Bibliographic record
Abstract
Integrins are adhesion receptors on the cell surface that enable cells to respond to their environment. Most integrins are heterodimers, comprising α and β type I transmembrane glycoprotein chains with large extracellular domains and short cytoplasmic tails. Integrins deliver signals through multiprotein complexes at the cell surface, which interact with cytoskeletal and signaling proteins to influence gene expression, cell proliferation, morphology, and migration. Integrin expression on γδ T cells (γδTc) has not been systematically investigated; however, reports in the literature dating back to the early 1990s reveal an understated role for integrins in γδTc function. Over the years, integrins have been investigated on resting and/or activated peripheral blood-derived polyclonal γδTc, γδTc clones, as well as γδ T intraepithelial lymphocytes. Differences in integrin expression have been found between αβ T cells (αβTc) and γδTc, as well as between Vδ1 and Vδ2 γδTc. While most studies have focused on human γδTc, research has also been carried out in mouse and bovine models. Roles attributed to γδTc integrins include adhesion, signaling, activation, migration, tissue localization, tissue retention, cell spreading, cytokine secretion, tumor infiltration, and involvement in tumor cell killing. This review attempts to encompass all reports of integrins expressed on γδTc published prior to December 2017, highlights areas warranting further investigation, and discusses the relevance of integrin expression for γδTc function.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".