Antitumor Impact of Interferon-γ Producing CD1d-restricted NKT Cells in Murine Malignant Mesothelioma
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
CD1d-restricted natural killer T (iNKT) cells have been shown to provide adjuvant activity against cancer by producing interferon (IFN)-γ. However, the role of invariant NKT (iNKT) cells in the tumor microenvironment has not yet been fully addressed. Our aim is to elucidate the antitumor effect of iNKT cells in the tumor microenvironment by using an intrathoracic murine malignant pleural mesothelioma model that we had previously developed and to provide pleural effusion as a good surrogate of the tumor microenvironment. We found that the number of iNKT cells increased dramatically in the pleural effusion after intrathoracic tumor cell injection at an earlier phase compared with accumulation of CD8 T cells. These iNKT cells showed increased expression of CD25 and increased ratio of cells positive for IFN-γ intracellular staining. iNKT cells sorted from pleural effusion of tumor burden mice produced larger amount of IFN-γ compared with naive mice. Mice pretreated in vivo with anti-CD1d-blocking Ab showed increased amount of pleural effusion and decreased ratio of total and effector-type CD8 T cells as well as decreased intracellular IFN-γ expression of CD8T-cell in the pleural effusion. In vivo administration of α-galactosylceramide (α-GalCer) showed prolonged survival associated with less pleural effusion and increased ratio of IFN-γ-positive iNKT cells and CD8 T cells in the pleural effusion. Therefore, this study suggests that iNKT cells accumulating in the tumor microenvironment play an antitumor effect by producing IFN-γ and enhancing subsequent CD8 T-cell response. Furthermore, in vivo administration of α-GalCer could suppress mesothelioma growth by activating iNKT cells.
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.
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) | 0.001 | 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 it