Additional file 5 of TRIM25 promotes Capicua degradation independently of ERK in the absence of ATXN1L
Bibliographic record
Abstract
Additional file 5: Figure S4 CIC interactors. A) Representative Western blot of CICKO cells with stable FLAG tagged CIC-S reintroduced treated with ATXN1L siRNA over 72 hours. Scrambled siRNA was used as a negative control. B) Immunofluorescence images of proximity ligation assay showing FLAG-tagged CIC-S-14-3-3 interaction in NHA-S cells treated with ATXN1L siRNA. Scrambled siRNA was used as a negative control. White bars denote 10μm. Right: Tukey boxplots showing quantification of number of FLAG-14-3-3 foci/cell. C) Immunofluorescence images of proximity ligation assay showing FLAG-tagged CIC-S-TPR interaction in NHA-S cells treated with ATXN1L siRNA. Scrambled siRNA was used as a negative control. White bars denote 10μm. Right: Tukey boxplots showing quantification of number of FLAG-TPR foci/cell. D) Representative Western blot of CIC immunoprecipitation showing interaction with TRIM25 in ATXN1LWT (HEK) and ATXN1LKO (A30) cell lines. E) Immunofluorescence images showing cellular TRIM25 localization in ATXN1LWT (NHA) and ATXN1LKO (B82) cell lines. * PLA quantifications were collected from 65 individual cells. Error bars represent one standard deviation. p-values were calculated using the two-tailed independent Student’s t-test. Statistically significant values are denoted (* = p < 0.05, ** = p < 0.01, *** = p < 0.001).
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.899 | 0.204 |
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".