Bibliographic record
Abstract
The decidua of human term placenta contains a cell population with highly immunomodulatory properties regulating viability, growth and invasion important for the fetal development, remarkably resembling the tumor-microenvironment. Prompted by previously published data from our group demonstrating the pro-apoptotic potential of placenta-derived supernatant on human lung cancer in vitro, the anti-tumor activity of placenta-conditioned medium was studied in more detail. For this purpose, human NSCLC cell lines A549 and H838 were challenged for 17h with placenta-derived conditioned medium, obtained from human fresh term placenta incubated overnight in DMEM with 2%FCS. Viability was analysed either by MTT assay or FACS using 7-AAD. For tumor growth, expression of proliferation marker Ki-67 was analysed, induction of apoptosis was determined by expression of annexin V and/or cleaved caspase 3 using immunofluorescence or FACS analysis. Overall, both suppression of Ki-67 expression and increase of apoptotic cells were induced by all placentas (n=6), although to strikingly varying extent. Based on these preliminary but promising results demonstrating consistent inhibitory effects on lung tumor cells, placenta-derived anti-tumor activity will be further studied including human NSCLC specimens and by using fractionated placenta-derived supernatants that will be also analysed by mass spectrometry to identify potential immunosuppressive mediators. Thus, these studies could result in the development of new therapeutic agents for a more effective treatment of NSCLC.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.691 | 0.485 |
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".