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.

Reproductive system diseases are among the primary contributors to the decline in social fertility rates and the intensification of aging, posing significant threats to both physical and mental health, as well as quality of life. Recent research has revealed the substantial potential of the gut microbiota in improving reproductive system diseases. Under healthy conditions, the gut microbiota maintains a dynamic balance, whereas dysfunction can trigger immune-inflammatory responses, metabolic disorders, and other issues, subsequently leading to reproductive system diseases through the gut-gonadal axis. Reproductive diseases, in turn, can exacerbate gut microbiota imbalance. This article reviews the impact of the gut microbiota and its metabolites on both male and female reproductive systems, analyzing changes in typical gut microorganisms and their metabolites related to reproductive function. The composition, diversity, and metabolites of gut bacteria, such as Bacteroides, Prevotella, and Firmicutes, including short-chain fatty acids, 5-hydroxytryptamine, γ-aminobutyric acid, and bile acids, are closely linked to reproductive function. As reproductive diseases develop, intestinal immune function typically undergoes changes, and the expression levels of immune-related factors, such as Toll-like receptors and inflammatory cytokines (including IL-6, TNF-α, and TGF-β), also vary. The gut microbiota and its metabolites influence reproductive hormones such as estrogen, luteinizing hormone, and testosterone, thereby affecting folliculogenesis and spermatogenesis. Additionally, the metabolism and absorption of vitamins can also impact spermatogenesis through the gut-testis axis. As the relationship between the gut microbiota and reproductive diseases becomes clearer, targeted regulation of the gut microbiota can be employed to address reproductive system issues in both humans and animals. This article discusses the regulation of the gut microbiota and intestinal immune function through microecological preparations, fecal microbiota transplantation, and drug therapy to treat reproductive diseases. Microbial preparations and drug therapy can help maintain the intestinal barrier and reduce chronic inflammation. Fecal microbiota transplantation involves transferring feces from healthy individuals into the recipient’s intestine, enhancing mucosal integrity and increasing microbial diversity. This article also delves into the underlying mechanisms by which the gut microbiota influences reproductive capacity through the gut-gonadal axis and explores the latest research in diagnosing and treating reproductive diseases using gut microbiota. The goal is to restore reproductive capacity by targeting the regulation of the gut microbiota. While the gut microbiota holds promise as a therapeutic target for reproductive diseases, several challenges remain. First, research on the association between gut microbiota and reproductive diseases is insufficient to establish a clear causal relationship, which is essential for proposing effective therapeutic methods targeting the gut microbiota. Second, although gut microbiota metabolites can influence lipid, glucose, and hormone synthesis and metabolism via various signaling pathways—thereby indirectly affecting ovarian and testicular function—more in-depth research is required to understand the direct effects of these metabolites on germ cells or granulosa cells. Lastly, the specific efficacy of gut microbiota in treating reproductive diseases is influenced by multiple factors, necessitating further mechanistic research and clinical studies to validate and optimize treatment regimens.

BACKGROUND:Studies have shown that patients with premature ovarian failure have changes in the structure of intestinal flora and that imbalance of intestinal microbiota may be one of the important mechanisms in the development of premature ovarian failure. OBJECTIVE:To investigate the effect of Liuwei Dihuang Wan on oxidative stress and intestinal microbiota in premature ovarian failure mice induced by cyclophosphamide. METHODS:Forty-five female ICR mice were randomized into three groups:blank group(normal mice),model group(premature ovarian failure mice),and Liuwei Dihuang Wan group.A mouse model of premature ovarian failure was prepared by one-time intraperitoneal injection of cyclophosphamide(120 mg/kg)in the latter two groups.After successful modeling,the Liuwei Dihuang Wan group was intragastrically administered for 28 continuous days,and the other two groups were intragastrically administered with the same amount of normal saline for 28 days.Mouse body mass was recorded weekly and ovarian index was calculated.The development of mouse follicles was observed using hematoxylin-eosin staining.ELISA method was used to detect serum levels of anti-Mullerian hormone,estradiol,follicle stimulating hormone,superoxide dismutase,glutathione peroxidase,and malondialdehyde.Meanwhile,the gut microbiome of all mice was detected through 16S rDNA sequencing. RESULTS AND CONCLUSION:The mice in the model group had loose hair,decreased vigor and grip strength,almost no increase in body mass,and decreased ovarian index.Whereas,the mouse body mass and ovarian index were increased after treatment with Liuwei Dihuang Wan(P<0.05).The estrous cycle of mice in the model group was disorganized;Liuwei Dihuang Wan could restore the estrous cycle and reduce the number of atretic follicles in mice with premature ovarian failure.The serum levels of follicle stimulating hormone and malondialdehyde in the model group significantly increased(P<0.01),while the levels of estradiol,anti-Mullerian hormone,superoxide dismutase,and glutathione peroxidase significantly decreased(P<0.01).Liuwei Dihuang Wan could significantly decrease the serum levels of follicle stimulating hormone and malondialdehyde(P<0.01),and increase the levels of estradiol,anti-Mullerian hormone,superoxide dismutase,and glutathione peroxidase.According to the 16S rDNA sequencing results,Liuwei Dihuang Wan could regulate the abundance and diversity of intestinal microbiota,and increase the relative abundance of beneficial bacteria.KEGG pathway analysis showed that the intestinal microbiota and metabolic pathways,biosynthesis of secondary metabolites,microbial metabolism in different environments,and biosynthesis of amino acids were regulated by Liuwei Dihuang Wan.To conclude,the changes in the structure of intestinal microbiome may be one of the potential mechanisms of Liuwei Dihuang Wan in treating premature ovarian failure.Liuwei Dihuang Wan can regulate the structure of intestinal microbiome,increase the number of beneficial bacteria,reduce the number of harmful bacteria,and thus improve the balance of intestinal microbiota.This regulatory effect helps to reduce oxidative stress levels and further inhibit ovarian oxidative stress in mice with premature ovarian failure.

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.

Objective:To describes the probability and rate of native liver survival (NLS) in biliary atresia (BA) patients after Kasai portoenterostomy (KPE)over various time periods and analyzes the perioperative factors associated with liver transplantation or death.Methods:A retrospective case-summary.BA patients administrated at the Department of Fetal and Neonatal Surgery in Hunan Children′s Hospital between January 2015 and December 2021.Probability and rate of NLS were calculated by life table.Cox proportional hazards regression model and Logistic model was applied to explore the perioperative factors related to post-Kasai liver transplantation/death.Results:The median age at Kasai surgery was 62 days.The rate of jaundice clearance (JC) was 64.5% within 3 months after Kasai, and 58.3% of the patients had cholangitis.The probability of NLS reached its lowest point in the first 1 year after Kasai (76.2%) and ranged from 93.2% to 98.0% in years 2-8 after Kasai.The rates of NLS in 2 years, 5 years and 8 years were 71.1%, 62.8% and 56.0%, respectively.Cytomegalovirus (CMV) infection before or on the day of Kasai without antiviral treatment can increase the risk of liver transplantation or death[ HR(95% CI): 1.628 (1.081-2.452), P=0.020].Preoperative gamma-glutamyl transferase increased the risk of liver transplantation/death within 1 year after Kasai[ OR(95% CI): 1.001 (1.000-1.001), P=0.021], and early cholangitis was a risk factor for liver transplantation/death within 5 years after Kasai[ OR(95% CI): 1.934 (1.004-3.726), P=0.048].JC within 3 months post-KPE was a protective factor of NLS. Conclusions:The first year after Kasai was the highest risk period for liver transplantation/death, which should be the focus of follow-up management.JC within 3 months after surgery is the protective factor for overall NLS, 1-year NLS and 5-year NLS.

Objective:To describes the probability and rate of native liver survival (NLS) in biliary atresia (BA) patients after Kasai portoenterostomy (KPE)over various time periods and analyzes the perioperative factors associated with liver transplantation or death.Methods:A retrospective case-summary.BA patients administrated at the Department of Fetal and Neonatal Surgery in Hunan Children′s Hospital between January 2015 and December 2021.Probability and rate of NLS were calculated by life table.Cox proportional hazards regression model and Logistic model was applied to explore the perioperative factors related to post-Kasai liver transplantation/death.Results:The median age at Kasai surgery was 62 days.The rate of jaundice clearance (JC) was 64.5% within 3 months after Kasai, and 58.3% of the patients had cholangitis.The probability of NLS reached its lowest point in the first 1 year after Kasai (76.2%) and ranged from 93.2% to 98.0% in years 2-8 after Kasai.The rates of NLS in 2 years, 5 years and 8 years were 71.1%, 62.8% and 56.0%, respectively.Cytomegalovirus (CMV) infection before or on the day of Kasai without antiviral treatment can increase the risk of liver transplantation or death[ HR(95% CI): 1.628 (1.081-2.452), P=0.020].Preoperative gamma-glutamyl transferase increased the risk of liver transplantation/death within 1 year after Kasai[ OR(95% CI): 1.001 (1.000-1.001), P=0.021], and early cholangitis was a risk factor for liver transplantation/death within 5 years after Kasai[ OR(95% CI): 1.934 (1.004-3.726), P=0.048].JC within 3 months post-KPE was a protective factor of NLS. Conclusions:The first year after Kasai was the highest risk period for liver transplantation/death, which should be the focus of follow-up management.JC within 3 months after surgery is the protective factor for overall NLS, 1-year NLS and 5-year NLS.

Objective:To establish a model for predicting the occurrence of contrast-induced acute kidney injury(CI-AKI)after percutaneous coronary intervention(PCI)in patients with acute myocardial infarction(AMI).Meth-ods:A total of 767 AMI patients who underwent PCI in the Second Affiliated Hospital of Harbin Medical University between January 2019 and December 2023 were retrospectively included.According to presence of CI-AKI,pa-tients were divided into CI-AKI group(n=62)and non-CI-AKI group(n=705).The risk factors of CI-AKI in AMI patients undergoing PCI were analyzed using multivariant Logistic regression,and a prediction model was es-tablished.The model was evaluated using receiver operating characteristic(ROC)curve,calibration curve and clini-cal decision curve analysis(DCA).Results:Multivariant Logistic regression analysis showed that extensive anterior wall myocardial infarction(OR=1.520,95％CI:1.140～2.028,P=0.004),Killip class≥Ⅲ(OR=1.982,95％CI:1.406～2.793,P＜0.001),chronic renal insufficiency(OR=1.397,95％CI:1.025-1.903,P=0.034),ACEF(age,creatinine,ejection fraction)score(OR=1.702,95％CI:1.246～2.327,P＜0.001)and systemic im-mune-inflammation index(SII,OR=1.419,95％CI:1.090～1.847,P=0.009)were independent risk factors for CI-AKI after PCI in AMI patients.A prediction model of CI-AKI after PCI in AMI patients was established:Logit(P)=-1.667+0.334 ×(chronic renal insufficiency)+0.419 ×(extensive anterior wall myocardial infarc-tion)+0.684 ×(Killip class ≥Ⅲ)+0.350 × SII+0.532 ×(ACEF score).The ROC curve showed that the AUC of the model predicting CI-AKI was 0.868(95％CI:0.823-0.912,P＜0.001).The calibration curve showed a good fit of the predicted results to the actual curves(x2=0.421,P=0.506),and DCA showed net benefit when the high-risk threshold was between 5％and 70％.Conclusion:The prediction model for CI-AKI after PCI in AMI patients included extensive anterior wall myocardial infarction,Killip class,chronic renal insufficiency,ACEF score and SII,which had a good predictive performance for CI-AKI.

Objective:To develop and validate machine learning models for predicting the cumulative live birth rate (CLBR) following in vitro fertilization (IVF) and to analyze key predictive features using SHAP values. Methods:This retrospective study included data from patients who underwent IVF-embryo transfer at the Department of Reproductive Medicine, Baoding Maternal and Child Health Hospital, between January 2017 and December 2022. Patients were categorized into two groups based on live birth outcome: the live birth group ( n=1 036) and the non-live birth group ( n=756). The dataset was randomly divided into a training set and a validation set in a ratio of 7∶3. Five algorithms were utilized for model development: logistic regression, random forest, extreme gradient boosting (XGBoost), support vector machine, and neural networks. Model performance was assessed using the area under the receiver operating characteristic (AUC) curve, F1 score, and calibration curves. Clinical decision curve analysis (DCA) was employed to evaluate the clinical utility of the models. SHAP values were used to interpret feature importance in the XGBoost model and enhance its explainability. Results:The XGBoost model demonstrated the best performance in predicting CLBR,with accuracy of 72.44%, AUC of 0.775, and F1 score of 0.654, accuracy and F1 score outperforming logistic regression (accuracy was 70.02%, F1 score was 0.585), random forest (accuracy was 71.69%, F1 score was 0.606), support vector machine (accuracy was 70.20%, F1 score was 0.607), and neural network (accuracy was 68.72%, F1 score was 0.560). The calibration curve of XGBoost closely aligned with the diagonal line, indicating that the predicted probabilities were very close to the actual outcomes, demonstrating good calibration. DCA indicated that the XGBoost model provided higher net benefits across a wide range of clinical decision thresholds. SHAP value analysis identified number of previous IVF failures, antral follicle count, anti-Müllerian hormone level, percentage of normal sperm morphology, and sperm DNA fragmentation index as key predictors of CLBR.Conclusion:The XGBoost model exhibits excellent predictive performance and calibration for CLBR, with SHAP values providing important insights into feature importance. This model has the potential to support the development of personalized treatment strategies in clinical practice. However, its generalizability needs to be validated using external datasets to ensure its applicability to diverse populations.