well ( P=0.938). The results of the internal validation of the model showed that the predicted risk of the calibration curve was generally consistent with the actual risk, and the decision threshold probability of the decision analysis curve ranged from 2% to 90%. Conclusions:The nomogram model developed in this study is simple, convenient and has relatively stable prediction performance, which can be externally validated to evaluate the extrapolation of the model, and provide a basis for individualized clinical prediction of the risk of VAP in patients with MV.

Objective: To explore the association between mammalian sterile 20-like kinase 2(MST2) gene polymorphism and haplotype and the risk of colorectal cancer, rectal cancer, and colon cancer in the Han population in Baotou area by case-control association study. Methods: A total of 390 patients with colorectal cancer diagnosed by pathology and 413 normal physical examination pop-ulation were collected, and 2 mL of peripheral blood was taken for subsequent gene genotyping. Single nucleotide polymorphisms(SNPs) of MST2 gene were screened according to the genetic polymorphism data of Chinese Han population provided by the NCBI-Hapmap database. Gene genotyping was performed by Taqman method. Logistic regression was used to calculate the association between each SNP and the risk of colorectal cancer, colon cancer, and rectal cancer under codominant, dominant, overdominant, and recessive genetic models. Results: Five SNPs of MST2 gene were screened, namely rs11783149, rs10955176, rs7827435, rs4075986, rs3019295. Among them, SNP rs4075986 was associated with the risk of colorectal cancer. Compared with the rs4075986 GG+AA genotype, carrying the AG genotype [OR(95%CI)=2.473(1.844-3.316) could increase the risk of colorectal cancer. Compared with the rs4075986 GG genotype, carrying the AG+AA genotype [OR(95%CI)=2.475(1.844-3.323) could increase the risk of colorectal cancer. SNP rs4075986 and rs3019295 were associated with the risk of rectal cancer. Compared with the rs4075986 GG+AA genotype, carrying the AG genotype [OR(95%CI)=3.411(2.387-4.874)] could increase the risk of rectal cancer. Compared with the rs3019295 GG+AA genotype, carrying the AG genotype [OR(95%CI)=0.706(0.501-0.996)] could reduce the risk of rectal cancer. SNP rs11783149 and rs4075986 were associated with the risk of colon cancer. Compared with the rs11783149 CC genotype, carrying the TT [OR(95%CI)=10.883(1.186-99.862)] and CT [OR(95%CI)=1.665(1.036-2.675)] genotype could increase the risk of colon cancer, respectively. Compared with the rs4075986 GG genotype, the AG+AA genotype [OR(95%CI)=1.824(1.262-2.638)] could increase the risk of colon cancer. Conclusion MST2 gene SNP rs3019295 AG genotype may be protective factor for rectal cancer. SNP rs11783149 CT and TT genotypes maybe risk factors for colon cancer. SNP rs4075986 AG and AG+AA genotypes may be a common risk factors for colorectal cancer, rectal cancer and colon cancer.

Objective Based on gender differences,this paper discusses the characteristics of facial color diagnosis in male and female patients with metaplastic chronic atrophic gastritis(CAG),and explores the pathological mechanism of different gender patients from the perspective of TCM pathogenesis,so as to provide personalized reference for TCM prevention and treatment of metaplastic CAG.Methods In this study,the complexion information of patients with chronic non atrophic gastritis(CNG)and CAG was collected by MT-BX-01 four-diagnostic instrument.The color colorimetric characteristics of male and female metaplastic CAG patients and CNG patients were analyzed by case-control study.Results In female patients,the L value and a value of liver region in CAG with mild intestinal metaplasia(IM)group,moderate and severe IM were significantly lower than those in CNG group(P<0.05).In male patients,the L value of spleen region in CAG with moderate and severe IM group was significantly higher than that in CNG group(P<0.05).Conclusion There is a certain gender difference in the facial color characteristics of patients with metaplastic CAG.The facial chromaticity value of female patients with metaplastic CAG changes most significantly in the liver area,while that of male patients mainly in the spleen area.It is suggested that the incidence of female metaplastic CAG is mostly related to liver,while that of male is mostly related to spleen,which provides a personalized method for clinical diagnosis and treatment of metaplastic CAG based on gender differences.

Objective:To explore a simplified and efficient early prediction model for severe acute pancreatitis (SAP) using the least absolute shrinkage and selection operator (LASSO) regression, and to construct both logistic regression and decision tree models. The aim is to identify high-risk individuals, guide clinical treatment, and improve patient outcomes.Methods:A retrospective analysis was conducted on the clinical data of 412 patients with acute pancreatitis admitted to the Emergency and Gastroenterology Departments of the First Affiliated Hospital of Anhui Medical University and its High-tech Branch from November 2020 to September 2023. LASSO regression was employed to identify factors significantly associated with SAP, followed by the construction of a multivariate logistic regression model and a decision tree model. The predictive performance of these models was evaluated and compared to the bedside index for severity in acute pancreatitis (BISAP).Results:Among the 412 patients, the incidence of SAP was 12.14% ( n=50). Seven variables significantly associated with SAP severity were identified by LASSO regression, including respiratory rate at admission, pain score at admission, pleural effusion, fibrin degradation products, C-reactive protein, serum creatinine, and serum albumin. The logistic regression model incorporated four variables: pleural effusion, pain score at admission, serum creatinine, and serum albumin. In the training set, the model demonstrated a sensitivity of 0.528, specificity of 0.984, accuracy (95% CI) of 0.928 (0.892-0.955), Kappa value of 0.606, and AUC (95% CI) of 0.920 (0.862-0.979). In the testing set, the model showed a sensitivity of 0.643, specificity of 0.925, accuracy (95% CI) of 0.891 (0.822-0.941), Kappa value of 0.519, and AUC (95% CI) of 0.923 (0.861-0.985). The decision tree model comprised three branches and four terminal nodes, indicating that serum creatinine, serum albumin, and pleural effusion could effectively predict SAP occurrence. In the training set, the decision tree model had a sensitivity of 0.500, specificity of 0.973, accuracy (95% CI) of 0.914 (0.876-0.944), Kappa value of 0.544, and AUC (95% CI) of 0.812 (0.731-0.894). In the testing set, the model exhibited a sensitivity of 0.500, specificity of 0.925, accuracy (95% CI) of 0.875 (0.802-0.928), Kappa value of 0.412, and AUC (95% CI) of 0.709 (0.565-0.853). The DeLong test revealed that in the training set, the AUC of the logistic regression model was significantly greater than that of the decision tree model ( P<0.01) and the BISAP score ( P<0.001), while the AUC difference between the decision tree model and the BISAP score was not statistically significant ( P=0.762). In the testing set, the AUC of the logistic regression model was again greater than that of the decision tree model ( P<0.01) and the BISAP score ( P=0.018), whereas the AUC of the decision tree model was lower than that of the BISAP score ( P=0.017). Conclusions:Both the logistic regression and decision tree models demonstrate good predictive value for SAP, and their combined use may provide valuable guidance for clinical practice.

The construction of experimental animal models plays an important supporting role in research into the mechanisms of action of Chinese medicines.There have been increasing reports of the construction and evaluation of animal models of spleen deficiency;however,the construction method have involved different standards and there has been insufficient objectification of the evaluation indexes.In this review,we summarize the construction and evaluation method of animal models of spleen deficiency from the aspects of animal selection,model establishment,macroscopic characterization,behavioral experiments,and objective indexes of spleen deficiency,with a view to providing theoretical guidance for the construction of experimental animal models of spleen deficiency and references for the selection of animal model platforms for spleen deficiency.

The discrimination of the cause of death is an important part in forensic medicine. With the advantages of simple operation， high test efficiency， and easy sensitivity to the death mechanism of the deceased， postmortem biochemistry analysis has become a significant auxiliary analysis method for discrimination of the cause of death. In this paper， we discuss the development status， advantages and current problems of postmortem biochemical analysis， and then describe the application prospect of postmortem biochemistry in the discrimination of the cause of death by posing feasible solutions， so that to provide an idea for this research.