E-Selectin Expression Increased in Human Ruptured Cerebral Aneurysm Tissues
Bibliographic record
Abstract
OBJECTIVES: The purpose of the present study is to investigate the expression of inflammation factor endothelial-leukocyte adhesion molecule (E-selectin, CD62E) in cerebral aneurysm walls and its relationship with aneurysm rupture. METHODS: Cerebral aneurysm tissue samples were collected at the time of surgical clipping of nine patients with history of subarachnoid hemorrhage, and then compared with control artery tissues from the superficial temporal arteries (STA) of five patients with intracranial tumors. Immunohistochemistry (IHC) was performed to reveal and localize E-selectin expression in the aneurysms and artery tissues. Western blot analysis was used to relatively quantify the level of E-selectine protein expression in cerebral aneurysms when compared with normal arteries. RESULTS: E-selectin was detected in the wall of all the aneurysm tissue samples and was rarely found in normal control arteries by IHC, and it was concentrated in proliferating and disorganized epithelia cells. Moreover, with the Western blot method, the E-selectin protein level increased significantly in aneurysm tissues compared to normal STA. CONCLUSIONS: E-selectin might be an important factor involved in the process of cerebral aneurysm formation and rupture, by promoting inflammation and weakening cerebral artery walls.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".