Journal: Frontiers in Microbiology

Article Title: Sanyin decoction alleviates psoriasis by reshaping gut microbiota and modulating the gut–spleen–skin axis

doi: 10.3389/fmicb.2026.1799928

Figure Lengend Snippet: Changes in intestinal short chain fatty acids and spleen transcriptome in mice treated with SYD. (A) The boxplot of acetic acid abundance among three groups; (B) The boxplot of isobutyric acid abundance among three groups; (C) Differences in PISA scores among the three groups; (D) Differences in body weight among three groups of mice; (E) and (F) The difference in thickness between the left and right ears of mice among the three groups; (G) The correlation between short chain fatty acids and phenotype indicators in mice, yellow represents positive correlation, blue represents negative correlation, and darker colors indicate higher correlation coefficients; (H) The volcano plot of transcriptome between Psoriasis and SYD Treatment groups; (I) The heatmap of inflammation related genes among significant differentially expressed genes; (J) The dot plot of GO enrichment analysis of upregulated genes; (K) The GSEA analysis of the G protein-coupled receptor signaling pathway; (L) The analysis of CIBERSORT, which displayed the relative abundance of different cell subpopulations in three groups; (M) The box plot shows significant differences in the abundance of plasma, Treg, and Tfh cell subpopulations among the three groups.

Article Snippet: High-quality RNA was subsequently used for transcriptome library construction using the MGIEasy Fast RNA Reagent (MGI, 940-002921-00), mRNA was enriched using oligo (dT) magnetic beads, followed by fragmentation with fragmentation buffer at a controlled temperature.

Techniques: Clinical Proteomics

Journal: Frontiers in Microbiology

Article Title: Sanyin decoction alleviates psoriasis by reshaping gut microbiota and modulating the gut–spleen–skin axis

doi: 10.3389/fmicb.2026.1799928

Figure Lengend Snippet: Changes in transcriptome of mouse skin after SYD treatment. (A) The volcano of differentially expressed genes; (B) The GO bioprocess (BP) analysis of significant upregulated genes; (C) The KEGG analysis of significant upregulated genes; (D) The GO molecular function (MF) analysis of significant upregulated genes; (E)-(H) The GSEA enrichment of significant regulated genes, NES < 0, represents downregulated signaling pathway, adjusted p value < 0.05, represents statistically significant; (I) The GSEA enrichment of upregulated signaling pathway; (J) The result of skin immune infiltration between Psoriasis group and Treatment group using CIBERSORT; (K) Boxplot of significant differences in immune cell subpopulations (Macrophage_M2, Neutrophils, Dendritic resting_cells).

Article Snippet: High-quality RNA was subsequently used for transcriptome library construction using the MGIEasy Fast RNA Reagent (MGI, 940-002921-00), mRNA was enriched using oligo (dT) magnetic beads, followed by fragmentation with fragmentation buffer at a controlled temperature.

Techniques:

Journal: Clinical & Translational Immunology

Article Title: Spatial omics for profiling the dynamic tumor microenvironment

doi: 10.1002/cti2.70084

Figure Lengend Snippet: Spatial omics driven characterisation of the TME evolution. (a) , Performing spatial multiomics on tumor samples collected from different stages of cancer development (normal, pre‐malignant, and malignant tissues) enables the characterisation of the spatial landscape associated with tumor progression. This will reveal stage‐specific changes in the spatial architecture of the tumor and will aid in the identification of potential targets to prevent the lesion from becoming malignant. (b) Decoding the spatial biology behind therapeutic response by using spatially resolved technologies reveals the region‐specific ligand‐receptor interactions driving therapeutic response and the cellular architecture that correlates with response. A few examples of spatial correlates of therapeutic response are given. Tumors sensitive to ICB are often associated with the presence of TLS, increased TILs, with elevation of T cell populations such as TCF7 + CD8 + T cells and GZMB + CD8 + T cells. An oncofetal niche consisting of POSTN + CAFs, FOLR2 + TAMs and PLVAP + endothelial cells has been identified to be associated with better response to combination immunotherapy in HCC. The spatial analysis of ICB resistant tumors from multiple cancer types has identified CAF subtypes forming physical barriers, which prevent the infiltration of immune cells into the tumor. ICB, immune checkpoint blockade, TLS, Tertiary Lymphoid Structure, TILs, Tumor‐infiltrating lymphocytes.

Article Snippet: Visium and Visium HD (10× Genomics) are sequencing‐based whole‐transcriptomic approaches, with Visium achieving 55 μM resolution covering 8–20 cells, and Visium HD with 2 μm single‐cell resolution., Spatially enhanced resolution omics sequencing (Stereo‐seq), commercialised as STOmics (BGI Group), uses chips with DNA nanoballs (DNBs) containing unique coordinate identity (CID), barcodes (UMI) and poly‐T oligonucleotides.

Techniques: Clinical Proteomics

Journal: Clinical & Translational Immunology

Article Title: Spatial omics for profiling the dynamic tumor microenvironment

doi: 10.1002/cti2.70084

Figure Lengend Snippet: AI‐Enabled Multi‐omics for Cancer Translational and Clinical Research. AI‐driven integration of different modalities, including (i) histology images (H&E/IHC whole‐slide images), (ii) spatial omics (spatial transcriptomics, spatial proteomics), and (iii) clinical metadata (treatment response and survival data) are jointly modelled with integrative analysis (IA), artificial intelligence (AI), machine learning (ML), and deep learning (DL). Central models learn representations across modalities to support downstream spatial analyses, including reconstruction of cellular landscapes, inference of spatially defined ligand–receptor interactions, cellular neighbourhood (CN) profiling, and trajectory/pseudotime analysis. Insights generalise to biological and clinical applications such as cancer detection, biomarker prediction, survival analysis, cell‐type clustering, tumor‐microenvironment (TME) studies, and personalised treatment selection. The bottom timeline shows the evolution of deep learning approaches.

Article Snippet: Visium and Visium HD (10× Genomics) are sequencing‐based whole‐transcriptomic approaches, with Visium achieving 55 μM resolution covering 8–20 cells, and Visium HD with 2 μm single‐cell resolution., Spatially enhanced resolution omics sequencing (Stereo‐seq), commercialised as STOmics (BGI Group), uses chips with DNA nanoballs (DNBs) containing unique coordinate identity (CID), barcodes (UMI) and poly‐T oligonucleotides.

Techniques: Biomarker Discovery, Spatial Transcriptomics, Spatial Proteomics, Selection