An Anti-Inflammatory and Antioxidant Patch Based on Injectable Bioadhesive Hydrogel Prevents Postoperative Atrial Fibrillation by Wei-Qi Lu (445130)

“…In a rat pericarditis model, this localized system significantly reduced atrial inflammation and oxidative stress, promoted anti-inflammatory M2 macrophage polarization, enhanced electrical stability, and markedly decreased POAF susceptibility.…”

An Anti-Inflammatory and Antioxidant Patch Based on Injectable Bioadhesive Hydrogel Prevents Postoperative Atrial Fibrillation by Wei-Qi Lu (445130)

“…In a rat pericarditis model, this localized system significantly reduced atrial inflammation and oxidative stress, promoted anti-inflammatory M2 macrophage polarization, enhanced electrical stability, and markedly decreased POAF susceptibility.…”

Table 1_The real-world safety of Nivolumab: a pharmacovigilance analysis based on the FDA adverse event reporting system.docx by Yutong Wu (3130584)

“…The most frequently reported AEs included fatigue, dyspnea, musculoskeletal pain, decreased appetite, cough, nausea, and constipation. …”

Table 1_Body mass index influences Antimüllerian Hormone and inhibin B in adult males.xls by Wen Zhou (49050)

“…However, the effect size for AMH was relatively low, which may limit its clinical significance. In the fully adjusted model, the increase in BMI in Q4 was linked to decreases of 1.62 ng ml-1 in AMH and 18.20 pg ml^-1 in INHB, but these associations were not statistically significant (P>0.05). …”

Image 4_Unraveling impact and potential mechanisms of baseline pain on efficacy of immunotherapy in lung cancer patients: a retrospective and bioinformatic analysis.jpg by Zexin Zhang (7507979)

Table 1_Integrative multiomics analysis reveals association of gut microbiota and its metabolites with susceptibility to keloids.xls by Dang Li (16400478)

“…An area under the curve analysis using a random forest model based on fecal metagenomics, plasma metabolomics, and tissue metabolomics revealed that gut bacteria, plasma, and tissue metabolites were effective in distinguishing between MK and NS groups. Decreased Bacteroides plebeius could lower uracil levels, altering systemic lipid metabolism, which may change the metabolic phenotype of secretory reticular fibroblasts in wounds, potentially leading to MK. …”

Image 13_Integrative multiomics analysis reveals association of gut microbiota and its metabolites with susceptibility to keloids.jpeg by Dang Li (16400478)

“…An area under the curve analysis using a random forest model based on fecal metagenomics, plasma metabolomics, and tissue metabolomics revealed that gut bacteria, plasma, and tissue metabolites were effective in distinguishing between MK and NS groups. Decreased Bacteroides plebeius could lower uracil levels, altering systemic lipid metabolism, which may change the metabolic phenotype of secretory reticular fibroblasts in wounds, potentially leading to MK. …”

Image 1_Integrative multiomics analysis reveals association of gut microbiota and its metabolites with susceptibility to keloids.jpeg by Dang Li (16400478)

“…An area under the curve analysis using a random forest model based on fecal metagenomics, plasma metabolomics, and tissue metabolomics revealed that gut bacteria, plasma, and tissue metabolites were effective in distinguishing between MK and NS groups. Decreased Bacteroides plebeius could lower uracil levels, altering systemic lipid metabolism, which may change the metabolic phenotype of secretory reticular fibroblasts in wounds, potentially leading to MK. …”

Image 2_Unraveling impact and potential mechanisms of baseline pain on efficacy of immunotherapy in lung cancer patients: a retrospective and bioinformatic analysis.jpg by Zexin Zhang (7507979)

Image 12_Integrative multiomics analysis reveals association of gut microbiota and its metabolites with susceptibility to keloids.jpeg by Dang Li (16400478)

“…An area under the curve analysis using a random forest model based on fecal metagenomics, plasma metabolomics, and tissue metabolomics revealed that gut bacteria, plasma, and tissue metabolites were effective in distinguishing between MK and NS groups. Decreased Bacteroides plebeius could lower uracil levels, altering systemic lipid metabolism, which may change the metabolic phenotype of secretory reticular fibroblasts in wounds, potentially leading to MK. …”

Image 11_Integrative multiomics analysis reveals association of gut microbiota and its metabolites with susceptibility to keloids.jpeg by Dang Li (16400478)

“…An area under the curve analysis using a random forest model based on fecal metagenomics, plasma metabolomics, and tissue metabolomics revealed that gut bacteria, plasma, and tissue metabolites were effective in distinguishing between MK and NS groups. Decreased Bacteroides plebeius could lower uracil levels, altering systemic lipid metabolism, which may change the metabolic phenotype of secretory reticular fibroblasts in wounds, potentially leading to MK. …”

Image 2_Integrative multiomics analysis reveals association of gut microbiota and its metabolites with susceptibility to keloids.jpeg by Dang Li (16400478)

“…An area under the curve analysis using a random forest model based on fecal metagenomics, plasma metabolomics, and tissue metabolomics revealed that gut bacteria, plasma, and tissue metabolites were effective in distinguishing between MK and NS groups. Decreased Bacteroides plebeius could lower uracil levels, altering systemic lipid metabolism, which may change the metabolic phenotype of secretory reticular fibroblasts in wounds, potentially leading to MK. …”

Image 1_Unraveling impact and potential mechanisms of baseline pain on efficacy of immunotherapy in lung cancer patients: a retrospective and bioinformatic analysis.jpg by Zexin Zhang (7507979)

Image 10_Integrative multiomics analysis reveals association of gut microbiota and its metabolites with susceptibility to keloids.jpeg by Dang Li (16400478)

“…An area under the curve analysis using a random forest model based on fecal metagenomics, plasma metabolomics, and tissue metabolomics revealed that gut bacteria, plasma, and tissue metabolites were effective in distinguishing between MK and NS groups. Decreased Bacteroides plebeius could lower uracil levels, altering systemic lipid metabolism, which may change the metabolic phenotype of secretory reticular fibroblasts in wounds, potentially leading to MK. …”

Image 9_Integrative multiomics analysis reveals association of gut microbiota and its metabolites with susceptibility to keloids.jpeg by Dang Li (16400478)

“…An area under the curve analysis using a random forest model based on fecal metagenomics, plasma metabolomics, and tissue metabolomics revealed that gut bacteria, plasma, and tissue metabolites were effective in distinguishing between MK and NS groups. Decreased Bacteroides plebeius could lower uracil levels, altering systemic lipid metabolism, which may change the metabolic phenotype of secretory reticular fibroblasts in wounds, potentially leading to MK. …”

Image 3_Integrative multiomics analysis reveals association of gut microbiota and its metabolites with susceptibility to keloids.jpeg by Dang Li (16400478)

“…An area under the curve analysis using a random forest model based on fecal metagenomics, plasma metabolomics, and tissue metabolomics revealed that gut bacteria, plasma, and tissue metabolites were effective in distinguishing between MK and NS groups. Decreased Bacteroides plebeius could lower uracil levels, altering systemic lipid metabolism, which may change the metabolic phenotype of secretory reticular fibroblasts in wounds, potentially leading to MK. …”

Image 7_Integrative multiomics analysis reveals association of gut microbiota and its metabolites with susceptibility to keloids.jpeg by Dang Li (16400478)

“…An area under the curve analysis using a random forest model based on fecal metagenomics, plasma metabolomics, and tissue metabolomics revealed that gut bacteria, plasma, and tissue metabolites were effective in distinguishing between MK and NS groups. Decreased Bacteroides plebeius could lower uracil levels, altering systemic lipid metabolism, which may change the metabolic phenotype of secretory reticular fibroblasts in wounds, potentially leading to MK. …”

Image 6_Integrative multiomics analysis reveals association of gut microbiota and its metabolites with susceptibility to keloids.jpeg by Dang Li (16400478)

“…An area under the curve analysis using a random forest model based on fecal metagenomics, plasma metabolomics, and tissue metabolomics revealed that gut bacteria, plasma, and tissue metabolites were effective in distinguishing between MK and NS groups. Decreased Bacteroides plebeius could lower uracil levels, altering systemic lipid metabolism, which may change the metabolic phenotype of secretory reticular fibroblasts in wounds, potentially leading to MK. …”

Image 8_Integrative multiomics analysis reveals association of gut microbiota and its metabolites with susceptibility to keloids.jpeg by Dang Li (16400478)

“…An area under the curve analysis using a random forest model based on fecal metagenomics, plasma metabolomics, and tissue metabolomics revealed that gut bacteria, plasma, and tissue metabolites were effective in distinguishing between MK and NS groups. Decreased Bacteroides plebeius could lower uracil levels, altering systemic lipid metabolism, which may change the metabolic phenotype of secretory reticular fibroblasts in wounds, potentially leading to MK. …”

Image 5_Integrative multiomics analysis reveals association of gut microbiota and its metabolites with susceptibility to keloids.jpeg by Dang Li (16400478)

“…An area under the curve analysis using a random forest model based on fecal metagenomics, plasma metabolomics, and tissue metabolomics revealed that gut bacteria, plasma, and tissue metabolites were effective in distinguishing between MK and NS groups. Decreased Bacteroides plebeius could lower uracil levels, altering systemic lipid metabolism, which may change the metabolic phenotype of secretory reticular fibroblasts in wounds, potentially leading to MK. …”