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 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. …”

Table 1_Characterization of glycogen-related glycoside hydrolase glgX and glgB from Klebsiella pneumoniae and their roles in biofilm formation and virulence.docx by Xinyue Liu (170148)

“…We found that both enzymes exhibited significant degradation activity against glycogen substrates and were capable of degrading amylopectin, amylose, and pullulan. …”

Image 1_The contribution of BTK signaling in myeloid cells to neuroinflammation.jpeg by Claudia Bassani (7235849)

“…Therapeutic intervention with evobrutinib ameliorated EAE severity and was associated with a significant modest decrease in the frequency of CNS-infiltrating proinflammatory macrophages. …”

Altering rRNA 2’O-methylation pattern during neuronal differentiation is regulated by FMRP by Michelle Ninochka D’Souza (22365912)

“…We found that FMRP influences a distinct rRNA 2’O-Methylation pattern across neuronal differentiation. …”

Data Sheet 1_Metabolomics analysis of aqueous humor from patients with high-myopia complicated nuclear cataract.pdf by Qiuyi Huo (21398225)

“…</p>Conclusion<p>This work identified valuable metabolic biomarkers and pathways that may improve understanding HMnC pathogenesis. Here, we found that a decrease in glutathione might promote the occurrence of HMnC. …”

Data Sheet 2_Metabolomics analysis of aqueous humor from patients with high-myopia complicated nuclear cataract.pdf by Qiuyi Huo (21398225)

“…</p>Conclusion<p>This work identified valuable metabolic biomarkers and pathways that may improve understanding HMnC pathogenesis. Here, we found that a decrease in glutathione might promote the occurrence of HMnC. …”

Presentation 1_Changes to inflammatory markers during 5 years of viral suppression and during viral blips in people with HIV initiating different integrase inhibitor based regimens... by Nicholas T. Funderburg (9422033)

“…Levels of D-dimer, sCD14, and TNFR1 decreased significantly from baseline in all treatment arms, with no significant differences between arms at any timepoint. …”

Cholecalciferol alleviates testicular dysfunction in experimental hyperthyroidism via antioxidant, anti-inflammatory and antiapoptotic effects by Heba Rady Salem (21356361)

“…It significantly decreased the levels of serum inflammatory markers and malondialdehyde levels. …”

Table 2_Relations between neurometabolism and clinical biomarkers in patients with metabolic disease.xlsx by Chao-Chao Chen (21090215)

“…The SUVRs were calculated using the standard methodology, where the mean standardized uptake value (SUV) of each region of interest (ROI) was divided by the mean SUV of the reference region, that is the whole cerebellum. …”

Image 3_Relations between neurometabolism and clinical biomarkers in patients with metabolic disease.tiff by Chao-Chao Chen (21090215)

“…The SUVRs were calculated using the standard methodology, where the mean standardized uptake value (SUV) of each region of interest (ROI) was divided by the mean SUV of the reference region, that is the whole cerebellum. …”

Table 1_Relations between neurometabolism and clinical biomarkers in patients with metabolic disease.xlsx by Chao-Chao Chen (21090215)

“…The SUVRs were calculated using the standard methodology, where the mean standardized uptake value (SUV) of each region of interest (ROI) was divided by the mean SUV of the reference region, that is the whole cerebellum. …”

Image 2_Relations between neurometabolism and clinical biomarkers in patients with metabolic disease.tiff by Chao-Chao Chen (21090215)

“…The SUVRs were calculated using the standard methodology, where the mean standardized uptake value (SUV) of each region of interest (ROI) was divided by the mean SUV of the reference region, that is the whole cerebellum. …”

Table 3_Relations between neurometabolism and clinical biomarkers in patients with metabolic disease.xlsx by Chao-Chao Chen (21090215)

“…The SUVRs were calculated using the standard methodology, where the mean standardized uptake value (SUV) of each region of interest (ROI) was divided by the mean SUV of the reference region, that is the whole cerebellum. …”

Image 1_Relations between neurometabolism and clinical biomarkers in patients with metabolic disease.tiff by Chao-Chao Chen (21090215)

“…The SUVRs were calculated using the standard methodology, where the mean standardized uptake value (SUV) of each region of interest (ROI) was divided by the mean SUV of the reference region, that is the whole cerebellum. …”

Image 8_Relations between neurometabolism and clinical biomarkers in patients with metabolic disease.tif by Chao-Chao Chen (21090215)

“…The SUVRs were calculated using the standard methodology, where the mean standardized uptake value (SUV) of each region of interest (ROI) was divided by the mean SUV of the reference region, that is the whole cerebellum. …”