In order to determine the causative agents responsible for the lethality of tumor disease in breeders,liver,spleen and other tissues of dead chickens were collected,and pathogen detection,se-quencing and genetic evolution analysis were carried out by PCR.The results showed that all three samples were negative for reticuloendotheliosis virus(REV),samples 1 and 2 wereavian leukosis virus subgroup J(ALV-J)positive,and sample 3 was positive for ALV-J and Marek's disease virus(MDV),which preliminarily determined that the breeder died of ALV-J infection or ALV-J and MDV mixed infection.Among them,the ALV-J gp85 gene had the highest nucleotide homology with the reference strain of ALV-J,ranging from 87.70％to 99.30％,and was in the same branch with the reference strain of subgroup J.Amino acid homology ranged from 78.00％to 96.20％,with some mutations.The nucleotide homology between the MDV meq gene and the vv+strain was the highest,which was 98.00％-99.00％,and they were in the same branch.The homology of amino acids was 95.90％-98.20％,and there were multiple mutation sites,among which the 176th amino acid destroyed the original Pro repeat of the virus MDV meq due to the mutation of Pro to Arg or Ala,which may lead to the enhancement of its virulence.This study will provide a reference for the prevention and control of neoplastic diseases in breeders in this region.

OBJECTIVE To explore the effect of hydrogen peroxide disinfectant on terminal disinfection in wards of medical institutions.METHODS The surfaces of highly frequent contact objects of the wards of the First Affilia-ted Hospital of Nanchang University from which the public health center patients were discharged between Apr.2024 and Jun.2024 were respectively disinfected with 0.5％(low)and 5％(high)concentrations of hydrogen peroxide disinfecting wipes,totally 180 samples were randomly collected before and after the disinfection,and the pathogens were detected.The air of the wards from which the public health center patients were discharged be-tween Jul.2024 and Aug.2024 were disinfected with hydrogen peroxide dry mist disinfection device,and 90 sam-ples were respectively collected before and after the disinfection.Geobacillus stearothermophilus was used as the biological indicator and placed at various points within the air-disinfected wards to evaluate the disinfection level.The environmental sampling results and distribution of bacteria were observed and compared.RESULTS The qualified rates of disinfection of the object surfaces were 95.56％(86/90)and 98.89％(89/90)respectively for the low and high concentratioins of hydrogen peroxide disinfecting wipes,and there was no significant difference in the disinfection effect.Totally 120 strains of pathogens were isolated from unqualified samples before the disinfection,among which gram-negative bacteria(69.17％)were dominant,and the isolation rate of multidrug-resistant or-ganisms was 22.50％(27/120);only 1 strain of carbapenem-resistant Acinetobacter baumannii was isolated after the disinfection.The qualified rate of disinfection of air in the wards was 96.00％by 7.5％hydrogen peroxide dry mist disinfection device,the average bacterial colony counts in the air were 2 CFU/(5 min·vsl)after the dis-infection,and the killing rate of Geobacillus stearothermophilus was 100.00％by the air disinfection.CONCLUSION The hydrogen peroxide disinfectant can meet the requirement for terminal disinfection of the wards of the medical institutions,and it is portable and highly efficient.

Objective To analyze the correlation between venous thromboembolism(VTE)and traditional Chinese medicine(TCM)constitution types in elderly frail patients.Methods A retrospective study was conducted on 1 428 elderly frail patients admitted to the Second Comprehensive Department of Guangdong Provincial Hospital of Chinese Medicine from January 2019 to June 2023.Patients were divided into a venous thrombsis(VT)group(n=187)and a non-VT group(n=1 241)based on VTE occurrence.Baseline data,including age distribution,Padua scores,Wells scores,and TCM constitution types,were compared between the two groups.Multivariate logistic regression analysis was performed to identify factors for influencing VTE in elderly frail patients.Results(1)Compared with the non-VT group,the VT group had significantly higher total hospitalization costs,length of stay,age,Fried scores,Padua scores,and Wells scores,with statistically significance(P＜0.001).(2)Compared with the non-VT group,the VT group had a higher proportion of high VTE-risk individuals and those with Wells scores of 2 points,with statistically significance(P＜0.001).(3)The age distribution of VTE patients showed an increasing trend in the age groups of 60-69,70-79,80-89,and ≥90-year-old,with a significant difference compared to the non-VT group(P＜0.001).(4)The VT group had a higher proportion of qi-deficiency,blood-stasis,and qi-depression constitutions than the non-VT group(P＜0.05 or P＜0.001).(5)Multivariate logistic regression analysis(after adjusting age,gender,frailty,and other scores)showed that qi-deficiency and yang-deficiency constitutions were non-susceptible,while damp-heat,blood-stasis,and qi-depression constitutions were susceptible to VTE in elderly frail patients(P＜0.05 or P＜0.01).Conclusion VTE in elderly frail patients is significantly correlated with TCM constitution types.Deviated constitutions are characteristic of TCM constitution types in elderly frail patients,and damp-heat,blood-stasis,and qi-depression constitutions are risk factors for VTE in this population.

Objective To investigate serum metabolites and metabolic pathways alterations in patients with ischemic stroke(IS)through metabolomic analysis,and to identify reliable serum metabolic biomarkers for IS diagnosis.Methods This prospective study enrolled patients with IS admitted to the Department of Neurology at Xiangcheng People's Hospital of Suzhou from December 1,2022 to December 31,2023.Age-and sex-matched healthy individuals were recruited as controls during the same period.Baseline characteristics were collected,including age,sex,height,body mass index,and blood pressure.Venous blood samples were obtained after an 8 h fast for biochemical analysis of blood glucose,total bilirubin,serum creatinine,urea nitrogen,total cholesterol,triglycerides,high-density lipoprotein cholesterol,and low-density lipoprotein cholesterol.Serum metabolites of both groups were extracted and analyzed using ultra-high-performance liquid chromatography coupled with tandem mass spectrometry.Metabolomic data were processed using Simca-p software for unsupervised principal component analysis(PCA)and orthogonal partial least squares discriminant analysis(OPLS-DA)to evaluate group separation and experimental stability.Differential metabolites were defined by variable importance in projection(VIP)≥1.0,fold change(FC)≥2.0 or ≤0.5,and P＜0.05.Drug-derived exogenous metabolites were excluded by cross-referencing the Human Metabolome Database(HMDB,https://hmdb.ca/)and PubChem(https://pubchem.ncbi.nlm.nih.gov/).MetaboAnalyst 6.0(http://www.metaboanalyst.ca),a comprehensive web-based tool for metabolomic data analysis,was employed to map differential metabolites to the Kyoto encyclopedia of genes and genomes(KEGG)databased and to perform pathway enrichment analysis.Machine learning models were developed using Python.Least absolute shrinkage and selection operator(LASSO)regression and random forest(RF)algorithms were employed to identify diagnostic biomarkers capable of effectively distinguishing IS patients from controls.Metabolites identified by both methods were integrated into an extreme gradient boosting(XGBoost)model.Model performance was evaluated using receiver operating characteristic(ROC)curves with 5-fold cross-validation and internal validation(70％training,30％validation set).Results A total of 51 IS patients and 51 matched controls were included.(1)A total of 1 255 serum metabolites were identified(964 in positive ion mode,291 in negative ion mode).PC A and OPLS-DA demonstrated distinct metabolic separation between IS patients and controls.In IS group,260 metabolites were upregulated and 337 downregulated in positive ion mode;99 were upregulated and 34downregulated in negative ion mode.(2)Among the 1 255 metabolites,259 were identified as differential metabolites based on the criteria of VIP ≥ 1.0,FC≥2.0 or≤0.5 and P＜0.05.After excluding drug-derived metabolite through referencing HMDB and PubChem databases,a total of 220 endogenous differential metabolites were found to coexist in both positive and negative ion modes.Among them,119 metabolites were up-regulated and 101 were down-regulated in the IS group.The expression of these 220 metabolites showed significant differences between the IS and control groups.(3)KEGG pathway analysis highlighted five dysregulated pathways:upregulation of denovo triacylglycerol biosynthesis,glycerophosphate shuttle,and cardiolipin biosynthesis;downregulation of bile acid biosynthesis and methylhistidine metabolism.(4)LASSO and RF algorithms identified 24 and 30 candidate biomarkers,respectively.Four overlapping metabolites were selected:2-((3R)-3-((3R,5S,7S,9S,10S,13R,14S,17R)-3,7-dihydroxy-10,13-dimethylhexadecahydro-1H-cyclopenta[a]phenanthren-17-yl)butanamido)ethane-1-sulfonic acid(m/z 971.571 29),arginine-conjugated cholic acid(m/z 587.379 21),laccaic acid A(m/z 576.010 93)and NCGC00380235-01_C32H48O9_beta-D-xylopyranoside,3,17-dihydroxyspirosta-5,25(27)-dien-1-yl(m/z 559.326 48).The expression levels of 2-((3R)-3-((3R,5S,7S,9S,10S,13R,14S,17R)-3,7-dihydroxy-10,13-dimethylhexadecahydro-1H-cyclopenta[a]phenanthren-17-yl)butanamido)ethane-1-sulfonic acid(m/z 971.571 29),arginine-conjugated cholic acid(m/z 587.379 21),and laccaic acid A(m/z 576.010 93)were upregulated,while the expression level of NCGC00380235-01_C32H48O9_beta-D-xylopyranoside,3,17-dihydroxyspirosta-5,25(27)-dien-1-yl(m/z 559.326 48)was downregulated.An IS diagnostic model was established based on four metabolic biomarkers using the XGBoost algorithm.The area under the ROC curve was 1.000(95％CI 1.000-1.000)in the training set and 0.988 in the validation set(95％CI 0.963-1.000).Conclusions Patients with IS exhibit significant metabolic disturbance.The four identified biomarkers may serve as potential biomarkers for the effective identification of IS:2-((3 R)-3-((3R,5S,7S,9S,10S,13R,14S,17R)-3,7-dihydroxy-10,13-dimethylhexadecahydro-1H-cyclopenta[a]phenanthren-17-yl)butanamido)ethane-1-sulfonic acid(m/z971.571 29),arginine-conjugated cholic acid(m/z587.379 21),laccaic acid A(m/z 576.010 93),and NCGC00380235-01_C32H48O9_beta-D-xylopyranoside,3,17-dihydroxyspirosta-5,25(27)-dien-1-yl(m/z 559.326 48).

In order to determine the causative agents responsible for the lethality of tumor disease in breeders,liver,spleen and other tissues of dead chickens were collected,and pathogen detection,se-quencing and genetic evolution analysis were carried out by PCR.The results showed that all three samples were negative for reticuloendotheliosis virus(REV),samples 1 and 2 wereavian leukosis virus subgroup J(ALV-J)positive,and sample 3 was positive for ALV-J and Marek's disease virus(MDV),which preliminarily determined that the breeder died of ALV-J infection or ALV-J and MDV mixed infection.Among them,the ALV-J gp85 gene had the highest nucleotide homology with the reference strain of ALV-J,ranging from 87.70％to 99.30％,and was in the same branch with the reference strain of subgroup J.Amino acid homology ranged from 78.00％to 96.20％,with some mutations.The nucleotide homology between the MDV meq gene and the vv+strain was the highest,which was 98.00％-99.00％,and they were in the same branch.The homology of amino acids was 95.90％-98.20％,and there were multiple mutation sites,among which the 176th amino acid destroyed the original Pro repeat of the virus MDV meq due to the mutation of Pro to Arg or Ala,which may lead to the enhancement of its virulence.This study will provide a reference for the prevention and control of neoplastic diseases in breeders in this region.

Objective To investigate serum metabolites and metabolic pathways alterations in patients with ischemic stroke(IS)through metabolomic analysis,and to identify reliable serum metabolic biomarkers for IS diagnosis.Methods This prospective study enrolled patients with IS admitted to the Department of Neurology at Xiangcheng People's Hospital of Suzhou from December 1,2022 to December 31,2023.Age-and sex-matched healthy individuals were recruited as controls during the same period.Baseline characteristics were collected,including age,sex,height,body mass index,and blood pressure.Venous blood samples were obtained after an 8 h fast for biochemical analysis of blood glucose,total bilirubin,serum creatinine,urea nitrogen,total cholesterol,triglycerides,high-density lipoprotein cholesterol,and low-density lipoprotein cholesterol.Serum metabolites of both groups were extracted and analyzed using ultra-high-performance liquid chromatography coupled with tandem mass spectrometry.Metabolomic data were processed using Simca-p software for unsupervised principal component analysis(PCA)and orthogonal partial least squares discriminant analysis(OPLS-DA)to evaluate group separation and experimental stability.Differential metabolites were defined by variable importance in projection(VIP)≥1.0,fold change(FC)≥2.0 or ≤0.5,and P＜0.05.Drug-derived exogenous metabolites were excluded by cross-referencing the Human Metabolome Database(HMDB,https://hmdb.ca/)and PubChem(https://pubchem.ncbi.nlm.nih.gov/).MetaboAnalyst 6.0(http://www.metaboanalyst.ca),a comprehensive web-based tool for metabolomic data analysis,was employed to map differential metabolites to the Kyoto encyclopedia of genes and genomes(KEGG)databased and to perform pathway enrichment analysis.Machine learning models were developed using Python.Least absolute shrinkage and selection operator(LASSO)regression and random forest(RF)algorithms were employed to identify diagnostic biomarkers capable of effectively distinguishing IS patients from controls.Metabolites identified by both methods were integrated into an extreme gradient boosting(XGBoost)model.Model performance was evaluated using receiver operating characteristic(ROC)curves with 5-fold cross-validation and internal validation(70％training,30％validation set).Results A total of 51 IS patients and 51 matched controls were included.(1)A total of 1 255 serum metabolites were identified(964 in positive ion mode,291 in negative ion mode).PC A and OPLS-DA demonstrated distinct metabolic separation between IS patients and controls.In IS group,260 metabolites were upregulated and 337 downregulated in positive ion mode;99 were upregulated and 34downregulated in negative ion mode.(2)Among the 1 255 metabolites,259 were identified as differential metabolites based on the criteria of VIP ≥ 1.0,FC≥2.0 or≤0.5 and P＜0.05.After excluding drug-derived metabolite through referencing HMDB and PubChem databases,a total of 220 endogenous differential metabolites were found to coexist in both positive and negative ion modes.Among them,119 metabolites were up-regulated and 101 were down-regulated in the IS group.The expression of these 220 metabolites showed significant differences between the IS and control groups.(3)KEGG pathway analysis highlighted five dysregulated pathways:upregulation of denovo triacylglycerol biosynthesis,glycerophosphate shuttle,and cardiolipin biosynthesis;downregulation of bile acid biosynthesis and methylhistidine metabolism.(4)LASSO and RF algorithms identified 24 and 30 candidate biomarkers,respectively.Four overlapping metabolites were selected:2-((3R)-3-((3R,5S,7S,9S,10S,13R,14S,17R)-3,7-dihydroxy-10,13-dimethylhexadecahydro-1H-cyclopenta[a]phenanthren-17-yl)butanamido)ethane-1-sulfonic acid(m/z 971.571 29),arginine-conjugated cholic acid(m/z 587.379 21),laccaic acid A(m/z 576.010 93)and NCGC00380235-01_C32H48O9_beta-D-xylopyranoside,3,17-dihydroxyspirosta-5,25(27)-dien-1-yl(m/z 559.326 48).The expression levels of 2-((3R)-3-((3R,5S,7S,9S,10S,13R,14S,17R)-3,7-dihydroxy-10,13-dimethylhexadecahydro-1H-cyclopenta[a]phenanthren-17-yl)butanamido)ethane-1-sulfonic acid(m/z 971.571 29),arginine-conjugated cholic acid(m/z 587.379 21),and laccaic acid A(m/z 576.010 93)were upregulated,while the expression level of NCGC00380235-01_C32H48O9_beta-D-xylopyranoside,3,17-dihydroxyspirosta-5,25(27)-dien-1-yl(m/z 559.326 48)was downregulated.An IS diagnostic model was established based on four metabolic biomarkers using the XGBoost algorithm.The area under the ROC curve was 1.000(95％CI 1.000-1.000)in the training set and 0.988 in the validation set(95％CI 0.963-1.000).Conclusions Patients with IS exhibit significant metabolic disturbance.The four identified biomarkers may serve as potential biomarkers for the effective identification of IS:2-((3 R)-3-((3R,5S,7S,9S,10S,13R,14S,17R)-3,7-dihydroxy-10,13-dimethylhexadecahydro-1H-cyclopenta[a]phenanthren-17-yl)butanamido)ethane-1-sulfonic acid(m/z971.571 29),arginine-conjugated cholic acid(m/z587.379 21),laccaic acid A(m/z 576.010 93),and NCGC00380235-01_C32H48O9_beta-D-xylopyranoside,3,17-dihydroxyspirosta-5,25(27)-dien-1-yl(m/z 559.326 48).

OBJECTIVE To explore the effect of hydrogen peroxide disinfectant on terminal disinfection in wards of medical institutions.METHODS The surfaces of highly frequent contact objects of the wards of the First Affilia-ted Hospital of Nanchang University from which the public health center patients were discharged between Apr.2024 and Jun.2024 were respectively disinfected with 0.5％(low)and 5％(high)concentrations of hydrogen peroxide disinfecting wipes,totally 180 samples were randomly collected before and after the disinfection,and the pathogens were detected.The air of the wards from which the public health center patients were discharged be-tween Jul.2024 and Aug.2024 were disinfected with hydrogen peroxide dry mist disinfection device,and 90 sam-ples were respectively collected before and after the disinfection.Geobacillus stearothermophilus was used as the biological indicator and placed at various points within the air-disinfected wards to evaluate the disinfection level.The environmental sampling results and distribution of bacteria were observed and compared.RESULTS The qualified rates of disinfection of the object surfaces were 95.56％(86/90)and 98.89％(89/90)respectively for the low and high concentratioins of hydrogen peroxide disinfecting wipes,and there was no significant difference in the disinfection effect.Totally 120 strains of pathogens were isolated from unqualified samples before the disinfection,among which gram-negative bacteria(69.17％)were dominant,and the isolation rate of multidrug-resistant or-ganisms was 22.50％(27/120);only 1 strain of carbapenem-resistant Acinetobacter baumannii was isolated after the disinfection.The qualified rate of disinfection of air in the wards was 96.00％by 7.5％hydrogen peroxide dry mist disinfection device,the average bacterial colony counts in the air were 2 CFU/(5 min·vsl)after the dis-infection,and the killing rate of Geobacillus stearothermophilus was 100.00％by the air disinfection.CONCLUSION The hydrogen peroxide disinfectant can meet the requirement for terminal disinfection of the wards of the medical institutions,and it is portable and highly efficient.

Objective:To evaluate the value of metagenomic Next Generation Sequencing (mNGS) for the pathogenetic diagnosis of bloodstream infections in patients with sepsis.Methods:A retrospective analysis was performed on 105 sepsis cases who received blood mNGS and blood culture tests during their hospitalization in the Intensive Care Department of the Affiliated Hospital of North Sichuan Medical College from September 2021 to August 2023, and the results were compared and analyzed. According to mNGS and blood culture results, the cases were divided into the positive group and negative group.The distribution of pathogens in the enrolled patients were analyzed, and the diagnostic performance and consistency of blood culture and mNGS were compared. The differences in clinical characteristics of patients in each group were analyzed, and the pathogenic diagnostic value of mNGS for bloodstream infections in patients with sepsis was evaluated.Results:①Among 105 blood samples, 61 cases (58.10%) had positive results of mNGS, and 32 cases (30.48%) had positive results of blood culture. The positive rate of mNGS was higher than that of blood culture, and the difference was statistically significant ( P < 0.05).The accuracy of mNGS was lower than that of blood culture②The mean values of ESR, PCT and CRP in positive group were higher than those in negative group, and the proportion of septic shock was higher than that in negative group, and the differences were statistically significant ( P < 0.05). There was no significant difference in 28-day mortality rate between the two groups ( P > 0.05). Conclusions:mNGS is beneficial to the etiological diagnosis and treatment of bloodstream infection in patients with sepsis.

Preeclampsia (PE), a multisystem disorder in pregnancy, is one of the leading causes of perinatal morbidity and mortality that poses financial and physical burdens worldwide. Preterm PE with delivery at <37 weeks of gestation is associated with a higher risk of adverse maternal and perinatal outcomes than term PE with delivery at ≥37 weeks of gestation. A myriad of first trimester screening models have been developed to identifying women at risk of preterm PE. In fact, the Fetal Medicine Foundation (FMF) first trimester prediction model has undergone successful internal and external validation. The FMF triple test enables the estimation of patient-specific risks, using Bayes theorem to combine maternal characteristics and medical history together with measurements of mean arterial pressure, uterine artery pulsatility index, and serum placental growth factor. Establishing a quality control process for regular monitoring and to ensure data standardization, reliability, and accuracy is key to maintaining optimal screening performance. The rate of preterm PE can be reduced by 62% by using the FMF prediction model, followed by the administration of low-dose aspirin. Recent evidence has also demonstrated that metformin has the potential for preventing PE in patients at high-risk of the disorder. In this article, we will summarize the existing literature on the different screening methods, different components of risk assessment, therapeutic interventions, and clinical implementation of the first trimester screening and prevention program for PE with specific considerations for Chinese mainland.

Preeclampsia (PE), a multisystem disorder in pregnancy, is one of the leading causes of perinatal morbidity and mortality that poses financial and physical burdens worldwide. Preterm PE with delivery at <37 weeks of gestation is associated with a higher risk of adverse maternal and perinatal outcomes than term PE with delivery at ≥37 weeks of gestation. A myriad of first trimester screening models have been developed to identifying women at risk of preterm PE. In fact, the Fetal Medicine Foundation (FMF) first trimester prediction model has undergone successful internal and external validation. The FMF triple test enables the estimation of patient-specific risks, using Bayes theorem to combine maternal characteristics and medical history together with measurements of mean arterial pressure, uterine artery pulsatility index, and serum placental growth factor. Establishing a quality control process for regular monitoring and to ensure data standardization, reliability, and accuracy is key to maintaining optimal screening performance. The rate of preterm PE can be reduced by 62% by using the FMF prediction model, followed by the administration of low-dose aspirin. Recent evidence has also demonstrated that metformin has the potential for preventing PE in patients at high-risk of the disorder. In this article, we will summarize the existing literature on the different screening methods, different components of risk assessment, therapeutic interventions, and clinical implementation of the first trimester screening and prevention program for PE with specific considerations for Chinese mainland.