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Increasing evidence highlights the role of bacteria in promoting tumorigenesis. The underlying mechanisms may be diverse and remain poorly understood. Here, we report that Salmonella infection leads to extensive de/acetylation changes in host cell proteins. The acetylation of mammalian cell division cycle 42 (CDC42), a member of the Rho family of GTPases involved in many crucial signaling pathways in cancer cells, is drastically reduced after bacterial infection. CDC42 is deacetylated by SIRT2 and acetylated by p300/CBP. Non-acetylated CDC42 at lysine 153 shows an impaired binding of its downstream effector PAK4 and an attenuated phosphorylation of p38 and JNK, consequently reduces cell apoptosis. The reduction in K153 acetylation also enhances the migration and invasion ability of colon cancer cells. The low level of K153 acetylation in patients with colorectal cancer (CRC) predicts a poor prognosis. Taken together, our findings suggest a new mechanism of bacterial infection-induced promotion of colorectal tumorigenesis by modulation of the CDC42-PAK axis through manipulation of CDC42 acetylation.

Growing evidence has shown that alterations in gut microbiota composition are associated with multiple autoimmune diseases (ADs). However, it is unclear whether these associations reflect a causal relationship. To reveal the causal association between gut microbiota and AD, we conducted a two-sample Mendelian randomization (MR) analysis. We assessed genome-wide association study (GWAS) summary statistics for gut microbiota and six common ADs, namely, systemic lupus erythematosus, rheumatoid arthritis, inflammatory bowel disease, multiple sclerosis, type 1 diabetes (T1D), and celiac disease (CeD), from published GWASs. Two-sample MR analyses were first performed to identify causal bacterial taxa for ADs in discovery samples. Significant bacterial taxa were further replicated in independent replication outcome samples. A series of sensitivity analyses was performed to validate the robustness of the results. Finally, a reverse MR analysis was performed to evaluate the possibility of reverse causation. Combining the results from the discovery and replication stages, we identified one causal bacterial genus, . A higher relative abundance of the genus was associated with a higher risk of T1D [odds ratio (OR): 1.605; 95% CI, 1.339-1.922; = 4.19 × 10 ] and CeD (OR: 1.401; 95% CI, 1.139-1.722; = 2.03 × 10 ), respectively. Further sensitivity analyses validated the robustness of the above associations. The results of reverse MR analysis showed no evidence of reverse causality from T1D and CeD to the genus. This study implied a causal relationship between the genus and T1D and CeD, thus providing novel insights into the gut microbiota-mediated development mechanism of ADs.

Recent studies have shown the relevance of gut microbiota in the occurrence and development of colorectal cancer (CRC), but the causal relationship remains unclear in the human population. The present study aims to assess the causal relationship from the gut microbiota to CRC and to identify specific causal microbe taxa via genome-wide association study (GWAS) summary statistics based two-sample Mendelian randomization (MR) analyses. Microbiome GWAS (MGWAS) in the TwinsUK 1,126 twin pairs was used as discovery exposure sample, and MGWAS in 1,812 northern German participants was used as replication exposure sample. GWAS of CRC in 387,156 participants from the UK Biobank (UKB) was used as the outcome sample. Bacteria were grouped into taxa features at both family and genus levels. In the discovery sample, a total of 30 bacteria features including 15 families and 15 genera were analyzed. Five features, including 2 families ( Verrucomicrobiaceae and Enterobacteriaceae ) and 3 genera ( Akkermansia , Blautia , and Ruminococcus ), were nominally significant. In the replication sample, the genus Blautia (discovery beta=-0.01, P  = 0.04) was successfully replicated (replication beta=-0.18, P  = 0.01) with consistent effect direction. Our findings identified genus Blautia that was causally associated with CRC, thus offering novel insights into the microbiota-mediated CRC development mechanism.

The poor stability of Ru-based acidic oxygen evolution (OER) electrocatalysts has greatly hampered their application in polymer electrolyte membrane electrolyzers (PEMWEs). Traditional understanding of performance degradation centered on influence of bias fails in describing the stability trend, calling for deep dive into the essential origin of inactivation. Here we uncover the decisive role of reaction route (including catalytic mechanism and intermediates binding strength) on operational stability of Ru-based catalysts. Using MRuO x (M = Ce 4+ , Sn 4+ , Ru 4+ , Cr 4+ ) solid solution as structure model, we find the reaction route, thereby stability, can be customized by controlling the Ru charge. The screened SnRuO x thus exhibits orders of magnitude lifespan extension. A scalable PEMWE single cell using SnRuO x anode conveys an ever-smallest degradation rate of 53 μV h −1 during a 1300 h operation at 1 A cm −2 . The poor stability of ruthenium-based catalysts has greatly hampered their application in polymer electrolyte membrane water electrolysis. Here, the authors uncover the decisive role of reaction route on catalytic performance, which enables the screening of efficient ruthenium-based water oxidation catalysts.

Objective To investigate the level of understanding and trust of medical students towards ChatGPT-like large language models, as well as their utilization and attitudes towards these models. Methods Data collection was concentrated from December 2023 to mid-January 2024, utilizing a self-designed questionnaire to assess the use of large language models among undergraduate medical students at Anhui Medical University. The normality of the data was confirmed with Shapiro-Wilk tests. We used Chi-square tests for comparisons of categorical variables, Mann-Whitney U tests for comparisons of ordinal variables and non-normal continuous variables between two groups, Kruskall-Wallis H tests for comparisons of ordinal variables between multiple groups, and Bonferroni tests for post hoc comparisons. Results A total of 1774 questionnaires were distributed and 1718 valid questionnaires were collected, with an effective rate of 96.84%. Among these students, 34.5% had heard and used large language models. There were statistically significant differences in the understanding of large language models between genders ( p  < 0.001), grade levels (junior-level students and senior-level students) ( p  = 0.03), and major ( p  < 0.001). Male, junior-level students, and public health management had a higher level of understanding of these models. Genders and majors had statistically significant effects on the degree of trust in large language models ( p  = 0.004; p  = 0.02). Male and nursing students exhibited a higher degree of trust in large language models. As for usage, Male and junior-level students showed a significantly higher proportion of using these models for assisted learning ( p  < 0.001). Neutral sentiments were held by over two-thirds of the students (66.7%) regarding large language models, with only 51(3.0%) expressing pessimism. There were significant gender-based disparities in attitudes towards large language models, and male exhibited a more optimistic attitude towards these models ( p  < 0.001). Notably, among students with different levels of knowledge and trust in large language models, statistically significant differences were observed in their perceptions of the shortcomings and benefits of these models. Conclusion Our study identified gender, grade levels, and major as influential factors in students’ understanding and utilization of large language models. This also suggested the feasibility of integrating large language models with traditional medical education to further enhance teaching effectiveness in the future.

Genetic variants and lifestyle factors have been associated with gastric cancer risk, but the extent to which an increased genetic risk can be offset by a healthy lifestyle remains unknown. We aimed to establish a genetic risk model for gastric cancer and assess the benefits of adhering to a healthy lifestyle in individuals with a high genetic risk. In this meta-analysis and prospective cohort study, we first did a fixed-effects meta-analysis of the association between genetic variants and gastric cancer in six independent genome-wide association studies (GWAS) with a case-control study design. These GWAS comprised 21 168 Han Chinese individuals, of whom 10 254 had gastric cancer and 10 914 geographically matched controls did not. Using summary statistics from the meta-analysis, we constructed five polygenic risk scores in a range of thresholds (p=5 × 10−4 p=5 × 10−5 p=5 × 10−6 p=5 × 10−7, and p=5 × 10−8) for gastric cancer. We then applied these scores to an independent, prospective, nationwide cohort of 100 220 individuals from the China Kadoorie Biobank (CKB), with more than 10 years of follow-up. The relative and absolute risk of incident gastric cancer associated with healthy lifestyle factors (defined as not smoking, never consuming alcohol, the low consumption of preserved foods, and the frequent intake of fresh fruits and vegetables), was assessed and stratified by genetic risk (low [quintile 1 of the polygenic risk score], intermediate [quintile 2–4 of the polygenic risk score], and high [quintile 5 of the polygenic risk score]). Individuals with a favourable lifestyle were considered as those who adopted all four healthy lifestyle factors, those with an intermediate lifestyle adopted two or three factors, and those with an unfavourable lifestyle adopted none or one factor. The polygenic risk score derived from 112 single-nucleotide polymorphisms (p<5 × 10−5) showed the strongest association with gastric cancer risk (p=7·56 × 10−10). When this polygenic risk score was applied to the CKB cohort, we found that there was a significant increase in the relative risk of incident gastric cancer across the quintiles of the polygenic risk score (ptrend<0·0001). Compared with individuals who had a low genetic risk, those with an intermediate genetic risk (hazard ratio [HR] 1·54 [95% CI 1·22–1·94], p=2·67 × 10−4) and a high genetic risk (2·08 [1·61–2·69], p<0·0001) had a greater risk of gastric cancer. A similar increase in the relative risk of incident gastric cancer was observed across the lifestyle categories (ptrend<0·0001), with a higher risk of gastric cancer in those with an unfavourable lifestyle than those with a favourable lifestyle (2·03 [1·46–2·83], p<0·0001). Participants with a high genetic risk and a favourable lifestyle had a lower risk of gastric cancer than those with a high genetic risk and an unfavourable lifestyle (0·53 [0·29–0·99], p=0·048), with an absolute risk reduction of 1·12% (95% CI 0·62–1·56). Chinese individuals at an increased risk of incident gastric cancer could be identified by use of our newly developed polygenic risk score. Compared with individuals at a high genetic risk who adopt an unhealthy lifestyle, those who adopt a healthy lifestyle could substantially reduce their risk of incident gastric cancer. National Key R&D Program of China, National Natural Science Foundation of China, 333 High-Level Talents Cultivation Project of Jiangsu Province, and China Postdoctoral Science Foundation.

The value of scientific research is manifested in its impact in the scientific community as well as among the general public. Given the importance of abstracts in determining whether research articles (RAs) may be retrieved and read, recent research is paying attention to the effect of abstract readability on the scientific impact of RAs. However, to date little research has looked into the effect of abstract readability on the impact of RAs among the general public. To address this gap, this study reports on an investigation into the relationship between abstract readability and online attention received by RAs. Our dataset consisted of the abstracts of 550 RAs from 11 disciplines published in Science in 2012 and 2018. Thirty-nine lexical and syntactic complexity indices were employed to measure the readability of the abstracts, and the Altmetric attention scores of the RAs were used to measure the online attention they received. Results showed that abstract readability is significantly related to the online attention RAs receive, and that this relationship is significantly affected by discipline and publication time. Our findings have useful implications for making RA abstracts accessible to the general public.

Generative AI (GenAI) is increasingly embedded in undergraduate thesis work, intensifying concerns about thesis quality. However, limited evidence is available on how GenAI engagement relates to teachers' and students' evaluations of thesis quality and whether these associations differ across institutional and disciplinary contexts. Using a stratified random sampling method across institutional tiers and disciplines, 934 participants were recruited (684 graduating students and 250 thesis teachers). Key variables (Extent of GenAI Involvement (EX), Perceived Effect on Thesis Quality (EF), Perceived Problems/Risks (PR), Attitudes Toward GenAI Use (AT), Perceived Writing Ability Development (AB)) were measured using structured scales, then five-step hierarchical regression analysis was employed to estimate main effects and test interactions. Results showed that EX (B = 0.200, p < .001) and AB (B = 0.185, p < .001) were positively associated with EF; AT showed a marginal association (B = 0.037, p = .053) and policy presence showed a small positive association (B = 0.118, p = .001). EX/AB/PR/AT and Group interactions increased explanatory power (R2 = .445; [Formula: see text]), PR was not significant (p = .220). Policy did not moderate Group differences ([Formula: see text], p = .684). Institutional tier and Group interactions further improved fit ([Formula: see text]), strongest in World-Class Universities (B = 0.986, p < .001). Disciplinary-category and Group interactions added incremental variance ([Formula: see text]; final R2 = .510), with the largest teacher-student gap in Natural Sciences. The findings revealed that EF was most consistently linked to EX and AB, with systematic heterogeneity by group and by institutional and disciplinary context, underscoring the need for differentiated guidance on policy-compliant, capability-oriented GenAI use; however, given the cross-sectional and self-reported design, EF captures perceived thesis quality.

Pulmonary fibrosis (PF) is a chronic and fatal aging-related pulmonary disease. Emerging evidence suggests that fibroblast senescence plays a pivotal role in the initiation and progression of PF. Senescent fibroblasts accumulate in fibrotic lungs, driving excessive extracellular matrix (ECM) deposition, which disrupts tissue architecture and compromises pulmonary function. Notably, senolytic therapy targeting these senescent fibroblasts has shown significant efficacy in ameliorating PF. Therefore, elucidating the mechanisms underlying fibroblast senescence is a promising approach to prevent PF. Herein, our results identify fibroblast growth factor-inducible 14 (Fn14) as a critical mediator in the senescence of fibroblasts. We found that Fn14 was up-regulated in pulmonary fibroblasts from both PF patients and bleomycin (BLM)-treated mice. While knockdown of Fn14 attenuated pulmonary structural disruption and reduced fibroblast senescence in the lung of BLM-treated mice. In vitro, Fn14 activation promoted cellular senescence in pulmonary fibroblasts. Mechanistically, Fn14-induced mitophagy impairment resulted in mitochondrial DNA (mtDNA) leakage, which subsequently activated the cGAS-STING signaling. Moreover, restoring mitophagy or inhibiting cGAS ameliorated fibroblast senescence induced by Fn14 activation. Collectively, these results provide comprehensive insight into the pro-fibrotic role of Fn14 in the development of PF by inducing fibroblast senescence and shed light on the Fn14-targeting therapeutics for PF.

Oxidative stress-induced lipid accumulation is mediated by lipid droplets (LDs) homeostasis, which sequester vulnerable unsaturated triglycerides into LDs to prevent further peroxidation. Here we identify the upregulation of lipopolysaccharide-binding protein (LBP) and its trafficking through LDs as a mechanism for modulating LD homeostasis in response to oxidative stress. Our results suggest that LBP induces lipid accumulation by controlling lipid-redox homeostasis through its lipid-capture activity, sorting unsaturated triglycerides into LDs. N-acetyl-L-cysteine treatment reduces LBP-mediated triglycerides accumulation by phospholipid/triglycerides competition and Peroxiredoxin 4, a redox state sensor of LBP that regulates the shuttle of LBP from LDs. Furthermore, chronic stress upregulates LBP expression, leading to insulin resistance and obesity. Our findings contribute to the understanding of the role of LBP in regulating LD homeostasis and against cellular peroxidative injury. These insights could inform the development of redox-based therapies for alleviating oxidative stress-induced metabolic dysfunction. Oxidative stress triggers lipid accumulation in cells by sequestering triglycerides in lipid droplets. Here, the authors show that lipopolysaccharide-binding protein interacts with redox sensor PRDX4 to control lipid-redox balance and promotes triglyceride accumulation in droplets by capturing unsaturated lipids.