Objective: To explore the related factors of college students social network addiction based on problem behavior theory, so as to provide a basis for improving social networking addiction in this population. Methods: From May to June 2023, a method combining convenient sampling and cluster random sampling was used to select 1 768 college students from five universities in Shanghai for a questionnaire survey on social networking addiction, self esteem, loneliness, depressive symptoms, social support, interpersonal needs, sense of distress and frustration; at the same time, the physical exercise, smoking and drinking of college students were investigated. Multivariate Logistic regression analysis was applied to explore the association between the three systems of the problem behavior theory (personality, behavior, and social environment) and social networking addiction among college students. Results: The score on the Social Network Addiction Tendency Scale was (21.08±6.29) among college students, and the detection rate of social networking addiction was 66.29%. After adjusting for gender, family economic status, parental divorce status, and whether being an only child, multivariate Logistic regression analysis showed that in the personality system, higher loneliness ( OR =1.66) and higher depressive symptoms ( OR =2.18) were associated with increased risk of social networking addiction among college students; in the behavior system, alcohol consumption ( OR =1.42) was associated with higher risk of soical networking addiction compared to non drinkers; and in the social environment system, low social support ( OR =1.43) was associated with increased risk of social networking addiction (all P <0.05). Conclusions The rate of social networking addiction among college students is relatively high, and the systems of personality, behavior, and social environment are all related to social network addiction. Providing social support, cultivating healthy lifestyle habits, and increasing interpersonal interactions may help reduce excessive dependence on social networking among college students.

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.

Plant-derived extracellular vesicles (PDEVs) are nanoscale extracellular vesicles secreted by plant cells, characterized by a lipid bilayer structure. These vesicles carry a variety of bioactive molecules, including proteins, nucleic acids, and lipids, and play essential roles in intercellular communication and physiological regulation in plants. Compared to animal-derived extracellular vesicles, PDEVs offer several advantages, such as a broad range of sources, high biocompatibility, low immunogenicity, and low production costs. Furthermore, PDEVs have demonstrated remarkable potential as natural nanocarriers for drug delivery, due to their ability to efficiently traverse biological barriers, such as the blood-brain barrier, making them promising candidates for drug delivery systems. This review systematically elaborates on the complex composition of PDEVs, which consists of lipids, proteins, and nucleic acids, the typical structural characteristics of their lipid bilayers ranging from 30 to 150 nm, and their versatile loading capabilities as drug carriers, efficiently encapsulating various types of therapeutic agents such as hydrophilic small molecules, hydrophobic drugs, nucleic acids, and proteins. We systematically summarize the recent advancements in strategies for enhancing the loading efficiency of PDEVs, which include methods such as co-incubation, ultrasound-assisted loading, electroporation, freeze-thaw cycles, and microfluidic technology. These techniques are evaluated based on their underlying principles, suitable drug types, and their respective advantages. In addition to loading strategies, we focus on the engineered approaches to achieve targeted delivery using PDEVs, such as genetic engineering modifications, chemical ligand conjugation, membrane fusion technology, and polyethylene glycol (PEG) modification. We discuss the mechanisms of these strategies in enhancing targeting efficiency, prolonging in vivo circulation time, and improving therapeutic efficacy. Further, this review highlights the application of PDEVs in various disease models, including tumor, skin inflammation, metabolic disorders, and neurodegenerative diseases, showcasing their therapeutic potential as multifunctional delivery platforms. The ability of PDEVs to encapsulate diverse therapeutic agents and target specific tissues or cells opens up new avenues for the treatment of complex diseases, offering advantages over conventional drug delivery systems. However, despite the promising applications of PDEVs, several challenges remain in their development and clinical translation. These challenges include variability in source materials, standardization of preparation processes, quality control, scalability of production, and the need for clinical validation. To overcome these obstacles, the integration of advanced technologies such as artificial intelligence-assisted design and multi-omics analysis is proposed as a way to facilitate the precise development of PDEVs. These emerging technologies hold the potential to further enhance the precision and effectiveness of plant-based drug delivery systems, ultimately advancing the field of precision medicine. In conclusion, the use of PDEVs as a platform for drug delivery represents a promising area of research with the potential to revolutionize therapeutic strategies. Their ability to encapsulate and deliver a wide variety of bioactive molecules, along with their inherent advantages in biocompatibility and versatility, makes them a valuable tool in the development of more efficient and targeted therapeutic interventions. Continued research and innovation in this field will pave the way for the clinical implementation of PDEVs in the treatment of various diseases, offering new hope for more effective and sustainable therapeutic options.

Acute kidney injury (AKI) is a prevalent and life-threatening clinical syndrome characterised by a rapid decline in renal function and diverse pathological etiologies. The condition has been demonstrated to be associated with elevated mortality rates and an increased risk of progression to chronic kidney disease. At present, clinicians depend heavily on conventional functional markers, such as serum creatinine and urine output, for the diagnosis and staging of the disease. It is evident that these conventional indicators characteristically manifest a considerable temporal delay and only undergo modification subsequent to considerable tissue damage. This severely restricts the timeframe for early detection and timely therapeutic intervention. Furthermore, standard markers fail to provide specific biological information regarding the underlying cellular injury mechanisms. The utilisation of advanced probe technologies in molecular imaging offers a robust alternative to overcome these inherent diagnostic limitations.This comprehensive review systematically evaluates recent progress in the design and application of two primary categories of molecular imaging tools for acute kidney disease, specifically reactive probes and enzyme-activated probes. Reactive probes are engineered to specifically interact with redox-active chemical species, including hydrogen peroxide, peroxynitrite, hypochlorous acid, and sulfur dioxide. Because oxidative stress constitutes a primary early event in acute renal tubular damage, these probes enable researchers and clinicians to visualize early cellular injury and radical accumulation well before global renal functional decline becomes evident. We discuss the application of these reactive probes across multiple imaging modalities including fluorescence imaging, magnetic resonance imaging (MRI), positron emission tomography (PET), and photoacoustic techniques. Photoacoustic imaging combines high spatial resolution with deep tissue penetration and has successfully demonstrated the ability to provide diagnostic alerts up to 12 h before any detectable rise in serum creatinine levels. Additionally, specific reactive probes have shown promising translational potential when tested by high-throughput screening in clinical human urine samples. Enzyme-activated probes target the specific catalytic activity of disease-relevant enzymes. These include well-documented renal tubular structural biomarkers such as NAG, GGT, and ALP, along with apoptosis-related caspases and specific nitroreductases. By responding only to enzymatic cleavage, these tools provide highly specific and pathology-directed imaging readouts. Recent structural design strategies in this field have advanced significantly beyond single-enzyme detection. Researchers are now focusing on sophisticated dual-target recognition to minimize background noise, multimodal integration to cross-validate imaging signals, and theranostic applications where probes simultaneously deliver diagnostic feedback and therapeutic agents to injured tissues. Nanotechnology serves as a fundamental enabler for realizing these advanced probe functions. By precisely optimizing nanoparticle parameters such as hydrodynamic size, surface charge, and targeting ligands, researchers can achieve amplified signal output, highly precise kidney delivery, and protection against premature degradation in the systemic circulation. For example, modifying surface charges can significantly enhance the active uptake of nanoprobes by damaged renal tubular epithelial cells.While preclinical probe development has progressed rapidly, moving these technologies into routine clinical practice remains a major challenge. We analyze the translational feasibility and current obstacles from biological, technological, and regulatory perspectives. Although biological targets such as KIM-1, FAP, and ALP have been validated in extensive patient cohorts, practical barriers severely limit their immediate clinical application. These obstacles involve complex changes in in vivo pharmacokinetics. During an acute injury episode, the extreme drop in the glomerular filtration rate alters probe clearance and can cause unwanted systemic accumulation or confusing background imaging signals. Other major hurdles include a lack of comprehensive long-term toxicity data and the absence of standardized manufacturing protocols to ensure batch-to-batch consistency. Future successful translation will require rigorous multi-center clinical studies to confirm the true diagnostic value of these probes over traditional markers. Researchers must also establish strict standardization of imaging procedures and comprehensive safety evaluations. Ultimately, this review provides a thorough reference framework for designing clinically translatable molecular probes and building a precision diagnostic imaging system for acute kidney injury.

OBJECTIVE To explore the efficacy and safety of toludesvenlafaxine in the treatment of patients with major depressive disorder （MDD） with anhedonia. METHODS This retrospective study included 160 patients with MDD with anhedonia who were treated at Hebei Mental Health Center from May 2023 to August 2025. These patients were divided into a control group （ n ＝81） and an observation group （ n ＝79） according to treatment regimens. All patients received transcranial magnetic stimulation therapy. On this basis，the control group was treated with Sertraline Hydrochloride Tablets， while the observation group received Toludesvenlafaxine Hydrochloride Sustained-Release Tablets，with an 8-week continuous treatment course.To compare t he clinical total effective rate， anhedonia remission rate，the severity of depressive symptoms，degree of anhedonia，cognitive function，social function and quality of life between the two groups before and after treatment， the incidence of adverse reactions during treatment was recorded simultaneously. RESULTS After treatment，the total effective rate and anhedonia remission rate of the observation group were significantly higher than the control group （ P ＜0.05）. At the 4th and 8th weeks of treatment， the scores of Snaith-Hamilton Pleasure Scale， Hamilton Depression Rating Scale-17 Items， and Sheehan Disability Scale of both groups were significantly lower than those before treatment in the same group， and the observation group was significantly lower than the control group （ P ＜0.05）； the scores of Montreal Cognitive Assessment and Quality of Life Enjoyment and Satisfaction Questionnaire-Short Form were significantly higher than those before treatment in the same group， and the observation group was significantly higher than the control group （ P ＜0.05）. There was no statistically significant difference in the overall incidence of adverse reactions between the two groups （ P ＞0.05）. CONCLUSIONS Toludesvenlafaxine can significantly improve depressive symptoms， cognitive function， and social function in MDD patients with anhedonia，with good safety.

Under the background of the medical model shifting from biomedicine to systems medicine， the traditional Chinese medicine （TCM） concept of "treating different diseases in the same way" demonstrates unique scientific value. From the perspective of systems biology， this study proposes that "treating different diseases in the same way" is essentially "treating the disease with same mechanism in the same way"； that is， different diseases share common pathological links at levels such as neuro-endocrine-immune network homeostasis， inflammatory signaling pathways， or gut microecology. Through the application of the "same formulas" and "same medicinals"， TCM intervenes in these shared network nodes. On this basis， the modern medical value of the "treating different diseases in the same way" concept is elucidated from three dimensions including "network causality" in epistemology， "systemic modulation" in methodology， and "comorbidity management" in practice. It reveals that as a life network regulation concept based on holism， "treating different diseases in the same way" provides novel diagnostic and therapeutic strategies for complex chronic diseases and multimorbidity.

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.

ObjectiveTo analyze the epidemiological and clinical characteristics of the 21 confirmed monkeypox cases in a district of Chengdu City, and to provide scientific guidance for the prevention and control of subsequent monkeypox epidemics. MethodsData of confirmed monkeypox cases residing in this district were collected from the Disease Control and Prevention Information System of China. A retrospective descriptive epidemiological analysis was used to analyze the demographic, distributional and behavioral characteristics of the cases. ResultsThe first confirmed case of monkeypox was reported on July 5, 2023. Up to April 30, 2025, a total of 21 confirmed cases of monkeypox have been reported. All cases were male, with a mean age of (30.9±6.2) years. The highest proportion of cases(47.62%) was in the 30‒40 years age group. The majority were men who have sex with men (MSM) population (90.48%, 19/21). The results showed that 19.05% of cases were co-infected with HIV, and 19.05% had a history of syphilis infection. Within 21 days prior to symptom onset, 19 cases (90.48%) self-reported engaging in male-to-male sexual contact, among whom 10 cases (52.63%) reported having taken protective measures, while 9 cases (47.37%) did not take safety precautions. Thirteen cases (61.90%) had no travel history to areas with reported monkeypox cases during the 21 days before symptom onset. The predominant manifestation was exanthem (100%, 21/21), followed by fever (57.14%, 12/21) and lymphadenectasis (47.62%, 10/21). Among febrile cases, 50.00% (6/12) had low-grade fever (37.3‒38.0 ℃). All cases were identified through active medical consultation. The median interval from symptom onset to the first medical visit was 3 (2, 6) days, with a maximum interval of 14 days. The median interval from symptom onset to laboratory confirmation was 7 (5, 9) days. Six cases (28.57%) had two or more visits to the hospital, with bacterial infection being the primary initial diagnosis. ConclusionMonkeypox prevention and control efforts in a district of Chengdu City should prioritize MSM population and young and middle-aged adults aged 30 to <40 years. It is recommended to establish an integrated monkeypox epidemic prevention and control network by leveraging existing HIV/AIDS prevention and control network. Concurrently, accelerating the deployment of the national intelligent infectious disease monitoring and early warning front-end software will strengthen early detection capabilities and be beneficial for the overall effectiveness of epidemic prevention and control efforts.

ObjectiveSpinal cord injury (SCI) directly impairs the regulatory function of the autonomic nervous system, induces intestinal dysfunction, and significantly reduces patients’ quality of life. Preclinical studies have shown that electroacupuncture (EA) therapy can regulate the brain-gut axis and is used to treat central nervous system diseases such as major depressive disorder, Alzheimer’s disease and Parkinson’s disease. Recent research has established that fecal microbiota transplantation (FMT) from EA-treated SCI rats restored intestinal motility and colonic morphology. However, it remains unclear whether the regulation of gut microbiota by EA therapy directly contributes to neural repair after SCI. This study aims to explore whether gut microbiota mediates the neuroprotective effect of EA in the treatment of SCI and its possible mechanism. MethodsThe study employed RNA transcriptome analysis of spinal cord tissue to characterize gene expression profiles and to identify key signaling pathways following EA treatment for SCI. Hematoxylin-Eosin (HE) staining and Nissl staining were used to observe the morphological changes in spinal cord tissue. Western blot (WB) and enzyme-linked immunosorbent assay (ELISA) were applied to detect the effects of EA on the expression of proteins related to nucleotide-binding domain leucine-rich repeat and pyrin domain-containing receptor 3 (NLRP3) -dependent pyroptosis. Using 16S rDNA sequencing, the study observed alterations in gut microbiota diversity and community composition in SCI rats. Prior to establishing SCI models, rats were pretreated with an antibiotic cocktail to induce gut dysbiosis, and the effects on intestinal function and spinal cord neural repair were evaluated. FMT was performed to investigate the regulatory effects of post-EA FMT on motor function, general status, liver and spleen indices, and NLRP3-mediated pyroptosis in SCI rats. ResultsEA improved motor function and reduced regulated neuronal cell death in SCI rats. Transcriptomic analysis demonstrated the activation of immune- and inflammation-related pathways post-SCI, including NOD-like receptors, nuclear factor-kappa B(NF-κB), and Toll-like receptor (TLR) pathways. EA primarily influenced intestinal inflammation and autoimmune functions. 16S rDNA sequencing illustrated that EA did not alter the diversity of gut microbiota. However, EA altered the gut microbiota composition in SCI rats, increasing Lactobacillus and Akkermansia genera while rebalancing the Firmicutes/Bacteroidetes ratio. Furthermore, depletion of gut microbiota by antibiotics disrupted the intestinal barrier, reduced the expression of intestinal barrier proteins Zonula Occludens-1 (ZO-1) and Occludin, elevated serum lipopolysaccharide-binding protein (LBP) levels, exacerbated spinal cord tissue damage, and hindered motor function recovery in SCI rats. FMT from donors treated with EA reduced LBP levels in the intestine, blood, and spinal cord of rats, inhibited the TLR4 myeloid differentiation primary response protein 88 (MyD88)-NF‑κB pathway and NLRP3-dependent pyroptosis, and improved motor function. On the other hand, FMT treatment resulted in decreased body weight and food intake, whereas FMT using EA-treated donors effectively alleviated these alterations. ConclusionEA effectively alleviated neuroinflammatory responses in rats with SCI, primarily through regulating the gut microbiota and suppressing the NLRP3-dependent pyroptosis signaling pathway.

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.