OBJECTIVE: To analyze the Epstein-Barr virus (EBV) load in different lymphocyte subsets, as well as clinical characteristics and outcomes in patients with hematologic malignancies experiencing EBV reactivation. METHODS: Peripheral blood samples from patients were collected. B, T, and NK cells were isolated sorting with magnetic beads by flow cytometry. The EBV load in each subset was quantitated by real-time quantitative polymerase chain reaction (RT-qPCR). Clinical data were colleted from electronic medical records. Survival status was followed up through outpatient visits and telephone calls. Statistical analyses were performed using SPSS 25.0. RESULTS: A total of 39 patients with hematologic malignancies were included, among whom 35 patients had undergone allogeneic hematopoietic stem cell transplantation (allo-HSCT). The median time to EBV reactivation was 4.8 months (range: 1.7-57.1 months) after allo-HSCT. EBV was detected in B, T, and NK cells in 20 patients, in B and T cells in 11 patients, and only in B cells in 4 patients. In the 35 patients, the median EBV load in B cells was 2.19×10⁴ copies/ml, significantly higher than that in T cells (4.00×10³ copies/ml, P <0.01) and NK cells (2.85×10² copies/ml, P <0.01). Rituximab (RTX) was administered for 32 patients, resulting in EBV negativity in 32 patients with a median time of 8 days (range: 2-39 days). Post-treatment analysis of 13 patients showed EBV were all negative in B, T, and NK cells. In the four non-transplant patients, the median time to EBV reactivation was 35 days (range: 1-328 days) after diagnosis of the primary disease. EBV was detected in one or two subsets of B, T, or NK cells, but not simultaneously in all three subsets. These patients received a combination chemotherapy targeting at the primary disease, with 3 patients achieving EBV negativity, and the median time to be negative was 40 days (range: 13-75 days). CONCLUSION In hematologic malignancy patients after allo-HSCT, EBV reactivation commonly involves B, T, and NK cells, with a significantly higher viral load in B cells compared to T and NK cells. Rituximab is effective for EBV clearance. In non-transplant patients, EBV reactivation is restricted to one or two lymphocyte subsets, and clearance is slower, highlighting the need for prompt anti-tumor therapy.
Humans ; Hematologic Neoplasms/virology* ; Herpesvirus 4, Human/physiology* ; Epstein-Barr Virus Infections ; Hematopoietic Stem Cell Transplantation ; Virus Activation ; Lymphocyte Subsets/virology* ; Flow Cytometry ; Killer Cells, Natural/virology* ; Male ; Female ; B-Lymphocytes/virology* ; Viral Load ; Adult ; T-Lymphocytes/virology* ; Middle Aged

This study was aimed at understanding the prevalence and drug resistance status of Salmonella of waterfowl ori-gin in the Guangdong region in the past decade,to guide prevention and control efforts.The drug-sensitive paper slide method was used to conduct drug susceptibility testing on 314 waterfowl-originating Salmonella strains isolated from 238 waterfowl farms in the Guangdong region from 2013 to 2023.The isolated Salmonella strains were most resistant to penicillin,amoxicil-lin,cefradine,and cefazolin in the β-lactam group;sulphadoxine dimethylpyrimidine in the sulphonamide group;and tetracy-cline in the tetracycline group.The resistance rates ranged from 73.57％to 89.49％.The highest sensitivity was observed to amikacin,gentamicin,and kanamycin in the aminoglycoside group,and norfloxacin in the quinolone group,with susceptibility rates all exceeding 50％.The 280 strains of Salmonella showed multi-drug resistance to six classes of antimicrobial drugs and high resistance(as much as 60.83％)to five drug classes.Correlation analysis revealed the highest correlations for florfenicol with gentamicin,and for amoxicillin with penicillin(r=0.650 for both),followed by gentamicin with kanamycin(r=0.620).Salmonella resistance in waterfowl in Guangdong Province was generally severe and showed a complex pattern of drug resist-ance.Detection of waterfowl pathogens should be strengthened to prevent the spread of drug-resistant bacteria and support ra-tional use of antibiotics.This work provides a reference for Salmonella prevention and control in waterfowl farms.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective:To construct a risk classification model for adverse events of medical consumables,so as to achieve automatic evaluation for risk level of such events,and enhance the capability for risk management of adverse events of medical consumables,and ensure the safety of medical apparatuses.Methods:The data of adverse events of medical consumables of 370 cases of 148 types that were reported by Shandong Provincial Third Hospital from 2020 to 2023 were selected,and they were divided into high-risk and low-risk types.Eight key factors of them,which included the number of cases,injury level,type of registration certificate,with source and without source,high-value and low-value,domestic and imports,product classification,and risk levels,were counted to form a dataset.K-nearest neighbor(KNN),support vector machine(SVM)and decision tree algorithms in machine learning were used to construct a risk classification model for adverse events of medical consumables.The data of 12 adverse events of medical consumables of 5 types of our hospital,which were newly reported in 2024,were integrated for their parameters.Then,the accuracy rate and prediction performance of the model were further analyzed.Results:By comparing the KNN,SVM and decision tree algorithm models,the effect of SVM algorithm model was better,and its accuracy rate was 90.54%,and its area under curve(AUC)value of the receiver operating characteristic(ROC)curve was 0.944,and its Kolmogorov-Smirnov(KS)test value was 0.808.The model had favorable predictive performance.The results,that invoked SVM algorithm model to conduct verification of actual prediction for 12 adverse events of medical consumables of 5 types,indicated it was same between predictive outcomes and risk levels of manual evaluation.Conclusion:The risk classification model of adverse events of medical consumables has established an operational model for assessing the risk level of such events,which can assist monitoring personnel for adverse event of medical apparatuses to quickly and accurately find risk signals of adverse events of medical consumables,and improve the monitoring capability of them for these adverse events.

Objective To evaluate the effects of fasting and high-fat diet on the pharmacokinetics of rabeprazole sodium enteric-coated tablets in healthy Chinese subjects.Methods A single-center,randomized,open,two-agent,two-sequence,four-cycle,fully repeated crossover,single-dose trial design was used in this study,healthy subjects were assigned to receive single dose of rabeprazole sodium enteric-coated tablets 0.1 g in either fasting or high-fat diet state,and blood samples were taken at different time points,respectively.The concentrations of rabeprazole sodium enteric-coated in plasma were determined by liquid chromatography-tandem mass spectrometry(LC-MS/MS),the model method of the non-compartmental was used to calculate the pharmacokinetic parameters by Phoenix WinNonlin 8.2.Results The main pharmacokinetic parameters of rabeprazole sodium enteric-coated tablets in fasting state and high-fat diet state were as follows:Cmax were(339.63±156.47)and(318.86±132.13)ng·mL-1;t1/2 were(2.34±0.68)and(3.60±2.40)h;AUC0_t were(556.62±251.65)and(528.50±201.78)ng·mL-1·h;AUC0-∞ were(563.39±255.69)and(535.15±203.24)ng·mL-1·h;tmax were 3.65 and 6.99 h.After high-fat diet,the Cmax and AUC of rapeprazole sodium after high-fat and high-calorie diet decreased,Cmax decreased by 6.12％,AUC0-t decreased by 5.05％,AUC0-∞ decreased by 5.01％,andtmaxwas delayed by about 3.34 h.Cmax,AUC0-t and AUC0-∞ 90％confidence interval were 73.13％-115.10％,83.22％-112.28％and 83.40％-112.13％,respectively.Neither was between 85.00％-125.00％.Conclusion High-fat diet affects the absorption rate and degree of rabeprazole sodium enteric-coated,so it is suitable to be administered on an empty stomach.

Objective:To explore the diagnostic value of shear wave elastography(SWE)for clinically significant prostate cancer(csPCa).Methods:We retrospectively analyzed the clinical data of 359 cases with suspected prostate cancer(PCa)in Baoji Central Hospital from June 2017 to July 2023.All the patients underwent the following examinations in the order of serum prostate-spe-cific antigen(PSA)testing,transrectal ultrasonography(TRUS),measurement of the stiffness of the entire prostate gland by SWE,and TRUS-guided prostate puncture biopsy.The stiffness of the entire prostate gland was defined as the average of Young's modulus at both sides of the base,middle,and apex of the prostate,including the maximum Young's modulus(Emax),mean Young's modulus(Emean),and minimum Young's modulus(Emin).We analyzed the correlation of the parameters of the stiffness of the entire prostate gland with the pathological results,focusing on their diagnostic performance for csPCa.Results:Of the 359 cases,189 were diag-nosed by pathological puncture biopsy as BPH,26 as non-csPCa,and 144 as csPCa.The PSA level,Emax,Emean and Emin were significantly higher in the csPCa than those in the BPH and non-csPCa groups(all P＜0.01),but showed no statistically significant difference between the BPH and non-csPCa groups(all P＞0.05).The area under the receiver operating characteristic curve(AUC),optimal cut-off value,sensitivity,specificity,positive predictive value(PPV),negative predictive value(NPV)and accura-cy of Emax in the diagnosis of csPCa were 0.852,143.92 kPa,72.22％,84.65％,75.91％,81.98％and 79.67％;those of Emean were 0.868,82.42 kPa,67.36％,91.16％,83.62％,80.66％and 81.62％;and those of Emin were 0.682,32.73 kPa,47.22％,89.30％,73.91％,71.54％and 72.14％,respectively.In the non-csPCa group,Emax,Emean and Emin were found be-low the optimal cut-off value in 73.08％(19/26),92.31％(24/26)and 88.46％(23/26),respectively.Conclusion:The stiff-ness of the entire prostate gland measured by SWE contributes to the diagnosis of csPCa,reduces unnecessary detection of non-csPCa,and provides some reference for its active surveillance.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

This study was aimed at understanding the prevalence and drug resistance status of Salmonella of waterfowl ori-gin in the Guangdong region in the past decade,to guide prevention and control efforts.The drug-sensitive paper slide method was used to conduct drug susceptibility testing on 314 waterfowl-originating Salmonella strains isolated from 238 waterfowl farms in the Guangdong region from 2013 to 2023.The isolated Salmonella strains were most resistant to penicillin,amoxicil-lin,cefradine,and cefazolin in the β-lactam group;sulphadoxine dimethylpyrimidine in the sulphonamide group;and tetracy-cline in the tetracycline group.The resistance rates ranged from 73.57％to 89.49％.The highest sensitivity was observed to amikacin,gentamicin,and kanamycin in the aminoglycoside group,and norfloxacin in the quinolone group,with susceptibility rates all exceeding 50％.The 280 strains of Salmonella showed multi-drug resistance to six classes of antimicrobial drugs and high resistance(as much as 60.83％)to five drug classes.Correlation analysis revealed the highest correlations for florfenicol with gentamicin,and for amoxicillin with penicillin(r=0.650 for both),followed by gentamicin with kanamycin(r=0.620).Salmonella resistance in waterfowl in Guangdong Province was generally severe and showed a complex pattern of drug resist-ance.Detection of waterfowl pathogens should be strengthened to prevent the spread of drug-resistant bacteria and support ra-tional use of antibiotics.This work provides a reference for Salmonella prevention and control in waterfowl farms.

Objective To evaluate the effects of fasting and high-fat diet on the pharmacokinetics of rabeprazole sodium enteric-coated tablets in healthy Chinese subjects.Methods A single-center,randomized,open,two-agent,two-sequence,four-cycle,fully repeated crossover,single-dose trial design was used in this study,healthy subjects were assigned to receive single dose of rabeprazole sodium enteric-coated tablets 0.1 g in either fasting or high-fat diet state,and blood samples were taken at different time points,respectively.The concentrations of rabeprazole sodium enteric-coated in plasma were determined by liquid chromatography-tandem mass spectrometry(LC-MS/MS),the model method of the non-compartmental was used to calculate the pharmacokinetic parameters by Phoenix WinNonlin 8.2.Results The main pharmacokinetic parameters of rabeprazole sodium enteric-coated tablets in fasting state and high-fat diet state were as follows:Cmax were(339.63±156.47)and(318.86±132.13)ng·mL-1;t1/2 were(2.34±0.68)and(3.60±2.40)h;AUC0_t were(556.62±251.65)and(528.50±201.78)ng·mL-1·h;AUC0-∞ were(563.39±255.69)and(535.15±203.24)ng·mL-1·h;tmax were 3.65 and 6.99 h.After high-fat diet,the Cmax and AUC of rapeprazole sodium after high-fat and high-calorie diet decreased,Cmax decreased by 6.12％,AUC0-t decreased by 5.05％,AUC0-∞ decreased by 5.01％,andtmaxwas delayed by about 3.34 h.Cmax,AUC0-t and AUC0-∞ 90％confidence interval were 73.13％-115.10％,83.22％-112.28％and 83.40％-112.13％,respectively.Neither was between 85.00％-125.00％.Conclusion High-fat diet affects the absorption rate and degree of rabeprazole sodium enteric-coated,so it is suitable to be administered on an empty stomach.

Objective:To construct a risk classification model for adverse events of medical consumables,so as to achieve automatic evaluation for risk level of such events,and enhance the capability for risk management of adverse events of medical consumables,and ensure the safety of medical apparatuses.Methods:The data of adverse events of medical consumables of 370 cases of 148 types that were reported by Shandong Provincial Third Hospital from 2020 to 2023 were selected,and they were divided into high-risk and low-risk types.Eight key factors of them,which included the number of cases,injury level,type of registration certificate,with source and without source,high-value and low-value,domestic and imports,product classification,and risk levels,were counted to form a dataset.K-nearest neighbor(KNN),support vector machine(SVM)and decision tree algorithms in machine learning were used to construct a risk classification model for adverse events of medical consumables.The data of 12 adverse events of medical consumables of 5 types of our hospital,which were newly reported in 2024,were integrated for their parameters.Then,the accuracy rate and prediction performance of the model were further analyzed.Results:By comparing the KNN,SVM and decision tree algorithm models,the effect of SVM algorithm model was better,and its accuracy rate was 90.54%,and its area under curve(AUC)value of the receiver operating characteristic(ROC)curve was 0.944,and its Kolmogorov-Smirnov(KS)test value was 0.808.The model had favorable predictive performance.The results,that invoked SVM algorithm model to conduct verification of actual prediction for 12 adverse events of medical consumables of 5 types,indicated it was same between predictive outcomes and risk levels of manual evaluation.Conclusion:The risk classification model of adverse events of medical consumables has established an operational model for assessing the risk level of such events,which can assist monitoring personnel for adverse event of medical apparatuses to quickly and accurately find risk signals of adverse events of medical consumables,and improve the monitoring capability of them for these adverse events.