Vascular endothelium: target or victim of cytostatic therapy?This paper is one of a selection of papers published in this Special Issue, entitled The Cellular and Molecular Basis of Cardiovascular Dysfunction, Dhalla 70th Birthday Tribute.
Bibliographic record
Abstract
Chemotherapy continues to be the main therapeutic approach in the treatment of hematological malignancies including acute leukemia. Generally, chemotherapy is used to eliminate cancer cells and to restore normal bone marrow function. Simultaneous action of cytostatic drugs on bone marrow angiogenesis decreases the formation of new capillaries and improves therapeutic effect. However, chemotherapeutic agents may also be cytodestructive for cellular elements of other tissues, particularly the vascular endothelium, which can lead to various cardiovascular complications. In this work, we studied the effects of 2 cytostatic drugs, cytosine arabinoside (ara-C) and daunorubicin (DNR), on cultured human vascular (i.e., umbilical) endothelial cells (ECs). Ara-C and DNR were added to cultured cells at concentrations ranging from 1 ng/mL to 100 microg/mL. Drug effects were studied using phase-contrast microscopy, cell viability tests, BRDU incorporation, immunohistochemistry, flow cytometry, and cell cloning. At various concentrations, ara-C and DNR are able to induce morphological and functional changes in cultured cells related to either cytostatic or cytotoxic action. Moreover, ara-C-treated cultured cells displayed significant disturbances in cell adhesion molecule expression and interaction with blood leukocytes. Preliminary data obtained on acute leukemia patients undergoing standard cytostatic therapy ("7+3" regimen) have shown that concentration of the circulating ECs was significantly increased compared with the control group and could be as high as 500-1500 cells/mL of blood. Results obtained suggest that anticancer chemotherapy may induce systemic damage of vascular endothelium related to massive cell loss and (or) alterations of endothelial function.
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.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".