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.

Objective: To assess the current status of bacterial detection capabilities in various blood collection and supply and related laboratories across China, and to identify key factors affecting the consistency of test results. Methods: A pooled analysis was conducted on data from 21 external quality assessment (EQA) rounds for blood bacterial detection carried out by the China International Transfusion Infection Prevention and Control (CITIC) project from 2019 to 2025. The study covered three types of laboratories-blood centers, central blood stations, and commercial laboratories—across 23 provincial-level administrative regions in China. Statistics were compiled on the number of participating laboratories, and the concordance rates were calculated for different institution types, different automated blood culture systems, different bacterial concentrations, and different strains. Non-standard reporting issues were also reviewed, and statistical methods were applied for analysis. Results: Over the seven-year period, the number of participating laboratories increased from 161 to 236, with an average annual growth rate of 6.58%, and the annual concordance rates ranged from 82.61% to 94.92%. The overall laboratory concordance rates for the three types of participating laboratories were all>89.0% (P>0.05), while commercial laboratories showed a significant year-by-year increase (70.97%-100%, P<0.05). The concordance rates of automated blood culture systems from eight manufacturers showed no significant differences (97.98%-100%, P>0.05), indicating stable performance across all devices. The overall sample concordance rate was 98.88%, with negative samples showing a lower rate than positive samples (97.97% vs 99.14%); positive sample rates increased with higher concentrations; and low-concentration Gram-negative bacterial samples had a lower concordance rate than Gram-positive ones (93.15% vs 100%). A total of 50 instances of non-standard result reporting were identified, with incorrect time units accounting for the highest proportion (52.0%). Conclusion The participation scale and overall testing proficiency of blood collection and supply and related laboratories nationwide have improved year by year, and all types of automated blood culture devices can meet the requirements for blood bacterial screening. Detection of negative and low-concentration positive samples remains a weak link in current bacterial EQA, and the standardization of laboratory data reporting requires further strengthening. Continuous: external quality assessment, targeted training, and standardized reporting procedures can effectively enhance the homogenization level of blood bacterial testing across the country and ensure the safety of clinical transfusion.

OBJECTIVE: To accurately measure human energy metabolism with high temporal resolution, a respiratory gas analysis system was designed using a breath-by-breath approach. METHODS: Firstly, indirect calorimetry was employed in respiratory gas analysis to measure the respiratory flow and concentration signals in real-time. Secondly, oxygen consumption QO2 and carbon dioxide production QCO2 were calculated through respiratory characteristic alignment and respiratory signal segmentation. Finally, metabolic indexes were calculated according to the Weir formula. Furthermore, a controlled trial was formulated for validation comparisons with the MGC ULTIMA SYSTEM PFX CARDIO2. RESULTS: The results indicate that the data points of metabolic indexes measured by this system all fall within the confidence interval when compared with those of the MGC. CONCLUSION The system has high consistency with the MGC measurement results. Thus, the system can accurately measure metabolism in real-time and provide data support for clinical nutrition assessment and therapy.
Humans ; Energy Metabolism ; Breath Tests/instrumentation* ; Calorimetry, Indirect/instrumentation* ; Equipment Design

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.

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 machine (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.

Ulcerative colitis (UC) is a chronic and non-specific inflammatory bowel disease (IBD). Huanglian Ganjiang decoction (HGD), derived from ancient book Beiji Qianjin Yao Fang, has demonstrated efficacy in treating UC patients traditionally. Previous research established that the compatibility of cold herb Coptidis Rhizoma + Phellodendri Chinensis Cortex (CP) and hot herb Angelicae Sinensis Radix + Zingiberis Rhizoma (AZ) in HGD synergistically improved colitis mice. This study investigated the compatibility mechanisms through which CP and AZ regulated inflammatory balance in colitis mice. The experimental colitis model was established by administering 3% dextran sulphate sodium (DSS) to mice for 7 days, followed by CP, AZ and CPAZ treatment for an additional 7 days. M1/M2 macrophage polarization levels, glucose metabolites levels and pyruvate dehydrogenase kinase 4 (PDK4) expression were analyzed using flow cytometry, Western blot, immunofluorescence and targeted glucose metabolomics. The findings indicated that CP inhibited M1 macrophage polarization, decreased inflammatory metabolites associated with tricarboxylic acid (TCA) cycle, and suppressed PDK4 expression and pyruvate dehydrogenase (PDH) (Ser-293) phosphorylation level. AZ enhanced M2 macrophage polarization, increased lactate axis metabolite lactate levels, and upregulated PDK4 expression and PDH (Ser-293) phosphorylation level. TCA cycle blocker AG-221 and adeno-associated virus (AAV)-PDK4 partially negated CP's inhibition of M1 macrophage polarization. Lactate axis antagonist oxamate and PDK4 inhibitor dichloroacetate (DCA) partially reduced AZ's activation of M2 macrophage polarization. In conclusion, the compatibility of CP and AZ synergistically alleviated colitis in mice through M1/M2 macrophage polarization balance via PDK4-mediated glucose metabolism reprogramming. Specifically, CP reduced M1 macrophage polarization by restoration of TCA cycle via PDK4 inhibition, while AZ increased M2 macrophage polarization through activation of PDK4/lactate axis.
Animals ; Drugs, Chinese Herbal/chemistry* ; Mice ; Macrophages/immunology* ; Glucose/metabolism* ; Pyruvate Dehydrogenase Acetyl-Transferring Kinase/genetics* ; Male ; Mice, Inbred C57BL ; Humans ; Colitis/drug therapy* ; Disease Models, Animal ; Colitis, Ulcerative/drug therapy* ; Metabolic Reprogramming

The biliary microbiota is an important component of the biliary system, the structure changes and dysbiosis of the biliary microbiota are closely related to the occurrence and development of biliary diseases. Recent studies have found that the dysbiosis of the biliary microbiota can lead to the occurrence of various biliary diseases such as cholelithiasis, cholangitis, and biliary tract cancer. However, the specific mechanisms of some of these diseases remain unclear. In addition, the alternation of biliary microbiota may also lead to the occurrence of postoperative complications of biliary diseases, such as the risk of infection increased after laparoscopic cholecystectomy (LC) and endoscopic retrograde cholangiopancreatography (ERCP). Although some studies have begun to explore the connection between biliary microbiota and biliary diseases, most research have mainly focused on a single disease type or specific microorganisms. There has been no comprehensive and systematic review of the overall changes in biliary microbiota across different diseases and their association with post biliary surgery infection.Therefore, this article presents a systematic review of current advances linking the alternations of biliary microbiota to the development of biliary diseases and their postoperative infections, as well as the changes in the biliary microbiota before and after various biliary diseases and their surgeries, aiming to provide insightful methods for the early diagnosis, prevention and treatment of biliary diseases and management of postoperative infections.

Objective : To explore the adverse effects of mild traumatic brain injury ( MTBI) on the memory monito- ring function of patients． Methods : This study adopted a paired control research method，combined neuropsycho- logical background tests and memory monitoring task ( feeling of knowing，FOK) to conduct cognitive assessments on two groups of subjects: the patient group ( n = 42) and the matched control group ( n = 42) ． Results : In neuropsychological background test，the patients' performance in digit span test，Stroop color task，digit link task and auditory verbal learning test were significantly lower than those in the control group ( P＜0. 05) ．In addition，there was significant difference in accuracy of FOK task between the two groups ( P ＜0. 05) ．The ratio of right judge- ment / right recognition was relatively high in the control group，while the ratio of correct judgement /wrong recogni- tion was relatively high in the patient group． Conclusion This study confirms that memory impairment in MTBI patients is centered on damage to memory monitoring function．Moreover，the damage to attention，execution，and item content memory abilities in MTBI patients are important driving factors for their memory monitoring dysfunction．