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Purpose Inulin is a type of fermentable dietary fiber, which is non-digestible, and can improve metabolic function by modulating intestinal microbiota. This study aimed to evaluate the role of inulin in hyperuricemia and microbial composition of the gut microbiota in a mouse model of hyperuricemia established through knockout of Uox (urate oxidase) gene. Methods KO ( Uox -knockout) and WT (wild-type) mice were given inulin or saline by gavage for 7 weeks. The effect of inulin to combat hyperuricemia was determined by assessing the changes in serum UA (uric acid) levels, inflammatory parameters, epithelial barrier integrity, fecal microbiota alterations, and SCFA (short-chain fatty acid) concentrations in KO mice. Results Inulin supplementation can effectively alleviate hyperuricemia, increase the expressions of ABCG2 in intestine, and downregulate expression and activity of hepatic XOD (xanthine oxidase) in KO mice. It was revealed that the levels of inflammatory cytokines and the LPS (lipopolysaccharide) were remarkably higher in the KO group than those in the WT group, indicating systemic inflammation of hyperuricemic mice, but inulin treatment ameliorated inflammation in KO mice. Besides, inulin treatment repaired the intestinal epithelial barrier as evidenced by increased levels of intestinal TJ (tight junction) proteins [ZO-1 (zonula occludens-1) and occluding] in KO mice. Moreover, serum levels of uremic toxins, including IS (indoxyl sulfate) and PCS ( p -cresol sulfate), were reduced in inulin-treated KO mice. Further investigation unveiled that inulin supplementation enhanced microbial diversity and raised the relative abundance of beneficial bacteria, involving SCFAs-producing bacteria (e.g., Akkermansia and Ruminococcus ). Additionally, inulin treatment increased the production of gut microbiota-derived SCFAs (acetate, propionate and butyrate concentrations) in KO mice, which was positively correlated with the effectiveness of hyperuricemia relief. Conclusions Our findings showed that inulin may be a promising therapeutic candidate for the treatment of hyperuricemia. Moreover, alleviation of hyperuricemia by inulin supplementation was, at least, partially conciliated by modulation of gut microbiota and its metabolites.

Fucoidan is a kind of the polysaccharide, which comes from brown algae and comprises of sulfated fucose residues. It has shown a large range of biological activities in basic researches, including many elements like anti-inflammatory, anti-cancer, anti-viral, anti-oxidation, anticoagulant, antithrombotic, anti-angiogenic and anti-Helicobacter pylori, etc. Cancer is a multifactorial disease of multiple causes. Most of the current chemotherapy drugs for cancer therapy are projected to eliminate the ordinary deregulation mechanisms in cancer cells. Plenty of wholesome tissues, however, are also influenced by these chemical cytotoxic effects. Existing researches have demonstrated that fucoidan can directly exert the anti-cancer actions through cell cycle arrest, induction of apoptosis, etc., and can also indirectly kill cancer cells by activating natural killer cells, macrophages, etc. Fucoidan is used as a new anti-tumor drug or as an adjuvant in combination with an anti-tumor drug because of its high biological activity, wide source, low resistance to drug resistance and low side effects. This paper reviews the mechanism by which fucoidan can eliminate tumor cells, delay tumor growth and synergize with anticancer chemotherapy drugs in vitro, in vivo and in clinical trials.

Background Globally, colorectal cancer (CRC) affects more than 1 million people each year. In addition to non-modifiable and other environmental risk factors, Fusobacterium nucleatum infection has been linked to CRC recently. In this study, we explored mechanisms underlying the role of Fusobacterium nucleatum infection in the progression of CRC in a mouse model. Methods C57BL/6 J-Adenomatous polyposis coli (APC) Min/J mice [APC (Min/+)] were treated with Fusobacterium nucleatum (10 9  cfu/mL, 0.2 mL/time/day, i.g., 12 weeks), saline, or FadA knockout (FadA−/−) Fusobacterium nucleatum . The number, size, and weight of CRC tumors were determined in isolated tumor masses. The human CRC cell lines HCT29 and HT116 were treated with lentiviral vectors overexpressing chk2 or silencing β-catenin. DNA damage was determined by Comet assay and γH2AX immunofluorescence assay and flow cytometry. The mRNA expression of chk2 was determined by RT-qPCR. Protein expression of FadA, E-cadherin, β-catenin, and chk2 were determined by Western blot analysis. Results Fusobacterium nucleatum treatment promoted DNA damage in CRC in APC (Min/+) mice. Fusobacterium nucleatum also increased the number of CRC cells that were in the S phase of the cell cycle. FadA−/− reduced tumor number, size, and burden in vivo. FadA−/− also reduced DNA damage, cell proliferation, expression of E-cadherin and chk2, and cells in the S phase. Chk2 overexpression elevated DNA damage and tumor growth in APC (Min/+) mice. Conclusions In conclusion, this study provided evidence that Fusobacterium nucleatum induced DNA damage and cell growth in CRC through FadA-dependent activation of the E-cadherin/β-catenin pathway, leading to up-regulation of chk2.

Background Dysbiosis of the gut microbiota is closely linked to hyperuricemia. However, the effect of the microbiome on uric acid (UA) metabolism remains unclear. This study aimed to explore the mechanisms through which microbiomes affect UA metabolism with the hypothesis that modifying the intestinal microbiota influences the development of hyperuricemia. Results We proposed combining an antibiotic strategy with protein-protein interaction analysis to test this hypothesis. The data demonstrated that antibiotics altered the composition of gut microbiota as UA increased, and that the spectrum of the antibiotic was connected to the purine salvage pathway. The antibiotic-elevated UA concentration was dependent on the increase in microbiomes that code for the proteins involved in purine metabolism, and was paralleled by the depletion of bacteria-coding enzymes required for the purine salvage pathway. On the contrary, the microbiota with abundant purine salvage proteins decreased hyperuricemia. We also found that the antibiotic-increased microbiota coincided with a higher relative abundance of bacteria in hyperuricemia mice. Conclusions An antibiotic strategy combined with the prediction of microbiome bacterial function presents a feasible method for defining the key bacteria involved in hyperuricemia. Our investigations discovered that the core microbiomes of hyperuricemia may be related to the gut microbiota that enriches purine metabolism related-proteins. However, the bacteria that enrich the purine salvage-proteins may be a probiotic for decreasing urate, and are more likely to be killed by antibiotics. Therefore, the purine salvage pathway may be a potential target for the treatment of both hyperuricemia and antibiotic resistance.

CCL2, a pivotal cytokine within the chemokine family, functions by binding to its receptor CCR2. The CCL2/CCR2 signaling pathway plays a crucial role in the development of fibrosis across multiple organ systems by modulating the recruitment and activation of immune cells, which in turn influences the progression of fibrotic diseases in the liver, intestines, pancreas, heart, lungs, kidneys, and other organs. This paper introduces the biological functions of CCL2 and CCR2, highlighting their similarities and differences concerning fibrotic disorders in various organ systems, and reviews recent progress in the diagnosis and treatment of clinical fibrotic diseases linked to the CCL2/CCR2 signaling pathway. Additionally, further in-depth research is needed to explore the clinical significance of the CCL2/CCR2 axis in fibrotic conditions affecting different organs.

Background: The gut microbiota is closely linked to cholesterol metabolism-related diseases such as obesity and cardiovascular diseases. However, whether gut microbiota plays a causal role in cholelithiasis remains unclear.Aims: This study explored the causal relationship between gut microbiota and cholelithiasis. We hypothesize that the gut microbiota influences cholelithiasis development.Methods: A two-sample Mendelian randomization method was combined with STRING analysis to test this hypothesis. Summary data on gut microbiota and cholelithiasis were obtained from the MiBioGen (n=13,266) and FinnGen R8 consortia (n=334,367), respectively.Results: Clostridium senegalense, Coprococcus3, and Lentisphaerae increased the risk of cholelithiasis and expressed more bile salt hydrolases. In contrast, Holdemania, Lachnospiraceae UCG010, and Ruminococcaceae NK4A214 weakly expressed bile salt hydrolases and were implied to have a protective effect against cholelithiasis by Mendelian randomization analysis.Conclusion: Gut microbiota causally influences cholelithiasis and may be related to bile salt hydrolases. This work improves our understanding of cholelithiasis causality to facilitate the development of treatment strategies.

Endoscopic submucosal dissection (ESD) is an effective treatment with minimal invasiveness for early gastric cancer (EGC). However, cases undergoing non-curative resection (NCR) may still undergo additional surgical procedures. We aimed to analyze the features of NCR under white light imaging (WLI), and develop a prediction model to assess the risk of NCR before ESD. We retrospectively collected and analyzed WLI and clinicopathological features of 568 EGC patients undergoing ESD between March 2016 and March 2024. A nomogram was developed on 455 patients from the training set after subgroup difference analysis. 91 out of 568 (16.0%) cases had NCR. WLI features including remarkable redness, ulceration, fold convergence, marginal elevation, whitish mucosal change, larger lesions, and Helicobacter pylori (Hp) infection were associated with independent risk factors for NCR. The nomogram based on these features showed good predictive value for NCR, with an area under the curve (AUC) of 0.8095 (95% CI: 0.7538–0.8651) in the training set and 0.7567 (95% CI: 0.6427–0.8707) in the validation set. We developed a nomogram incorporating WLI features that exhibits good predictive performance and could potentially assist in selecting optimal treatment strategies for EGC.

Abstract Background: Gut microbiota are important for uric acid (UA) metabolism in hyperuricemia (HUA); however, the underlying mechanisms of how the gut microbiota regulate intestinal UA metabolism remain unclear. This study aimed to explore the function of the intestine in HUA and to further reveal the possible mechanism. Methods: We conducted gut microbiota depletion to validate the role of gut microbiota in UA metabolism. A mouse model of HUA was established, and the gut microbiota and microbiome-derived metabolites were analyzed via 16S RNA gene sequencing and metabolomics analysis. The mechanism of the gut microbiota in HUA was elucidated by in vivo and in vitro experiments. Results: Antibiotic treatment elevated serum UA, disturbed purine metabolism, and decreased the relative abundance of Lactobacillus. HUA mice had a lower relative abundance of Lactobacillus johnsonii (L. johnsonii) and decreased gut butyrate concentration. Supplementation of L. johnsonii significantly reduces serum UA in hyperuricemia mice by preventing UA synthesis and promoting the excretion of gut purine metabolites. In addition, L. johnsonii enhanced intestinal UA excretion by heightening the urate transporter ABCG2 (adenosine triphosphate-binding cassette transporter, subfamily G, member 2) expression, and increasing the levels of butyrate, which upregulated ABCG2 expression via the Wnt5a/b/β-catenin signaling pathway. Conclusion: Our results suggest that gut microbiota and microbiota-derived metabolites directly regulate gut UA metabolism, highlighting potential applications in the treatment of diet-induced HUA by targeting gut microbiota and its metabolites.

FAT atypical cadherin 1 (FAT1) is a mutant gene frequently found in human cancers and mainly accumulates at the plasma membrane of cancer cells. Emerging evidence has implicated FAT1 in the progression of gastric cancer (GC). This study intended to identify a regulatory network related to FAT1 in GC development. Upregulated expression of FAT1 was confirmed in GC tissues, and silencing FAT1 was observed to result in suppression of GC cell oncogenic phenotypes. Mechanistic investigation results demonstrated that FAT1 upregulated AP‐1 expression by phosphorylating c‐JUN and c‐FOS, whereas LINC00857 elevated the expression of FAT1 by recruiting a transcription factor TFAP2C. Functional experiments further suggested that LINC00857 enhanced the malignant biological characteristics of GC cells through TFAP2C‐mediated promotion of FAT1. More importantly, LINC00857 silencing delayed the tumor growth and blocked epithelial–mesenchymal transition in tumor‐bearing mice, which was associated with downregulated expression of TFAP2C/FAT1. To conclude, LINC00857 plays an oncogenic role in GC through regulating the TFAP2C/FAT1/AP‐1 axis. Therefore, this study contributes to extended the understanding of gastric carcinogenesis and LINC00857 may serve as a therapeutic target for GC. This study contributes to extended understanding of gastric carcinogenesis and LINC00857 may serve as a therapeutic target for GC.

Objective To develop and validate a prognostic model incorporating microRNA-1246 (miR-1246), high-mobility group box 1 (HMGB-1), α1-antitrypsin (A1AT), and inflammatory markers for predicting outcomes in early gastric cardia cancer after endoscopic submucosal dissection (ESD). Methods We retrospectively enrolled 280 patients with early gastric cardia cancer who underwent ESD between January 2021 and December 2023. Patients were divided into a training set ( n  = 196) and a validation set ( n  = 84) at a ratio of 7:3. Influencing factors were screened using univariate, Least Absolute Shrinkage and Selection Operator (LASSO), and multivariate logistic regression analyses in the training set. A nomogram was constructed, and the predictive performance was assessed using receiver operating characteristic (ROC) curves and calibration curves. Decision curve analysis (DCA) was used to evaluate the clinical value. Results The incidence of poor prognosis was comparable between training (43.88%) and validation set (34.52%). Multivariate logistic regression analysis identified miR-1246, HMGB-1, A1AT, tumor necrosis factor-α (TNF-α), and Helicobacter pylori infection as independent risk factors for poor prognosis (All P  < 0.05). The nomogram demonstrated acceptable discriminative ability, with AUC of 0.789 (95% CI: 0.701–0.877) in the training set and 0.735 (95% CI: 0.638–0.835) in the validation set. The sensitivity and specificity were 0.625 and 0.841 for the training set, and 0.481 and 0.786 for the validation set, respectively. Calibration curves indicated good agreement between predicted and observed probabilities. Conclusion The proposed prognostic model offers a practical tool for individualized risk assessment post-ESD. However, the clinical application warrants further validation in large-scale, multi-center prospective studies with long-term follow-up.