Additional file 4 of PGRMC1 effects on metabolism, genomic mutation and CpG methylation imply crucial roles in animal biology and disease
Bibliographic record
Abstract
Additional file 4 Fig. S4. PGRMC1 phosphorylation status affects the NNMT pathway. Related to Fig. 6. (A) Metabolomics quantification of S-adenosyl-Methionine (SAM) levels for the indicated cell lines, representing n = 12 (four technical replicates for each of three independent cell lines per PGRMC1 condition). (B) RT-PCR quantification of NNMT mRNA levels after treatment by an NNMT-specific shRNA (NN) or a random scramble shRNA control (scr) in TM cells stably expressing lentiplasmid-driven shRNAs. RT-PCR Methods follow A. p < 0.003 (2-tailed T test). Methods follow Fig. 6b. (C) 1-MNA ion intensities in cells from B, determined following methods from Fig. 6a, using two technical replicates of each of three biological replicates per cell condition (n = 6). Labels follow B. The result was significantly different by T-test (p < 0.001) after removal of one Scr outlier (panel displayed) or by Mann-Whitney U test (p < 0.002) including the outlier. (D) SAM ion intensities in the cells from B were not significantly different (T-test). Labels follow B. (E) 1-MNA attenuates rounded morphology in DM cells. Results for n = 5 for each 1-MNA concentration are shown in the boxplot. 0.5 mM 1-MNA was significantly different (p < 0.0001, ANOVA, post hoc Tukey HSD) to all other treatments.
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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 | 0.002 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 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 | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.894 | 0.219 |
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".