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BioSpyder Technologies tempo-seq human whole transcriptome probe set
Comparison of estrogen receptor alpha (ERα) bioactivity and transcriptomic points of departure (tPODs) derived from the whole <t>transcriptome</t> analysis in MCF-7 cells ( n = 3–4 per concentration) exposed to bisphenol A and 15 alternative chemicals at a range of concentrations (0.0005–100 µM) for 48 h. ERα prediction is based on at least one concentration yielding an agonist or antagonist call. For tPOD derivation, data were prefiltered using the Williams trend test ( p ≤ .05) and a fold-change of ≥1.5 or ≤1.5. Data were also postfiltered with the following settings in BMDExpress v2.3: Best BMD/BMDL <20, Best BMDU/BMD <20, Best BMDU/BMDL <40, and Best fitPvalue >.1. tPODs representing the 25th rank ordered gene benchmark concentration (BMC) (shown in µM), the median gene BMC for the lowest pathway (at least 3 genes and 5% of pathway) as well as the median gene BMC for the ERα biomarker gene set are shown in the table and in the top panel. The chemicals are shown in decreasing order of potency based on tPODS from the 25th gene BMC.
Tempo Seq Human Whole Transcriptome Probe Set, supplied by BioSpyder Technologies, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/transcriptomics+data+sets/tempo+seq+human+whole+transcriptome+probe+set/pmc09936204-55-13-12
Average 90 stars, based on 1 article reviews
tempo-seq human whole transcriptome probe set - by Bioz Stars, 2026-10
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1) Product Images from "In vitro transcriptomic analyses reveal pathway perturbations, estrogenic activities, and potencies of data-poor BPA alternative chemicals"

Article Title: In vitro transcriptomic analyses reveal pathway perturbations, estrogenic activities, and potencies of data-poor BPA alternative chemicals

Journal: Toxicological Sciences

doi: 10.1093/toxsci/kfac127

Comparison of estrogen receptor alpha (ERα) bioactivity and transcriptomic points of departure (tPODs) derived from the whole transcriptome analysis in MCF-7 cells ( n = 3–4 per concentration) exposed to bisphenol A and 15 alternative chemicals at a range of concentrations (0.0005–100 µM) for 48 h. ERα prediction is based on at least one concentration yielding an agonist or antagonist call. For tPOD derivation, data were prefiltered using the Williams trend test ( p ≤ .05) and a fold-change of ≥1.5 or ≤1.5. Data were also postfiltered with the following settings in BMDExpress v2.3: Best BMD/BMDL <20, Best BMDU/BMD <20, Best BMDU/BMDL <40, and Best fitPvalue >.1. tPODs representing the 25th rank ordered gene benchmark concentration (BMC) (shown in µM), the median gene BMC for the lowest pathway (at least 3 genes and 5% of pathway) as well as the median gene BMC for the ERα biomarker gene set are shown in the table and in the top panel. The chemicals are shown in decreasing order of potency based on tPODS from the 25th gene BMC.
Figure Legend Snippet: Comparison of estrogen receptor alpha (ERα) bioactivity and transcriptomic points of departure (tPODs) derived from the whole transcriptome analysis in MCF-7 cells ( n = 3–4 per concentration) exposed to bisphenol A and 15 alternative chemicals at a range of concentrations (0.0005–100 µM) for 48 h. ERα prediction is based on at least one concentration yielding an agonist or antagonist call. For tPOD derivation, data were prefiltered using the Williams trend test ( p ≤ .05) and a fold-change of ≥1.5 or ≤1.5. Data were also postfiltered with the following settings in BMDExpress v2.3: Best BMD/BMDL <20, Best BMDU/BMD <20, Best BMDU/BMDL <40, and Best fitPvalue >.1. tPODs representing the 25th rank ordered gene benchmark concentration (BMC) (shown in µM), the median gene BMC for the lowest pathway (at least 3 genes and 5% of pathway) as well as the median gene BMC for the ERα biomarker gene set are shown in the table and in the top panel. The chemicals are shown in decreasing order of potency based on tPODS from the 25th gene BMC.

Techniques Used: Comparison, Derivative Assay, Concentration Assay, Biomarker Discovery

Comparison of ERα bioactivity and tPODs derived from the whole transcriptome analysis in MCF-7 cells ( n = 3–4 per concentration) exposed to BPA and 15 alternative chemicals at a range of concentrations (0.0005–100 μM) for 48 h. ERα prediction is based on at least one concentration yielding an agonist or antagonist call. For tPOD derivation, data were prefiltered using the Williams trend test ( p ≤ .05) and a fold-change of ≥1.5 or ≤1.5. Data were also post-filtered with the following settings in BMDExpress v2.3: Best BMD/BMDL <20, Best BMDU/BMD <20, Best BMDU/BMDL <40, and Best fitPvalue >.1. tPODs representing the 25th rank ordered gene BMC (shown in μM), the median gene BMC for the lowest pathway (at least 3 genes and 5% of pathway) as well as the median gene BMC for the ERα biomarker gene set are shown in the table and in the top panel. The chemicals are shown in decreasing order of potency based on tPODS from the 25th gene BMC. 25th gene, ERα biomarker, lowest median pathway.
Figure Legend Snippet: Comparison of ERα bioactivity and tPODs derived from the whole transcriptome analysis in MCF-7 cells ( n = 3–4 per concentration) exposed to BPA and 15 alternative chemicals at a range of concentrations (0.0005–100 μM) for 48 h. ERα prediction is based on at least one concentration yielding an agonist or antagonist call. For tPOD derivation, data were prefiltered using the Williams trend test ( p ≤ .05) and a fold-change of ≥1.5 or ≤1.5. Data were also post-filtered with the following settings in BMDExpress v2.3: Best BMD/BMDL <20, Best BMDU/BMD <20, Best BMDU/BMDL <40, and Best fitPvalue >.1. tPODs representing the 25th rank ordered gene BMC (shown in μM), the median gene BMC for the lowest pathway (at least 3 genes and 5% of pathway) as well as the median gene BMC for the ERα biomarker gene set are shown in the table and in the top panel. The chemicals are shown in decreasing order of potency based on tPODS from the 25th gene BMC. 25th gene, ERα biomarker, lowest median pathway.

Techniques Used: Comparison, Derivative Assay, Concentration Assay, Biomarker Discovery

Related Articles

other:

Article Title: Clinical and immune responses to neoadjuvant fulvestrant with or without enzalutamide in ER+/Her2- breast cancer.
Article Snippet: The TempO-Seq Human Whole Transcriptome kit from BioSpyder was used to lyse and prepare the samples for shipment.

Article Title: High-throughput transcriptomics analysis of equipotent and human relevant mixtures of BPA alternatives reveal additive effects in vitro.
Article Snippet: Gene expression was measured using the TempO-Seq Human Whole Transcriptome v2.1 kit (BioSpyder Technologies Inc, Carlsbad, California) as per the manufacturer’s instructions and as previously described (Matteo et al. 2023).

Article Title: High-throughput transcriptomics toxicity assessment of eleven data-poor bisphenol A alternatives.
Article Snippet: Gene expression changes were measured using the TempO-Seq Human Whole Transcriptome Panel v2.1 Assay, Index E, F, and G (BioSpyder Technologies Inc, Carlsbad, California) following manufacturer’s instructions.

Article Title: High-throughput transcriptomics analysis of equipotent and human relevant mixtures of BPA alternatives reveal additive effects in vitro.
Article Snippet: Data were processed as described below and reads were aligned to the BioSpyder TempO-Seq Human Whole Transcriptome probe set (22,537 probes over 19,687 genes).

Article Title: Assessing the Impact of In Vitro Xenobiotic Metabolism on Estrogenic Chemical Bioactivity in High-Throughput Profiling Assays.
Article Snippet: High-throughput profiling assays such as high-throughput phenotypic profiling (HTPP) with Cell Painting and high-throughput transcriptomics (HTTr) are new approach methods that have been used to characterize the bioactivity and potential hazards of chemicals.. To enhance the ability to identify potential in vivo hazards during chemical screening, we previously coupled both assays to an in vitro metabolism platform, Alginate Immobilization of Metabolic Enzymes (AIME).. In this study, we used the AIME platform to expand upon our previous results for three estrogenic reference chemicals by screening an additional 40 chemicals anticipated to have varied activity and/or shifts in activity with metabolism in an estrogen receptor transactivation assay (ERTA) in VM7Luc4E2 breast carcinoma cells.

Article Title: Clinical and immune responses to neoadjuvant fulvestrant with or without enzalutamide in ER+/Her2− breast cancer
Article Snippet: The TempO-Seq Human Whole Transcriptome kit from BioSpyder was used to lyse and prepare the samples for shipment.

Article Title: Unlocking the Power of Transcriptomic Biomarkers in Qualitative and Quantitative Genotoxicity Assessment of Chemicals
Article Snippet: For data set 2, the reads were aligned to the BioSpyder TempO-Seq Human Whole Transcriptome probe set (22,537 probes over 19,687 genes).



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Single-nucleus transcriptome and spatial transcriptomics landscape of the ileal tissue of SAP and CON group rats. (A) Schematic illustration of the workflow for this study. (B) Representative Hematoxylin and Eosin (H&E)–stained ileal sections from CON and SAP rats. (C) UMAP plot of single-nucleus transcriptome profiles of SAP and CON group samples. Colors indicate groups, clusters and cell types. (D) Heatmap plot of marker genes for cell annotation. (E) Bar plot showing cell-type proportions (mean ± SEM) in snRNA-seq data. (F) Spatial transcriptomics profiles of SAP and CON group samples. Colors indicate cell types. (G) Bar plot showing cell-type proportions (mean ± SEM) in spatial transcriptomics (Stereo-seq) data. Statistical significance: ns, not significant; *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001.

Journal: Frontiers in Immunology

Article Title: Single-nucleus and spatial transcriptomics reveal intestinal cellular heterogeneity, differentiation, and cell communication mechanisms in SAP-induced intestinal injury

doi: 10.3389/fimmu.2026.1719902

Figure Lengend Snippet: Single-nucleus transcriptome and spatial transcriptomics landscape of the ileal tissue of SAP and CON group rats. (A) Schematic illustration of the workflow for this study. (B) Representative Hematoxylin and Eosin (H&E)–stained ileal sections from CON and SAP rats. (C) UMAP plot of single-nucleus transcriptome profiles of SAP and CON group samples. Colors indicate groups, clusters and cell types. (D) Heatmap plot of marker genes for cell annotation. (E) Bar plot showing cell-type proportions (mean ± SEM) in snRNA-seq data. (F) Spatial transcriptomics profiles of SAP and CON group samples. Colors indicate cell types. (G) Bar plot showing cell-type proportions (mean ± SEM) in spatial transcriptomics (Stereo-seq) data. Statistical significance: ns, not significant; *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001.

Article Snippet: The spatial transcriptomics data were obtained according to the protocol of STOmics Gene Expression Set-S1 on the website ( https://www.stomics.tech/ ), which is an improved version of initial procedures.

Techniques: Spatial Transcriptomics, Staining, Marker