ObjectiveTo analyze the phylogroups of Klebsiella pneumoniae isolates from laboratory rats and mice housed at the Laboratory Animal Center Fudan University, optimize the identification method for Klebsiella pneumoniae, and perform virulence genes detection and antimicrobial susceptibility testing, thereby providing a practical basis for microbial detection strategies and prevention and control measures in laboratory animal facilities. MethodsBetween September 2023 and September 2025, ileocecal contents were collected from laboratory rats and mice purchased from laboratory animal suppliers, from which 11 strains of Klebsiella pneumoniae were isolated and cryopreserved. These strains were tested for β-lactamase genes using multiplex PCR for phylogrouping. Furthermore, representative strains from different phylogroups were selected for biochemical tests, mass spectrometry analysis, 16S rRNA gene and tyrB gene sequencing, as well as virulence genes detection and antimicrobial susceptibility testing. ResultsMultiplex PCR detection of β-lactamase genes revealed that among 11 strains, 4 were identified as Klebsiella pneumoniae (Kp1), 4 as Klebsiella quasipneumoniae (Kp2), and 3 as Klebsiella variicola (Kp3). Kp1-Kp3 could not be differentiated using biochemical tests, mass spectrometry analysis, or 16S rRNA gene sequencing, whereas multiplex PCR of β-lactamase genes and tyrB gene sequencing enabled phylogrouping of all three. There were differences in the detection rates of capsular genes (capsule associated gene G and magnesium transport system ATP-binding protein A) and siderophore genes (Klebsiella pneumoniae iron uptake system genes) among Kp1-Kp3; susceptibility to different antibiotics also varied considerably. ConclusionKlebsiella pneumoniae phylogroups isolated from commercially produced laboratory rats and mice are similar to those in human clinical samples and likewise include multiple phylogroups of the species complex. In this study, the identification methods of Kp1-Kp3 were optimized,furthermore selected virulence genes and antimicrobial resistance in Kp1-Kp3 were preliminarily investigated, which could provide precise reference for the treatment of infections caused by different phylogroups occurring in laboratory animal facilities.

Objective To verify the accuracy of Youssef's formula and evaluate whether fetal biacromial diameter(BA)and other fetal biological diameters estimated by ultrasound can be used to predict macrosomia and shoulder dystocia,so as to provide the possibility for clinical prediction of shoulder dystocia.Methods A total of 200 pregnant women with a gestational period of 37-42 weeks were examined with ultrasound within 3 days before delivery for collecting biparietal diameter(BPD),head circumference(HC),abdominal circumference(AC),humerus length(HL),femur length(FL),thoracic transverse diameter and midpoint diameter of upper arm;and the fetal BA was estimated by Youssef's formula.Neonatal BA,body mass and body length were measured within 1 day after delivery.The above data were analyzed for correlation.Newborns were grouped according to their body mass(macrosomia vs non-macrosomia)and whether they had shoulder dystocia or not(shoulder dystocia vs non-shoulder dystocia).Results(1)The fetal BA estimated by Youssef's formula was consistent with neonatal BA(P>0.05),and the estimated BA was positively correlated with BPD,HC,AC and neonatal body mass(P<0.001).(2)The BA,BA/AC and BA/HC in macrosomia group were different from those in non-macrosomia group(P<0.05).ROC curve showed that the sensitivity and specificity were 92.3%and 88.2%for macrosomia prediction when the estimated BA threshold was 16.05 cm,and those were 61.5%and 77.0%when BA/AC threshold was 0.455,and 76.9%and 72.7%when BA/HC threshold was 0.465.(3)Shoulder dystocia group had neonatal weight close to non-shoulder dystocia group(P>0.05),but higher BA/BPD,BA/HC and BA-BPD(P<0.05).ROC curve showed that the sensitivity and specificity were 100.0%and 66.8%for shoulder dystocia when BA threshold was 15.45 cm,100.0%and 80.6%when BA/BPD threshold was 1.695,100.0%and 81.6%when BA/HC threshold was 0.475,and 100.0%and 76.0%when the threshold difference between BA and BPD was 6.35 cm.Conclusion Fetal BA,BA/BPD,BA/HC,BA/AC and BA-BPD may be effective predictors of shoulder dystocia and macrosomia.

To formulate an expert consensus on the principles of preoperative hair removal and provide scientific guidance for standardized removal of hair before surgical procedures so as to reduce the incidence of surgical site infections.METHODS Led by the Hospital Management Institute of National Health Commission of the People's Republic of China,this consensus was reached with the joint efforts from the expects of relevant fields such as surgeries,interventional therapies,nursing,and infection prevention and control.The consensus facilitates the classification and evaluation of literatures by following the evidence grade formulated by Oxford Evidence-based Medicine Center and focuses on the association of preoperative hair removal with surgical site infection,it reaches the evidence grade of expert consensus and recommendation intensity by integrating with discussions on meetings and clinical experience of the expects from relevant fields.RESULTS A total of 6 items of consensus were reached by summarizing the latest evidence on the aspects including the indications for preoperative hair removal,tools,range,timing and places.CONCLUSION The consensus,to some extent,make supplements to and complete the exiting regulations and standards.It provides guidance for the medical institutions to carry out the preoperative hair removal.

To formulate an expert consensus on the principles of preoperative hair removal and provide scientific guidance for standardized removal of hair before surgical procedures so as to reduce the incidence of surgical site infections.METHODS Led by the Hospital Management Institute of National Health Commission of the People's Republic of China,this consensus was reached with the joint efforts from the expects of relevant fields such as surgeries,interventional therapies,nursing,and infection prevention and control.The consensus facilitates the classification and evaluation of literatures by following the evidence grade formulated by Oxford Evidence-based Medicine Center and focuses on the association of preoperative hair removal with surgical site infection,it reaches the evidence grade of expert consensus and recommendation intensity by integrating with discussions on meetings and clinical experience of the expects from relevant fields.RESULTS A total of 6 items of consensus were reached by summarizing the latest evidence on the aspects including the indications for preoperative hair removal,tools,range,timing and places.CONCLUSION The consensus,to some extent,make supplements to and complete the exiting regulations and standards.It provides guidance for the medical institutions to carry out the preoperative hair removal.

Osteoarthritis (OA) is one of the most prevalent joint disorders, with aging considered a primary, irreversible factor contributing to its progression. Telomere-related cellular senescence may be a crucial factor influencing the OA process, yet biomarkers for OA based on telomere-related genes have not been clearly identified. The datasets GSE51588, GSE12021, and GSE55457 were retrieved from the Gene Expression Omnibus database. Initially, R software was utilized to identify differentially expressed genes between OA and normal samples. Subsequently, differentially expressed telomere-related genes (DETMRGs) were obtained, and their functional enrichment was analyzed. Feature genes for OA diagnosis were selected from DETMRGs using a combination of least absolute shrinkage and selection operator, support vector machine-recursive feature elimination, and Random Forest algorithms. The diagnostic value of these feature genes was then validated through receiver operating characteristic (ROC) curves and decision curve analysis. Additionally, CIBERSORT and xCell were employed to assess the infiltration of immune cells in OA tissues.Finally, potential drugs targeting candidate genes were predicted. Three telomererelated genes, PGD, SLC7A5, and TKT, have been identified as biomarkers for OA diagnosis and were confirmed through ROC diagnostic tests. The immune infiltration of mast cells, neutrophils, common lymphoid precursors, and eosinophils associated with PGD, SLC7A5, and TKT was reduced. Recognizing telomere-related genes PGD, SLC7A5, and TKT as potential diagnostic biomarkers for OA is significant, as it offers valuable insights into the role of telomere-related genes in OA. This discovery also provides valuable information for the diagnosis and treatment of OA.

Osteoarthritis (OA) is one of the most prevalent joint disorders, with aging considered a primary, irreversible factor contributing to its progression. Telomere-related cellular senescence may be a crucial factor influencing the OA process, yet biomarkers for OA based on telomere-related genes have not been clearly identified. The datasets GSE51588, GSE12021, and GSE55457 were retrieved from the Gene Expression Omnibus database. Initially, R software was utilized to identify differentially expressed genes between OA and normal samples. Subsequently, differentially expressed telomere-related genes (DETMRGs) were obtained, and their functional enrichment was analyzed. Feature genes for OA diagnosis were selected from DETMRGs using a combination of least absolute shrinkage and selection operator, support vector machine-recursive feature elimination, and Random Forest algorithms. The diagnostic value of these feature genes was then validated through receiver operating characteristic (ROC) curves and decision curve analysis. Additionally, CIBERSORT and xCell were employed to assess the infiltration of immune cells in OA tissues.Finally, potential drugs targeting candidate genes were predicted. Three telomererelated genes, PGD, SLC7A5, and TKT, have been identified as biomarkers for OA diagnosis and were confirmed through ROC diagnostic tests. The immune infiltration of mast cells, neutrophils, common lymphoid precursors, and eosinophils associated with PGD, SLC7A5, and TKT was reduced. Recognizing telomere-related genes PGD, SLC7A5, and TKT as potential diagnostic biomarkers for OA is significant, as it offers valuable insights into the role of telomere-related genes in OA. This discovery also provides valuable information for the diagnosis and treatment of OA.

Osteoarthritis (OA) is one of the most prevalent joint disorders, with aging considered a primary, irreversible factor contributing to its progression. Telomere-related cellular senescence may be a crucial factor influencing the OA process, yet biomarkers for OA based on telomere-related genes have not been clearly identified. The datasets GSE51588, GSE12021, and GSE55457 were retrieved from the Gene Expression Omnibus database. Initially, R software was utilized to identify differentially expressed genes between OA and normal samples. Subsequently, differentially expressed telomere-related genes (DETMRGs) were obtained, and their functional enrichment was analyzed. Feature genes for OA diagnosis were selected from DETMRGs using a combination of least absolute shrinkage and selection operator, support vector machine-recursive feature elimination, and Random Forest algorithms. The diagnostic value of these feature genes was then validated through receiver operating characteristic (ROC) curves and decision curve analysis. Additionally, CIBERSORT and xCell were employed to assess the infiltration of immune cells in OA tissues.Finally, potential drugs targeting candidate genes were predicted. Three telomererelated genes, PGD, SLC7A5, and TKT, have been identified as biomarkers for OA diagnosis and were confirmed through ROC diagnostic tests. The immune infiltration of mast cells, neutrophils, common lymphoid precursors, and eosinophils associated with PGD, SLC7A5, and TKT was reduced. Recognizing telomere-related genes PGD, SLC7A5, and TKT as potential diagnostic biomarkers for OA is significant, as it offers valuable insights into the role of telomere-related genes in OA. This discovery also provides valuable information for the diagnosis and treatment of OA.

Osteoarthritis (OA) is one of the most prevalent joint disorders, with aging considered a primary, irreversible factor contributing to its progression. Telomere-related cellular senescence may be a crucial factor influencing the OA process, yet biomarkers for OA based on telomere-related genes have not been clearly identified. The datasets GSE51588, GSE12021, and GSE55457 were retrieved from the Gene Expression Omnibus database. Initially, R software was utilized to identify differentially expressed genes between OA and normal samples. Subsequently, differentially expressed telomere-related genes (DETMRGs) were obtained, and their functional enrichment was analyzed. Feature genes for OA diagnosis were selected from DETMRGs using a combination of least absolute shrinkage and selection operator, support vector machine-recursive feature elimination, and Random Forest algorithms. The diagnostic value of these feature genes was then validated through receiver operating characteristic (ROC) curves and decision curve analysis. Additionally, CIBERSORT and xCell were employed to assess the infiltration of immune cells in OA tissues.Finally, potential drugs targeting candidate genes were predicted. Three telomererelated genes, PGD, SLC7A5, and TKT, have been identified as biomarkers for OA diagnosis and were confirmed through ROC diagnostic tests. The immune infiltration of mast cells, neutrophils, common lymphoid precursors, and eosinophils associated with PGD, SLC7A5, and TKT was reduced. Recognizing telomere-related genes PGD, SLC7A5, and TKT as potential diagnostic biomarkers for OA is significant, as it offers valuable insights into the role of telomere-related genes in OA. This discovery also provides valuable information for the diagnosis and treatment of OA.

Osteoarthritis (OA) is one of the most prevalent joint disorders, with aging considered a primary, irreversible factor contributing to its progression. Telomere-related cellular senescence may be a crucial factor influencing the OA process, yet biomarkers for OA based on telomere-related genes have not been clearly identified. The datasets GSE51588, GSE12021, and GSE55457 were retrieved from the Gene Expression Omnibus database. Initially, R software was utilized to identify differentially expressed genes between OA and normal samples. Subsequently, differentially expressed telomere-related genes (DETMRGs) were obtained, and their functional enrichment was analyzed. Feature genes for OA diagnosis were selected from DETMRGs using a combination of least absolute shrinkage and selection operator, support vector machine-recursive feature elimination, and Random Forest algorithms. The diagnostic value of these feature genes was then validated through receiver operating characteristic (ROC) curves and decision curve analysis. Additionally, CIBERSORT and xCell were employed to assess the infiltration of immune cells in OA tissues.Finally, potential drugs targeting candidate genes were predicted. Three telomererelated genes, PGD, SLC7A5, and TKT, have been identified as biomarkers for OA diagnosis and were confirmed through ROC diagnostic tests. The immune infiltration of mast cells, neutrophils, common lymphoid precursors, and eosinophils associated with PGD, SLC7A5, and TKT was reduced. Recognizing telomere-related genes PGD, SLC7A5, and TKT as potential diagnostic biomarkers for OA is significant, as it offers valuable insights into the role of telomere-related genes in OA. This discovery also provides valuable information for the diagnosis and treatment of OA.

Objective To verify the accuracy of Youssef's formula and evaluate whether fetal biacromial diameter(BA)and other fetal biological diameters estimated by ultrasound can be used to predict macrosomia and shoulder dystocia,so as to provide the possibility for clinical prediction of shoulder dystocia.Methods A total of 200 pregnant women with a gestational period of 37-42 weeks were examined with ultrasound within 3 days before delivery for collecting biparietal diameter(BPD),head circumference(HC),abdominal circumference(AC),humerus length(HL),femur length(FL),thoracic transverse diameter and midpoint diameter of upper arm;and the fetal BA was estimated by Youssef's formula.Neonatal BA,body mass and body length were measured within 1 day after delivery.The above data were analyzed for correlation.Newborns were grouped according to their body mass(macrosomia vs non-macrosomia)and whether they had shoulder dystocia or not(shoulder dystocia vs non-shoulder dystocia).Results(1)The fetal BA estimated by Youssef's formula was consistent with neonatal BA(P>0.05),and the estimated BA was positively correlated with BPD,HC,AC and neonatal body mass(P<0.001).(2)The BA,BA/AC and BA/HC in macrosomia group were different from those in non-macrosomia group(P<0.05).ROC curve showed that the sensitivity and specificity were 92.3%and 88.2%for macrosomia prediction when the estimated BA threshold was 16.05 cm,and those were 61.5%and 77.0%when BA/AC threshold was 0.455,and 76.9%and 72.7%when BA/HC threshold was 0.465.(3)Shoulder dystocia group had neonatal weight close to non-shoulder dystocia group(P>0.05),but higher BA/BPD,BA/HC and BA-BPD(P<0.05).ROC curve showed that the sensitivity and specificity were 100.0%and 66.8%for shoulder dystocia when BA threshold was 15.45 cm,100.0%and 80.6%when BA/BPD threshold was 1.695,100.0%and 81.6%when BA/HC threshold was 0.475,and 100.0%and 76.0%when the threshold difference between BA and BPD was 6.35 cm.Conclusion Fetal BA,BA/BPD,BA/HC,BA/AC and BA-BPD may be effective predictors of shoulder dystocia and macrosomia.