OBJECTIVE To investigate the effects of metformin （Met） on liver injury in non-alcoholic steatohepatitis （NASH） rats by regulating the PI3K/AKT/PDGF signaling pathway. METHODS NASH model was constructed by feeding rats with a high- glucose and high-fat diet， and assigned into Model group， Met low-dose group （Met-L group， 100 mg/kg）， Met medium-dose group （Met-M group， 200 mg/kg）， Met high-dose group （Met-H group， 400 mg/kg）， and high dose of Met+PI3K activator group （Met-H+740 Y-P group， 400 mg/kg Met+50 mg/kg 740 Y-P）， with 12 rats in each group. Another 12 rats were regarded as the Control group. Each group of rats was orally administered/injected with the corresponding medication once a day for 6 consecutive weeks. The changes in body weight and liver index of rats were recorded and analyzed. The pathological damage [evaluation of non-alcoholic fatty liver disease activity score （NAS）]， lipid deposition （calculation of the proportion of oil red O-positive staining area）， and fibrosis （calculation of collagen deposition score） were observed in liver tissue of rats. The levels of inflammatory factors [interleukin-6 （IL-6） and tumor necrosis factor-α （TNF-α）] in serum and liver tissue， the levels of serum lipid metabolism indicators [total cholesterol （TC）， triglyceride （TG）， and low-density lipoprotein cholesterol （LDL-C）] and liver function indicators [aspartate aminotransferase （AST） and alanine Δ 基金项目 武汉市知识创新专项项目（No.2022020801010588）； aminotransferase （ALT）] were measured. The expression levels of PI3K/AKT/PDGF signaling pathway-related proteins and Caspase-3 in liver tissue of rats were determined. RESULTS Compared with the Control group， body weight， liver index， the levels of serum lipid metabolism indicators and liver function indicators， the levels of IL-6 and TNF-α in serum and liver tissue， the NAS， the proportion of oil red O-positive staining area， the collagen deposition fraction， and the levels of phosphorylated PI3K and AKT proteins， as well as the expression levels of PDGF and Caspase-3 proteins in liver tissue， were all significantly increased （P＜0.05）. The liver tissue showed severe pathological damage， characterized by an abundance of lipid droplets and pronounced collagen deposition. After the intervention with Met， the aforementioned quantitative indicators and pathological changes in rats were significantly improved in a dose- dependent manner （P＜0.05）. 740 Y-P could reverse the improvement effects of high dose of Met on the above indexes of rats （P＜ 0.05）. CONCLUSIONS Met can improve liver damage， and alleviate inflammatory reactions and liver fibrosis of NASH rats， the mechanism of which may be associated with inhibiting PI3K/AKT/PDGF signaling pathway.

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

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.

Purpose: Combinations of immune checkpoint inhibitors (ICIs) and chemotherapy have become the standard first-line treatment for human epidermal growth factor receptor 2 (HER-2)-negative advanced gastric cancer. However, primary resistance remains a challenge, with no effective biomarkers available for its prediction. This retrospective study explores the relationship between the baseline inflammatory burden index (IBI) and primary resistance in such context. Materials and Methods: We analyzed 62 patients with HER-2-negative advanced gastric cancer who received ICIs and chemotherapy as their first-line treatment. The IBI was calculated as follows: C-reactive protein (mg/L) × neutrophil count (10 3 /mm 3 )/lymphocyte count (10 3 /mm 3 ). Based on disease progression within 6 months, patients were categorized into the primary resistant or the control group. We compared baseline characteristics and IBI scores between the groups and assessed the predictive value of the IBI using the receiver operating characteristic curve. Both univariate and multivariate binary logistic regression analyses were conducted to identify factors influencing primary resistance. Results: Nineteen patients were included in the primary resistance group, and forty-three patients were included in the control group. The IBI was significantly higher in the resistant group compared to the control group (P<0.01). The area under the curve for the IBI was 0.82, indicating a strong predictive value. Multivariate analysis identified the IBI as an independent predictor of primary resistance (P=0.014). Conclusions The baseline IBI holds promise as a predictor of primary resistance to combined ICIs and chemotherapy in patients with HER-2-negative advanced gastric cancer.

Purpose: Combinations of immune checkpoint inhibitors (ICIs) and chemotherapy have become the standard first-line treatment for human epidermal growth factor receptor 2 (HER-2)-negative advanced gastric cancer. However, primary resistance remains a challenge, with no effective biomarkers available for its prediction. This retrospective study explores the relationship between the baseline inflammatory burden index (IBI) and primary resistance in such context. Materials and Methods: We analyzed 62 patients with HER-2-negative advanced gastric cancer who received ICIs and chemotherapy as their first-line treatment. The IBI was calculated as follows: C-reactive protein (mg/L) × neutrophil count (10 3 /mm 3 )/lymphocyte count (10 3 /mm 3 ). Based on disease progression within 6 months, patients were categorized into the primary resistant or the control group. We compared baseline characteristics and IBI scores between the groups and assessed the predictive value of the IBI using the receiver operating characteristic curve. Both univariate and multivariate binary logistic regression analyses were conducted to identify factors influencing primary resistance. Results: Nineteen patients were included in the primary resistance group, and forty-three patients were included in the control group. The IBI was significantly higher in the resistant group compared to the control group (P<0.01). The area under the curve for the IBI was 0.82, indicating a strong predictive value. Multivariate analysis identified the IBI as an independent predictor of primary resistance (P=0.014). Conclusions The baseline IBI holds promise as a predictor of primary resistance to combined ICIs and chemotherapy in patients with HER-2-negative advanced gastric cancer.

Purpose: Combinations of immune checkpoint inhibitors (ICIs) and chemotherapy have become the standard first-line treatment for human epidermal growth factor receptor 2 (HER-2)-negative advanced gastric cancer. However, primary resistance remains a challenge, with no effective biomarkers available for its prediction. This retrospective study explores the relationship between the baseline inflammatory burden index (IBI) and primary resistance in such context. Materials and Methods: We analyzed 62 patients with HER-2-negative advanced gastric cancer who received ICIs and chemotherapy as their first-line treatment. The IBI was calculated as follows: C-reactive protein (mg/L) × neutrophil count (10 3 /mm 3 )/lymphocyte count (10 3 /mm 3 ). Based on disease progression within 6 months, patients were categorized into the primary resistant or the control group. We compared baseline characteristics and IBI scores between the groups and assessed the predictive value of the IBI using the receiver operating characteristic curve. Both univariate and multivariate binary logistic regression analyses were conducted to identify factors influencing primary resistance. Results: Nineteen patients were included in the primary resistance group, and forty-three patients were included in the control group. The IBI was significantly higher in the resistant group compared to the control group (P<0.01). The area under the curve for the IBI was 0.82, indicating a strong predictive value. Multivariate analysis identified the IBI as an independent predictor of primary resistance (P=0.014). Conclusions The baseline IBI holds promise as a predictor of primary resistance to combined ICIs and chemotherapy in patients with HER-2-negative advanced gastric cancer.

Objective: To explore relationship of sleep quality with overweight and obesity among middle school students, so as to provide a reference basis for improving adolescent sleep health. Methods: From September to December 2023, 5 713 middle school students aged 13 to 18 were selected by stratified cluster random sampling method in six regions, including Shanghai, Suzhou, Taiyuan, Wuyuan, Xingyi and Urumqi. Sleep quality survey was conducted on middle school students by Pittsburgh Sleep Quality Index. Height and weight were measured, and World Health Organization s standards for growth and development of children and adolescents was used to evaluate their nutritional status. Both χ 2 test and Logistic regression analysis were used to analyze the association between sleep quality and nutritional status of middle school students. Results: The non compliance detection rate of sleep quality was 38.4% among girls, but 29.2% among boys, and the difference was of statistical significance( χ 2=54.08, P < 0.01 ). The detection rate of substandard sleep quality was 34.2% in the group with normal nutritional status, 38.3% in the group with overweight, 43.7% in the group with obesity and 26.0% in the group with emaciation, and the difference in the rates of substandard sleep quality among middle school students of different nutritional status was statistically significant ( χ 2=68.15, P <0.01). Logistic regression analysis showed that, after controlling for mental health and physical activity, the detection rate of substandard sleep quality in the obese groups was 1.30 times higher than that in the normal group, respectively( OR =1.30, 95% CI =1.06- 1.59 , P <0.01). Conclusions Sleep quality is correlated with overweight and obesity among middle school students, and there are gender differences. Intervention policies should be formulated according to the characteristics of different genders.

ObjectiveFunctional near-infrared spectroscopy (fNIRS), a novel non-invasive technique for monitoring cerebral activity, can be integrated with upper limb rehabilitation robots to facilitate the real-time assessment of neurological rehabilitation outcomes. The rehabilitation robot is designed with 3 training modes: passive, active, and resistance. Among these, the resistance mode has been demonstrated to yield superior rehabilitative outcomes for patients with a certain level of muscle strength. The control modes in the resistance mode can be categorized into dynamic and static control. However, the effects of different control modes in the resistance mode on the motor function of patients with upper limb hemiplegia in stroke remain unclear. Furthermore, the effects of force, an important parameter of different control modes, on the activation of brain regions have rarely been reported. This study investigates the effects of dynamic and static resistance modes under varying resistance levels on cerebral functional alterations during motor rehabilitation in post-stroke patients. MethodsA cohort of 20 stroke patients with upper limb dysfunction was enrolled in the study, completing preparatory adaptive training followed by 3 intensity-level tasks across 2 motor paradigms. The bilateral prefrontal cortices (PFC), bilateral primary motor cortices (M1), bilateral primary somatosensory cortices (S1), and bilateral premotor and supplementary motor cortices (PM) were examined in both the resting and motor training states. The lateralization index (LI), phase locking value (PLV), network metrics were employed to examine cortical activation patterns and topological properties of brain connectivity. ResultsThe data indicated that both dynamic and static modes resulted in significantly greater activation of the contralateral M1 area and the ipsilateral PM area when compared to the resting state. The static patterns demonstrated a more pronounced activation in the contralateral M1 in comparison to the dynamic patterns. The results of brain network analysis revealed significant differences between the dynamic and resting states in the contralateral PFC area and contralateral M1 area (F=4.709, P=0.038), as well as in the contralateral PM area and ipsilateral M1 area (F=4.218, P=0.049). Moreover, the findings indicated a positive correlation between the activation of the M1 region and the increase in force in the dynamic mode, which was reversed in the static mode. ConclusionBoth dynamic and static resistance training modes have been demonstrated to activate the corresponding brain functional regions. Dynamic resistance modes elicit greater oxygen changes and connectivity to the region of interest (ROI) than static resistance modes. Furthermore, the effects of increasing force differ between the two modes. In patients who have suffered a stroke, dynamic modes may have a more pronounced effect on the activation of exercise-related functional brain regions.

Objective To explore the changing trend in the disease burden of gout in China from 1990 to 2021, and analyze the incidence, prevalence, and disability-adjusted life years (DALYs) by age and gender, with comparisons to global patterns, and to predict the disease burden of gout in China in 2030. Methods Data from the Global Burden of Disease (GBD) database were used to analyze changes in gout burden. Joinpoint regression was used to estimate the average annual percentage change (AAPC) with 95% confidence intervals (CIs). Comparative analyses were conducted on data from China and the world, and an ARIMA model was used to project China's gout burden in 2030. Results From 1990 to 2021, China's age-standardized incidence rate (ASIR) rose from 122.52 to 151.61/100,000, exceeding the global rise from 93.09 to 109.07/100,000. The age-standardized prevalence rate (ASPR) in China increased from 640.67/100,000 to 810.35/100,000, compared to a global rise from 536.54/100,000 to 653.81/100,000. The age-standardized DALYs rate (ASDR) in China increased from 20.2/100,000 to 25.43/100,000, surpassing the global increase from 16.67/100,000 to 20.21/100,000. AAPCs for ASIR, ASPR, and ASDR in China were 0.70%, 0.77%, and 0.75%, respectively, all higher than global rates. Middle-aged and elderly men faced the highest burden. It was predicted that there will be a decline in China's ASIR and ASPR by 2030, while ASDR will remain stable. Conclusion The disease burden of gout in China has increased significantly, outpacing global trends. Targeted interventions for hyperuricemia, particularly in elderly men, are crucial to reduce the future disease burden.

Anti-CD20 monoclonal antibodies for the treatment of refractory nephrotic syndrome （RNS） in children. The first- generation rituximab is the most widely used in clinical practice； it shows definite efficacy in children with RNS， is recommended by guidelines， particularly for achieving a high remission rate in minimal change nephrosis， and can significantly reduce the cumulative use of glucocorticoids and immunosuppressants. The second-generation ofatumumab has potential as an alternative treatment for patients who are intolerant or resistant to rituximab， while the third-generation obinutuzumab has shown efficacy in complex cases such as rituximab resistance or post-transplant recurrence. However， there is still controversy regarding the optimization of rituximab treatment dosage and whether ofatumumab and obinutuzumab offer greater advantages than rituximab for the treatment of RNS in children. The most common adverse reaction induced by anti-CD20 monoclonal antibodies is infusion reactions， and long-term adverse events mainly include increased risks of sustained immunosuppression and infections. Rituximab has significant economic advantages for the treatment of RNS， but additional pharmacoeconomic research based on China’s healthcare environment is needed to evaluate the cost-effectiveness of ofatumumab and obinutuzumab in this population. Given that the current use of ofatumumab and obinutuzumab in this field is considered off-label use， clinical application should only proceed after a rigorous evaluation of the patient’s benefits and risks.