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. …”

Image 3_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 4_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. …”

Table1_Drought stress reduces arbuscular mycorrhizal colonization of Poncirus trifoliata (L.) roots and plant growth promotion via lipid metabolism.docx by Wei Zhang (405)

“…Results indicated that AM fungal inoculation significantly promoted the drought tolerance of P. trifoliata (L.), with the effect size decreasing along with drought severity. …”

Table2_Drought stress reduces arbuscular mycorrhizal colonization of Poncirus trifoliata (L.) roots and plant growth promotion via lipid metabolism.xlsx by Wei Zhang (405)

“…Results indicated that AM fungal inoculation significantly promoted the drought tolerance of P. trifoliata (L.), with the effect size decreasing along with drought severity. …”

DataSheet1_Drought stress reduces arbuscular mycorrhizal colonization of Poncirus trifoliata (L.) roots and plant growth promotion via lipid metabolism.docx by Wei Zhang (405)

“…Results indicated that AM fungal inoculation significantly promoted the drought tolerance of P. trifoliata (L.), with the effect size decreasing along with drought severity. …”