Adenoviral-Mediated Gene Transfer of Lymphotactin to the Lungs of Mice and Rats Results in Infiltration and Direct Accumulation of CD4 <sup>+</sup> , CD8 <sup>+</sup> , and NK Cells
Bibliographic record
Abstract
Chemokines are small 8-12-kDa chemotactic cytokines that were initially characterized for their ability to control leukocyte trafficking and, to a lesser extent, leukocyte function. Lymphotactin was first described as a T lymphocyte-specific chemotactic factor. However, it has since been shown to also be a potent attractant for natural killer (NK) cells. The chemotactic properties of lymphotactin suggested from in vitro data prompted us to study the in vivo activity of this chemokine. We constructed an adenovirus vector expressing murine lymphotactin (Ad mLym) and used this construct to overexpress lymphotactin in the lungs of both mice and rats, with similar outcomes. In brief, the accumulation of CD4(+) and CD8(+) T cells and NK cells surprisingly demonstrated slow kinetics, uncharacteristic of the chemoattractant potential seen with other chemokines. Lymphocyte accumulation in the lung was not evident prior to 24 h after gene transfer and reached a peak by day 7 in mice and day 14 in rats. Interestingly, the cellular infiltrate recruited to the lung by lymphotactin was a heterogeneous mixture of lymphocytes, monocytes, and neutrophils. Administration of Ad mLym to BALB/c SCID mice demonstrated that the presence of monocytes and neutrophils in the bronchoalveolar lavage (BAL) of wild-type BALB/c mice was likely due to the action of lymphotactin on lymphocytes. These findings extend the previous in vitro findings on the activity of lymphotactin and provide a model for studying the local effects of overexpressing chemokines in various tissues in vivo.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".