Alzheimer's disease （AD） is a common type of dementia， primarily characterized by cognitive and behavioral impairments as well as deficits in learning and memory. The progression of AD has imposed a significant economic burden on society and families. However， its exact pathogenesis has not yet been fully elucidated. Currently， available therapeutic drugs are limited and are often accompanied by serious adverse effects. Traditional Chinese medicines （TCMs） and their extracts are mostly natural products and possess advantages such as multi-pathway regulation and relatively few adverse reactions. Experimental studies have shown that TCMs exhibit great potential in the prevention and treatment of AD. For example， Huanglian Jieduang， Danggui Shaoyaosan， Kaixin San， Liuwei Dihuangwan， Buyang Huanwutang， as well as Ginseng Radix et Rhizoma， Astragali Radix， Uncariae Ramulus cum Uncis， Coptidis Rhizoma， Gardeniae Fructus， Ginkgo Folium， Salviae Miltiorrhizae Radix et Rhizoma， and Curcumae Longae Rhizoma， can reduce β-amyloid deposition， inhibit excessive Tau protein phosphorylation， restore mitochondrial function， alleviate oxidative stress， suppress neuroinflammation and apoptosis， repair synaptic function， and improve gut microbiota. This article mainly summarizes the effects of several TCMs and compound prescriptions on AD， aiming to provide a reference for subsequent TCM-based treatment of AD.

ObjectiveThis study aims to explore the potential of different orders of magnitude single-nucleotide polymorphism (SNP) locus combinations for predicting distant kinship relationships. A high-density SNP locus set was constructed, and a comprehensive assessment of its inference capability was conducted. MethodsFirstly, we selected three commercial chip panels, CGA (Chinese genotyping array, Illumina), GSA (Global screening array, Illumina), Affy (23MF_V2 high-density SNP array, Affymetrix) and merged them after quality control, forming a high-density SNP locus panel(1 180 k). Secondly, we selected 161 samples and collected their peripheral blood samples by using whole-genome sequencing technology. Within this sample population, the levels of kinship relationships fully covered the range from level 1 to level 9, and the number of kinship pairs at each level was consistently maintained at over 50 pairs. From 161 samples data of whole-genome sequencing, the 1 180 k locus set was extracted, which is referred to as the high-density SNP locus set in the following text. The kinship inference was conducted using the identity-by-descent (IBD) algorithm with the selected optimal parameters. To comprehensively evaluate the performance of the high-density SNP locus set in kinship inference, we compared it with the three commercial chip panels, the intersection of these three chip loci, and the control sets constructed by randomly reducing the number of the high-density SNP locus set. Based on the changes in the IBD lengths, as well as the dynamic trends in prediction accuracy, we conducted a scientific assessment of the kinship inference capability of the high-density SNP locus set. ResultsAfter screening, a set of 1 184 334 autosomal SNPs was obtained. During the process of screening the optimal IBD length threshold, the result revealed that 0 cM, 1 cM, and 2 cM all demonstrated good applicability. However, to avoid the issue of a large amount of redundant information caused by setting a too low IBD length threshold, this study ultimately selected 2 cM as the optimal threshold. Compared with the average results of three chip panels, the high-density SNP locus set increased the total IBD length and the average IBD length across levels 1-9; the accuracy of the confidence interval for level 8 was 70.97%, which represented a 3.50% improvement; the average confidence interval accuracy for levels 1-8 was 91.39%, representing a 1.00% increase; and the false negative rates at levels 8 and 9 were reduced by 2.42% and 6.76%, respectively. The system efficacy of the high-density SNP locus set for kinship inference of first to eighth degree relationships reached 98.91%. Through random reduction of the high-density SNP locus set results, it is found that increasing the number of SNPs with the panel, the detection efficiency of IBD length showed a significant upward trend. At the same time, the overall trend in the accuracy of kinship relationship prediction as well as the confidence interval accuracy also indicated that both metrics steadily increased with the addition of more loci. ConclusionThe results show that the high-density SNPs panel significantly enhances the efficacy of distant kinship inference, accurately covering kinship degrees, with the average confidence interval accuracy for first to eighth degree relationships stably above 90%. The study finds that increasing the number of SNPs panel can improve the ability to predict distant kinship.

Objective: To analyze changes in tuberculosis infection among junior high school students before and after tuberculosis exposure, so as to provide a reference for improving school tuberculosis prevention and control measures and policy formulation. Methods: Retrospectively collect data on a tuberculosis outbreak that occurred in a grade of a junior high school in Chongqing in 2025, including tuberculosis screening records of students in this grade upon their enrollment in 2022 (1 156 students) and after two tuberculosis outbreaks in 2023 (206 students) and 2025 (171 students). The Wilcoxon signed rank test for paired design was used to compare the induration diameters of the subjects, and the Chi square test was adopted to analyze the rate of tuberculosis infection among students. Results: In the tuberculosis outbreak in 2023, the rate of tuberculosis infection among close contacts ( 11.84 %) and the rate of tuberculosis infection among freshrman at school enrollment (12.89%) showed no statistically significant difference ( χ 2=0.25, P >0.05). The rate of tuberculosis infection of close contacts in the 2025 tuberculosis outbreak (55.56%) was higher than that in the 2023 outbreak (11.84%) ( χ 2=30.42, P <0.01). Among the 106 students included in the cohort analysis, the median induration diameter was 3.50 (1.50, 7.50) mm in 2023 and 8.75 (4.25, 11.50) mm in 2025, with a statistically significant difference ( Z=-5.76, P <0.01). There was no statistically significant difference between the infection rate in 2022 (16.98%) and that in 2023 (10.38%) ( χ 2=1.96, P =0.16). The infection rate in 2025 (43.40%) was higher than those in 2022 and 2023 ( χ 2=17.55, 29.39, both P <0.017). The seroconversion rate of students in the same class in 2025 ( 58.00 %) was higher than that of students in different classes (16.07%), with a statistically significant difference ( χ 2=20.19, P <0.01). All 72 individuals with latent tuberculosis infections identified during the pandemic in 2023 and 2025 refused to undergo prophylactic treatment. Conclusions The lack of preventive treatment may be the underlying cause of the successive outbreaks during the epidemic. Early detection of infection sources and standardized outbreak management are crucial to controlling the spread of the epidemic.

Aberrant activation of glycolysis represents a key metabolic mechanism underlying the initiation and progression of nasal inflammation. Allergic rhinitis, chronic rhinosinusitis, and vasomotor rhinitis exhibit distinct etiologies, yet all are characterized by inflammatory responses, impaired epithelial barrier function, and neurovascular dysregulation, in which glycolytic metabolic reprogramming acts as a central hub connecting immunometabolism and inflammatory regulation.Recent evidence indicates that glycolysis-dependent activation of immune cells provides the essential energy basis for inflammatory onset. In dendritic cells, eosinophils, mast cells, and Th2 cells, the expression of key glycolytic enzymes including HK2, PKM2, and LDHA is upregulated, thereby promoting cellular activation and proinflammatory cytokine release via the mTOR-HIF-1α signaling axis. Notably, the metabolic reprogramming of eosinophils prolongs their survival and enhances the release of cytotoxic granules, while in mast cells, enhanced glycolysis facilitates IgE-mediated degranulation and histamine release. Furthermore, glycolysis also influences the Th17/Treg balance, with enhanced glycolytic flux promoting Th17 differentiation and contributing to the heterogeneous inflammatory profiles observed across different rhinitis subtypes.As a central metabolite, lactate contributes to the formation of a metabolism-inflammation vicious cycle through multiple mechanisms. Lactate acidifies the local microenvironment to activate TRPV1 channels and facilitate neuropeptide release, mediates immune cell chemotaxis through GPR81, and regulates gene expression via histone lactylation, thereby sustaining proinflammatory gene transcription. These lactate-mediated processes collectively amplify local inflammation and contribute to the persistence of nasal symptoms.Glycolytic reprogramming in epithelial cells is modulated by the EGF/EGFR pathway, and its dysregulation may result in disrupted tight junctions, abnormal goblet cell hyperplasia, and subsequent tissue remodeling. Substance P and calcitonin gene-related peptide released from sensory neurons, in conjunction with metabolic products, synergistically maintain persistent inflammatory stimulation by activating mast cells, forming a neuro-immune-metabolic regulatory network that drives disease chronicity.From a therapeutic perspective, glycolytic inhibitors such as 2-deoxyglucose, FX11, and 3-bromopyruvate exert anti-inflammatory effects by targeting key enzymes including HK2 and LDHA, each with distinct mechanisms: 2-DG competitively inhibits hexokinase, FX11 selectively targets LDHA to reduce lactate production, and 3-BrPA modulates multiple glycolytic enzymes. Moreover, traditional Chinese medicine formulas, monomeric active components, and small-molecule compounds have shown promising potential in alleviating nasal inflammation by regulating the mTOR-HIF-1α axis, exerting antioxidant effects, and modulating endoplasmic reticulum stress pathways. The multi-target characteristics of these natural products offer advantages in addressing the complex pathophysiology of nasal inflammatory diseases.Despite these advances, several challenges remain. The non-selective inhibition of glycolysis may interfere with epithelial repair and mucosal regeneration, leading to delayed wound healing. Technical limitations in dynamic metabolic monitoring and sampling precision hinder the accurate assessment of local nasal metabolism. Furthermore, current animal models, which predominantly rely on acute stimulation protocols, inadequately recapitulate the chronic tissue remodeling processes characteristic of human rhinitis.This review systematically summarizes glycolysis as a common metabolic node shared by different rhinitis subtypes, offering a novel theoretical basis for the development of precision therapeutic strategies targeting metabolic reprogramming.

Aberrant activation of glycolysis represents a key metabolic mechanism underlying the initiation and progression of nasal inflammation. Allergic rhinitis, chronic rhinosinusitis, and vasomotor rhinitis exhibit distinct etiologies, yet all are characterized by inflammatory responses, impaired epithelial barrier function, and neurovascular dysregulation, in which glycolytic metabolic reprogramming acts as a central hub connecting immunometabolism and inflammatory regulation.Recent evidence indicates that glycolysis-dependent activation of immune cells provides the essential energy basis for inflammatory onset. In dendritic cells, eosinophils, mast cells, and Th2 cells, the expression of key glycolytic enzymes including HK2, PKM2, and LDHA is upregulated, thereby promoting cellular activation and proinflammatory cytokine release via the mTOR-HIF-1α signaling axis. Notably, the metabolic reprogramming of eosinophils prolongs their survival and enhances the release of cytotoxic granules, while in mast cells, enhanced glycolysis facilitates IgE-mediated degranulation and histamine release. Furthermore, glycolysis also influences the Th17/Treg balance, with enhanced glycolytic flux promoting Th17 differentiation and contributing to the heterogeneous inflammatory profiles observed across different rhinitis subtypes.As a central metabolite, lactate contributes to the formation of a metabolism-inflammation vicious cycle through multiple mechanisms. Lactate acidifies the local microenvironment to activate TRPV1 channels and facilitate neuropeptide release, mediates immune cell chemotaxis through GPR81, and regulates gene expression via histone lactylation, thereby sustaining proinflammatory gene transcription. These lactate-mediated processes collectively amplify local inflammation and contribute to the persistence of nasal symptoms.Glycolytic reprogramming in epithelial cells is modulated by the EGF/EGFR pathway, and its dysregulation may result in disrupted tight junctions, abnormal goblet cell hyperplasia, and subsequent tissue remodeling. Substance P and calcitonin gene-related peptide released from sensory neurons, in conjunction with metabolic products, synergistically maintain persistent inflammatory stimulation by activating mast cells, forming a neuro-immune-metabolic regulatory network that drives disease chronicity.From a therapeutic perspective, glycolytic inhibitors such as 2-deoxyglucose, FX11, and 3-bromopyruvate exert anti-inflammatory effects by targeting key enzymes including HK2 and LDHA, each with distinct mechanisms: 2-DG competitively inhibits hexokinase, FX11 selectively targets LDHA to reduce lactate production, and 3-BrPA modulates multiple glycolytic enzymes. Moreover, traditional Chinese medicine formulas, monomeric active components, and small-molecule compounds have shown promising potential in alleviating nasal inflammation by regulating the mTOR-HIF-1α axis, exerting antioxidant effects, and modulating endoplasmic reticulum stress pathways. The multi-target characteristics of these natural products offer advantages in addressing the complex pathophysiology of nasal inflammatory diseases.Despite these advances, several challenges remain. The non-selective inhibition of glycolysis may interfere with epithelial repair and mucosal regeneration, leading to delayed wound healing. Technical limitations in dynamic metabolic monitoring and sampling precision hinder the accurate assessment of local nasal metabolism. Furthermore, current animal models, which predominantly rely on acute stimulation protocols, inadequately recapitulate the chronic tissue remodeling processes characteristic of human rhinitis.This review systematically summarizes glycolysis as a common metabolic node shared by different rhinitis subtypes, offering a novel theoretical basis for the development of precision therapeutic strategies targeting metabolic reprogramming.

Background/Aims: Acetyl coenzyme A (acetyl-CoA) is one of the most essential metabolites in cell metabolism but its function and concentration in hepatocellular carcinoma (HCC) remain elusive and controversial. Methods: A comprehensive analysis of acetyl-CoA levels and acetyl-CoA synthetase 2 (ACSS2) expression across a range of samples, including patient specimens from both hepatitis B virus (HBV) positive and HBV negative HCC individuals, HBV-transgenic mouse HCC models, and multiple cell lines. Furthermore, to evaluate the functional significance of ACSS2 in HBV-related HCC, we implemented both genetic and pharmacological inhibition strategies targeting ACSS2. Molecular mechanism and mitophagy assessment were revealed by cleavage under target and tagmentation sequencing, RNA sequencing, bioinformatic analyses, transmission electron microscopy and JC-1 staining. Results: Our study revealed a distinct metabolic signature of HBV-related HCC, marked by elevated acetyl-CoA, which was driven by ACSS2. ACSS2 was upregulated by the carbohydrate response element-binding protein in HBV-related HCC. Furthermore, ACSS2 improved tumor cell proliferation, an effect that was dependent on its enzymatic activity. Mechanistically, ACSS2-induced acetyl-CoA accumulation activated voltage-dependent anion channels 1 transcription through increased H3K27ac occupancy, which subsequently promoted mitophagy and HBV-related HCC tumorigenesis. Notably, targeting ACSS2 by depletion or inhibition with a catalytic inhibitor significantly suppressed tumor growth. Conclusions These findings not only illustrate the interplay between metabolic reprogramming, epigenetic modification, and tumorigenesis in the context of HBV infection, but also highlight ACSS2 as a novel metabolic vulnerability in HBV-related HCC. Therefore, targeting ACSS2 could be a novel strategy against HBV-related HCC.

ObjectiveTo investigate the application value of a machine learning model based on preoperative clinical indicators in predicting the risk of hypoalbuminemia after partial hepatectomy. MethodsA retrospective analysis was performed for the clinical data of 700 patients who underwent partial hepatectomy in Nanfang Hospital， Southern Medical University， from January 2018 to January 2023， including demographic data， history of underlying diseases， tumor characteristics， preoperative laboratory markers， and perioperative indicators. The research data were divided into a training set and a test set at a ratio of 7∶3. The two-independent-samples t test was used for comparison of normally distributed continuous data between two groups； the two-independent-samples Wilcoxon rank-sum test was used for comparison of continuous data with skewed distribution between two groups； the chi-square test or the Fisher’s exact test was used for comparison of categorical data between two groups. The least absolute shrinkage and selection operator （LASSO） regression analysis was used to identify characteristic variables， and 7 machine learning algorithms were used to construct predictive models， i.e.， logistic regression， decision tree， artificial neural network， K-nearest neighbors （KNN）， support vector machine， eXtreme gradient boosting， and light gradient boosting machine. The receiver operating characteristic （ROC） curve and the area under the ROC curve （AUC） were used to assess the discriminatory ability of models， and the DeLong test was used for comparison of AUC. The calibration curve and decision curve analysis were used to assess the calibration and clinical practicability of models， and the models were compared with albumin-bilirubin （ALBI） score and Model for End-Stage Liver Disease （MELD） score. SHapley Additive exPlanations （SHAP） were used to interpret the key influencing factors for the optimal model. ResultsA total of 700 patients were finally enrolled， 283 （40.42%） developed hypoalbuminemia after surgery. The LASSO regression analysis identified 8 predictive factors of age， hepatitis B， fatty liver， blockade time， preoperative albumin （Alb）， time of operation， intraoperative blood loss， and preoperative aspartate aminotransferase （AST）. Among the 7 machine learning models， the KNN model showed the best overall predictive performance， with an AUC of 0.835 （95% confidence interval： 0.781 — 0.889）， a sensitivity of 84.0%， and a specificity of 65.5% in the test set. ALBI and MELD scores had an AUC of 0.652 and 0.524， respectively， and the KNN model had a better predictive performance than these two scores （Z=5.309 and 8.945， both P <0.001）. The calibration curve showed good consistency between predicted probabilities and actual incidence rates， and the decision curve analysis showed that the KNN model had net clinical benefit across a wide threshold range. The SHAP analysis showed that preoperative Alb， hepatitis B， time of operation， and age were the most significant influencing factors， and a synergistic effect was observed between hepatitis B and age/time of operation. ConclusionThe KNN machine learning model constructed based on preoperative clinical indicators can effectively predict the risk of hypoalbuminemia after partial hepatectomy and has a better performance than traditional scoring models， which provides a reference for the early identification of high-risk patients in clinical practice.

ObjectiveTo explore the potential mechanism underlying electroacupuncture therapy with the midnight-noon ebb-low method with hour-prescription for chronic obstructive pulmonary disease （COPD） with lung-qi deficiency syndrome from the perspective of brain and muscle basic helix-loop-helix ARNT-like 1 （BMAL1） as well as neutrophil extracellular traps （NETs）. MethodsThe experiment was conducted in two phases. For the therapeutic effectiveness observation， 24 rats were randomly allocated into control group 1， model group 1， midnight-noon electro-acupuncture group 1 and conventional electro-acupuncture group， with 6 rats per group. Rat models of COPD with lung-qi deficiency syndrome were established via cigarette smoke exposure combined with intratracheal instillation of lipopolysaccharide （LPS）. After successful modelling， rats in midnight-noon electro-acupuncture group 1 received electro-acupuncture at acupoints "Taiyuan （LU 9）"， "Feishu （BL 13）" and "Zusanli （ST 36）" during 05：00—07：00， 30 minutes per treatment once every other day for 14 consecutive days （7 sessions in total）. Rats in the conventional electro-acupuncture group received identical electroacupuncture manipulation at random daytime hours （08：00—18：00）. Pulmonary function parameters including forced expiratory volume in 0.3 second （FEV_0.3）， forced vital capacity （FVC） and FEV_0.3/FVC ratio were detected. Pulmonary histopathological changes were observed via hematoxylin-eosin （HE） staining. Plasma levels of pro-inflammatory factors interleukin-1β （IL-1β） and tumor necrosis factor-α （TNF-α）， as well as pulmonary reactive oxygen species （ROS） content， BMAL1 protein expression and the levels of neutrophil extracellular traps （NETs） biomarkers such as myeloperoxidase （MPO）， neutrophil elastase （NE）， and citrullinated histone H3 （CitH3） in lung tissue were determined. For the mechanistic verification phase， 36 rats were divided into control group 2， model group 2， midnight-noon electro-acupuncture group 2， overexpression empty group， overexpression BMAL1 group and overexpression with midnight-noon electro-acupuncture group， with 6 rats in each group. At the 5th week of model construction， rats in the overexpression BMAL1 group and overexpression with midnight-noon electro-acupuncture group received intratracheal instillation of 100 μl adenoviral suspension carrying overexpressed Bmal1 gene. Rats in the overexpression empty group were injected with an equal titer and equal volume of blank adenovirus without the Bmal1 coding sequence into the lung at the identical time point. Midnight-noon electro-acupuncture group 2 and overexpression with midnight-noon electro-acupuncture group were consistent with the aforementioned protocol. Finally， pulmonary levels of MPO， NE and CitH3 were measured in all groups. ResultsCompared with the control group 1， the model group 1 exhibited decreased FEV_0.3， FVC and FEV_0.3/FVC ratio， elevated plasma IL-1β， TNF-α and pulmonary ROS levels， downregulated lung BMAL1 protein expression， and increased contents of MPO， NE and CitH3 （all P＜0.05）； typical NETs-like structures with sparse granular substances attached to fibrous networks were observed under scanning electron microscopy； HE staining revealed damaged alveolar architecture accompanied by inflammatory cell infiltration. Compared with model group 1， both the midnight-noon electro-acupuncture group 1 and conventional electro-acupuncture group achieved obvious improvements in all above indicators， with superior therapeutic effects in midnight-noon electro-acupuncture group 1 （P＜0.05）. Consistently， midnight-noon electro-acupuncture group 1 showed more prominent alleviation of NETs-like structure formation and lung pathological injury compared to the conventional electro-acupuncture group. Mechanistic validation results demonstrated that compared with model group 2， the average optical density of MPO as well as the protein levels of MPO， NE and CitH3 were markedly reduced in midnight-noon electro-acupuncture group 2， overexpression BMAL1 group and overexpression with midnight-noon electro-acupuncture group （P＜0.05）； furthermore， these parameters were significantly lower in the overexpression with midnight-noon electro-acupuncture group than in midnight-noon electro-acupuncture group 2 （P＜0.05）. ConclusionElectro-acupuncture based on the midnight-noon ebb-low method with hour-prescription may alleviate pulmonary inflammation in COPD by upregulating the expression of clock protein BMAL1 and inhibiting excessive accumulation of NETs in lung tissue.

Objective:To understand the current situation and influencing factors of functional constipation among elderly people in nursing homes, and construct a risk prediction model.Methods:Conveniently select 542 elderly people from 8 nursing homes in Tangshan urban area from July to November 2023 as the research subjects, use binary logistic regression analysis to construct a risk prediction model, and conduct internal validation of the model.Results:Among the 542 elderly people who were included in the study, there were 250 males and 292 females with an average age of 78.00 (70.00, 86.00) years. The incidence of functional constipation among elderly people in nursing homes was 54.06%(293/542). The predictive model includes six predictive factors: age, Barthel index, water intake, daily vegetable intake, insomnia, and perianal disease. The model AUC was 0.885 (95% CI 0.858-0.913), the Youden index was 0.628, the best critical value was 0.585, sensitivity was 0.819, specificity was 0.809. The Hosmer-Lemeshow test χ2=6.38, P=0.605. The internal validation results of the Bootstrap method showed that the AUC of the model was 0.876, the calibration curve was close to the standard line, and the Brier score was 0.135. The DCA results showed that the threshold was 0.1-0.9, and the model had good clinical net benefits. Conclusions:The incidence of functional constipation in elderly care institutions is relatively high. The functional constipation risk prediction model constructed in this study has good predictive efficacy and applicability, which can provide reference for nursing home staff.

Objective To investigate the efficacy and safety of lobaplatin in promoting liver wound healing following hepatectomy for patients with primary hepatocellular carcinoma.Methods From January 2019 to June 2024,120 patients with primary hepatocellular carcinoma(HCC)at CNLC stages Ia to IIa were randomly divided into an observation group(n=60)and a control group(n=60).The observation group underwent hepatectomy and received lobaplatin application on the liver wound during surgery,while the control group underwent hepatectomy alone without lobaplatin application.All patients were followed up for 66 months.Postoperative levels of ALT,AST,blood creatinine,white blood cells,and platelets were compared between the two groups.Additionally,the incidence of hemorrhage and bile leakage was compared,as well as the recurrence-free survival time after surgery.Results There were no significant differences between the two groups in terms of postoperative ALT,AST,blood creatinine,white blood cell count,or platelet levels(P>0.05).Additionally,no significant differences were ob-served in the incidence of postoperative hemorrhage and bile leakage between the two groups(P>0.05).However,a significant difference was noted in recurrence-free survival time between the groups(P>0.05),with the recurrence-free survival curve indicating a higher recurrence-free survival rate in the observation group compared to the control group(P>0.05).Conclusions Lobaplatin application for liver wound healing in hepatectomy of patients with primary hepatocellular carcinoma represents a feasible,safe,and effective adjuvant therapy.This approach can decrease the early recurrence rate in patients with early-stage primary hepatocellular carcinoma,making it worthy of clinical promotion.