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A carboxymethyl cellulose/chitosan interpenetrating network hydrogel was prepared to adsorb and desorb anionic and cationic dyes applying different pH conditions. The three-dimensional network structure of the hydrogel was investigated using Scanning Electron Microscopy (SEM). Fourier Transform Infrared (FT–IR) was used to analyze the bonding mechanism of the hydrogel. The compression modulus of the hydrogel under neutral conditions exhibited an increase in parallel with the increase of carboxymethyl cellulose content. Under alkaline conditions, the swelling properties of hydrogels in water were enhanced with the increase of the carboxymethyl cellulose content. On the other hand, under acidic conditions, the swelling performance of hydrogels in water was decreased with the increase of carboxymethyl cellulose content. The adsorption capacity and desorption ratio of carboxymethyl cellulose/chitosan hydrogel for Acid Orange II were higher than 100 mg/g and 90%, respectively, while for Methylene Blue were higher than 110 mg/g and 95% even after five adsorption/desorption cycles. This study suggests that the carboxymethyl cellulose/chitosan interpenetrating network hydrogel showed different swelling behaviors under different pH values, which could present great potential as carrier materials in the controllable release-based applications.Graphic abstract

Evidence for the involvement of N 6 -Methyladenosine (m 6 A) modification in the etiology and progression of liver fibrosis has emerged and holds promise as a therapeutic target. Insulin-like growth factor 2 (IGF2) mRNA-binding protein 2 (IGF2BP2) is a newly identified m 6 A-binding protein that functions to enhance mRNA stability and translation. However, its role as an m 6 A-binding protein in liver fibrosis remains elusive. Here, we observed that IGF2BP2 is highly expressed in liver fibrosis and activated hepatic stellate cells (HSCs), and inhibition of IGF2BP2 protects against HSCs activation and liver fibrogenesis. Mechanistically, as an m 6 A-binding protein, IGF2BP2 regulates the expression of Aldolase A ( ALDOA ), a key target in the glycolytic metabolic pathway, which in turn regulates HSCs activation. Furthermore, we observed that active glycolytic metabolism in activated HSCs generates large amounts of lactate as a substrate for histone lactylation. Importantly, histone lactylation transforms the activation phenotype of HSCs. In conclusion, our findings reveal the essential role of IGF2BP2 in liver fibrosis by regulating glycolytic metabolism and highlight the potential of targeting IGF2BP2 as a therapeutic for liver fibrosis.

Multiple studies have shown knockdown of chromobox 7 (CBX7) promotes the regenerative capacity of various cells or tissues. We examined the effect of CBX7 on hepatocyte proliferation and liver regeneration after 2/3 hepatectomy in a mouse model. For in vitro experiments, NCTC 1469 and BNL CL.2 hepatocytes were co-transfected with siRNA-CBX7-1 (si-CBX7-1), siRNA-CBX7-2 (si-CBX7-2), pcDNA-CBX7, si-BMI1-1, si-BMI1-2, pcDNA-BMI1, or their negative control. For in vivo experiments, mice were injected intraperitoneally with lentivirus-packaged shRNA and shRNA CBX7 before hepatectomy. Our results showed that CBX7 was rapidly induced in the early stage of liver regeneration. CBX7 regulated hepatocyte proliferation, cell cycle, and apoptosis of NCTC 1469 and BNL CL.2 hepatocytes. CBX7 interacted with BMI1 and inhibited BMI1 expression in hepatocytes. Silencing BMI1 aggregated the inhibitory effect of CBX7 overexpression on hepatocyte viability and the promotion of apoptosis. Furthermore, silencing BMI1 enhanced the regulatory effect of CBX7 on Nrf2/ARE signaling in HGF-induced hepatocytes. In vivo, CBX7 silencing enhanced liver/body weight ratio in PH mice. CBX7 silencing promoted the Ki67-positive cell count and decreased the Tunel-positive cell count after hepatectomy, and also increased the expression of nuclear Nrf2, HO-1, and NQO-1. Our results suggest that CBX7 silencing may increase survival following hepatectomy by promoting liver regeneration.

Gastric cancer, a prevalent malignancy globally, is influenced by various factors. The imbalance in the gut microbiome and the existence of particular intratumoural microbiota could have a strong connection with the onset and progression of gastric cancer. High-throughput sequencing technology and bioinformatics analysis have revealed a close correlation between abnormal abundance of specific microbial communities and the risk of gastric cancer. These microbial communities contribute to gastric cancer progression through mechanisms including increasing cellular genomic damage, inhibiting DNA repair, activating abnormal signaling pathways, exacerbating tumor hypoxia, and shaping a tumor immune-suppressive microenvironment. This significantly impacts the efficacy of gastric cancer treatments, including chemotherapy and immunotherapy. Probiotic, prebiotic, antibiotic, carrier-based, dietary interventions, fecal microbiota transplantation, and traditional Chinese medicine show potential applications in gastric cancer treatment. However, the molecular mechanisms regarding dysbiosis of microbiota, including gut microbiota, and intra-tumoral microbiota during the progression of gastric cancer, as well as the therapeutic efficacy of microbiota-related applications, still require extensive exploration through experiments.

Previous evidence suggests a link between gut microbiota and chronic pain, but the causal relationship is not yet fully understood. We categorized gut microbiota based on phylum, class, order, family, and genus levels and gathered pain-related information from the UKB and FinnGen GWAS project. Then, we conducted MR analysis to explore the potential causal relationship between gut microbiota and chronic pain at 12 specific locations. We have discovered a direct connection between genetic susceptibility in the gut microbiota (gut metabolites) and pain experienced at 12 specific locations. Notably, Serotonin (5-HT) and Glycine were found to be associated with a higher risk of pain in the extremities. On the other hand, certain microbial families and orders were found to have a protective effect against migraines. Specifically, the family Bifidobacteriaceae (IVW, FDR  = 0.013) was associated with a lower risk of migraines. Furthermore, the genus Oxalobacter (IVW, FDR  = 0.044) was found to be linked to an increased risk of low back pain. Importantly, these associations remained significant even after applying the Benjamini-Hochberg correction test. Our analysis did not find any heterogeneity in the data (  > 0.05), as confirmed by the Cochrane's -test. Additionally, both the MR-Egger and MR-PRESSO tests indicated no significant evidence of horizontal pleiotropy (  > 0.05). Our MR analysis demonstrated a causal relationship between the gut microbiota and pain, highlighting its potential significance in advancing our understanding of the underlying mechanisms and clinical implications of microbiota-mediated pain.

Background The relationship between urban vegetation and dengue risk remains unclear, partly because most studies rely on static residential exposure and coarse greenness measures. This study examined how street-view vegetation and human mobility jointly influence neighborhood-level dengue risk in Guangzhou, China. Methods We analyzed 1,054 communities in Guangzhou using 3,972 locally acquired dengue cases from 2015 to 2019. Street-view images were used to derive grass, plant, and tree cover, while Landsat imagery provided NDVI. Row-standardized origin-destination mobility networks were used to construct mobility-weighted vegetation metrics. Negative binomial regression models with a population offset were fitted to estimate associations of local and mobility-weighted vegetation with dengue risk. Sub-group analyses were conducted by sex and age, and sensitivity analyses tested the robustness of the findings. Results In the local-only model, plant cover was significantly associated with lower dengue risk (IRR = 0.883, 95% CI: 0.807–0.967). In the full model, local grass (IRR = 0.885, 95% CI: 0.793–0.988) and plant cover (IRR = 0.807, 95% CI: 0.731–0.891) remained protective, while mobility-weighted tree exposure was strongly associated with higher dengue risk (IRR = 2.443, 95% CI: 2.171–2.749). Mobility-weighted grass (IRR = 0.836, 95% CI: 0.729–0.959) and plant cover (IRR = 0.597, 95% CI: 0.524–0.679) were protective, whereas NDVI was not significant in either local or weighted models. Model fit improved substantially after adding mobility-weighted vegetation metrics (AIC: 3859.14 vs. 4147.97). Associations were more evident among people aged 60 years or younger, while no greenery metric was statistically significant among older adults. Conclusions Urban dengue risk is shaped by both local streetscape vegetation and mobility-mediated exposure to vegetation in connected destination communities. Dense tree canopies in daily activity destinations may increase dengue risk, whereas understory plants and grass may be protective. These findings support mobility-aware urban planning and vector-control strategies.

Background Many studies assessing urban air-pollution health impacts assign outdoor PM₂.₅ at a single residential address, ignoring children’s daily movements between home and school. This simplification may misclassify exposure and bias short-term risk estimates, potentially misguiding school-area prevention priorities. Methods Using 2,543 laboratory-confirmed influenza cases among school-aged children in Guangzhou (2014–2019) and hourly monitoring–derived PM₂.₅ concentration fields, we tested whether mobility-aware exposure assignment changes short-term PM₂.₅–influenza risk estimates. We constructed a residence-based model (RBM) and a multi-context activity-weighted model (MCAWM) that reallocates hourly PM₂.₅ across home, school, and street-network commute corridors using stylized school-day schedules and open-source street networks. Results Although RBM and MCAWM lag-0 daily PM₂.₅ estimates were highly correlated ( r  = 0.93), 15.8% of child-days differed by ≥ 10 µg/m³. Per 10 µg/m³, cumulative relative risks were 1.04 (95% CI: 1.02–1.06) for RBM and 1.10 (1.06–1.14) for MCAWM, with improved fit and slightly more persistent lag effects under MCAWM. The concentration-dependent difference in cumulative relative risk between MCAWM and RBM increased above ~ 20 µg/m³, with a breakpoint near 45 µg/m³ indicating more rapid RBM underestimation at higher concentrations. Stratification by school environment revealed the largest mobility gains in high-density, low-greenspace schools. Scenario-based population attributable fractions indicated that, at 50 µg/m³, residence-only exposure would miss roughly 0.20 additional attributable cases per 1,000 children per season. Conclusions A synthetic “ground-truth” experiment and sensitivity analyses suggest these gains reflect structural reductions in exposure misclassification rather than model tuning. Aligning hourly PM₂.₅ with children’s home–school–commute activity spaces indicates that residence-only assignment tends to attenuate the estimated PM₂.₅–influenza relationship and can understate preventable burden, supporting scalable targeting of school-area interventions such as school greening, near-school traffic management, and lower-exposure commuting corridors.

Background Alzheimer's disease is one common type of dementia. Numerous studies have suggested a correlation between Alzheimer's disease and inflammation. Microglia mainly participate in the inflammatory response in the brain. Currently, ample evidence has shown that microglia are closely related to the occurrence and development of Alzheimer's disease. Objective We opted for bibliometric analysis to comprehensively summarize the advancements in the study of microglia in Alzheimer's disease, aiming to provide researchers with current trends and future research directions. Methods All articles and reviews pertaining to microglia in Alzheimer's disease from 2000 to 2022 were downloaded through Web of Science Core Collection. The results were subjected to bibliometric analysis using VOSviewer 1.6.18 and CiteSpace 6.1 R2. Results Overall, 7449 publications were included. The number of publications was increasing yearly. The United States has published the most publications. Harvard Medical School has published the most papers of all institutions. Journal of Alzheimer’s Disease and Journal o f Neuroscience were the journals with the most studies and the most commonly cited, respectively. Mt Heneka is the author with the highest productivity and co-citation. After analysis, the most common keywords are neuroinflammation, amyloid-beta, inflammation, neurodegeneration. Gut microbiota, extracellular vesicle, dysfunction and meta-analysis are the hotspots of research at the present stage and are likely to continue. Conclusion NLRP3 inflammasome, TREM2, gut microbiota, mitochondrial dysfunction, exosomes are research hotspots. The relationship between microglia-mediated neuroinflammation and Alzheimer's disease have been the focus of current research and the development trend of future research.

Hypertension remains a major global health challenge, significantly increasing cardiovascular and all-cause mortality risks. While exercise therapy is effective, conventional approaches face limitations in accessibility and personalization, compromising adherence. Artificial intelligence (AI)-assisted remote rehabilitation enables real-time monitoring and personalized guidance, offering a promising alternative. Nevertheless, its clinical benefits and applicability require further systematic validation. This study aimed to evaluate the efficacy of an 8-week AI-assisted telerehabilitation program on improving exercise capacity and related health outcomes in patients with hypertension. This prospective, dual-arm, parallel, open-label, randomized controlled trial enrolled 62 patients with hypertension recruited via convenience sampling. Participants were adults aged between 18 and 75 years with a confirmed hypertension diagnosis who were excluded for severe cardiac complications, recent myocardial infarction, unstable angina, or physical disabilities preventing exercise. The participants were randomly assigned (1:1) to an intervention group that received AI-assisted remote rehabilitation plus routine health education, or a control group that received health education and conventional offline exercise guidance. The supervised exercise program included warm-up, cardiorespiratory endurance, strength resistance, balance, and flexibility training, followed by a cooldown. Sessions lasted between 30 and 50 minutes and were performed at least 3 times weekly for 8 weeks. Assessments at baseline and 8 weeks included the 6-minute walk test (6MWT), cardiopulmonary exercise testing (CPET), International Physical Activity Questionnaire (IPAQ), Short-Form Health Survey 12 (SF-12), Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7), exercise self-efficacy, blood pressure (BP), body weight, handgrip strength, and other health-related indicators. The primary outcome was the change in 6-minute walk distance (6MWD). Data were analyzed according to the intention-to-treat principle. Throughout the 8-week intervention period, no serious adverse events related to the AI-assisted telerehabilitation intervention occurred. After 8 weeks, the intervention group demonstrated significantly greater improvements than the control group in 6-minute walk distance (6MWD; adjusted mean difference 62.77, 95% CI 26.33-99.22; P=.002), systolic BP reduction (adjusted mean difference 4.11, 95% CI 0.11-8.28; P=.046), IPAQ score (adjusted mean difference 658.96, 95% CI 159.23-1158.69; P=.011), exercise self-efficacy score (adjusted mean difference 21.71, 95% CI 13.59-29.82; P<.001), total exercise time (adjusted mean difference 98.24, 95% CI 49.39-147.08; P=.001) peak oxygen uptake (peak VO ) (adjusted mean difference 3.39, 95% CI 0.49-6.29; P=.026), and peak oxygen uptake percent predicted (peak VO %pred) (adjusted mean difference 11.58, 95% CI 2.06-21.10; P=.021). Compared with conventional exercise rehabilitation, AI-assisted remote rehabilitation was found to improve exercise capacity, boost regular physical activity and exercise self-efficacy, and aid in systolic BP control among patients with hypertension. This study positioned AI-assisted rehabilitation as a scalable and effective strategy for real-world hypertension management. It further contributes actionable guidance for developing effective home-based exercise strategies tailored to populations with hypertension. Chinese Clinical Trial Registry ChiCTR2300076451; https://www.chictr.org.cn/showproj.html?proj=208353.

The electrospinning of poly(L-lactic acid)/poly(D-lactic acid) (PLLA/PDLA) microfiber membranes were carried out with dichloromethane (DCM), DCM/ethanol, DCM/acetone, DCM/hexane as the spinning solvent. Scanning electron microscope observation showed that the electrospun fiber obtained using DCM/ethanol (L/D-DE) mixed solvent was homogeneous without visible bead, which was better than any others. Moreover, plenty of pores could be found on the surface of the fibers obtained using the mixed solvents. The porous structure of fibers was significantly influenced by the ethanol (non-solvent) content. When the DCM/ethanol was 50:10 (v/v), the fibers were uniform and had isolated pores. XRD and DSC results indicated that the exclusive stereocomplex poly(lactide acid) (sc-PLA) crystallites without any homocrystallites poly(lactide acid) (hc-PLA) did form in all types of fibers. The crystallinity of sc-PLA in the L/D-DE fiber was higher than other samples due to the slowest evaporation rate. TGA test further indicated that the thermal stabilities of PLLA/PDLA electrospun fibers were slightly better than the PLLA. Furthermore, L/D-DE had the excellent mechanical properties and underwent the course of ductile fracture. Possible mechanisms accounting for the morphologies and tensile properties were also proposed in this study.