heatmaps of gene expression z scores  (GraphPad Software Inc)

Journal: bioRxiv

Article Title: Precursor of chemically expanded hepatocytes (pre-cHep) with 1-million-fold expansion potential and liver repopulation capacity

doi: 10.64898/2026.05.15.725446

Figure Lengend Snippet: Characterization of cHep. A. Direct differentiation of cryopreserved pre-cHep using a protocol equivalent to 3D PHH spheroid formation. B. Representative images of 3D PHH and cHep. C. Principal component analysis (PCA) plot including cHep generated from day 30 (D30) J03, J06, and J13 L4 pre-cHep, 3D PHH, and published hepatocyte-like cells (HLC). D. Heatmap showing expression of 264 liver-enriched genes. E–H. Distance-based similarity scores based on gene expression associated with xenobiotic metabolism (E), amino acid biosynthesis (F), bile acid biosynthesis (G), and the urea cycle (H). I. Immunofluorescence staining for albumin, HNF4α, CYP2E1, and ASGR1. J. Cholyl-lysyl-fluorescein (CLF) staining.

Article Snippet: Hierarchical clustering and gene expression heatmap analysis of 264 liver-enriched genes from Human Protein Atlas (gene list in Supplementary Table S3) also showed that D30 cHep clustered closely with 3D PHH, although expression of some genes remained lower than in uncultured PHH and liver samples ( ).

Techniques: Generated, Expressing, Gene Expression, Immunofluorescence, Staining

Journal: bioRxiv

Article Title: Precursor of chemically expanded hepatocytes (pre-cHep) with 1-million-fold expansion potential and liver repopulation capacity

doi: 10.64898/2026.05.15.725446

Figure Lengend Snippet: Gene expression analysis of HLC. Distance-based similarity score and gene expression heatmap with KEGG gene sets: Fatty acid metabolism (A, D), Retinol metabolism (B, E) and Complement coagulation cascade (C, F).

Article Snippet: Hierarchical clustering and gene expression heatmap analysis of 264 liver-enriched genes from Human Protein Atlas (gene list in Supplementary Table S3) also showed that D30 cHep clustered closely with 3D PHH, although expression of some genes remained lower than in uncultured PHH and liver samples ( ).

Techniques: Gene Expression, Coagulation

Journal: Discover Oncology

Article Title: Single cell RNA sequencing decodes cellular heterogeneity and identifies prognostic immune signatures in bladder cancer microenvironment

doi: 10.1007/s12672-025-03878-1

Figure Lengend Snippet: Multi-level integrated analysis of bladder cancer single-cell transcriptome. (A) Cell type identification based on NMF algorithm. (B) Differential gene expression heatmap; (C-D) Cell trajectory inference analysis; (E) Cell-cell interaction network; (F-G) GAR and HGF signaling pathway network activity analysis

Article Snippet: Fig. 4 Comprehensive analysis of bladder cancer cell communication networks and transcriptional regulation. (A) Cell signaling output and reception patterns; (B) Signaling molecule correlation matrix; (C) Biological process enrichment analysis of NMF subtypes; (D) Characteristic gene expression heatmap; (E) Spatial distribution of transcriptional regulator activation states

Techniques: Gene Expression, Activity Assay

Journal: Discover Oncology

Article Title: Single cell RNA sequencing decodes cellular heterogeneity and identifies prognostic immune signatures in bladder cancer microenvironment

doi: 10.1007/s12672-025-03878-1

Figure Lengend Snippet: Comprehensive analysis of bladder cancer cell communication networks and transcriptional regulation. (A) Cell signaling output and reception patterns; (B) Signaling molecule correlation matrix; (C) Biological process enrichment analysis of NMF subtypes; (D) Characteristic gene expression heatmap; (E) Spatial distribution of transcriptional regulator activation states

Article Snippet: Fig. 4 Comprehensive analysis of bladder cancer cell communication networks and transcriptional regulation. (A) Cell signaling output and reception patterns; (B) Signaling molecule correlation matrix; (C) Biological process enrichment analysis of NMF subtypes; (D) Characteristic gene expression heatmap; (E) Spatial distribution of transcriptional regulator activation states

Techniques: Gene Expression, Activation Assay

Journal: Discover Oncology

Article Title: Single cell RNA sequencing decodes cellular heterogeneity and identifies prognostic immune signatures in bladder cancer microenvironment

doi: 10.1007/s12672-025-03878-1

Figure Lengend Snippet: Dynamic trajectory and communication network analysis of bladder cancer single-cell transcriptome. (A) Cell typeidentification based on NMF; (B) Characteristic gene expression heatmap; (C-D) Cell differentiation trajectory inference; (E) Cell-cell interaction network; (F) Signaling pathway activation state analysis

Article Snippet: Fig. 4 Comprehensive analysis of bladder cancer cell communication networks and transcriptional regulation. (A) Cell signaling output and reception patterns; (B) Signaling molecule correlation matrix; (C) Biological process enrichment analysis of NMF subtypes; (D) Characteristic gene expression heatmap; (E) Spatial distribution of transcriptional regulator activation states

Techniques: Gene Expression, Cell Differentiation, Activation Assay

Journal: Discover Oncology

Article Title: Single cell RNA sequencing decodes cellular heterogeneity and identifies prognostic immune signatures in bladder cancer microenvironment

doi: 10.1007/s12672-025-03878-1

Figure Lengend Snippet: Multi-level analysis of bladder cancer transcriptional regulatory networks. (A) Correlation analysis between transcription factors and target genes; (B) Transcriptional regulator activation heatmap; (C) Spatial distribution of regulatory network activation; (D) Core regulatory factor activity comparison; (E) Biological process enrichment analysis

Article Snippet: Fig. 4 Comprehensive analysis of bladder cancer cell communication networks and transcriptional regulation. (A) Cell signaling output and reception patterns; (B) Signaling molecule correlation matrix; (C) Biological process enrichment analysis of NMF subtypes; (D) Characteristic gene expression heatmap; (E) Spatial distribution of transcriptional regulator activation states

Techniques: Activation Assay, Activity Assay, Comparison

Journal: Biological Psychiatry Global Open Science

Article Title: Regional Molecular Changes in Chronic Lipopolysaccharide-Induced Neuroinflammation

doi: 10.1016/j.bpsgos.2025.100515

Figure Lengend Snippet: Circulating inflammatory cytokines and brain tissue expression of inflammatory and apoptotic markers. Serum concentrations of IL-1β (A) , TNF-α (B) , and IL-6 (C) in the ST- and LT-LPS and CON groups. (D–K) Heatmaps of real-time polymerase chain reaction results showing the effect of ST- and LT-LPS treatment on the mRNA expression of inflammatory markers in the Hyp, Pfc, Str, Hip, Mdb, Ctx, and Cbm. (G–I, K) Heatmaps of the sagittal plane of the rat brain showing upregulated or downregulated mRNA expression in the different brain regions as a result of LPS administration. LPS (1 mg/kg, i.p.; ST, n = 8; LT, n = 9) and saline (0.1 mL, i.p.; ST, n = 10; LT, n = 10) were administered once off (ST; n = 18) and once a week for 4 weeks (LT; n = 19). Data are presented as mean ± SD relative to the housekeeping gene Tbp . Data were analyzed using a 2-way analysis of variance followed by a Tukey’s post hoc test, and heatmaps are represented as expression values ( z scores) for differentially expressed genes. (A–C) p < .05 ( ∗ ), p < .01 ( ∗∗ ), p < .0001 ( ∗∗∗∗ ). (D–F, J) a ST-CON vs. ST-LPS; b ST-LPS vs. LT-LPS; c LT-CON vs. LT-LPS. p < .05 (a, b, c), p < .01 (aa, bb, cc), p < .001 (aaa, bbb, ccc), p < .0001 (aaaa, bbbb, cccc). Cbm, cerebellum; CON, control; Ctx, cortex; Hip, hippocampus; Hyp, hypothalamus; IFN-γ, interferon gamma; IL, interleukin; i.p., intraperitoneally; LPS, lipopolysaccharide; LT, long-term; Mdb, midbrain; mRNA, messenger RNA; Pfc, prefrontal cortex; ST, short-term; Str, striatum; TNF-α, tumor necrosis factor α.

Article Snippet: Heatmaps of gene expression z scores (see for additional information) for ST- and LT-CON and LPS-groups were generated in GraphPad Prism version 10 (GraphPad Software).

Techniques: Expressing, Real-time Polymerase Chain Reaction, Saline, Control

Journal: Biological Psychiatry Global Open Science

Article Title: Regional Molecular Changes in Chronic Lipopolysaccharide-Induced Neuroinflammation

doi: 10.1016/j.bpsgos.2025.100515

Figure Lengend Snippet: Brain tissue expression of apoptotic markers and H&E stained sections of rat sagittal hippocampus. (A) Heatmap of real-time polymerase chain reaction results showing the effect of ST- and LT-LPS treatment on the mRNA expression of apoptotic markers in the Hyp, Pfc, Str, Hip, Mdb, Ctx, and Cbm. (B) Heatmaps of the sagittal plane of the rat brain showing upregulated or downregulated mRNA expression in the different brain regions as a result of LPS. LPS (1 mg/kg, i.p.; ST, n = 8; LT, n = 9) and saline (0.1 mL, i.p.; ST, n = 10; LT, n = 10) were administered once off (ST; n = 18) and once a week for 4 weeks (LT; n = 19). Data are presented as mean ± SD relative to the housekeeping gene Tbp . Data were analyzed using a 2-way analysis of variance followed by a Tukey’s post hoc test, and heatmaps are represented as expression values ( z scores) for differentially expressed genes. (A) a ST-CON vs. ST-LPS; b ST-LPS vs. LT-LPS; c LT-CON vs. LT-LPS. p < .05 (a, b, c), p < .01 (aa, bb, cc), p < .001 (aaa, bbb, ccc), p < .0001 (aaaa, bbbb, cccc). (C, D) H&E staining of rat sagittal hippocampus (scale bars = 50 μm) after treatment with (C) saline (0.1 mL, i.p.) CON showing the normal structure, (D) LPS (1 mg/kg, i.p.) showing vacuolated cells (black arrows) and immune cell infiltration (blue arrows). Bax, Bcl-2-associated X protein; Bcl2, B-cell leukemia/lymphoma 2 protein; Cbm, cerebellum; CON, control; Ctx, cortex; H&E, hematoxylin and eosin; Hip, hippocampus; Hyp, hypothalamus; i.p., intraperitoneally; LPS, lipopolysaccharide; LT, long-term; Mdb, midbrain; mRNA, messenger RNA; Pfc, prefrontal cortex; ST, short-term; Str, striatum.

Article Snippet: Heatmaps of gene expression z scores (see for additional information) for ST- and LT-CON and LPS-groups were generated in GraphPad Prism version 10 (GraphPad Software).

Techniques: Expressing, Staining, Real-time Polymerase Chain Reaction, Saline, Control

Journal: Biological Psychiatry Global Open Science

Article Title: Regional Molecular Changes in Chronic Lipopolysaccharide-Induced Neuroinflammation

doi: 10.1016/j.bpsgos.2025.100515

Figure Lengend Snippet: Brain tissue mRNA expression of neurotrophic factors and associations of molecular and behavioral outcomes in LPS treatment. Heatmaps of real-time polymerase chain reaction results showing the effect of ST- and LT-LPS treatment on the mRNA expression of Creb (B, F) and neurotrophic markers (A, C, D, E, G, H) in the Hyp, Pfc, Str, Hip, Mdb, Ctx, and Cbm. (E–H) Heatmaps of the sagittal plane of the rat brain showing the upregulated or downregulated mRNA expression in the different brain regions as a result of LPS. LPS (1 mg/kg, i.p.; ST, n = 8; LT, n = 9) and saline (0.1 mL, i.p.; ST, n = 10; LT, n = 10) were administered once off (ST; n = 18) and once a week for 4 weeks (LT; n = 19). Data are presented as mean ± SD relative to the housekeeping gene Tbp . Data were analyzed using a 2-way analysis of variance followed by a Tukey’s post hoc test, and heatmaps are presented as expression values ( z scores) for differentially expressed genes. ( A – D ) a ST-CON vs. ST-LPS; b ST-LPS vs. LT-LPS; c LT-CON vs. LT-LPS. p < .05 (a, b, c), p < .01 (aa, bb, cc), p < .001 (aaa, bbb, ccc), p < .0001 (aaaa, bbbb, cccc). (I) Volcano plot of all behavioral and molecular data with filtering criteria of |log 2 FC| > 1.3 and p < .05, and (J) Pearson’s correlation coefficient matrix heatmap of all molecular and behavioral analysis; p < .05. B dnf , brain-derived neurotrophic factor; Cbm, cerebellum; CON, control; C reb , cyclic-AMP response-element binding protein; Ctx, cortex; FC, fold change; Hip, hippocampus; Hyp, hypothalamus; I fn -γ, interferon gamma; I l , interleukin; i.p., intraperitoneally; LPS, lipopolysaccharide; LT, long-term; Mdb, midbrain; mRNA, messenger RNA; N gf , nerve growth factor; Pfc, prefrontal cortex; ST, short-term; Str, striatum.

Article Snippet: Heatmaps of gene expression z scores (see for additional information) for ST- and LT-CON and LPS-groups were generated in GraphPad Prism version 10 (GraphPad Software).

Techniques: Expressing, Real-time Polymerase Chain Reaction, Saline, Derivative Assay, Control, Binding Assay

Journal: Acta Neuropathologica

Article Title: Perivascular glial reactivity is a feature of phosphorylated tau lesions in chronic traumatic encephalopathy

doi: 10.1007/s00401-025-02854-x

Figure Lengend Snippet: RNA and protein distribution for reactive gliosis markers in CTE lesion sulcus. a Spatial gene expression heatmaps generated from the Visium spatial transcriptomics data illustrates the mRNA distribution for NQO1, CHI3L1, GFAP, AQP4 and FTL (L-ferritin) within a lesion sulcus for CTE case AU6 from the Australia Sports Brain Bank. b Immunohistochemistry was performed for the corresponding protein in (a) on a different lesion sulcus from the same case. The p-tau (AT8) labelling for the same tissue sections is shown at the bottom (c–d) . Scale bar: 200 µm. In all three cases, focal increases in NQO1, CHI3L1, GFAP, AQP4 and FTL (L-ferritin) mRNA and protein expression are seen in cortical layer 1, the white matter and within the lesion area (yellow arrow) where AT8 tau is highly concentrated. The sulcal border is marked with an asterisk

Article Snippet: Fig. 3 RNA and protein distribution for reactive gliosis markers in CTE lesion sulcus. a Spatial gene expression heatmaps generated from the Visium spatial transcriptomics data illustrates the mRNA distribution for NQO1, CHI3L1, GFAP, AQP4 and FTL (L-ferritin) within a lesion sulcus for CTE case AU6 from the Australia Sports Brain Bank. b Immunohistochemistry was performed for the corresponding protein in (a) on a different lesion sulcus from the same case.

Techniques: Gene Expression, Generated, Immunohistochemistry, Expressing