Identification of Tissue Transglutaminase as a Novel Molecule Involved In Human CD8+ T Cell Transendothelial Migration
Bibliographic record
Abstract
During inflammation, T lymphocytes migrate out of the blood across the vascular endothelium in a multistep process. The receptors mediating T cell adhesion to endothelium are well characterized; however, the molecules involved in T cell transendothelial migration (TEM) subsequent to lymphocyte adhesion to the endothelium are less clear. To identify receptors mediating TEM, mAbs were produced against human blood T cells adhering to IFN-gamma-activated HUVEC in mice and tested for inhibition of lymphocyte TEM across cytokine-activated HUVEC. Most of the mAbs were against beta(1) and beta(2) integrins, but one mAb, 6B9, significantly inhibited T cell TEM across IFN-gamma, TNF-alpha, and IFN-gamma plus TNF-alpha-stimulated HUVEC, and did not react with an integrin. 6B9 mAb did not inhibit T cell adhesion to HUVEC, suggesting that 6B9 blocked a novel pathway in T cell TEM. The 6B9 Ag was 80 kDa on SDS-PAGE, and was expressed by both blood leukocytes and HUVEC. Immunoaffinity purification and mass spectrometry identified this Ag as tissue transglutaminase (tTG), a molecule not known to mediate T cell TEM. Treatment of HUVEC with 6B9 was more effective than treatment of T cells. 6B9 blockade selectively inhibited CD4(-), but not CD4(+), T cell TEM, suggesting a role for tTG in recruitment of CD8(+) T lymphocytes. Thus, 6B9 is a new blocking mAb to human tTG, which demonstrates that tTG may have a novel role in mediating CD8(+) T cell migration across cytokine-activated endothelium and infiltration of tissues during inflammation.
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 | 0.001 | 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".