Upregulation and Expression Patterns of the Angiogenic Transcription Factor Ets-1 in Alzheimer's Disease Brain
Bibliographic record
Abstract
Immunohistochemical staining has been used to determine expression patterns of the angiogenic transcription factor, Ets-1, in the brains of Alzheimer's disease (AD) individuals. Brain tissue from non-demented controls showed little expression of Ets-1 whereas in AD brain tissue, Ets-1 was ubiquitously expressed in cortex and hippocampus. Double immunostaining with von Willerbrand factor demonstrated prominent Ets-1 intravascular immunoreactivity (ir) in AD cortical microvessels. In addition, Ets-1 also exhibited extravascular expression characterized by a diffuse pattern of Ets-1 ir in AD brain. Double staining also showed Ets-1 colocalization in microvasculature with the potent angiogenic agent, vascular endothelial growth factor (VEGF). Cell-associated tumor necrosis factor-α (TNF-α), a pro-inflammatory cytokine with pro-angiogenic activity, was primarily associated with diffuse extravascular Ets-1 ir. Clusters of HLA-DR positive microglia, resident immune cells of brain which release TNF-α, were also localized with diffuse Ets-1. Intravascular Ets-1 ir was maximally co-localized with soluble amyloid-β peptide (Aβ), Aβ1-40, in microvasculature whereas diffuse extravascular Ets-1 ir appeared in proximity to Aβ plaques in brain parenchyma. Similar overall results were obtained for patterns of Ets-1 staining in AD hippocampal tissue. This work provides novel findings on expression of the angiogenic transcription factor, Ets-1, in vascular remodeling and its association with pro-angiogenic factors, reactive microglia, and Aβ deposition in AD brain.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".