heatmap  (Plotly Technologies Inc)

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: Nature Communications

Article Title: Natural variation of an E3 ubiquitin ligase encoding gene Chalk9 regulates grain chalkiness in rice

doi: 10.1038/s41467-025-61683-4

Figure Lengend Snippet: a The genome-wide association signals for chalky grain rate (CGR) and degree of chalkiness (DC) in the region at 18–21 Mb on chromosome 9 ( x -axis) across two years. Negative log 10 -transformed P values from the linear mixed model are plotted on the y -axis. The horizontal dashed line indicates the genome-wide significance threshold ( P = 1×10 –6 ). P values were determined using a two-sided Wald test and assessed after Bonferroni correction for multiple comparisons. b Linkage disequilibrium (LD) heatmap of the Chalk9 locus region. Pairwise linkage disequilibrium was determined by calculating r 2 (the square of the correlation coefficient between SNPs). c Relative expression level of the 12 candidate genes in the endosperm of eight high-chalky and eight low-chalky varieties at 20 days after flowering (DAF). The 12 predicted genes in the Chalk9 locus region are labeled by I to XII. Data show means ± SD ( n = 8 varieties). P values were calculated for comparisons between high-chalky and low-chalky groups, with each group comprising 8 varieties. d Relative expression level of the candidate gene III ( Chalk9 ) in the endosperm from the selected varieties at 20 DAF. The P value was calculated for the comparison between high-chalky and low-chalky groups, with each group comprising 8 varieties. Data show means ± SD ( n = 3 biological replicates). e Relative expression level of the 12 candidate genes in the leaves of eight high-chalky and eight low-chalky varieties. Data show means ± SD ( n = 8 varieties). In c – e , statistical analysis between high-chalky and low-chalky groups was performed by two-tailed Student’s t -test. Source data are provided as a Source Data file.

Article Snippet: Correlation analysis, heatmap plotting, and volcano plot analysis were performed using BMKCloud ( www.biocloud.net ).

Techniques: GWAS, Transformation Assay, Genome Wide, Expressing, Labeling, Comparison, Two Tailed Test

Journal: bioRxiv

Article Title: ODFormer: a Virtual Organoid for Predicting Personalized Therapeutic Responses in Pancreatic Cancer

doi: 10.1101/2025.07.08.663664

Figure Lengend Snippet: ( a ) Schematic illustrating the conversion of continuous DR-AUC values into binary sensitivity labels (sensitive vs. non-sensitive). ( b ) Receiver operating characteristic (ROC) and precision-recall (PR) curves comparing the performance of ODFormer, DeepCDR, and PANCANR in predicting drug sensitivity. Area under the ROC curve (AUC) and area under the PR curve (AUPR) values are shown. ( c,d ) Waterfall plot showing the individual patient performance of ODFormer, as measured by AUC. Waterfall plot showing the individual patient performance of PANCANR, as measured by AUC. ( e-f ) Kaplan-Meier survival curves comparing overall survival (OS) of patients stratified based on 5-FU ( e ) and AG ( f ) sensitivity using OS-based cut-points. P-values were calculated using the log-rank test. Density plots show the distribution of DR-AUC values and the cut-point used for stratification. ( g ) Kaplan-Meier survival curves comparing overall survival of patients stratified based on AG sensitivity in the external cohort using survival-adapted labels. P-value was calculated using the log-rank test. ( h ) Heatmap showing differential gene expression between samples labeled by the external AG survival classifier and those from the internal cohort. Known AG-resistance markers ( i )MUC2 and ( j ) SPINK4 are highlighted. Receiver operating characteristic (ROC) curves comparing the performance of ODFormer in predicting drug sensitivity in the internal cohort. Area under the ROC curve (AUC) values are shown.

Article Snippet: The AUC heatmap for the secondary screening was generated with GraphPad Prism 8.

Techniques: Gene Expression, Labeling