metabolomic profiling  (Baylor Genetics)

Journal: Bioactive Materials

Article Title: Oxygen-vacancy-engineered t-ZnO-CeO 2 Schottky junction enhanced infectious bone regeneration via photoelectric-photocatalytic effects-induced mitochondrial quality control

doi: 10.1016/j.bioactmat.2026.04.042

Figure Lengend Snippet: Analysis of RNA changes and metabolite alterations in 3D-printed scaffolds. (a) Schematic representation depicting the process of transcriptomics analysis and metabolomic analysis in rBMSCs cultured with the 3D-printed scaffolds. (b) Heatmap of differentially expressed genes (DEGs) in PLLA/tZC + NIR groups vs NIR groups (n = 3). (c) Volcano diagram of the gene characteristics of rBMSCs. (d, e) GO enrichment analysis of the (d) up-regulated terms and (e) down-regulated terms among DEGs. (f, g) KEGG enrichment analysis of the (f) up-regulated and (g) down-regulated pathways among DEGs. (h) PCA analysis of untargeted metabolomics of rBMSCs in PLLA/tZC + NIR groups vs NIR groups (n = 5). (i) Volcano diagram of the metabolite characteristics of rBMSCs. (j) The heatmap of differentially expressed metabolites (DEMs). (k) Sankey diagram of pathways for DEMs.

Article Snippet: For metabolomic profiling, the samples were sent to Bioprofile Co., Ltd. (Shanghai, China) for analysis.

Techniques: Transcriptomics, Metabolomic, Cell Culture

Journal: Metabolites

Article Title: Metabolomic Signature of Visceral Adiposity: Insights from a Population-Based Cohort

doi: 10.3390/metabo16050343

Figure Lengend Snippet: ( A ) The fitted regression line and cross-validated model performance (R 2 = 0.66) show the link between observed DXA-derived VAT z-scores and PLS-predicted VAT z-scores based on the metabolomics data. ( B ) The PLS model’s variable importance in projection (VIP) scores were used to rank the top 30 metabolites; higher VIP values indicate a larger contribution to the metabolomic signature linked to VAT. Metabolites are colored by VIP score intensity (purple—low to yellow—high). * and ** indicates a compound that has not been officially confirmed based on a standard, but that Metabolon is confident in its identity.

Article Snippet: Additionally, the dataset included information on medication usage [ ], medical history, and a metabolomics profile covering more than 1000 metabolites using the Metabolon platform [ ].

Techniques: Derivative Assay, Metabolomic

Journal: Animals : an Open Access Journal from MDPI

Article Title: Effects of Feeding High-Moisture Corn on Meat Performance, Meat Quality, Muscle Metabolism, and Gut Microbiota in Kazakh Rams

doi: 10.3390/ani16091387

Figure Lengend Snippet: Principal component analysis diagram between the two groups. ( a ) Three-dimensional PCA score plot. PC1, PC2, and PC3 represent the first three principal components, explaining 28.6%, 23.9%, and 14.8% of the total variance, respectively. Each sphere represents an individual muscle sample; red spheres = GS group ( n = 8), blue spheres = CT group ( n = 4). The spatial separation between groups indicates distinct metabolic profiles; ( b ) Orthogonal partial least squares-discriminant analysis (OPLS-DA) score plot of muscle metabolomics data between GS group and CT group. The horizontal axis (t ) represents the predictive principal component (explaining 17.7% of variance), capturing the maximum separation between groups. The vertical axis (to ) represents the orthogonal principal component (explaining 21.7% of variance), capturing within-group variation. GS samples (red) cluster at approximately (0.8, –0.2), and CT samples (blue) cluster at approximately (–0.8, 0.2). Model quality parameters: R 2 Y = 0.963, Q 2 = 0.706.; ( c ) The OPLS-DA model, validation plot displays the horizontal axis representing model accuracy and the vertical axis showing the frequency of classification outcomes. Specifically, this model conducted 200 randomized permutation experiments on datasets. When Q2’s p -value reaches 0.01, it indicates that 4 randomized grouping models outperformed the OPLS-DA model in this permutation test. If R2Y’s p -value equals 0.545, it suggests that 109 randomized grouping models demonstrated higher explanatory power for the Y matrix compared to the OPLS-DA model. Generally, models with p -values below 0.05 are considered optimal.

Article Snippet: For metabolomic profiling, 100 mg of longissimus muscle tissue was combined with 400 μL of methanol (A452-4, Fisher Chemical, Thermo Fisher Scientific, Waltham, MA, USA), vortex-mixed for 1 min, and subjected to five cycles of ultrasonication in an ice-water bath (1 min each, with 1 min intervals).

Techniques: Biomarker Discovery