BRCA2-deficiency Causes Global Transcriptomic Alterations in Endothelial Cells
Bibliographic record
Abstract
Abstract This study aims to explore the alterations in gene expression following BRCA2 loss in endothelial cells and to investigate the potential contribution of BRCA2 in regulating the endothelial protein-coding transcriptome. Cultured human umbilical vein endothelial cells (HUVECs) were transfected with siBRCA2 or non-targeting scrambled RNA as control. Total RNA was extracted and used for RNA sequencing following purification and quality check. Transcription profiles and differentially expressed genes (DEGs) were identified. Enrichment of functions and signaling pathways analysis were performed based on Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. In total, 3196 DEGs with (cut-off 1.5-fold) were identified, of which 1852 genes were upregulated, and 1344 genes were downregulated in BRCA2 -deficient HUVECs. Cell cycle exit and neuronal differentiation 1 (CEND1) and mannose receptor C-type 1 (MRC1) were the most significantly up- and downregulated genes, respectively, in BRCA2-deficient endothelial cells. The expression of top DEGs were further validated by RT-qPCR in HUVECs and in human coronary artery endothelial cells. The GO and KEGG analysis suggest that cell adhesion molecules and cytokine-cytokine receptor interaction may play an important role in BRCA2-deficient endothelial cells. Overall, these findings contribute to a greater understanding of the mechanisms involved in BRCA2-mediated endothelial function.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".