Enhanced natural-killer cell and erythropoietic activities in VEGF-A–overexpressing mice delay F-MuLV–induced erythroleukemia
Bibliographic record
Abstract
We have previously reported that VEGF-A, in combination with MCP-5, contributes to leukemia progression within the splenic microenvironment of mice infected with F-MuLV. To study the influence of constitutively elevated VEGF-A levels on the progression of erythroleukemia, mice heterozygous for a VEGF-A "hypermorphic" allele (Vegfhi/+) were inoculated with F-MuLV. Unexpectedly, a significant delay in erythroleukemia was observed in Vegfhi/+ mice when compared with wild-type controls. These results suggested an altered physiologic response arising from elevated VEGF-A levels that decelerated erythroleukemic progression. Characterization of hematopoiesis in Vegfhi/+ spleens showed a higher natural killer cell activity, elevated B cells, and a decrease in T-cell number. Furthermore, higher erythroid progenitors (ie, CD34+, CD36+, and Ter119+ cells) were evident in the bone marrow, spleen, and peripheral blood of Vegfhi/+ mice. The CFU-E levels were significantly elevated in Vegfhi/+ bone marrow cultures, and this elevation was blocked by a neutralizing antibody to VEGF-A receptor (VEGFR-2). Moreover, erythroleukemic mice were treated with recombinant erythropoietin and, similar to diseased Vegfhi/+ mice, showed a delay in disease progression. We propose that a compensatory erythropoietic response combined with increased natural killer (NK) cell activity account for the extended survival of erythroleukemic, Vegfhi/+ mice.
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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 | 0.000 | 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 | 0.001 |
| 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".