Data in support of a harmine-derived beta-carboline in vitro effects in cancer cells through protein synthesis
Bibliographic record
Abstract
by targeting protein synthesis" (Carvalho et al., 2017)[1]. This data article provides accompanying data on CM16 cytostatic evaluation in cancer cells as well as data related to its effects on transcription and translation. After confirming the cytostatic effect of CM16, we investigated its ability to arrest the cell cycle in the glioma Hs683 and SKMEL-28 melanoma cell lines but no modification was evidenced. According to the global protein synthesis inhibition induced by CM16 [1], transcription phase, a step prior to mRNA translation, evaluated by labelled nucleotide incorporation assay was not shown to be affected under CM16 treatment in the two cell lines. By contrast, mRNA translation and particularly the initiation step were shown to be targeted by CM16 in [1]. To further decipher those effects, we established herein a list of main actors in the protein synthesis process according to literature survey for comparative analysis of cell lines displaying different sensitivity levels to CM16. Finally, one of these proteins, PERK, a kinase regulating eIF2-α phosphorylation and thereby activity, was evaluated under treatment with CM16 in a cell-free system.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".