Concentration- and time-dependent effects of enoxaparin on human adenocarcinomic epithelial cell line A549 proliferation in vitro
Bibliographic record
Abstract
Non-small cell lung cancer (NSCLC) is a major health problem. Surgery is the only potential curative treatment, in spite of the high recurrence and mortality rates. Low molecular weight heparins (LMWH) have been suggested to have a positive impact on the outcome of various cancers, mainly attributed to their anticoagulant properties; yet a direct antineoplastic effect has not been excluded. We thought to evaluate the direct effect of the LMWH enoxaparin on the human lung adenocarcinomic epithelial cell line A549 and to determine potential antiproliferative and antimetastatic effects that could guide future trials. A549 cells were cultured with different concentrations of enoxaparin (1-30 U/mL). Cell counting was performed at 24, 48, and 72 h. Detection of c-Myc protein and CD44 protein was performed by electrophoresis and Western blotting. Statistical analysis was performed using paired Student's t tests. Cell counts were decreased with increasing concentrations and time of exposure to enoxaparin. This corresponds to decreased expression of c-Myc and CD44. In conclusion, enoxaparin displayed a direct dose and exposure duration dependent suppressor effect on A549 cell proliferation and the expression of both c-Myc and CD44 in vitro, suggesting reduced proliferative and metastatic potentials of these 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) | 0.002 | 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".