Objectives:To discuss the inhibitory effect of Lactobacillus reuteri on the replication of rotavirus(RV)strain SA11 in vivo and in vitro,and to clarify its effect on the expression of related immune factors.Methods:For in vitro experiments,Lactobacillus reuteri was cultured and identified,and the standard curve and growth curve were plotted to screen the optimal time and concentration for Lactobacillus reuteri cultivation.The cells were infected with Lactobacillus reuteri at the concentrations of 5×108,10×108,50×108,100×108,200×108,and 500×108 CFU·mL-1,and the surival rates of Caco-2 cells were detected by trypan blue staining method.Various concentrations of Lactobacillus reuteri were co-incubated with RV in vitro and applied to the Caco-2 cells.The cells were divided into negative control group(NC group),positive control group(PC group),and 107,108,109,and 1010 CFU·mL-1 Lactobacillus reuteri groups.Immunofluorescence focus method was used to detect the viral titers in the Caco-2 cells after treated with Lactobacillus reuteri and real-time fluorescence quantitative PCR(RT-qPCR)method was used to detect the copy numbers of RV VP6 gene in the Caco-2 cells after treated with various concentrations of Lactobacillus reuteri.In in vivo experiments,25 litters of SPF suckling mice were divided into control group,RV group(infected with SA11 strain),Ab-NC group(treated with antibiotic to deplete gut microbiota),Ab-RV group(depleting gut microbiota and then infected with SA11 strain),and Ab-Lac-RV group(depleting gut microbiota,treated with Lactobacillus reuteri,and then infected with SA11 strain).The fecal samples were collected on days 2,4,6,8,and 10 gavage,colon tissue sample were collected on day 4 of and RT-qPCR method was used to detect the copy numbers of RV VP6 gene in feces and the mRNA expression levels of interleukin(IL)-1β,IL-8,IL-10,interferon-γ(IFN-γ),and tumor necrosis factor-α(TNF-α)in colon tissue of the suckling mice in vartious groups.Results:The Lactobacillus reuteri grew well,with round,smooth,and milky white convex colonies and neat edges.After Gram staining,the bacteria appeared purple,irregular,and square-shaped rods.16SrDNA sequencing showed 99%sequence homology,indicating successful activation of Lactobacillus reuteri.The number of live Lactobacillus reuteri was linearly related to the absorbance(A)value,and the standard curve for regression analysis was Y=0.437 5X+0.000 6,R2=0.999 4.During the 0-2 h cultivation period,the bacteria were at the logarithmic growth phase with slow growth;from 2-14 h,the bacteria grew rapidly and stabilized at 14-16 h,reaching the growth rate peak at 16 h,after which they entered the decline phase.Infection with Lactobacillus reuteri at concentrations of 5×108,10×108,50×108,100×108,and 200×108 CFU·mL-1 resulted in the survival rates of Caco-2 cells were all>90%,so these concentrations were selected for the further experiments.Compared with PC group,the copy numbers of RV VP6 gene in the Caco-2 cells in 5×108,10×108,50×108,100×108,and 200×108 CFU·mL-1 Lactobacillus reuteri groups were significantly decreased(P<0.01).Compared with PC group,the viral titers in the Caco-2 cells in 107,108,109,and 1010 CFU·mL-1 Lactobacillus reuteri groups were significantly decreased(P<0.01).Compared with control group,the numbers of gut microbiota colonies in Ab-NC,Ab-RV,and Ab-Lac-RV groups were significantly decreased,indicating successful depletion of gut microbiota in the suckling mice.On days 2 and 4 after gavage,the RV VP6 gene copy number in the feces in Ab-RV group was significantly lower than that in RV group(P<0.05).On days 4,6,8,and 10 after gavage,the RV VP6 gene copy number in the feces in Ab-Lac-RV group was significantly lower than that in Ab-RV group(P<0.05).Compared with control group,the expression levels of IL-1β,IL-10,IFN-γ,and TNF-α mRNA in colon tissue in Ab-RV and Ab-Lac-RV groups were significantly increased(P<0.05 or P<0.01),while the expression level of IL-8 mRNA was significantly decreased(P<0.05),and the expression level of IL-10 mRNA in colon tissue in Ab-LAC-RV group was significantly increased(P<0.01).Conclusion:Lactobacillus reuteri may inhibit the RV replication by upregulating the expressions of IL-1β,IL-10,IFN-γ,and TNF-α mRNA and downregulating the expression of IL-8 mRNA.

Objective:To analyze the genetic characteristics of the complete genome of a strain of human respiratory syncytial virus (HRSV) in Qinghai province in 2024.Methods:A total of 300 samples were collected during 2024 influenza surveillance in Qinghai province sentinel hospitals from patients with fever accompanied by severe respiratory infection symptoms. We used real-time fluorescent quantitative reverse transcription polymerase chain reaction RT-PCR) method to screen out HRSV subtype B (HRSVB) positive specimens, whole genome sequencing was performed on positivespecimens meeting the requirements for the sequencing. After downloading the global representative HRSVB genotypes at GenBank database, sequence alignment was performed, related evolutionary tree was built and the calculation and analyses of genetic distance were done, analyses of HRSVB sequencing of sequence homology of nucleotides, amino acids and amino acid mutation were performed.Results:The first strain in Qinghai, China/qinghai/2024-03 had a complete sequence of 15 140 bp nucleotides, with HRSV′s all structural characteristics, and subtype HRSVA prototype strain Long strains of nucleotide the lowest homology was 80.0%, and subtype HRSVB prototype strain nucleotide homology was above 94.7%. The result indicated that the first strain in Qinghai belonged to HRSVB subtype. Genetic evolution shows China/qinghai/2024-03 and USA/WA-S23450/2021 (OR326803.1) and Germany/2021 (OR795235.1) all belong to a branch, they have the closest relationship. Phylogenetic analysis of G gene showed that the strain belonged to BA9 genotype of HRSVB subtype, and the hypervariable regions of the genome were SH and G genes.Conclusions:In this study, the complete genome sequence of HRSV China/qinghai/2024-03 was obtained for the first time, and the basic molecular structural characteristics were elucidated, which filled the gaps in the gene and amino acid data of HRSV in our province, and also provided a basis for HRSV epidemiology.

As the foremost among the four examinations in traditional Chinese medicine （TCM）， inspection and related equipment research face challenges in landing and transformation due to variations in evidence quality， lack of standardization， insufficient algorithm transparency， and poor reliability and stability of decision-making. Against the backdrop of rapid development of emerging technologies such as big data， the internet of things， and artificial intelligence， coupled with macro policy support from the government， digital and intelligent generalized inspection in TCM has emerged， with the aim of utilizing digital technologies to overcome the limitations of naked-eye inspection and comprehensively perceive and analyze facial and bodily expressions. The research in this field intelligently correlates Zang-fu organ functions with health conditions and disease progression and establishes a technical system for digital and intelligent inspection， multi-dimensional and multimodal perception， fusion analysis， and decision-making. This system aims to enhance the accuracy of disease risk warning and diagnosis， bridging the gap between inspection equipment and assistance in clinical decision-making. From an evidence-based perspective， this paper systematically examines the research ideas of digital and intelligent inspection and the development of related equipment， deeply explores how to propose clinical practice-oriented key scientific issues， comprehensively acquire and co-apply multi-dimensional data， establish precise inspection models driven by digital intelligence， optimize standards to enhance equipment interoperability and reliability， construct post-effect evaluation mechanisms to promote improvement， and actively address potential risks such as the black box nature and information security in the application of intelligent technology. This paper not only demonstrates the tremendous potential of digital technologies in improving the accuracy and clinical application efficiency of inspection but also provides new perspectives and ideas for the modernization of inspection in TCM， paving the way for the application of inspection in the global medical and health field.

Objective To discuss the clinical efficacy of absolute ethanol and foam hardening agent in the treatment of large venous malformations(VM)in child patients.Methods The clinical data of a total of 60 child patients with solitary large VM were retrospectively analyzed.The child patients were divided into group A(n=30)and group B(n=30).Patients in group A received absolute ethanol injection followed by foam hardening agent injection,while patients in group B received foam hardening agent injection followed by absolute ethanol injection.The clinical efficacy,complications,mean number of injections and mean dosage of absolute ethanol were compared between the two groups.Results The total effective rate in both group A and group B was 100%.The markedly effective rate in group A and group B was 63.33%(19/30)and 90%(27/30)respectively,and the difference was statistically significant(P＜0.05).In group A and group B,the mean dosage of absolute ethanol was(10.30±3.19)mL and(6.73±2.06)mL respectively,the mean number of injection was(3.57±1.01)times and(2.63±0.61)times respectively,and the differences in the above two indexes were statistically significant(both P＜0.05).No serious complications occurred in either group.The incidence of blisters in group A and group B was 30%(9/30)and 6.67%(2/30)respectively,and the difference was statistically significant(P＜0.05).Conclusion For large VM in child patients,combination use of absolute ethanol and foam hardening agent can improve the curative efficacy,reduce the dosage of absolute ethanol,and lower the incidence of complications.In addition,the therapeutic mode of foam hardening agent injection followed by absolute ethanol injection can achieve better efficacy.(J Intervent Radiol,2024,32:28-32)

Objective:To predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer based on preoperative inflammatory and immune nutritional indicators,and to construct a nomo-gram prediction model,providing a basis and tool for preoperative diagnosis of lymph node metastasis in cervical cancer.Methods:A retrospective analysis was conducted on the clinical data of 307 patients preoperatively diag-nosed with early-stage cervical cancer who underwent surgical treatment at the Obstetrics and Gynecology De-partment of the Second Affiliated Hospital of Zhengzhou University from January 2018 to July 2023.R software was used to randomize the groups into a training set(n=231)and a validation set(n=76)in a 3∶1 ratio.Uni-variate and multivariate logistic regression analyses were employed to identify factors influencing lymph node me-tastasis in patients preoperatively diagnosed with early-stage cervical cancer.R software was used to establish a nomogram prediction model and draw receiver operating characteristic(ROC)curves and calibration curves for validation.Results:① The results of univariate logistic regression analysis showed that positive lymphovascular invasion,platelet-to-lymphocyte ratio(PLR)≥151.70,neutrophil-to-white blood cell ratio(NWR)≥0.65,plate-let-to-albumin ratio(PAR)≥ 4.94,preoperative systemic immune-inflammation index(SII)≥604.03,and sys-temic inflammatory response index(SIRI)≥ 1.05 were associated with lymph node metastasis(P＜0.05).②Multivariate logistic regression analysis found that positive lymphovascular invasion,NWR≥0.65,and PAR≥4.94 were independent risk factors for lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer(OR＞1,P＜0.05).③ A nomogram was constructed to predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer.The ROC curve shows an area under the train-ing set curve(AUC)of 0.821 and a validation set AUC of 0.858.The calibration curve shows an average abso-lute error of 0.024 for the training set and 0.059 for the validation set.Conclusions:The prediction model for lymph node metastasis in cervical cancer constructed using preoperative inflammatory and immune nutritional indi-cators such as NWR,PAR is helpful for gynecological oncologists to predict lymph node metastasis in cervical cancer patients before surgery.

Objective:To predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer based on preoperative inflammatory and immune nutritional indicators,and to construct a nomo-gram prediction model,providing a basis and tool for preoperative diagnosis of lymph node metastasis in cervical cancer.Methods:A retrospective analysis was conducted on the clinical data of 307 patients preoperatively diag-nosed with early-stage cervical cancer who underwent surgical treatment at the Obstetrics and Gynecology De-partment of the Second Affiliated Hospital of Zhengzhou University from January 2018 to July 2023.R software was used to randomize the groups into a training set(n=231)and a validation set(n=76)in a 3∶1 ratio.Uni-variate and multivariate logistic regression analyses were employed to identify factors influencing lymph node me-tastasis in patients preoperatively diagnosed with early-stage cervical cancer.R software was used to establish a nomogram prediction model and draw receiver operating characteristic(ROC)curves and calibration curves for validation.Results:① The results of univariate logistic regression analysis showed that positive lymphovascular invasion,platelet-to-lymphocyte ratio(PLR)≥151.70,neutrophil-to-white blood cell ratio(NWR)≥0.65,plate-let-to-albumin ratio(PAR)≥ 4.94,preoperative systemic immune-inflammation index(SII)≥604.03,and sys-temic inflammatory response index(SIRI)≥ 1.05 were associated with lymph node metastasis(P＜0.05).②Multivariate logistic regression analysis found that positive lymphovascular invasion,NWR≥0.65,and PAR≥4.94 were independent risk factors for lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer(OR＞1,P＜0.05).③ A nomogram was constructed to predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer.The ROC curve shows an area under the train-ing set curve(AUC)of 0.821 and a validation set AUC of 0.858.The calibration curve shows an average abso-lute error of 0.024 for the training set and 0.059 for the validation set.Conclusions:The prediction model for lymph node metastasis in cervical cancer constructed using preoperative inflammatory and immune nutritional indi-cators such as NWR,PAR is helpful for gynecological oncologists to predict lymph node metastasis in cervical cancer patients before surgery.

Objective:To predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer based on preoperative inflammatory and immune nutritional indicators,and to construct a nomo-gram prediction model,providing a basis and tool for preoperative diagnosis of lymph node metastasis in cervical cancer.Methods:A retrospective analysis was conducted on the clinical data of 307 patients preoperatively diag-nosed with early-stage cervical cancer who underwent surgical treatment at the Obstetrics and Gynecology De-partment of the Second Affiliated Hospital of Zhengzhou University from January 2018 to July 2023.R software was used to randomize the groups into a training set(n=231)and a validation set(n=76)in a 3∶1 ratio.Uni-variate and multivariate logistic regression analyses were employed to identify factors influencing lymph node me-tastasis in patients preoperatively diagnosed with early-stage cervical cancer.R software was used to establish a nomogram prediction model and draw receiver operating characteristic(ROC)curves and calibration curves for validation.Results:① The results of univariate logistic regression analysis showed that positive lymphovascular invasion,platelet-to-lymphocyte ratio(PLR)≥151.70,neutrophil-to-white blood cell ratio(NWR)≥0.65,plate-let-to-albumin ratio(PAR)≥ 4.94,preoperative systemic immune-inflammation index(SII)≥604.03,and sys-temic inflammatory response index(SIRI)≥ 1.05 were associated with lymph node metastasis(P＜0.05).②Multivariate logistic regression analysis found that positive lymphovascular invasion,NWR≥0.65,and PAR≥4.94 were independent risk factors for lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer(OR＞1,P＜0.05).③ A nomogram was constructed to predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer.The ROC curve shows an area under the train-ing set curve(AUC)of 0.821 and a validation set AUC of 0.858.The calibration curve shows an average abso-lute error of 0.024 for the training set and 0.059 for the validation set.Conclusions:The prediction model for lymph node metastasis in cervical cancer constructed using preoperative inflammatory and immune nutritional indi-cators such as NWR,PAR is helpful for gynecological oncologists to predict lymph node metastasis in cervical cancer patients before surgery.

Objective:To predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer based on preoperative inflammatory and immune nutritional indicators,and to construct a nomo-gram prediction model,providing a basis and tool for preoperative diagnosis of lymph node metastasis in cervical cancer.Methods:A retrospective analysis was conducted on the clinical data of 307 patients preoperatively diag-nosed with early-stage cervical cancer who underwent surgical treatment at the Obstetrics and Gynecology De-partment of the Second Affiliated Hospital of Zhengzhou University from January 2018 to July 2023.R software was used to randomize the groups into a training set(n=231)and a validation set(n=76)in a 3∶1 ratio.Uni-variate and multivariate logistic regression analyses were employed to identify factors influencing lymph node me-tastasis in patients preoperatively diagnosed with early-stage cervical cancer.R software was used to establish a nomogram prediction model and draw receiver operating characteristic(ROC)curves and calibration curves for validation.Results:① The results of univariate logistic regression analysis showed that positive lymphovascular invasion,platelet-to-lymphocyte ratio(PLR)≥151.70,neutrophil-to-white blood cell ratio(NWR)≥0.65,plate-let-to-albumin ratio(PAR)≥ 4.94,preoperative systemic immune-inflammation index(SII)≥604.03,and sys-temic inflammatory response index(SIRI)≥ 1.05 were associated with lymph node metastasis(P＜0.05).②Multivariate logistic regression analysis found that positive lymphovascular invasion,NWR≥0.65,and PAR≥4.94 were independent risk factors for lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer(OR＞1,P＜0.05).③ A nomogram was constructed to predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer.The ROC curve shows an area under the train-ing set curve(AUC)of 0.821 and a validation set AUC of 0.858.The calibration curve shows an average abso-lute error of 0.024 for the training set and 0.059 for the validation set.Conclusions:The prediction model for lymph node metastasis in cervical cancer constructed using preoperative inflammatory and immune nutritional indi-cators such as NWR,PAR is helpful for gynecological oncologists to predict lymph node metastasis in cervical cancer patients before surgery.

Objective:To predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer based on preoperative inflammatory and immune nutritional indicators,and to construct a nomo-gram prediction model,providing a basis and tool for preoperative diagnosis of lymph node metastasis in cervical cancer.Methods:A retrospective analysis was conducted on the clinical data of 307 patients preoperatively diag-nosed with early-stage cervical cancer who underwent surgical treatment at the Obstetrics and Gynecology De-partment of the Second Affiliated Hospital of Zhengzhou University from January 2018 to July 2023.R software was used to randomize the groups into a training set(n=231)and a validation set(n=76)in a 3∶1 ratio.Uni-variate and multivariate logistic regression analyses were employed to identify factors influencing lymph node me-tastasis in patients preoperatively diagnosed with early-stage cervical cancer.R software was used to establish a nomogram prediction model and draw receiver operating characteristic(ROC)curves and calibration curves for validation.Results:① The results of univariate logistic regression analysis showed that positive lymphovascular invasion,platelet-to-lymphocyte ratio(PLR)≥151.70,neutrophil-to-white blood cell ratio(NWR)≥0.65,plate-let-to-albumin ratio(PAR)≥ 4.94,preoperative systemic immune-inflammation index(SII)≥604.03,and sys-temic inflammatory response index(SIRI)≥ 1.05 were associated with lymph node metastasis(P＜0.05).②Multivariate logistic regression analysis found that positive lymphovascular invasion,NWR≥0.65,and PAR≥4.94 were independent risk factors for lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer(OR＞1,P＜0.05).③ A nomogram was constructed to predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer.The ROC curve shows an area under the train-ing set curve(AUC)of 0.821 and a validation set AUC of 0.858.The calibration curve shows an average abso-lute error of 0.024 for the training set and 0.059 for the validation set.Conclusions:The prediction model for lymph node metastasis in cervical cancer constructed using preoperative inflammatory and immune nutritional indi-cators such as NWR,PAR is helpful for gynecological oncologists to predict lymph node metastasis in cervical cancer patients before surgery.

Objective:To predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer based on preoperative inflammatory and immune nutritional indicators,and to construct a nomo-gram prediction model,providing a basis and tool for preoperative diagnosis of lymph node metastasis in cervical cancer.Methods:A retrospective analysis was conducted on the clinical data of 307 patients preoperatively diag-nosed with early-stage cervical cancer who underwent surgical treatment at the Obstetrics and Gynecology De-partment of the Second Affiliated Hospital of Zhengzhou University from January 2018 to July 2023.R software was used to randomize the groups into a training set(n=231)and a validation set(n=76)in a 3∶1 ratio.Uni-variate and multivariate logistic regression analyses were employed to identify factors influencing lymph node me-tastasis in patients preoperatively diagnosed with early-stage cervical cancer.R software was used to establish a nomogram prediction model and draw receiver operating characteristic(ROC)curves and calibration curves for validation.Results:① The results of univariate logistic regression analysis showed that positive lymphovascular invasion,platelet-to-lymphocyte ratio(PLR)≥151.70,neutrophil-to-white blood cell ratio(NWR)≥0.65,plate-let-to-albumin ratio(PAR)≥ 4.94,preoperative systemic immune-inflammation index(SII)≥604.03,and sys-temic inflammatory response index(SIRI)≥ 1.05 were associated with lymph node metastasis(P＜0.05).②Multivariate logistic regression analysis found that positive lymphovascular invasion,NWR≥0.65,and PAR≥4.94 were independent risk factors for lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer(OR＞1,P＜0.05).③ A nomogram was constructed to predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer.The ROC curve shows an area under the train-ing set curve(AUC)of 0.821 and a validation set AUC of 0.858.The calibration curve shows an average abso-lute error of 0.024 for the training set and 0.059 for the validation set.Conclusions:The prediction model for lymph node metastasis in cervical cancer constructed using preoperative inflammatory and immune nutritional indi-cators such as NWR,PAR is helpful for gynecological oncologists to predict lymph node metastasis in cervical cancer patients before surgery.