BACKGROUND:Steroid-induced femoral head necrosis is mostly caused by long-term and extensive use of hormones,but its specific pathogenesis is not yet clear and needs further study. OBJECTIVE:To screen out the differential miRNAs in osteoclast exosomes after the intervention of Panax notoginseng saponins,and on this basis,to further construct an osteogenic-related ferroptosis regulatory network to explore the potential mechanism and research direction of steroid-induced osteonecrosis of the femoral head. METHODS:MTT assay was used to detect the toxic effects of different concentrations of dexamethasone and different mass concentrations of Panax notoginseng saponins on Raw264.7 cell line.Tartrate resistant acid phosphatase staining and TUNEL assay were used to detect the effects of Panax notoginseng saponins on osteoclast inhibition and apoptosis.Exosomes were extracted from cultured osteoclasts with Panax notoginseng saponins intervention.Exosomes from different groups were sequenced to identify differentially expressed miRNAs.CytoScape 3.9.1 was used to construct and visualize the regulatory network between differentially expressed miRNAs and mRNAs.Candidate mRNAs were screened by GO analysis and KEGG analysis.Finally,the differential genes related to ferroptosis were screened out,and the regulatory network of ferroptosis-related genes was constructed. RESULTS AND CONCLUSION:(1)The concentration of dexamethasone(0.1 μmol/L)and Panax notoginseng saponins(1 736.85 μg/mL)suitable for intervention of Raw264.7 cells was determined by MTT assay.(2)Panax notoginseng saponins had an inhibitory effect on osteoclasts and could promote their apoptosis.(3)Totally 20 differentially expressed miRNAs were identified from osteoclast-derived exosome samples,and 11 differentially expressed miRNAs related to osteogenesis were predicted by target mRNAs.The regulatory networks of 4 up-regulated differentially expressed miRNAs corresponding to 155 down-regulated candidate mRNAs and 7 down-regulated differentially expressed miRNAs corresponding to 238 up-regulated candidate mRNAs were constructed.(4)Twenty-four genes related to ferroptosis were screened out from the differential genes.Finally,12 networks were constructed(miR-98-5p/PTGS2,miR-23b-3p/PTGS2,miR-425-5p/TFRC,miR-133a-3p/TFRC,miR-185-5p/TFRC,miR-23b-3p/NFE2L2,miR-23b-3p/LAMP2,miR-98-5p/LAMP2,miR-182-5p/LAMP2,miR-182-5p/TLR4,miR-23b-3p/ZFP36,and miR-182-5p/ZFP36).These results indicate that Panax notoginseng saponins may regulate osteoblast ferroptosis by regulating the expression of miRNAs derived from osteoclast exosomes,thus providing a new idea for the study of the mechanism of steroid-induced femoral head necrosis.

ObjectiveTo explore the spatial distribution patterns of flavonoid glycosides in Epimedium sagittatum and the influences of environmental factors on the accumulation of these components. MethodsThe spatial statistical analysis and GeoDetector model were used to analyze the distribution patterns of epimedin A，epimedin B，epimedin C，icariin，and total flavonoid glycosides in E. sagittatum samples from 92 different production areas in 36 cities of 13 provinces/municipalities/autonomous regions of China，as well as the effects of 28 environmental factors on the accumulation of each component. ResultsThe average content of flavonoid glycosides 64 （69.56%） producing areas and 30 （83.33%） cities met the quality standard of no less than 1.50% of total flavonoid glycosides in the 2020 edition of Chinese Pharmacopoeia.Epimedin A，epimedin B，epimedin C，icariin，and their sum showed significantly high accumulation.The hot spots regions of epimedin A and epimedin B were similar with each other，mainly located in western Hunan，eastern Hubei，eastern Guizhou，and northern Guangxi.The common hot spot areas of epimedin C and total flavonoid glycosides were in western and southwestern Hunan，southern Henan，northern Anhui，eastern Guizhou，and southern Chongqing.The hot spots areas of icariin were in southern Chongqing，western Hunan，and eastern and northeastern Guizhou.The interactions between environmental factors had stronger explanatory power for the accumulation of components than single factors.The strongest single factor and interactive factor affecting the accumulation of epimedin C were precipitation of wettest quarter （q=0.16） and its interaction with temperature seasonality （q=0.35），respectively.The strongest single factor influencing both the accumulation of icariin and total flavonoid glycosides was the precipitation of coldest quarter （q equals 0.15 and 0.22，respectively）.The strongest interactions were observed between precipitation of coldest quarter and gravel content （q=0.34），as well as between precipitation of coldest quarter and aspect （q=0.35）. ConclusionThirteen cities，including Zhumadian and Nanyang in Henan，Huaihua，Shaoyang，and Zhangjiajie in Hunan，and Zunyi，Qiandongnan，and Tongren in Guizhou，were hot spots of total flavonoid glycosides in E.sagittatum.Precipitation，gravel content，temperature seasonality，and aspect significantly influence the accumulation of flavonoid glycosides in E.sagittatum.This study provides reference for the utilization and production zoning of E.sagittatum.

Urinary system tumors are very common nowadays，including prostate cancer，renal cancer，bladder cancer，and urothelial carcinoma.In recent years，the incidence of these tumors has been on the rise.This paper briefly summarizes the emerging technologies explored by West China Hospital in recent years for urinary system tumors，such as gene sequencing analysis，radiomics and big data，liquid chromatography-mass spectrometry，multi-modal intelligent fusion diagnostic technology，surgical decision-making tools built with artificial intelligence and big data，mRNA vaccines，combination of targeted and immune therapies，and irreversible electroporation technology.These technologies provide strong support and point out the ways for the prevention，early diagnosis，and individualized treatment of urinary system tumors.

Objective: To compare the efficacy of heat and acid elution methods for IgG anti-M and anti-Ku. Methods: Ten samples with IgG anti-M and two samples with IgG anti-Ku were selected and standardized to a titer of 64. These antibodies underwent overnight absorption at 4℃ with O-type MM and kk-type erythrocytes, and then heat and acid elution methods were used on the absorbed sensitized erythrocytes respectively by detecting the titer of anti-M and anti-Ku in the eluate to compare the differences in the elution efficiency of IgG anti-M and anti-Ku between the two elution methods. Results: In heat elution tests, all 10 anti-M samples showed positive results with titers ranging from 8 to 64, while 2 anti-Ku samples yielded negative results. In acid elution tests, all 10 anti-M samples demonstrated negative results, whereas both anti-Ku (n=2) samples exhibited positive reactions with consistent titers of 32. Following acid elution with subsequent heat elution, 8 of 10 anti-M samples showed positive results with titers ranging from 8 to 32, while 2 remained negative. Both anti-Ku samples demonstrated positive with titers of 4. Conclusion: Heat elution demonstrated superior efficiency for IgG anti-M compared to acid elution, whereas acid elution showed greater efficacy for IgG anti-Ku than heat elution.

background Current assessment of noise-induced hearing loss relies on the hearing threshold statistical distribution table of ISO 7029-2017 standard (ISO 7029), which is based on foreign population data and lacks a hearing threshold distribution table derived from pure-tone audiometry data of the Chinese population, hindering accurate evaluation of hearing loss in this group. Objective To establish a statistical distribution table of hearing threshold level (HTL) for otologically normal Chinese adults and to provide a scientific basis for revising the diagnostic criteria of occupational noise-induced deafness in China. Methods A total of 1271 otologically normal Chinese adults aged 18-60 years were divided into four groups with 10-year age intervals. Based on the pure tone audiometry data and power function operation formula, the relevant parameters of the median and percentile calculation formula of ISO 7029 were adjusted. Based on the adjusted parameters, a statistical distribution table of HTL of normal Chinese adults in otology was preliminarily constructed according to the calculation formula of ISO 7029. A nonparametric rank sum test was used to compare the difference between the adjusted median deviation value and the ISO 7029 calculation. Results Except for a few frequencies (2000, 3000, and 8000 Hz), the value of parameter α adjusted for the auditory threshold deviation of the Chinese population (α_CHN-md) increased with the increase of frequency, while the value of parameter β adjusted for the auditory threshold deviation of the Chinese population (β_CHN-md) decreased with the increase of frequency. The preliminary distribution table of otologically normal Chinese adults' median hearing threshold deviation (ΔH_CHN-md) showed that the hearing threshold deviation increased with age and frequency. At 8000 Hz, the increase in ΔH_CHN-md with age was the greatest for both men and women, from 0 dB to 23 dB and 21 dB respectively. The minimal threshold elevation was noted at 500, 1000, and 2000 Hz, which increased from 0 dB to 2 dB. In otologically normal Chinese adults, the maximum increase of ΔH_CHN-md with frequency was observed at age of 50 years, which increased from 2 dB at 500 Hz to 23 dB at 8000 Hz in men and from 2 dB at 500 Hz to 21 dB at 8000 Hz in women. The comparison results with the ISO 7029 calculation showed that the trend was consistent. The median hearing threshold deviation value of the adjusted Chinese population was lower than that of the ISO 7029 calculation (ΔH_md). However, they had no significant statistical difference (P>0.05). For otologically normal normal Chinese men and women, the maximum difference of ΔH_md between the 50-year-old group and the ISO calculation at 8000 Hz was 7 dB and 9 dB, respectively. Conclusion This preliminary analysis of hearing threshold deviations in otologically normal Chinese adults suggests that current standards may potentially underestimate hearing loss at frequencies below 8000 Hz while possibly overestimating it at 8000 Hz. These findings require further validation through expanded sample sizes to more accurately assess the characteristics of hearing thresholds in the Chinese population and their discrepancies with existing standards.

ObjectivePrimary liver cancer, predominantly hepatocellular carcinoma (HCC), is a significant global health issue, ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality. Accurate and early diagnosis of HCC is crucial for effective treatment, as HCC and non-HCC malignancies like intrahepatic cholangiocarcinoma (ICC) exhibit different prognoses and treatment responses. Traditional diagnostic methods, including liver biopsy and contrast-enhanced ultrasound (CEUS), face limitations in applicability and objectivity. The primary objective of this study was to develop an advanced, light-weighted classification network capable of distinguishing HCC from other non-HCC malignancies by leveraging the automatic analysis of brightness changes in CEUS images. The ultimate goal was to create a user-friendly and cost-efficient computer-aided diagnostic tool that could assist radiologists in making more accurate and efficient clinical decisions. MethodsThis retrospective study encompassed a total of 161 patients, comprising 131 diagnosed with HCC and 30 with non-HCC malignancies. To achieve accurate tumor detection, the YOLOX network was employed to identify the region of interest (ROI) on both B-mode ultrasound and CEUS images. A custom-developed algorithm was then utilized to extract brightness change curves from the tumor and adjacent liver parenchyma regions within the CEUS images. These curves provided critical data for the subsequent analysis and classification process. To analyze the extracted brightness change curves and classify the malignancies, we developed and compared several models. These included one-dimensional convolutional neural networks (1D-ResNet, 1D-ConvNeXt, and 1D-CNN), as well as traditional machine-learning methods such as support vector machine (SVM), ensemble learning (EL), k-nearest neighbor (KNN), and decision tree (DT). The diagnostic performance of each method in distinguishing HCC from non-HCC malignancies was rigorously evaluated using four key metrics: area under the receiver operating characteristic (AUC), accuracy (ACC), sensitivity (SE), and specificity (SP). ResultsThe evaluation of the machine-learning methods revealed AUC values of 0.70 for SVM, 0.56 for ensemble learning, 0.63 for KNN, and 0.72 for the decision tree. These results indicated moderate to fair performance in classifying the malignancies based on the brightness change curves. In contrast, the deep learning models demonstrated significantly higher AUCs, with 1D-ResNet achieving an AUC of 0.72, 1D-ConvNeXt reaching 0.82, and 1D-CNN obtaining the highest AUC of 0.84. Moreover, under the five-fold cross-validation scheme, the 1D-CNN model outperformed other models in both accuracy and specificity. Specifically, it achieved accuracy improvements of 3.8% to 10.0% and specificity enhancements of 6.6% to 43.3% over competing approaches. The superior performance of the 1D-CNN model highlighted its potential as a powerful tool for accurate classification. ConclusionThe 1D-CNN model proved to be the most effective in differentiating HCC from non-HCC malignancies, surpassing both traditional machine-learning methods and other deep learning models. This study successfully developed a user-friendly and cost-efficient computer-aided diagnostic solution that would significantly enhances radiologists’ diagnostic capabilities. By improving the accuracy and efficiency of clinical decision-making, this tool has the potential to positively impact patient care and outcomes. Future work may focus on further refining the model and exploring its integration with multimodal ultrasound data to maximize its accuracy and applicability.

Objective: To compare the efficacy of heat and acid elution methods for IgG anti-M and anti-Ku. Methods: Ten samples with IgG anti-M and two samples with IgG anti-Ku were selected and standardized to a titer of 64. These antibodies underwent overnight absorption at 4℃ with O-type MM and kk-type erythrocytes, and then heat and acid elution methods were used on the absorbed sensitized erythrocytes respectively by detecting the titer of anti-M and anti-Ku in the eluate to compare the differences in the elution efficiency of IgG anti-M and anti-Ku between the two elution methods. Results: In heat elution tests, all 10 anti-M samples showed positive results with titers ranging from 8 to 64, while 2 anti-Ku samples yielded negative results. In acid elution tests, all 10 anti-M samples demonstrated negative results, whereas both anti-Ku (n=2) samples exhibited positive reactions with consistent titers of 32. Following acid elution with subsequent heat elution, 8 of 10 anti-M samples showed positive results with titers ranging from 8 to 32, while 2 remained negative. Both anti-Ku samples demonstrated positive with titers of 4. Conclusion: Heat elution demonstrated superior efficiency for IgG anti-M compared to acid elution, whereas acid elution showed greater efficacy for IgG anti-Ku than heat elution.

ObjectiveTransfer RNA-derived fragments (tRFs) are a recently characterized and rapidly expanding class of small non-coding RNAs, typically ranging from 13 to 50 nucleotides in length. They are derived from mature or precursor tRNA molecules through specific cleavage events and have been implicated in a wide range of cellular processes. Increasing evidence indicates that tRFs play important regulatory roles in gene expression, primarily by interacting with target messenger RNAs (mRNAs) to induce transcript degradation, in a manner partially analogous to microRNAs (miRNAs). However, despite their emerging biological relevance and potential roles in disease mechanisms, there remains a significant lack of computational tools capable of systematically predicting the interaction landscape between tRFs and their target mRNAs. Existing databases often rely on limited interaction features and lack the flexibility to accommodate novel or user-defined tRF sequences. The primary goal of this study was to develop a machine learning based prediction algorithm that enables high-throughput, accurate identification of tRF:mRNA binding events, thereby facilitating the functional analysis of tRF regulatory networks. MethodsWe began by assembling a manually curated dataset of 38 687 experimentally verified tRF:mRNA interaction pairs and extracting seven biologically informed features for each pair: (1) AU content of the binding site, (2) site pairing status, (3) binding region location, (4) number of binding sites per mRNA, (5) length of the longest consecutive complementary stretch, (6) total binding region length, and (7) seed sequence complementarity. Using this dataset and feature set, we trained 4 distinct machine learning classifiers—logistic regression, random forest, decision tree, and a multilayer perceptron (MLP)—to compare their ability to discriminate true interactions from non-interactions. Each model’s performance was evaluated using overall accuracy, receiver operating characteristic (ROC) curves, and the corresponding area under the ROC curve (AUC). The MLP consistently achieved the highest AUC among the four, and was therefore selected as the backbone of our prediction framework, which we named tRF Prospect. For biological validation, we retrieved 3 high-throughput RNA-seq datasets from the gene expression omnibus (GEO) in which individual tRFs were overexpressed: AS-tDR-007333 (GSE184690), tRF-3004b (GSE197091), and tRF-20-S998LO9D (GSE208381). Differential expression analysis of each dataset identified genes downregulated upon tRF overexpression, which we designated as putative targets. We then compared the predictions generated by tRF Prospect against those from three established tools—tRFTar, tRForest, and tRFTarget—by quantifying the number of predicted targets for each tRF and assessing concordance with the experimentally derived gene sets. ResultsThe proposed algorithm achieved high predictive accuracy, with an AUC of 0.934. Functional validation was conducted using transcriptome-wide RNA-seq datasets from cells overexpressing specific tRFs, confirming the model’s ability to accurately predict biologically relevant downregulation of mRNA targets. When benchmarked against established tools such as tRFTar, tRForest, and tRFTarget, tRF Prospect consistently demonstrated superior performance, both in terms of predictive precision and sensitivity, as well as in identifying a higher number of true-positive interactions. Moreover, unlike static databases that are limited to precomputed results, tRF Prospect supports real-time prediction for any user-defined tRF sequence, enhancing its applicability in exploratory and hypothesis-driven research. ConclusionThis study introduces tRF Prospect as a powerful and flexible computational tool for investigating tRF:mRNA interactions. By leveraging the predictive strength of deep learning and incorporating a broad spectrum of interaction-relevant features, it addresses key limitations of existing platforms. Specifically, tRF Prospect: (1) expands the range of detectable tRF and target types; (2) improves prediction accuracy through multilayer perceptron model; and (3) allows for dynamic, user-driven analysis beyond database constraints. Although the current version emphasizes miRNA-like repression mechanisms and faces challenges in accurately capturing 5'UTR-associated binding events, it nonetheless provides a critical foundation for future studies aiming to unravel the complex roles of tRFs in gene regulation, cellular function, and disease pathogenesis.

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.