Objective To investigate the preventive effects of lidocaine administered through different routes on cardiovascular stress responses during anesthesia tracheal intubation. Methods Total 120 patients scheduled for elective surgery under general anesthesia were randomly divided into three groups: intravenous injection group （group IV）, throat spray group （group LJ）, and control group （group CT）, with 40 patients in each. Group IV received 50 mg of lidocaine via intravenous injection 1 minute before tracheal intubation. Group LJ received 50 mg of lidocaine sprayed into the pharyngeal cavity, glottis, and subglottic area. Group CT did not receive any treatment, and the remaining procedures were performed following the routine general anesthesia induction protocol. Heart rate （HR）, systolic blood pressure （SBP）, diastolic blood pressure （DBP）, and mean arterial pressure （MAP） were recorded at four time points: T₀ （before tracheal intubation）, T₁ （immediately after tracheal intubation）, T₂ （3 minutes after intubation）, and T₃ （5 minutes after intubation）. Statistical analysis of the data was performed using SPSS 22.0. Results There were no significant differences in HR at various time points within the group LJ. The changes in HR in the group IV and group CT were different statistically from those in the throat spray group. The blood pressure of patients in all three groups increased to varying degrees immediately after tracheal intubation, with the group CT showing particularly significant changes that differed significantly from both the group IV and the group LJ. The group LJ rapidly returned to levels close to those before intubation. Conclusion The preventive effects of lidocaine on stress responses during tracheal intubation were different depending on the route of administration. The inhibitory preventive effect of the throat spray method was superior to that of intravenous lidocaine, especially in preventing changes in heart rate.

Exercise-induced metabolic remodeling is a fundamental adaptive process whereby the body reorganizes systemic and cellular metabolism to meet the dynamic energy demands posed by physical activity. Emerging evidence reveals that such remodeling not only enhances energy homeostasis but also profoundly influences immune function through complex molecular interactions involving glucose, lipid, and protein metabolism. This review presents an in-depth synthesis of recent advances, elucidating how exercise modulates immune regulation via metabolic reprogramming, highlighting key molecular mechanisms, immune-metabolic signaling axes, and the authors’ academic perspective on the integrated “exercise-metabolism-immunity” network. In the domain of glucose metabolism, regular exercise improves insulin sensitivity and reduces hyperglycemia, thereby attenuating glucose toxicity-induced immune dysfunction. It suppresses the formation of advanced glycation end-products (AGEs) and interrupts the AGEs-RAGE-inflammation positive feedback loop in innate and adaptive immune cells. Importantly, exercise-induced lactate, traditionally viewed as a metabolic byproduct, is now recognized as an active immunomodulatory molecule. At high concentrations, lactate can suppress immune function through pH-mediated effects and GPR81 receptor activation. At physiological levels, it supports regulatory T cell survival, promotes macrophage M2 polarization, and modulates gene expression via histone lactylation. Additionally, key metabolic regulators such as AMPK and mTOR coordinate immune cell energy balance and phenotype; exercise activates the AMPK-mTOR axis to favor anti-inflammatory immune cell profiles. Simultaneously, hypoxia-inducible factor-1α (HIF-1α) is transiently activated during exercise, driving glycolytic reprogramming in T cells and macrophages, and shaping the immune landscape. In lipid metabolism, exercise alleviates adipose tissue inflammation by reducing fat mass and reshaping the immune microenvironment. It promotes the polarization of adipose tissue macrophages from a pro-inflammatory M1 phenotype to an anti-inflammatory M2 phenotype. Moreover, exercise alters the secretion profile of adipokines—raising adiponectin levels while reducing leptin and resistin—thereby influencing systemic immune balance. At the circulatory level, exercise improves lipid profiles by lowering pro-inflammatory free fatty acids (particularly saturated fatty acids) and triglycerides, while enhancing high-density lipoprotein (HDL) function, which has immunoregulatory properties such as endotoxin neutralization and macrophage cholesterol efflux. Regarding protein metabolism, exercise triggers the expression of heat shock proteins (HSPs) that act as intracellular chaperones and extracellular immune signals. Exercise also promotes the secretion of myokines (e.g., IL-6, IL-15, irisin, FGF21) from skeletal muscle, which modulate immune responses, facilitate T cell and macrophage function, and support immunological memory. Furthermore, exercise reshapes amino acid metabolism, particularly of glutamine, arginine, and branched-chain amino acids (BCAAs), thereby influencing immune cell proliferation, biosynthesis, and signaling. Leucine-mTORC1 signaling plays a key role in T cell fate, while arginine metabolism governs macrophage polarization and T cell activation. In summary, this review underscores the complex, bidirectional relationship between exercise and immune function, orchestrated through metabolic remodeling. Future research should focus on causative links among specific metabolites, signaling pathways, and immune phenotypes, as well as explore the epigenetic consequences of exercise-induced metabolic shifts. This integrated perspective advances understanding of exercise as a non-pharmacological intervention for immune regulation and offers theoretical foundations for individualized exercise prescriptions in health and disease contexts.

ObjectiveTo explore the effect and mechanism of Qigui Didang decoction， formulated based on the principle of Tonifying Deficiency and Unblocking Collaterals， on improving metabolic memory of db/db mice with diabetic nephropathy （DN） through silent information regulator 1 signal regulator 1 （Sirt1）/p53/nuclear factor kappa-B （NF-κB） p65 pathway. MethodsFifteen db/db mice were randomly divided into model group （10 mL·kg^-1·d^-1）， resveratrol group （20 mg·kg^-1·d^-1）， and Qigui Didang decoction group （3.34 g·kg^-1·d^-1） Another five db/m mice were selected as the normal group （10 mL·kg^-1·d^-1）. After the intervention， the kidney weight of each group was measured， and the kidney index （KI） was calculated. Fasting blood glucose （FBG）， creatinine （CRE）， β2-microglobulin （β2-MG）， blood urea nitrogen （BUN）， and cystatin C （CysC） were measured. Renal pathology was observed by hematoxylin-eosin （HE） staining and Masson staining. The mRNA and protein expression levels of Sirt1， NF-κB， tumor suppressor gene p53， interleukin-1β （IL-1β）， and cysteine aspartate protease-3 （Caspase-3） were detected using real-time quantitative polymerase chain reaction （Real-time PCR） and Western blot. ResultsCompared with the normal group， the model group showed disordered renal structure， obvious renal damage， and markedly elevated levels of renal function indexes （CRE， β2-MG， BUN， and CysC） （P<0.01）. The KI and blood glucose were significantly increased （P<0.01）， while Sirt1 expression was markedly decreased （P<0.01）. Expression levels of NF-κB p65， p53， IL-1β， and Caspase-3 were increased significantly （P<0.05）. Compared with those in the model group， DN mice treated with Qigui Didang decoction exhibited significantly decreased FBG， improved renal function， and markedly decreased KI （P<0.01）， along with reduced CRE， β2-MG， BUN， and CysC levels （P<0.05）. Protein expression of Sirt1 was significantly upregulated （P<0.05）， while that of NF-κB p65， p53， IL-1β， and Caspase-3 was markedly decreased （P<0.05）. The mRNA expression levels of NF-κB p65， p53， IL-1β， and Caspase-3 were significantly decreased （P<0.05）. The staining results indicate improved renal fibrosis， significantly decreased fiber deposition （P<0.05）， and less inflammatory infiltration in the Qigui Didang decoction group. ConclusionThe findings suggest that Qigui Didang decoction can alleviate the metabolic memory effect of DN， thereby inhibiting renal cell apoptosis and inflammatory response in mice， and improving renal function. The mechanism of action is closely related to the Sirt1/p53/NF-κB p65 signaling pathway.

In recent years, the application of artificial intelligence (AI) in the field of biology has witnessed remarkable advancements. Among these, the most notable achievements have emerged in the domain of protein structure prediction and design, with AlphaFold and related innovations earning the 2024 Nobel Prize in Chemistry. These breakthroughs have transformed our ability to understand protein folding and molecular interactions, marking a pivotal milestone in computational biology. Looking ahead, it is foreseeable that the accurate prediction of various physicochemical properties of proteins—beyond static structure—will become the next critical frontier in this rapidly evolving field. One of the most important protein properties is thermodynamic stability, which refers to a protein’s ability to maintain its native conformation under physiological or stress conditions. Accurate prediction of protein stability, especially upon single-point mutations, plays a vital role in numerous scientific and industrial domains. These include understanding the molecular basis of disease, rational drug design, development of therapeutic proteins, design of more robust industrial enzymes, and engineering of biosensors. Consequently, the ability to reliably forecast the stability changes caused by mutations has broad and transformative implications across biomedical and biotechnological applications. Historically, protein stability was assessed via experimental methods such as differential scanning calorimetry (DSC) and circular dichroism (CD), which, while precise, are time-consuming and resource-intensive. This prompted the development of computational approaches, including empirical energy functions and physics-based simulations. However, these traditional models often fall short in capturing the complex, high-dimensional nature of protein conformational landscapes and mutational effects. Recent advances in machine learning (ML) have significantly improved predictive performance in this area. Early ML models used handcrafted features derived from sequence and structure, whereas modern deep learning models leverage massive datasets and learn representations directly from data. Deep neural networks (DNNs), graph neural networks (GNNs), and attention-based architectures such as transformers have shown particular promise. GNNs, in particular, excel at modeling spatial and topological relationships in molecular structures, making them well-suited for protein modeling tasks. Furthermore, attention mechanisms enable models to dynamically weigh the contribution of specific residues or regions, capturing long-range interactions and allosteric effects. Nevertheless, several key challenges remain. These include the imbalance and scarcity of high-quality experimental datasets, particularly for rare or functionally significant mutations, which can lead to biased or overfitted models. Additionally, the inherently dynamic nature of proteins—their conformational flexibility and context-dependent behavior—is difficult to encode in static structural representations. Current models often rely on a single structure or average conformation, which may overlook important aspects of stability modulation. Efforts are ongoing to incorporate multi-conformational ensembles, molecular dynamics simulations, and physics-informed learning frameworks into predictive models. This paper presents a comprehensive review of the evolution of protein thermodynamic stability prediction techniques, with emphasis on the recent progress enabled by machine learning. It highlights representative datasets, modeling strategies, evaluation benchmarks, and the integration of structural and biochemical features. The aim is to provide researchers with a structured and up-to-date reference, guiding the development of more robust, generalizable, and interpretable models for predicting protein stability changes upon mutation. As the field moves forward, the synergy between data-driven AI methods and domain-specific biological knowledge will be key to unlocking deeper understanding and broader applications of protein engineering.

ObjectiveRepetitive transcranial magnetic stimulation (rTMS) has demonstrated efficacy in enhancing neurocognitive performance in Alzheimer’s disease (AD), but the neurobiological mechanisms linking synaptic pathology, neural oscillatory dynamics, and brain network reorganization remain unclear. This investigation seeks to systematically evaluate the therapeutic potential of rTMS as a non-invasive neuromodulatory intervention through a multimodal framework integrating clinical assessments, molecular profiling, and neurophysiological monitoring. MethodsIn this prospective double-blind trial, 12 AD patients underwent a 14-day protocol of 20 Hz rTMS, with comprehensive multimodal assessments performed pre- and post-intervention. Cognitive functioning was quantified using the mini-mental state examination (MMSE) and Montreal cognitive assessment (MOCA), while daily living capacities and neuropsychiatric profiles were respectively evaluated through the activities of daily living (ADL) scale and combined neuropsychiatric inventory (NPI)-Hamilton depression rating scale (HAMD). Peripheral blood biomarkers, specifically Aβ1-40 and phosphorylated tau (p-tau181), were analyzed to investigate the effects of rTMS on molecular metabolism. Spectral power analysis was employed to investigate rTMS-induced modulations of neural rhythms in AD patients, while brain network analyses incorporating topological properties were conducted to examine stimulus-driven network reorganization. Furthermore, systematic assessment of correlations between cognitive scale scores, blood biomarkers, and network characteristics was performed to elucidate cross-modal therapeutic associations. ResultsClinically, MMSE and MOCA scores improved significantly (P<0.05). Biomarker showed that Aβ1-40 level increased (P<0.05), contrasting with p-tau181 reduction. Moreover, the levels of Aβ1-40 were positively correlated with MMSE and MOCA scores. Post-intervention analyses revealed significant modulations in oscillatory power, characterized by pronounced reductions in delta (P<0.05) and theta bands (P<0.05), while concurrent enhancements were observed in alpha, beta, and gamma band activities (all P<0.05). Network analysis revealed frequency-specific reorganization: clustering coefficients were significantly decreased in delta, theta, and alpha bands (P<0.05), while global efficiency improvement was exclusively detected in the delta band (P<0.05). The alpha band demonstrated concurrent increases in average nodal degree (P<0.05) and characteristic path length reduction (P<0.05). Further research findings indicate that the changes in the clinical scale HAMD scores before and after rTMS stimulation are negatively correlated with the changes in the blood biomarkers Aβ1-40 and p-tau181. Additionally, the changes in the clinical scales MMSE and MoCA scores were negatively correlated with the changes in the node degree of the alpha frequency band and negatively correlated with the clustering coefficient of the delta frequency band. However, the changes in MMSE scores are positively correlated with the changes in global efficiency of both the delta and alpha frequency bands. Conclusion20 Hz rTMS targeting dorsolateral prefrontal cortex (DLPFC) significantly improves cognitive function and enhances the metabolic clearance of β-amyloid and tau proteins in AD patients. This neurotherapeutic effect is mechanistically associated with rTMS-mediated frequency-selective neuromodulation, which enhances the connectivity of oscillatory networks through improved neuronal synchronization and optimized topological organization of functional brain networks. These findings not only support the efficacy of rTMS as an adjunctive therapy for AD but also underscore the importance of employing multiple assessment methods—including clinical scales, blood biomarkers, and EEG——in understanding and monitoring the progression of AD. This research provides a significant theoretical foundation and empirical evidence for further exploration of rTMS applications in AD treatment.

In recent years, the deep integration of artificial intelligence (AI) into medical education has created new opportunities for teaching Biochemistry and Molecular Biology, while also offering innovative solutions to the pedagogical challenges associated with protein structure and function. Focusing on the case of anaplastic lymphoma kinase (ALK) gene mutations in non-small-cell lung cancer (NSCLC), this study integrates AI into case-based learning (CBL) to develop an AI-CBL hybrid teaching model. This model features an intelligent case-generation system that dynamically constructs ALK mutation scenarios using real-world clinical data, closely linking molecular biology concepts with clinical applications. It incorporates AI-powered protein structure prediction tools to accurately visualize the three-dimensional structures of both wild-type and mutant ALK proteins, dynamically simulating functional abnormalities resulting from conformational changes. Additionally, a virtual simulation platform replicates the ALK gene detection workflow, bridging theoretical knowledge with practical skills. As a result, a multidimensional teaching system is established—driven by clinical cases and integrating molecular structural analysis with experimental validation. Teaching outcomes indicate that the three-dimensional visualization, dynamic interactivity, and intelligent analytical capabilities provided by AI significantly enhance students’ understanding of molecular mechanisms, classroom engagement, and capacity for innovative research. This model establishes a coherent training pathway linking “fundamental theory-scientific research thinking-clinical practice”, offering an effective approach to addressing teaching challenges and advancing the intelligent transformation of medical education.

ObjectiveTraditional Chinese medicine (TCM) constitutes a valuable cultural heritage and an important source of antitumor compounds. Poria (Poria cocos (Schw.) Wolf), the dried sclerotium of a polyporaceae fungus, was first documented in Shennong’s Classic of Materia Medica and has been used therapeutically and dietarily in China for millennia. Traditionally recognized for its diuretic, spleen-tonifying, and sedative properties, modern pharmacological studies confirm that Poria exhibits antioxidant, anti-inflammatory, antibacterial, and antitumor activities. Pachymic acid (PA; a triterpenoid with the chemical structure 3β-acetyloxy-16α-hydroxy-lanosta-8,24(31)-dien-21-oic acid), isolated from Poria, is a principal bioactive constituent. Emerging evidence indicates PA exerts antitumor effects through multiple mechanisms, though these remain incompletely characterized. Neuroblastoma (NB), a highly malignant pediatric extracranial solid tumor accounting for 15% of childhood cancer deaths, urgently requires safer therapeutics due to the limitations of current treatments. Although PA shows multi-mechanistic antitumor potential, its efficacy against NB remains uncharacterized. This study systematically investigated the potential molecular targets and mechanisms underlying the anti-NB effects of PA by integrating network pharmacology-based target prediction with experimental validation of multi-target interactions through molecular docking, dynamic simulations, and in vitro assays, aimed to establish a novel perspective on PA’s antitumor activity and explore its potential clinical implications for NB treatment by integrating computational predictions with biological assays. MethodsThis study employed network pharmacology to identify potential targets of PA in NB, followed by validation using molecular docking, molecular dynamics (MD) simulations, MM/PBSA free energy analysis, RT-qPCR and Western blot experiments. Network pharmacology analysis included target screening via TCMSP, GeneCards, DisGeNET, SwissTargetPrediction, SuperPred, and PharmMapper. Subsequently, potential targets were predicted by intersecting the results from these databases via Venn analysis. Following target prediction, topological analysis was performed to identify key targets using Cytoscape software. Molecular docking was conducted using AutoDock Vina, with the binding pocket defined based on crystal structures. MD simulations were performed for 100 ns using GROMACS, and RMSD, RMSF, SASA, and hydrogen bonding dynamics were analyzed. MM/PBSA calculations were carried out to estimate the binding free energy of each protein-ligand complex. In vitro validation included RT-qPCR and Western blot, with GAPDH used as an internal control. ResultsThe CCK-8 assay demonstrated a concentration-dependent inhibitory effect of PA on NB cell viability. GO analysis suggested that the anti-NB activity of PA might involve cellular response to chemical stress, vesicle lumen, and protein tyrosine kinase activity. KEGG pathway enrichment analysis suggested that the anti-NB activity of PA might involve the PI3K/AKT, MAPK, and Ras signaling pathways. Molecular docking and MD simulations revealed stable binding interactions between PA and the core target proteins AKT1, EGFR, SRC, and HSP90AA1. RT-qPCR and Western blot analyses further confirmed that PA treatment significantly decreased the mRNA and protein expression of AKT1, EGFR, and SRC while increasing the HSP90AA1 mRNA and protein levels. ConclusionIt was suggested that PA may exert its anti-NB effects by inhibiting AKT1, EGFR, and SRC expression, potentially modulating the PI3K/AKT signaling pathway. These findings provide crucial evidence supporting PA’s development as a therapeutic candidate for NB.

ObjectiveTo explore the effect of modified Lianpoyin formula （LPYJWF） in the treatment of Helicobacter pylori （Hp）-associated gastric mucosal damage based on mitochondrial autophagy and NLRP3 inflammasome signaling pathway. MethodsA total of 60 eight-week-old Balb/c male mice were assigned via the random number table method into control， model， high-dose LPYJWF （LPYJWF-H， 27.3 g·kg^-1·d^-1）， medium-dose LPYJWF （LPYJWF-M， 13.65 g·kg^-1·d^-1）， low-dose LPYJWF （LPYJWF-L， 6.83 g·kg^-1·d^-1）， and quadruple therapy groups. Except the control group， other groups were modeled for Hp infection. Mice were administrated with LPYJWF at corresponding doses by gavage. Quadruple therapy group was given omeprazole （6.06 mg·kg^-1·d^-1） + amoxicillin （303 mg·kg^-1·d^-1） + clarithromycin （151.67 mg·kg^-1·d^-1） + colloidal pectin capsules （30.3 mg·kg^-1·d^-1） by gavage. The control group was given an equal volume of 0.9% NaCl for 14 days. Hematoxylin-eosin （HE） staining was used to observe the pathological changes of gastric mucosa， and Warthin-Starry （W-S） silver staining was used to detect Hp colonization. Transmission electron microscopy was employed to observe the mitochondrial ultrastructure of the gastric tissue， and immunofluorescence co-localization assay was adopted to detect the expression of mitochondrial transcription factor A （TFAM） and translocase of the outer mitochondrial membrane member 20 （TOMM20）. The water-soluble tetrazolium salt method and thiobarbituric acid method were used to determine the levels of superoxide dismutase （SOD） and malondialdehyde （MDA）， respectively， in the gastric tissue. Western blot was employed to measure the protein levels of PTEN-induced kinase 1 （PINK1）， Parkin， p62， microtubule-associated protein 1 light chain 3 （LC3）， NOD-like receptor protein 3 （NLRP3）， apoptosis-associated speck-like protein containing a CARD （ASC）， interleukin-1β （IL-1β）， and interleukin-18 （IL-18）. Real-time quantitative PCR was employed to assess the mRNA levels of PINK1， Parkin， p62， and LC3. ResultsCompared with the control group， the model group presented obvious gastric mucosal damage， colonization of a large number of Hp， severe mitochondrial damage， vacuolated structures due to excessive autophagy， reduced TOMM20 and TFAM co-expression in the gastric mucosal tissue， and reduced SOD and increased MDA （P<0.01）. In addition， the gastric tissue in the model group showed up-regulated protein and mRNA levels of PINK1， Parkin， and LC3 and down-regulated protein and mRNA levels of p62 （P<0.01， as well as increased expression of inflammasome-associated proteins NLRP3， ASC， IL-1β， and IL-18 （P<0.01）. Compared with the model group， the LPYJWF and quadruple therapy groups showed alleviated pathological damage of gastric mucosa， reduced Hp colonization， mitigated mitochondrial damage， and increased co-expression of TOMM20 and TFAM. The SOD level was elevated in the LPYJWF-L group （P<0.01）， and the MDA levels became lowered in the LPYJWF and quadruple therapy groups （P<0.05， P<0.01）. Furthermore， the LPYJWF and quadruple therapy groups showed down-regulated mRNA levels of PINK1， Parkin， and LC3 and protein levels of PINK1 and Parkin， and up-regulated mRNA level of p62 （P<0.01）. The LPYJWF-M， LPYJWF-H， and quadruple therapy groups showcased down-regulated LC3 Ⅱ/LC3 Ⅰ level （P<0.05， P<0.01） and up-regulated protein level of p62 （P<0.01）. The expression of inflammasome-associated proteins NLRP3， ASC， IL-1β， and IL-18 were reduced in the LPYJWF and quadruple therapy groups （P<0.05， P<0.01）. ConclusionLPYJWF ameliorates gastric mucosal damage and exerts mucosa-protective effects in Hp-infected mice， which may be related to the inhibition of excessive mitochondrial autophagy， thereby inhibiting the activation of the NLRP3 inflammasome pathway.

ObjectiveTo explore the effect of modified Lianpoyin formula （LPYJWF） in the treatment of Helicobacter pylori （Hp）-associated gastric mucosal damage based on mitochondrial autophagy and NLRP3 inflammasome signaling pathway. MethodsA total of 60 eight-week-old Balb/c male mice were assigned via the random number table method into control， model， high-dose LPYJWF （LPYJWF-H， 27.3 g·kg^-1·d^-1）， medium-dose LPYJWF （LPYJWF-M， 13.65 g·kg^-1·d^-1）， low-dose LPYJWF （LPYJWF-L， 6.83 g·kg^-1·d^-1）， and quadruple therapy groups. Except the control group， other groups were modeled for Hp infection. Mice were administrated with LPYJWF at corresponding doses by gavage. Quadruple therapy group was given omeprazole （6.06 mg·kg^-1·d^-1） + amoxicillin （303 mg·kg^-1·d^-1） + clarithromycin （151.67 mg·kg^-1·d^-1） + colloidal pectin capsules （30.3 mg·kg^-1·d^-1） by gavage. The control group was given an equal volume of 0.9% NaCl for 14 days. Hematoxylin-eosin （HE） staining was used to observe the pathological changes of gastric mucosa， and Warthin-Starry （W-S） silver staining was used to detect Hp colonization. Transmission electron microscopy was employed to observe the mitochondrial ultrastructure of the gastric tissue， and immunofluorescence co-localization assay was adopted to detect the expression of mitochondrial transcription factor A （TFAM） and translocase of the outer mitochondrial membrane member 20 （TOMM20）. The water-soluble tetrazolium salt method and thiobarbituric acid method were used to determine the levels of superoxide dismutase （SOD） and malondialdehyde （MDA）， respectively， in the gastric tissue. Western blot was employed to measure the protein levels of PTEN-induced kinase 1 （PINK1）， Parkin， p62， microtubule-associated protein 1 light chain 3 （LC3）， NOD-like receptor protein 3 （NLRP3）， apoptosis-associated speck-like protein containing a CARD （ASC）， interleukin-1β （IL-1β）， and interleukin-18 （IL-18）. Real-time quantitative PCR was employed to assess the mRNA levels of PINK1， Parkin， p62， and LC3. ResultsCompared with the control group， the model group presented obvious gastric mucosal damage， colonization of a large number of Hp， severe mitochondrial damage， vacuolated structures due to excessive autophagy， reduced TOMM20 and TFAM co-expression in the gastric mucosal tissue， and reduced SOD and increased MDA （P<0.01）. In addition， the gastric tissue in the model group showed up-regulated protein and mRNA levels of PINK1， Parkin， and LC3 and down-regulated protein and mRNA levels of p62 （P<0.01， as well as increased expression of inflammasome-associated proteins NLRP3， ASC， IL-1β， and IL-18 （P<0.01）. Compared with the model group， the LPYJWF and quadruple therapy groups showed alleviated pathological damage of gastric mucosa， reduced Hp colonization， mitigated mitochondrial damage， and increased co-expression of TOMM20 and TFAM. The SOD level was elevated in the LPYJWF-L group （P<0.01）， and the MDA levels became lowered in the LPYJWF and quadruple therapy groups （P<0.05， P<0.01）. Furthermore， the LPYJWF and quadruple therapy groups showed down-regulated mRNA levels of PINK1， Parkin， and LC3 and protein levels of PINK1 and Parkin， and up-regulated mRNA level of p62 （P<0.01）. The LPYJWF-M， LPYJWF-H， and quadruple therapy groups showcased down-regulated LC3 Ⅱ/LC3 Ⅰ level （P<0.05， P<0.01） and up-regulated protein level of p62 （P<0.01）. The expression of inflammasome-associated proteins NLRP3， ASC， IL-1β， and IL-18 were reduced in the LPYJWF and quadruple therapy groups （P<0.05， P<0.01）. ConclusionLPYJWF ameliorates gastric mucosal damage and exerts mucosa-protective effects in Hp-infected mice， which may be related to the inhibition of excessive mitochondrial autophagy， thereby inhibiting the activation of the NLRP3 inflammasome pathway.

To analyze the in vitro antibacterial effects of colistin (COL) or tigecycline (TGC) in combination with imipenem (IPM), amikacin (AMK), and cefoperazone-sulbactam (CSL) against carbapenem-resistant Acinetobacter baumannii(CRAB), so as to provide evidence for screening effective combination regimens for clinical microbial infections.