T‐helper type 2‐dependent early recruitment of antigen non‐specific CD4<sup>+</sup> T cells in experimental asthma
Bibliographic record
Abstract
BACKGROUND: Following antigen challenge, adoptively transferred antigen-specific CD4(+) T cells induce allergic airway inflammation, comprised primarily of an increase in lymphocytes and eosinophils. OBJECTIVE: Our goal was to better understand the contribution of the GATA-3 transcription factor to the ability of adoptively transferred T cells to induce airway inflammation in the Brown Norway rat model of adoptively transferred asthma. METHODS: We transduced antigen-stimulated CD4+ T cells with recombinant retroviruses encoding enhanced green fluorescent protein (EGFP) only or EGFP and the GATA-3 transcription factor. Each population of transduced cells was adoptively transferred to naïve recipients that were then challenged with antigen. Airway inflammatory responses were then quantified. RESULTS: Our data indicate that T cells transduced with retroviruses encoding GATA-3 expressed high levels of GATA-3 protein as well as T-helper type 2 cytokines. Following adoptive transfer and airway antigen challenge, these gene-modified T cells induced robust inflammatory responses in the lungs and draining lymph nodes. Increased numbers of total inflammatory cells and eosinophils were recovered in the bronchoalveolar lavage fluid (BALF). In addition, the number of antigen non-specific CD4+ T cells recovered in the BALF as well as the lung and draining lymph nodes was enhanced in recipients of GATA-3 overexpressing T cells following antigen challenge. Nevertheless, the transduced CD4+ T cells comprised only a small percentage of the population of CD4+ T cells infiltrating the lung and were not detectable at all in the draining lymph nodes. CONCLUSION: These data provide evidence that GATA-3 plays a significant role in the ability of antigen-specific T cells to amplify allergic inflammatory responses in vivo by promoting the recruitment of endogenous antigen non-specific T cells to the lung.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".