Role of the microenvironment in promoting angiogenesis in acute myeloid leukemia
Bibliographic record
Abstract
Angiogenesis is a crucial event in the survival and progression of solid tumors. To determine whether angiogenesis in acute myeloid leukemia (AML) is an intrinsic property of leukemic cells, the vascularity of bone marrow biopsies was determined. Bone marrow vascularity in newly diagnosed or post-chemotherapy AML patients was increased 4-fold (P < 0.01) and 8.7-fold (P < 0.01), respectively, relative to controls. Vascular endothelial growth factor (VEGF) expression by AML blast cells was assessed by immunohistochemistry, and bone marrow cell supernatants were assayed for secretion of VEGF, fibroblast growth factor-2 (FGF-2), and endostatin by enzyme-linked immunosorbent assay. Diffuse cytoplasmic and strong extracellular VEGF immunoreactivity was seen in bone marrow aspirates from AML patients, but not controls. In contrast, there was no difference in the levels of VEGF, FGF-2, and endostatin secreted by mononuclear cells cultured from bone marrows of AML patients compared to normal controls following two days of culture in vitro. Total angiogenic potential of bone marrow cell supernatants was assessed by endothelial sprouting in vitro and by a chick chorioallantoic membrane assay. No differences were found between 2-day conditioned medium from normal and AML bone marrow mononuclear cells in either assay. Our data show a discrepancy between bone marrow vascularity and VEGF expression in vivo and VEGF expression and angiogenesis from 2-day conditioned medium ex vivo. This suggests that angiogenesis in AML likely represents a response to microenvironmental factors in vivo, rather than being an intrinsic property of leukemic cells.
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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) | 0.000 | 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 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".