BACKGROUND:The Guilu Erxian Glue consists of Testudinis Plastrum,Cornu Cervi,Lycii Fructus,and Ginseng Radix.In earlier clinical observations,it is discovered that using Guilu Erxian Glue to treat patients with liver-kidney deficiency type knee osteoarthritis effectively alleviated knee pain,increased the range of motion,and improved walking ability.However,the exact mechanism by which oral administration of Guilu Erxian Glue can produce local therapeutic effects on the knee joint is still unclear.OBJECTIVE:To investigate the effects of Guilu Erxian Glue on gut microbiota in rats with knee osteoarthritis and to evaluate its mechanism using 16S rDNA sequencing and machine learning analysis.METHODS:Totally 18 female SD rats were randomly divided into three groups:blank group,model group,and Guilu Erxian Glue group,with 6 rats in each group.A knee osteoarthritis model was prepared using the destabilization of the medial meniscus surgical method.After successful modeling,the Guilu Erxian Glue group was given a decoction of Guilu Erxian Glue by gavage,while the blank and model groups were given an equal amount of distilled water.After 28 days of continuous intervention,high performance liquid chromatography was used to detect the active ingredients of Guilu Erxian Glue.MRI imaging was used to observe the condition of rat knee articular cartilage.Fecal samples were collected;DNA was extracted using a kit,amplified and purified by PCR,and an Illumina sequencing library was constructed.The Illumina MiSeq platform was used for high-throughput sequencing to generate raw sequence data.After obtaining the raw data,QIIME2 software was used to process the data.Linear Discriminant Analysis Effect Size analysis and random forest algorithm were used to screen for differential species in microbial data.KEGG and MetaCyc functional pathway analyses were used to explore the association between key microbial communities and experimental groups.Linear discriminant analysis effect values and random forest algorithm were used to screen for differential species.Association networks were used to analyze the interactions between microbial communities,and machine learning methods were used to analyze the composition and changes of gut microbiota.RESULTS AND CONCLUSION:(1)LC-MS component identification was conducted on the traditional Chinese medicine formula of Guilu Erxian Glue,and a total of 7 effective ingredients were identified.(2)MRI imaging showed that synovitis scope of high-density shadows in rats of the Guilu Erxian Glue group was reduced,and the degeneration of medial femoral condyle cartilage was less than that in the model group.(3)16S rDNA sequencing showed that the model group rats exhibited significant microbial imbalance,with a significant decrease in the abundance of Firmicutes and Bacteroidetes at the phylum level,while the proportion of Proteobacteria increased significantly(P＜0.05).The gut microbiota structure of rats in the Guilu Erxian Glue group was significantly improved,and the proportion of Firmicutes and Bacteroidetes increased,restoring a more diverse microbiota composition,approaching that of the blank group(P＜0.05).(4)KEGG and MetaCyc functional pathway analysis showed that the Guilu Erxian Glue group significantly activated multiple metabolic pathways,including amino acid metabolism,lipid metabolism,and biotin synthesis pathways(P＜0.05).(5)The results indicate that Guilu Erxian Glue contains seven active ingredients,and the changes in gut microbiota of knee osteoarthritis rats were analyzed using 16S rDNA sequencing.Guilu Erxian Glue can significantly improve the imbalance of gut microbiota,restore the abundance of beneficial bacteria,and have a significant impact on the composition of gut microbiota,providing scientific basis for the efficacy and mechanism of Guilu Erxian Glue.

BACKGROUND:The Guilu Erxian Glue consists of Testudinis Plastrum,Cornu Cervi,Lycii Fructus,and Ginseng Radix.In earlier clinical observations,it is discovered that using Guilu Erxian Glue to treat patients with liver-kidney deficiency type knee osteoarthritis effectively alleviated knee pain,increased the range of motion,and improved walking ability.However,the exact mechanism by which oral administration of Guilu Erxian Glue can produce local therapeutic effects on the knee joint is still unclear.OBJECTIVE:To investigate the effects of Guilu Erxian Glue on gut microbiota in rats with knee osteoarthritis and to evaluate its mechanism using 16S rDNA sequencing and machine learning analysis.METHODS:Totally 18 female SD rats were randomly divided into three groups:blank group,model group,and Guilu Erxian Glue group,with 6 rats in each group.A knee osteoarthritis model was prepared using the destabilization of the medial meniscus surgical method.After successful modeling,the Guilu Erxian Glue group was given a decoction of Guilu Erxian Glue by gavage,while the blank and model groups were given an equal amount of distilled water.After 28 days of continuous intervention,high performance liquid chromatography was used to detect the active ingredients of Guilu Erxian Glue.MRI imaging was used to observe the condition of rat knee articular cartilage.Fecal samples were collected;DNA was extracted using a kit,amplified and purified by PCR,and an Illumina sequencing library was constructed.The Illumina MiSeq platform was used for high-throughput sequencing to generate raw sequence data.After obtaining the raw data,QIIME2 software was used to process the data.Linear Discriminant Analysis Effect Size analysis and random forest algorithm were used to screen for differential species in microbial data.KEGG and MetaCyc functional pathway analyses were used to explore the association between key microbial communities and experimental groups.Linear discriminant analysis effect values and random forest algorithm were used to screen for differential species.Association networks were used to analyze the interactions between microbial communities,and machine learning methods were used to analyze the composition and changes of gut microbiota.RESULTS AND CONCLUSION:(1)LC-MS component identification was conducted on the traditional Chinese medicine formula of Guilu Erxian Glue,and a total of 7 effective ingredients were identified.(2)MRI imaging showed that synovitis scope of high-density shadows in rats of the Guilu Erxian Glue group was reduced,and the degeneration of medial femoral condyle cartilage was less than that in the model group.(3)16S rDNA sequencing showed that the model group rats exhibited significant microbial imbalance,with a significant decrease in the abundance of Firmicutes and Bacteroidetes at the phylum level,while the proportion of Proteobacteria increased significantly(P＜0.05).The gut microbiota structure of rats in the Guilu Erxian Glue group was significantly improved,and the proportion of Firmicutes and Bacteroidetes increased,restoring a more diverse microbiota composition,approaching that of the blank group(P＜0.05).(4)KEGG and MetaCyc functional pathway analysis showed that the Guilu Erxian Glue group significantly activated multiple metabolic pathways,including amino acid metabolism,lipid metabolism,and biotin synthesis pathways(P＜0.05).(5)The results indicate that Guilu Erxian Glue contains seven active ingredients,and the changes in gut microbiota of knee osteoarthritis rats were analyzed using 16S rDNA sequencing.Guilu Erxian Glue can significantly improve the imbalance of gut microbiota,restore the abundance of beneficial bacteria,and have a significant impact on the composition of gut microbiota,providing scientific basis for the efficacy and mechanism of Guilu Erxian Glue.

Objective To investigate the temporal changes in pathological damage and macrophage polarization in liver and spleen tissues of mice infected with Angiostrongylus cantonensis, and to preliminarily unravel the peripheral immune responses during the early stage of A. cantonensis infection. Methods Forty female BALB/c mice at ages of 6 to 8 weeks were randomly divided into four groups, including the control group and 7-, 14-, and 21-day infection groups, with 10 mice in each group. Each mouse in the infection groups was inoculated with 30 third-stage (L3) larvae of A. cantonensis by oral gavage, and five mice were randomly selected from each infection group on days 7, 14, and 21 post-infection, while mice in the control group were given the same volume of physiological saline and five mice were randomly selected from the control group on the day of oral gavage. Mouse liver and spleen tissues were sampled. The histopathological changes of mouse liver and spleen tissues were observed using hematoxylin and eosin (HE) staining, and the percentage of positive staining area and the co-localization positive rates of the macrophage surface antigens F4/80, CD86, and CD206 were quantified in mouse liver and spleen tissues using immunohistochemical and immunofluorescence staining. In addition, five mice were collected from each infection group on days 7, 14, and 21 post-infection, and five mice were collected from the control group on the day of oral gavage. Mouse liver and spleen tissues were sampled for detection of macrophage markers CD86 and CD206 and macrophage phenotyping using flow cytometry, and the expression of M1 macrophage markers, including inducible nitric oxide synthase (Nos2), tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β) and M2 markers, including arginase 1 (Arg1), mannose receptor C-type 1 (Mrc1) and chitinase-like protein 3 (Chil3) was quantified in mouse liver and spleen tissues using real-time quantitative PCR (RT-qPCR) assay. Results Proliferative lesions of the hepatocyte were observed in mouse liver tissues and the follicular structures of the mouse spleen white pulp were disrupted 21 days post-infection with A. cantonensis. Immunohistochemical staining showed that there were significant differences in the percentages of F4/80, CD86 and CD206 positive staining areas in the liver and spleen tissues among the four groups of mice (F = 242.40, 197.14, 183.19, 157.65, 242.35 and 146.24; all P values < 0.001), and the percentages of positive staining in the liver and spleen tissues of mice in the 14-day infection group [(4.45 ± 0.51)%, (3.74 ± 0.67)%, (8.32 ± 0.72)%, (16.56 ± 1.14)%, (11.62 ± 0.52)%, and (8.29 ± 0.72)%, respectively] and the 21-day infection group [(3.70 ± 0.11)%, (3.22 ± 0.43)%, (11.53 ± 1.03)%, (12.59 ± 1.05)%, (9.02 ± 0.83)%, and (11.67 ± 1.10)%, respectively] were higher than in the control group [(0.35 ± 0.16)%, (0.40 ± 0.02)%, (0.93 ± 0.05)%, (2.78 ± 0.26)%, (2.33 ± 0.20)%, and (1.85 ± 0.20)%, respectively] (all P values < 0.05). Immunofluorescence staining showed significant differences in the positive rates of F4/80 co-localization with CD86 and CD206 in mouse liver and spleen tissues among the four groups (F = 24.42, 25.28, 54.51 and 130.55; all P values < 0.001). Flow cytometry detected significant differences in the proportions of CD86⁺ and CD206⁺ macrophages in mouse liver and spleen tissues among the four groups (F = 67.98, 18.41, 29.77, 172.80; all P values < 0.001), and the proportions of CD206⁺ macrophages in the liver and spleen of the 21-day infection group were significantly higher than those in the control group [(9.25 ± 2.55)% vs (3.83 ± 0.72)%, and (4.22 ± 0.56)% vs (0.47 ± 0.18)%, respectively] (both P values < 0.05). In addition, RT-qPCR assay quantified significant differences in the relative mRNA expression of M1 macrophage markers (IL-1β, TNF-α and Nos2) and M2 macrophage markers (Arg1, Chil3 and Mrc1) in mouse liver and spleen tissues among the four groups (F = 41.30, 31.82, 199.33, 19.96, 62.01, 119.76, 23.67, 95.90, 72.27, 82.59, 123.41 and 29.75; all P values < 0.05). Conclusions A. cantonensis infection may cause progressive pathological damage in mouse liver and spleen tissues, accompanied by dynamic temporal changes in macrophage polarization. M1 macrophage polarization predominates at the early stage of A. cantonensis infection and shifts towards M2 polarization at the later stages, suggesting that M2 polarization may participate in immune regulation at late stages of A. cantonensis infection by suppressing excessive inflammatory responses and promoting tissue repair.

Cardiovascular disease (CVD), chronic kidney disease (CKD), and metabolic disorders are the 3 major chronic diseases threatening human health, which are closely related and often coexist, significantly increasing the difficulty of disease management. In response, the American Heart Association (AHA) proposed a novel disease concept of “cardiovascular-kidney-metabolic (CKM) syndrome” in October 2023, which has triggered widespread concern about the co-treatment of heart and kidney diseases and the prevention and treatment of metabolic disorders around the world. This review posits that effectively managing CKM syndrome requires a new and multidimensional paradigm for diagnosis and risk prediction that integrates biological insights, advanced technology and social determinants of health (SDoH). We argue that the core pathological driver is a “metabolic toxic environment”, fueled by adipose tissue dysfunction and characterized by a vicious cycle of systemic inflammation and oxidative stress, which forms a common pathway to multi-organ injury. The at-risk population is defined not only by biological characteristics but also significantly impacted by adverse SDoH, which can elevate the risk of advanced CKM by a factor of 1.18 to 3.50, underscoring the critical need for equity in screening and care strategies. This review systematically charts the progression of diagnostic technologies. In diagnostics, we highlight a crucial shift from single-marker assessments to comprehensive multi-marker panels. The synergistic application of traditional biomarkers like NT-proBNP (reflecting cardiac stress) and UACR (indicating kidney damage) with emerging indicators such as systemic immune-inflammation index (SII) and Klotho protein facilitates a holistic evaluation of multi-organ health. Furthermore, this paper explores the pivotal role of non-invasive monitoring technologies in detecting subclinical disease. Techniques like multi-wavelength photoplethysmography (PPG) and impedance cardiography (ICG) provide a real-time window into microcirculatory and hemodynamic status, enabling the identification of early, often asymptomatic, functional abnormalities that precede overt organ failure. In imaging, progress is marked by a move towards precise, quantitative evaluation, exemplified by artificial intelligence-powered quantitative computed tomography (AI-QCT). By integrating AI-QCT with clinical risk factors, the predictive accuracy for cardiovascular events within 6 months significantly improves, with the area under the curve (AUC) increasing from 0.637 to 0.688, demonstrating its potential for reclassifying risk in CKM stage 3. In the domain of risk prediction, we trace the evolution from traditional statistical tools to next-generation models. The new PREVENT equation represents a major advancement by incorporating key kidney function markers (eGFR, UACR), which can enhance the detection rate of CKD in primary care by 20%-30%. However, we contend that the future lies in dynamic, machine learning-based models. Algorithms such as XGBoost have achieved an AUC of 0.82 for predicting 365-day cardiovascular events, while deep learning models like KFDeep have demonstrated exceptional performance in predicting kidney failure risk with an AUC of 0.946. Unlike static calculators, these AI-driven tools can process complex, multimodal data and continuously update risk profiles, paving the way for truly personalized and proactive medicine. In conclusion, this review advocates for a paradigm shift toward a holistic and technologically advanced framework for CKM management. Future efforts must focus on the deep integration of multimodal data, the development of novel AI-driven biomarkers, the implementation of refined SDoH-informed interventions, and the promotion of interdisciplinary collaboration to construct an efficient, equitable, and effective system for CKM screening and intervention.

Objective To study the distribution characteristics of TCM constitutions in the middle-aged and elderly Mongolian population undergoing physical examinations in Inner Mongolia;To analyze the correlation with related risk factors.Methods Health information and related risk factors(including BMI index,lifestyle habits,dietary habits and exercise status)of middle-aged and elderly Mongolian people who visited the physical examination departments of Inner Mongolia Autonomous Region Traditional Chinese Medicine Hospital and Tongliao City Traditional Chinese Medicine Hospital from March 2024 to April 2024 were collected.A total of 213 Mongolian people were surveyed,including 65 people who have lived in Hohhot for more than 2 years and 148 people who have lived in Tongliao for more than 2 years.Through investigation,research and analysis,the distribution characteristics of TCM constitutions in the population and its correlation with related risk factors were observed.Results Constitution distribution:101 people(47.41%)had a moderate constitution.Among the biased constitutions,the phlegm dampness constitution had the highest number of people(64 people,30.05%),with the blood deficiency constitution having the lowest number of people(2 people,0.94%).In the investigation of related risk factors,there was a significant correlation(P<0.01)between phlegm dampness and dietary habits and reduced exercise volume.Moreover,individuals with this constitution tend to have good sleep,reduced physical activity,faster eating and a diet primarily consisting of high-calorie foods(P<0.05).Conclusion The TCM constitution of the Mongolian population in Inner Mongolia is mostly composed of moderate constitution,while the biased constitution is mostly composed of phlegm dampness constitution,which is mainly related to dietary habits and reduced exercise volume.

Sarin(GB)is a typical representative of nerve agents with high toxicity,and very low amount can cause death.GB can cause water and atmospheric environment poisoning,so the detection of GB in water and air is of great significance.In this work,a colorimetric sensor array(CSA)based on GB inhibition of cholinesterase activity was constructed to detect GB with high selectivity.A 4×4 colorimetric array was constructed using acetylcholinesterase(AChE),butyryl cholinesterase(BuChE)and the corresponding substrate acetylthiocholine iodide(S-ACh),butyryl thiocholine iodide(S-BCh),acetylcholine chloride(ACh),butyryl choline chloride(BCh)and 2,6-dichloroindophenol ethyl ester(DCIE).The linear curve of the sensor was Y=131.3×lgC+271.6(R2=0.997),where Y was the array response Euclidean distance,C was the concentration of GB(mg/L),the linear range was 0.03?0.32 mg/L,and the detection limit was 27.6 μg/L.The method could effectively distinguish chemical warfare agents(CWA)such as VX,Soman(GD),mustard gas(HD),Louie reagent(L),and had high anti-interference ability,sensitivity and good repeatability.It was successfully applied to the detection of GB in simulated water and simulated air samples,and the sample recovery rate was 97.2% ?100.9%.This method would be potentially applied to the field rapid detection of nerve agents.

Cerebral palsy in children is a motor developmental disorder caused by non-progressive brain damage occurring prenatally,perinatally,or postnatally,with the spastic type being the most common clinical manifestation.This article systematically introduces Qin Min's academic philosophy in treating spastic cerebral palsy using Lingnan Flying Needle Therapy based on the Inner Canon's theory of"maintaining patency of qi and meridians".It elaborates on the core pathogenesis of"deficiency and stagnation of qi and meridians,leading to malnourishment of tendons and vessels"and the treatment approach of"regulating the conception vessel and governor vessel to unblock qi and meridians".By employing characteristic needling techniques such as Lingnan scalp acupuncture and Lingnan abdominal-back acupuncture,the therapy aims to activate yang qi,regulate and unblock qi and meridians,thereby achieving the goals of nourishing the spirit,softening tendons,and balancing yin and yang,with demonstrated favorable clinical efficacy.

The accumulation of uremic toxins such as urea nitrogen, blood creatinine, and uric acid of patients with renal failure in vivo would lead to aggravated kidney damage. In this study, coated aldehyde oxy-starch (CAO) was used as an adsorbent to investigate its in vitro adsorption performance on renal failure indexes for urea, indoxyl sulfate (INS), monomethylamine (MMA), dimethylamine (DMA), uric acid (UA), and creatinine (Cr). The effects of variables such as pH, temperature, concentration, dosage, and time on the adsorption capacity of CAO were systematically investigated, employing analytical techniques of high-performance liquid chromatography (HPLC) and gas chromatography (GC). The results revealed that CAO exhibited a strong adsorption capacity for urea, INS, and MMA, alongside a moderate adsorption capacity for DMA, UA, and Cr. The adsorption kinetics and thermodynamic studies indicated that the adsorption of urea and UA by CAO were fitted in pseudo-first-order kinetics, and the adsorption isotherm aligned with the Freundlich adsorption model. The enthalpy change ΔH of urea in adsorption was in the range of 40 to 60 kJ·mol^-1, which demonstrated the presence of strong adsorption force due to the interactions of coordinating groups. The ΔH of UA was greater than 80 kJ·mol^-1, indicating the generation of chemical bonds during the adsorption. Both of them, Gibbs free energy ΔG was less than 0, within the range of -20 to 0 kJ·mol^-1, suggested that the adsorption of urea and UA by CAO occurred spontaneously as physical adsorption process. The adsorption entropy ΔS of urea and UA was > 0, which indicated an increase in entropy throughout the adsorption. The infrared spectroscopygram showed the formation of a chemical bond, specifically the imine bond, following the adsorption of urea by CAO, thereby indicating a chemical reaction during the adsorption. This study elucidates the adsorption mechanism of CAO on various indexes of renal failure, providing a scientific basis for its clinical usage.

Objective: To explore the dynamic association and gender difference among body dissatisfaction, weight bias internalization and eating disorders in junior high school students, so as to provide the reference for the rational implementation of relevant intervention activitites. Methods: From June to December 2023, a cluster sampling method was used to select 698 students from a middle school in Fuzhou for three followup surveys for a period of 6 months (T1:June 2023, T2:September 2023, T3:December 2023). The Eating Disorders Inventory-Body Dissatisfaction (EDI-BD), the Chinese Version of the Weight Bias Internalization Scale for Mainland Chinese Children and Adolescents (C-WBIS), and the Chinese Version of the Eating Disorder Examination Questionnaire (C-EDE-QS) were used for investigation. Analysis of variance, t test, Pearson correlation analysis and crosslagged analysis were used for statistical analysis. Results: T1 there were statistically significant differences in body dissatisfaction scores among junior high school students of different grades and with or without leftbehind experience (t=-3.25, 2.12, P<0.05). There were statistically significant differences in weight bias internalization (t=-3.03, -2.43, 2.43) and eating disorders (t=-4.64, -2.04, 2.63) among junior high school students of different genders, grades and with or without leftbehind experience (P<0.05). Crosslagged analysis showed that body dissatisfaction was a predictor of weight bias internalization (βT1-T2=0.22, βT2-T3=0.12) and eating disorders (βT1-T2=0.09, βT2-T3=0.17, P<0.01). Eating disorders could predict body dissatisfaction (βT1-T2=0.15, βT2-T3=0.13) and weight bias internalization (βT1-T2=0.14, βT2-T3=0.23, P<0.01). The mutual predictive effect of body dissatisfaction, weight bias internalization and eating disorders varied with gender. T2 weight bias internalization in girls had a predictive effect on T3 body dissatisfaction (β=0.11). T1 and T2 eating disorders in girls had a predictive effect on T2 and T3 weight bias internalization (βT1-T2=0.26, βT2-T3=0.21) (P<0.01). Conclusions Body dissatisfaction, weight bias internalization, and eating disorders of the junior high school students are interconnected. And there is a certain twoway correlation and gender difference between body dissatisfaction, weight bias internalization and eating disorders in junior high school students.

Objective To investigate the changes in eosinophil counts and the activation of microglial cells in the brain tissues of mice at different stages of Angiostrongylus cantonensis infection, and to examine the role of microglia in regulating the progression of angiostrongyliasis and unravel the possible molecular mechanisms. Methods Fifty BALB/c mice were randomly divided into the control group and the 7-d, 14-d, 21-day and 25-d infection groups, of 10 mice in each group. All mice in infection groups were infected with 30 stage III A. cantonensis larvae by gavage, and animals in the control group was given an equal amount of physiological saline. Five mice were collected from each of infection groups on days 7, 14, 21 d and 25 d post-infection, and 5 mice were collected from the control group on the day of oral gavage. The general and focal functional impairment was scored using the Clark scoring method to assess the degree of mouse neurological impairment. Five mice from each of infection groups were sacrificed on days 7, 14, 21 d and 25 d post-infection, and 5 mice from the control group were sacrificed on the day of oral gavage. Mouse brain tissues were sampled, and the pathological changes of brain tissues were dynamically observed using hematoxylin and eosin (HE) staining. Immunofluorescence staining with eosinophilic cationic protein (ECP) and ionized calcium binding adaptor molecule 1 (Iba1) was used to assess the degree of eosinophil infiltration and the counts of microglial cells in mouse brain tissues in each group, and the morphological parameters of microglial cells (skeleton analysis and fractal analysis) were quantified by using Image J software to determine the morphological changes of microglial cells. In addition, the expression of M1 microglia markers Fcγ receptor III (Fcgr3), Fcγ receptor IIb (Fcgr2b) and CD86 antigen (Cd86), M2 microglia markers Arginase 1 (Arg1), macrophage mannose receptor C-type 1 (Mrc1), chitinase-like 3 (Chil3), and phagocytosis genes myeloid cell triggering receptor expressed on myeloid cells 2 (Trem2), CD68 antigen (Cd68), and apolipoprotein E (Apoe) was quantified using real-time quantitative reverse transcription PCR (RT-qPCR) assay in the mouse cerebral cortex of mice post-infection. Results A large number of A. cantonensis larvae were seen on the mouse meninges surface post-infection, and many neuronal nuclei were crumpled and deeply stained, with a large number of bleeding points in the meninges. The median Clark scores of mouse general functional impairment were 0 (interquartile range, 0), 0 (interquartile range, 0.5), 6 (interquartile range, 1.0), 14 (interquartile range, 8.5) points and 20 (interquartile range, 9.0) points in the control group and the 7-d, 14-d, 21-d and 25-d groups, respectively (H = 22.45, P < 0.01), and the median Clark scores of mouse focal functional impairment were 0 (interquartile range, 0), 2 (interquartile range, 2.5), 7 (interquartile range, 3.0), 18 (interquartile range, 5.0) points and 25 (interquartile range, 6.5) points in the control group and the 7-d, 14-d, 21-d and 25-d groups, respectively (H = 22.72, P < 0.01). The mean scores of mice general and focal functional impairment were all higher in the infection groups than in the control group (all P values < 0.05). Immunofluorescence staining showed a significant difference in the eosinophil counts in mouse brain tissues among the five groups (F = 40.05, P < 0.000 1), and the eosinophil counts were significantly higher in mouse brain tissues in the 14-d (3.08 ± 0.78) and 21-d infection groups (5.97 ± 1.37) than in the control group (1.00 ± 0.28) (both P values < 0.05). Semi-quantitative analysis of microglia immunofluorescence showed a significant difference in the counts of microglial cells among the five groups (F = 17.66, P < 0.000 1), and higher Iba1 levels were detected in mouse brain tissues in 14-d (5.75 ± 1.28), 21-d (6.23 ± 1.89) and 25-d infection groups (3.70 ± 1.30) than in the control group (1.00 ± 0.30) (all P values < 0.05). Skeleton and fractal analyses showed that the branch length [(162.04 ± 34.10) μm vs. (395.37 ± 64.11) μm; t = 5.566, P < 0.05] and fractal dimension of microglial cells (1.30 ± 0.01 vs. 1.41 ± 0.03; t = 5.266, P < 0.05) were reduced in mouse brain tissues in the 21-d infection group relative to the control group. In addition, there were significant differences among the 5 groups in terms of M1 and M2 microglia markers Fcgr3 (F = 48.34, P < 0.05), Fcgr2b (F = 55.46, P < 0.05), Cd86 (F = 24.44, P < 0.05), Arg1 (F = 31.18, P < 0.05), Mrc1 (F = 15.42, P < 0.05) and Chil3 (F = 24.41, P < 0.05), as well as phagocytosis markers Trem2 (F = 21.19, P < 0.05), Cd68 (F = 43.95, P < 0.05) and Apoe (F = 7.12, P < 0.05) in mice brain tissues. Conclusions A. cantonensis infections may induce severe pathological injuries in mouse brain tissues that are characterized by massive eosinophil infiltration and persistent activation of microglia cells, thereby resulting in progressive deterioration of neurological functions.