Tumor conditions induce bone marrow expansion of granulocytic, but not monocytic, immunosuppressive leukocytes with increased CXCR2 expression in mice
Bibliographic record
Abstract
Myeloid-derived suppressor cells (MDSCs) promote tumor growth through, in part, inhibiting T-cell immunity. However, mechanisms underlying MDSC expansion and guidance of MDSCs toward the tumor microenvironment remain unclear. Employing Percoll density gradients, we separate bone marrow (BM) leukocytes from tumor-bearing mice into four density-increasing bands with myeloid leukocytes enriched in bands III and IV. Band III comprises monocytes and low-density granulocytes, both confirmed to be M-MDSCs and G-MDSCs, respectively, by displaying potent inhibition of T-cell proliferation. However, monocytes act as M-MDSCs not only under tumor conditions but also the healthy condition. In contrast, band IV contains non-inhibitory, mature granulocytes. Only band III G-MDSCs display significant expansion in mice bearing B16 melanoma, Lewis lung carcinoma, or MC38 colon carcinoma. The expanded G-MDSCs also show increased CXCR2 expression, which guides egress out of BM, and produce arginase-1 and ROS upon encountering antigen-activated T cells. Adoptive transfer assays demonstrate that both G-MDSCs and mature granulocytes infiltrate tumors, but only the former displays sustention and accumulation. Intratumoral administrations of granulocytes further demonstrate that G-MDSCs promote tumor growth, whereas mature granulocytes exert minimal effects, or execute powerful anti-tumor effects providing the presence of PMN activation mechanisms in the tumor microenvironment.
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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 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".