Expression of E- and P-selectin in Tumor Necrosis Factor—induced Dermatitis in Dogs
Bibliographic record
Abstract
Adhesion molecules on endothelial cells play an important role in leukocyte recruitment in several inflammatory processes. Vascular selectins mediate the initial adhesion of leukocytes to the blood vessel wall during their extravasation into inflamed tissues, and in vitro studies in dogs have shown that selectin expression can be induced by cytokines such as tumor necrosis factor-alpha (TNF-alpha) and interleukin-1 (IL-1). The objective of this study was to determine whether vascular selectins are induced by cytokines in vivo in a cutaneous model of inflammation in dogs. Skin biopsies were collected from nine dogs at various time points after an intradermal injection of TNF-alpha (10 ng/site) or phosphate-buffered saline containing 0.1% bovine serum albumin, and immunohistochemistry was performed using anti-P-selectin (MD3) and anti-E-selectin (CL37) monoclonal antibodies. In all animals, TNF-alpha induced an inflammatory reaction that was maximal at 12 hours and then decreased by 24 and 48 hours. Control skin displayed no expression of E- and P-selectin, whereas TNF-alpha induced the expression of P-selectin and E-selectin on dermal vessels that was highest at 12 hours and 3 hours, respectively (P < 0.05). Numerous platelet aggregates recognized by the anti-P-selectin antibody were present in the lumina of vessels and in perivascular tissues. These results demonstrate that TNF-alpha can induce the expression of P- and E-selectin in vivo in dog skin and suggest that these selectins are involved in leukocyte recruitment in canine dermatitis.
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 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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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; a candidate call from one teacher head, 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".