Objective:To evaluate the clinical efficacy of Tianma Xionglin Zhixuan Tablets in treating hypertension patients with liver yang hyperactivity or comorbid phlegm-stasis syndrome and explore its therapeutic mechanisms through plasma metabolomics.Methods:Thirty-six hypertension patients(4 dropouts)diagnosed with liver yang hyperactivity or phlegm-stasis syndrome were enrolled as the treatment group from June 2022 to September 2023 at the First Affiliated Hospital of Hunan University of Chinese Medicine,while 30 healthy volunteers with balanced constitutions were recruited as the blank group.Plasma samples were collected from patients pre-and post-treatment and from healthy volunteers.Clinical outcomes,including syndrome scores,office blood pressure(BP),and 24-hour ambulatory BP,were recorded.Plasma metabolomic profiling was performed using liquid chromatography-mass spectrometry(LC-MS).Results:Compared with baseline,Tianma Xionglin Zhixuan Tablets significantly reduced traditional Chinese medicine syndrome scores(P＜0.01),office systolic/diastolic BP(P＜0.01),and 24-hour ambulatory BP parameters(24-hour mean BP,daytime/nighttime mean BP;all P＜0.01).Metabolomic analysis identified 45 differential metabolites between the blank group and pretreatment patients,and 64 metabolites altered post-treatment(VIP＞1,P＜0.05).Enrichment analysis of 16 overlapping endogenous metabolites revealed that Tianma Xionglin Zhixuan Tablets primarily modulated arachidonic acid metabolism and sphingolipid metabolism pathways.Conclusion:Tianma Xionglin Zhixuan Tablets demonstrates significant clinical efficacy in hypertension patients with liver yang hyperactivity or phlegm-stasis syndrome,potentially mediated through regulation of arachidonic acid and sphingolipid metabolism.

Objective:To evaluate the clinical efficacy of Tianma Xionglin Zhixuan Tablets in treating hypertension patients with liver yang hyperactivity or comorbid phlegm-stasis syndrome and explore its therapeutic mechanisms through plasma metabolomics.Methods:Thirty-six hypertension patients(4 dropouts)diagnosed with liver yang hyperactivity or phlegm-stasis syndrome were enrolled as the treatment group from June 2022 to September 2023 at the First Affiliated Hospital of Hunan University of Chinese Medicine,while 30 healthy volunteers with balanced constitutions were recruited as the blank group.Plasma samples were collected from patients pre-and post-treatment and from healthy volunteers.Clinical outcomes,including syndrome scores,office blood pressure(BP),and 24-hour ambulatory BP,were recorded.Plasma metabolomic profiling was performed using liquid chromatography-mass spectrometry(LC-MS).Results:Compared with baseline,Tianma Xionglin Zhixuan Tablets significantly reduced traditional Chinese medicine syndrome scores(P＜0.01),office systolic/diastolic BP(P＜0.01),and 24-hour ambulatory BP parameters(24-hour mean BP,daytime/nighttime mean BP;all P＜0.01).Metabolomic analysis identified 45 differential metabolites between the blank group and pretreatment patients,and 64 metabolites altered post-treatment(VIP＞1,P＜0.05).Enrichment analysis of 16 overlapping endogenous metabolites revealed that Tianma Xionglin Zhixuan Tablets primarily modulated arachidonic acid metabolism and sphingolipid metabolism pathways.Conclusion:Tianma Xionglin Zhixuan Tablets demonstrates significant clinical efficacy in hypertension patients with liver yang hyperactivity or phlegm-stasis syndrome,potentially mediated through regulation of arachidonic acid and sphingolipid metabolism.

Objective To evaluate the effect of donor gender on short-term survival rate of lung transplant recipients. Methods A retrospective analysis was conducted on the data of 1 066 lung transplant recipients. The log-rank test was used to evaluate the differences in short-term fatality among different donor gender groups and donor-recipient gender combination groups. Multivariate Cox regression, propensity score (PS) regression, and propensity score matching (PSM) were employed to control for confounding factors and further assess the differences in fatality. Subgroup analyses were also performed based on donor gender. Results Multivariate Cox regression analysis showed no statistically significant differences in fatality at 30 days, 1 year, 2 years and 3 years postoperatively between male and female donor groups (all P>0.05). After PS regression and PSM, univariate Cox regression analysis indicated that recipients from female donors had a higher fatality at 2 years postoperatively compared to those from male donors, with hazard ratios (95% confidence intervals) of 1.29 (1.01-1.65) and 1.36 (1.03-1.80) respectively. Multivariate Cox regression analysis also revealed no statistically significant differences in fatality at various follow-up time points among different donor-recipient gender combination groups (all P>0.05). Subgroup analyses based on donor sex showed no statistically significant differences in fatality among recipients of different gender within either male or female donor groups (all P>0.05). Conclusions Female donors may reduce the short-term postoperative survival rate of lung transplant recipients, but this negative impact is not sustainable in the long term. At present, there is no evidence to support the inclusion of sex as a factor in lung allocation rules.

Lung transplantation is an important means to treat end-stage lung disease and improve the survival rate and quality of life of patients. However, many postoperative complications seriously affect the prognosis of recipients. Accurate identification of key prognostic factors and construction of individualized and accurate prediction models are of great significance for postoperative prognosis evaluation, treatment strategy formulation and clinical decision-making. In recent years, the clinical prediction model of lung transplantation has gradually changed from traditional statistical methods to machine learning-driven. Compared with traditional models such as Cox regression and Logistic regression, machine learning models such as random forest, support vector machine and artificial neural network have certain advantages in postoperative survival rate prediction, early warning of complications and pulmonary function evaluation. However, their application is also affected by insufficient sample size and poor interpretability of models. Under the condition of small samples, the traditional model still has important value in prediction accuracy. The appropriate prediction model should be selected according to the clinical status of lung transplantation in China, considering the factors such as sample size, variable complexity and model interpretability. In the future, a multi-center, large-sample lung transplantation database should be constructed to further optimize and tap the potential of machine learning algorithms to improve the robustness and clinical applicability of the model.

Lung transplantation is an important means to treat end-stage lung disease and improve the survival rate and quality of life of patients. However, many postoperative complications seriously affect the prognosis of recipients. Accurate identification of key prognostic factors and construction of individualized and accurate prediction models are of great significance for postoperative prognosis evaluation, treatment strategy formulation and clinical decision-making. In recent years, the clinical prediction model of lung transplantation has gradually changed from traditional statistical methods to machine learning-driven. Compared with traditional models such as Cox regression and Logistic regression, machine learning models such as random forest, support vector machine and artificial neural network have certain advantages in postoperative survival rate prediction, early warning of complications and pulmonary function evaluation. However, their application is also affected by insufficient sample size and poor interpretability of models. Under the condition of small samples, the traditional model still has important value in prediction accuracy. The appropriate prediction model should be selected according to the clinical status of lung transplantation in China, considering the factors such as sample size, variable complexity and model interpretability. In the future, a multi-center, large-sample lung transplantation database should be constructed to further optimize and tap the potential of machine learning algorithms to improve the robustness and clinical applicability of the model.

Organ transplantation has become an effective treatment for multiple end-stage diseases. However, the recipients of organ transplantation need to take immunosuppressive drugs for a long time after operation, which leads to low immune function and relatively high incidence of bacterial, viral and fungal infections. Traditional microbial detection methods, such as pathogen culture, immunological detection and polymerase chain reaction, have been widely applied in infection detection, whereas these methods may cause problems, such as long detection time and presumed pathogens. Metagenomic next-generation sequencing has been widely adopted in infection prevention and control in organ transplantation in recent years due to high detection rate and comprehensive detection of pathogen spectrum. In this article, the application of metagenomic next-generation sequencing in the prevention and control of infection in solid organ transplantation was reviewed, aiming to provide reference for the diagnosis and treatment of transplantation-related infection.

Objective To investigate the relationship between single nucleotide polymorphisms(SNPs)in the eNOS gene and genetic susceptibility to systemic lupus erythematosus(SLE)in Hainan.Methods Blood samples were collected from SLE patients(SLE group,n=214)and healthy controls(control group,n=214)from January 2020 to December 2022 at the First Affiliated Hospital of Hainan Medical College and Hainan Provincial People's Hospital.The bases of eNOS gene rs3918188,rs1799983 and rs1007311 loci in each group were detected by SNaPshot sequencing technology.Logistic regression was used to analyze the correlation between genotypes,alleles and gene models(dominant model,recessive model,and overdominant model)of the above 3 target loci of the eNOS gene and genetic susceptibility to SLE.Haplotype analysis was conducted using HaploView 4.2 software to investigate the relationship between haploid and genetic susceptibility to SLE at each site.Results The results of logistic regression analysis revealed that the CC genotype and the C allele at rs3918188 locus were risk factors for genetic susceptibility to SLE(CC vs.AA:OR=2.449,P<0.05;C vs.A:OR=2.133,P<0.001).In recessive model at rs3918188 locus,CC genotype carriers had an increased risk of SLE development compared with AA+AC genotype carriers(OR=2.774,P<0.001).In contrast,in overdominant model at this locus,AC genotype carriers had a decreased risk of SLE occurrence compared with AA+CC genotype carriers(OR=0.385,P<0.001).In addition,polymorphisms of rs1799983 and rs1007311 were not associated with susceptibility to SLE in genotype,allele type and the 3 genetic models(P>0.05).Haplotype analysis revealed a strong linkage disequilibrium between the rs1007311 and rs1799983 loci of the eNOS gene,but no significant correlation was found between haplotype and genetic susceptibility to SLE(P>0.05).Conclusion The CC genotype and C allele at rs3918188 locus of eNOS gene may be risk factors for SLE in Hainan,while the risk of SLE occurrence is reduced in carriers of AC genotype under the overdominant model.

Objective:To investigate the expression and prognostic value of ANO1 in oral squamous cell carcinoma(OSCC)tissues.Methods:Immunohistochemistry(IHC,n=163)and Quantitative real-time PCR(qRT-PCR,n=42)were employed to detect the expression level of ANO1 protein and mRNA in OSCC tissues and paracancerous normal tissues.The relationship between ANO1 ex-pression and clinicopathological features(n=163)and prognosis(n=93)of the patients were analyzed,and the results were compared with those in TCGA database.Results:IHC and qRT-PCR confirmed that ANO1 was highly expressed in OSCC(P＜0.05),which was consistent with the results of the TCGA database.Cox regression analysis showed that ANO1 expression was significantly correlated with T stage,lymph node metastasis and TNM stage and poor prognosis(P＜0.05).By Cox regression analysis,ANO1 overexpression(P=0.002)and differentiation degree(P=0.034)were independent prognostic factors.Conclusion:ANO1 is highly expressed in OSCC and is correlated with poor prognosis,which can be used as a novel biomarker for poor prognosis of OSCC patients.

Objective To evaluate the process risk of the implementation of prevention and control measures for surgical site infection(SSI)after colorectal surgery,and explore the application effect of failure mode and effects analysis(FMEA)based on action priority.Methods FMEA based on action priority was adopted to evaluate the whole process of the implementation of prevention and control measures for SSI after colorectal surgery.Prioritiza-tion ranking was conducted according to whether optimized measures were taken.Standard-reaching rate of comp-liance to SSI prevention and control measures as well as SSI incidence before and after the implementation of FMEA were compared.Results After evaluation,there were 7 high-priority and 22 medium-priority prevention and control measures for SSI.The control of medium-priority measures was strengthened,with a focus on developing further preventive and detectable measures for high-priority measures.The re-evaluation results after improvement showed that 7 high-priority measures have been downgraded to medium priority,and 16 medium-priority measures have been downgraded to low priority.Standard-reaching rate of compliance to SSI prevention and control measures in-creased from 77.15％(2 566/3 326)to 92.47％(3 096/3 348),and SSI incidence decreased from 6.04％(58/960)to 2.54％(60/2 364).Conclusion Application of FMEA based on action priority can effectively evaluate the risk of prevention and control process of SSI after colorectal surgery,and adopting preventive risk control measures accord-ing to the current situation can reduce the incidence of SSI after colorectal surgery.

Objective To understand the change in distribution and antimicrobial resistance of bacteria isolated from blood specimens of Hunan Province,and provide for the initial diagnosis and treatment of clinical bloodstream infection(BSI).Methods Data reported from member units of Hunan Province Antimicrobial Resistance Survei-llance System from 2012 to 2021 were collected.Bacterial antimicrobial resistance surveillance method was imple-mented according to the technical scheme of China Antimicrobial Resistance Surveillance System(CARSS).Bacteria from blood specimens and bacterial antimicrobial susceptibility testing results were analyzed by WHONET 5.6 soft-ware and SPSS 27.0 software.Results A total of 207 054 bacterial strains were isolated from blood specimens from member units in Hunan Province Antimicrobial Resistance Surveillance System from 2012 to 2021,including 107 135(51.7％)Gram-positive bacteria and 99 919(48.3％)Gram-negative bacteria.There was no change in the top 6 pathogenic bacteria from 2012 to 2021,with Escherichia coli(n=51 537,24.9％)ranking first,followed by Staphylococcus epidermidis(n=29 115,14.1％),Staphylococcus aureus(n=17 402,8.4％),Klebsiella pneu-moniae(17 325,8.4％),Pseudomonas aeruginosa(n=4 010,1.9％)and Acinetobacter baumannii(n=3 598,1.7％).The detection rate of methicillin-resistant Staphylococcus aureus(MRSA)decreased from 30.3％in 2015 to 20.7％in 2021,while the detection rate of methicillin-resistant coagulase-negative Staphylococcus(MRCNS)showed an upward trend year by year(57.9％-66.8％).No Staphylococcus was found to be resistant to vancomy-cin,linezolid,and teicoplanin.Among Gram-negative bacteria,constituent ratios of Escherichia coli and Klebsiella pneumoniae were 43.9％-53.9％and 14.2％-19.5％,respectively,both showing an upward trend(both P＜0.001).Constituent ratios of Pseudomonas aeruginosa and Acinetobacter baumannii were 3.6％-5.1％and 3.0％-4.5％,respectively,both showing a downward trend year by year(both P＜0.001).From 2012 to 2021,resistance rates of Escherichia coli to imipenem and ertapenem were 1.0％-2.0％and 0.6％-1.1％,respectively;presenting a downward trend(P＜0.001).The resistant rates of Klebsiella pneumoniae to meropenem and ertapenem were 7.4％-13.7％and 4.8％-6.4％,respectively,presenting a downward trend(both P＜0.001).The resistance rates of Pseudomonas aeruginosa and Acinetobacter baumannii to carbapenem antibiotics were 7.1％-15.6％and 34.7％-45.7％,respectively.The trend of resistance to carbapenem antibiotics was relatively stable,but has de-creased compared with 2012-2016.The resistance rates of Escherichia coli to the third-generation cephalosporins from 2012 to 2021 were 41.0％-65.4％,showing a downward trend year by year.Conclusion The constituent ra-tio of Gram-negative bacillus from blood specimens in Hunan Province has been increasing year by year,while the detection rate of carbapenem-resistant Gram-negative bacillus remained relatively stable in the past 5 years,and the detection rate of coagulase-negative Staphylococcus has shown a downward trend.