Additional file 1 of MiR-34c downregulation leads to SOX4 overexpression and cisplatin resistance in nasopharyngeal carcinoma
Bibliographic record
Abstract
Additional file 1: Figure S1. (A) Relative miR-34c expression assessed by qRT-PCR in C666–1 cells treated with SB431542 (10 or 20 μM) for 72 h compared to untreated cells (UT). (B and C) Relative expression of putative miR-34c targets assessed by qRT-PCR in NP69, NP460, and C666–1 cells, normalized to C666–1 cells. (B) Genes that are highly expressed in C666–1 (NPC) cells vs. NP69 and NP460 (normal nasopharyngeal) cells. (C) Genes with no significant differences in expression between C666–1 cells and NP69/NP460. Note that MARCKS and PML expression were significant only between C666–1 and NP460 cells. The data are represented as the mean ± SEM of at least three independent experiments. * P < 0.05; ** P < 0.01; *** P < 0.001.
Stored with the screening record, where it is evidence for the labels above.
How this classification was reachedexpand
The three-model screen
all 5,600 screened works →All three models called this out of scope.
Supplementary figure file for a cancer biology paper on miR-34c and cisplatin resistance.
This is a supplementary molecular-biology figure file and does not study research itself.
Supplementary figure file for a cancer molecular paper; domain biomedical content.
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 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.903 | 0.199 |
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".