BACKGROUND:Spondylolisthesis is a common disease,and there is a lack of effective drugs to treat it.There is still a need to further define the pathogenesis and screen out more suitable therapeutic targets for spondylolisthesis.Mendelian randomization analysis can be used to explore the drugable genes associated with spondylolisthesis and provide valuable guidance for the development of more effective and targeted therapeutic drugs.OBJECTIVE:To explore potential therapeutic targets and effective drugs for spondylolisthesis by means of pharmaceutically available genome-wide Mendelian randomization analysis.METHODS:Using the Finnish database,eQTLGen consortium,drug signature database,drug-gene interaction database,protein-protein interaction database,organic small molecule biological activity database and protein structure database,which contains genome and health information of half a million Finns,data on druggable genes were subjected to two-sample Mendelian randomization analysis and co-localization analysis with data from genome-wide association studies of spondylolisthesis to identify genes highly associated with spondylolisthesis.In addition,GO and KEGG enrichment analysis,protein network construction,drug prediction and molecular docking were performed to provide valuable guidance for the development of more effective and targeted therapeutic agents.RESULTS AND CONCLUSION:In this study,we identified 34 potential drug target genes that were significantly associated with spondylolisthesis,particularly the gene APOBEC3G.This gene showed a significant association with spondylolisthesis outcomes through Mendelian analysis and co-localization analysis,suggesting that APOBEC3G may be a priority therapeutic target.As for other potential mechanisms and drugs,we still need to conduct more in-depth research to determine their roles.This study used a database from a European population,which can be used as a reference for the study of population genetics in China.

BACKGROUND:Spondylolisthesis is a common disease,and there is a lack of effective drugs to treat it.There is still a need to further define the pathogenesis and screen out more suitable therapeutic targets for spondylolisthesis.Mendelian randomization analysis can be used to explore the drugable genes associated with spondylolisthesis and provide valuable guidance for the development of more effective and targeted therapeutic drugs.OBJECTIVE:To explore potential therapeutic targets and effective drugs for spondylolisthesis by means of pharmaceutically available genome-wide Mendelian randomization analysis.METHODS:Using the Finnish database,eQTLGen consortium,drug signature database,drug-gene interaction database,protein-protein interaction database,organic small molecule biological activity database and protein structure database,which contains genome and health information of half a million Finns,data on druggable genes were subjected to two-sample Mendelian randomization analysis and co-localization analysis with data from genome-wide association studies of spondylolisthesis to identify genes highly associated with spondylolisthesis.In addition,GO and KEGG enrichment analysis,protein network construction,drug prediction and molecular docking were performed to provide valuable guidance for the development of more effective and targeted therapeutic agents.RESULTS AND CONCLUSION:In this study,we identified 34 potential drug target genes that were significantly associated with spondylolisthesis,particularly the gene APOBEC3G.This gene showed a significant association with spondylolisthesis outcomes through Mendelian analysis and co-localization analysis,suggesting that APOBEC3G may be a priority therapeutic target.As for other potential mechanisms and drugs,we still need to conduct more in-depth research to determine their roles.This study used a database from a European population,which can be used as a reference for the study of population genetics in China.

By reviewing modern research and integrating clinical practice， this paper interprets the correlation between "deep heat， deep syncope" and the "macrocirculation-microcirculation" uncoupling in sepsis， alongside its clinical applications in sepsis prevention and treatment. It is considered that "deep heat" corresponds to peripheral vasodilation and the hypermetabolic state at the macrocirculation level， whereas "deep syncope" manifests as hypoperfusion and impaired oxygen utilization at the microcirculation level. These two states interact detrimentally， forming the core contradiction of macrocirculation-microcirculation uncoupling in sepsis. Based on the traditional Chinese medicine （TCM） connotations of "deep heat， deep syncope" and modern medical research， this paper elucidates the systemic pathological evolution of sepsis from the inflammatory cascade to impaired oxygen utilization. Accordingly， the following therapeutic principles are proposed. In the early stage， it is suggested to clear heat and drain fire to vent the constrained yang. In the progressive stage， the focus is put on unblocking the lower jiao （焦） and expelling stasis to dredge the vessels and collaterals. In the recovery stage， the method of regulating and harmonizing yin and yang can be used to smooth the flow of qi and blood.

BACKGROUND:Observational studies have shown that intervertebral disc degeneration affects sedentary and physical activity levels;however,the causal relationship between sedentary and physical activity levels in the Oswestry disability index score and intervertebral disc degeneration is unclear. OBJECTIVE:To explore the causal relationship between sedentary and physical activity levels in the Oswestry disability index score and intervertebral disc degeneration using the Mendelian randomization method. METHODS:Five features associated with behavioral correlations in the Oswestry disability index score,including time spent watching TV,time spent on the computer,and light/moderate/vigorous physical activity,were selected from large-scale population-based genome-wide association studies,and instrumental variables were extracted for each of these behaviorally related features.Mendelian randomization analyses were performed in conjunction with the extraction of intervertebral disc degeneration as an outcome from the Finn Gen latest version 9 database.The results were analyzed using the inverse variance weighted,MR-Egger regression,simple mode,weighted mode,weighted median estimator,and regression model odds ratios(OR)and 95%confidence interval(CI)to assess the causal relationship between sedentary and physical activity levels in the Oswestry disability index scoring and intervertebral disc degeneration.Cochran's Q was used to test for heterogeneity,MR-Egger intercept to test for multiplicity,and leave-one-out to test the sensitivity of single nucleotide polymorphisms to the causal relationship between exposure factors and disc degeneration. RESULTS AND CONCLUSION:The results of the Mendelian randomization analysis using inverse variance weighted method showed a positive causal association between time spent watching TV/on the computer and the risk of intervertebral disc degeneration(OR=1.775,95%CI:1.418-2.221,P<0.001)/(OR=1.384,95%CI:1.041-1.839,P<0.001),an inverse causal association between light physical activity and the risk of intervertebral disc degeneration(OR=1.000,95%CI:0.999-1.000,P=0.020).MR-Egger intercept analysis indicated there was potential horizontal polytropy between light physical activity and intervertebral disc degeneration(P=0.005),while there was no horizontal pleiotropy between time spent watching TV,time spent on the computer and intervertebral disc degeneration(P=0.521,P=0.851).Cochran's Q analysis showed that heterogeneity was observed between time spent watching TV,time spent on the computer and intervertebral disc degeneration(P=3.33×10-11,P=0.001),and no significant heterogeneity was observed between light physical activity and intervertebral disc degeneration(P=0.186).Overall,there is a bidirectional causal relationship between sedentary and physical activity levels in the Oswestry disability index score and intervertebral disc degeneration,i.e.,not only does intervertebral disc degeneration affect sedentary and physical activity levels in the Oswestry disability index score,but sedentary and physical activity levels in the Oswestry disability index score also affect intervertebral disc degeneration.These findings add to the genetic evidence for a positive effect of light physical activity on intervertebral disc degeneration,indicate that moderate/vigorous physical activity shows no significant causal relationship with intervertebral disc degeneration,and expand the evidence base for sedentary behaviors such as prolonged time spent watching TV/on the computer as a risk factor for intervertebral disc degeneration.

Objective To investigate the association between plasma homocysteine(Hcy)level and coronary artery calcification(CAC)and its clinical predictive efficacy.Methods A total of 172 patients who underwent coronary CT angiography North China University of Science and Technology Affiliated Hospital from April 2019 to May 2021 and CAC score(CACS)＞0 were enrolled.According to the CACS value,the subjects were divided into mild calcification group(n=136)and severe calcification group(n=36),and the clinical characteristics of two groups were compared and analyzed.Multivariate Logistic regression model was used to screen the independent influencing factors of CAC severity,and a prediction model was constructed based on the Hcy detection value.The clinical diagnostic value was evaluated by the receiver operating characteristic(ROC)curve.Results There were significant differences in Hcy,white blood cell count,triglyceride and magnesium ion levels between two groups(P＜0.05).Multivariate Logistic regression analysis showed that Hcy,white blood cell count and magnesium ion level were independent risk factors for the progression of CAC.Furthermore,a regression model based on Hcy was constructed and ROC curve was fitted to evaluate its predictive efficacy.The results suggested that the predictive model had the best performance when the critical value of Hcy was set at 27.4μmol/L:the sensitivity was 55.6％,the specificity was 97.1％,and the area under the curve was 0.765.Conclusion Hcy serves as an independent risk factor for the severity of CAC and can effectively predict the progression of CAC with high accuracy.

This study aims to establish BHK-21 stable cell lines expressing APN from four species(human,pig,dog,and cat),the APN fragments were amplified from pEGFP-C1-APN plasmids of the four species stored in the laboratory to generate the recombinant plasmids pcDNA4.0-APN.Af-ter the recombinant plasmids were transfected into BHK-21 cells,the stable BHK-21 cell lines ex-pressing the APNs were selected by two rounds of limited dilution.The constructed BHK-21 cell lines were identified by indirect immunofluorescence assay(IFA),and their susceptibility to PD-CoV and TGEV was tested for these four cell lines.Virus infection experiments revealed that PD-CoV infected cells expressing human,pig,and dog APNs,while it did not infect cells expressing cat APN.Simultaneously,TGEV infected cells expressing pig,dog,and cat APNs,but did not infect cells expressing human APN.The results suggest that the risk of cross-species infection for different coronaviruses and the established cell line can be used effectively to evaluate the virus in-fection.The findings also revealed that PDCoV has the potential risk of cross-species infection of human and dog,and TGEV has the potential risk of cross-species infection of dog and cat.These results provide a basis for the prevention and control strategy of coronaviruses.

With the advent of the genomic era, genomics has gradually become a part of nursing. The use of genomic data can explore the mechanisms of disease occurrence and progression, accurately identify intervention targets and regulatory pathways of diseases, provide precise and personalized nursing services for patients, and improve their quality of life. This paper reviews the current application status of genomics in nursing, deeply analyzes the development process of genomics in genetic risk assessment, symptom precision nursing, precision nursing decision-making, and nursing education, and proposes corresponding development strategies. Through a comprehensive and in-depth exploration of the combination of genomics and nursing, the aim is to provide strong theoretical guidance for the future development of genomics nursing in China.

Objective To explore the functional connectivity(FC)changes of hippocampus and amygdala in type 2 diabetes mellitus(T2DM)patients with erectile dysfunction(DMED),and the central pathological neural mechanisms underlying DMED.Methods 61 T2DM patients who visited Department of Endocrinology,Nanjing First Hospital,Nanjing Medical University from January 2020 to December 2021 were selected and divided into a simple T2DM group(n=30)and a combined DMED group(n=31).Another 47 healthy individuals were selected as control group(NC).The international erectile function scale(IIEF-5)was used to evaluate the erectile function.Resting-state functional magnetic resonance imaging(rs-fMRI)data were acquired from all participants.MRI data were preprocessed by the DPABI software package.Bilateral hippocampus and amygdala were selected as regions of interest(ROI)and the whole brain FC values were calculated.The FC values of brain regions between groups were tested by two-sample t-test with REST software package.Results Left hippocampus as ROI:compared with the NC group,FC values of the left superior temporal gyrus increased in the T2DM group,FC values of the left superior frontal gyrus,left inferior temporal gyrus,left posterior central gyrus and rectus gyrus decreased in the DMED group.Compared with the T2DM group,FC values of the left inferior parietal gyrus,left supramarginal gyrus,left middle occipital gyrus and right posterior central gyrus decreased in the DMED group.Right hippocampus as ROI:compared with the NC group,FC values of the right middle temporal gyrus and right rolandic operculum increased while FC values of the right calcarine fissure decreased in the T2DM group;FC values of bilateral anterior cingulate gyrus,right middle temporal gyrus and left rectus gyrus decreased in the DMED group.Compared with the T2DM group,FC values of the left middle frontal gyrus,left inferior parietal gyrus and right inferior temporal gyrus decreased in the DMED group.Left amygdala as ROI:compared with the NC group,FC values in the left parahippocampal gyrus,left fusiform gyrus and right insula increased in the T2DM group;FC value of the left middle temporal gyrus decreased in the DMED group.Compared with the T2DM group,FC values of the left middle frontal gyrus and left supramarginal gyrus decreased in the DMED group.Right amygdala as ROI:compared with the NC group,FC values of the left insula,right parahippocampal gyrus,right superior temporal gyrus and right supramarginal gyrus increased while FC values in the right caudate decreased in the T2DM group;FC values of the right middle frontal gyrus,left rectus gyrus and left middle occipital gyrus decreased in the DMED group.Compared with the T2DM group,FC values of the left middle frontal gyrus and left inferior parietal gyrus decreased in the DMED group.Conclusions DMED patients have abnormalities in the hippocampus,amygdala and other brain regions,especially the frontal lobe functional cortex,which may be related to changes in their brain function.

Metabolomics covers a wide range of applications in life sciences,biomedicine,and phytology.Data acquisition(to achieve high coverage and efficiency)and analysis(to pursue good classification)are two key segments involved in metabolomics workflows.Various chemometric approaches utilizing either pattern recognition or machine learning have been employed to separate different groups.However,insufficient feature extraction,inappropriate feature selection,overfitting,or underfitting lead to an insufficient capacity to discriminate plants that are often easily confused.Using two ginseng varieties,namely Panax japonicus(PJ)and Panax japonicus var.major(PJvm),containing the similar ginsenosides,we integrated pseudo-targeted metabolomics and deep neural network(DNN)modeling to achieve accurate species differentiation.A pseudo-targeted metabolomics approach was optimized through data acquisition mode,ion pairs generation,comparison between multiple reaction monitoring(MRM)and scheduled MRM(sMRM),and chromatographic elution gradient.In total,1980 ion pairs were monitored within 23 min,allowing for the most comprehensive ginseng metabolome analysis.The established DNN model demonstrated excellent classification performance(in terms of accuracy,precision,recall,F1 score,area under the curve,and receiver operating characteristic(ROC))using the entire metabolome data and feature-selection dataset,exhibiting superior advantages over random forest(RF),support vector ma-chine(SVM),extreme gradient boosting(XGBoost),and multilayer perceptron(MLP).Moreover,DNNs were advantageous for automated feature learning,nonlinear modeling,adaptability,and generalization.This study confirmed practicality of the established strategy for efficient metabolomics data analysis and reliable classification performance even when using small-volume samples.This established approach holds promise for plant metabolomics and is not limited to ginseng.

With the advent of the genomic era, genomics has gradually become a part of nursing. The use of genomic data can explore the mechanisms of disease occurrence and progression, accurately identify intervention targets and regulatory pathways of diseases, provide precise and personalized nursing services for patients, and improve their quality of life. This paper reviews the current application status of genomics in nursing, deeply analyzes the development process of genomics in genetic risk assessment, symptom precision nursing, precision nursing decision-making, and nursing education, and proposes corresponding development strategies. Through a comprehensive and in-depth exploration of the combination of genomics and nursing, the aim is to provide strong theoretical guidance for the future development of genomics nursing in China.