Characterization of sequences in human TWIST required for nuclear localization
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Twist is a transcription factor that plays an important role in proliferation and tumorigenesis. Twist is a nuclear protein that regulates a variety of cellular functions controlled by protein-protein interactions and gene transcription events. The focus of this study was to characterize putative nuclear localization signals (NLSs) 37RKRR40 and 73KRGKK77 in the human TWIST (H-TWIST) protein. RESULTS: Using site-specific mutagenesis and immunofluorescences, we observed that altered TWISTNLS1 K38R, TWISTNLS2 K73R and K77R constructs inhibit nuclear accumulation of H-TWIST in mammalian cells, while TWISTNLS2 K76R expression was un-affected and retained to the nucleus. Subsequently, co-transfection of TWIST mutants K38R, K73R and K77R with E12 formed heterodimers and restored nuclear localization despite the NLSs mutations. Using a yeast-two-hybrid assay, we identified a novel TWIST-interacting candidate TCF-4, a basic helix-loop-helix transcription factor. The interaction of TWIST with TCF-4 confirmed using NLS rescue assays, where nuclear expression of mutant TWISTNLS1 with co-transfixed TCF-4 was observed. The interaction of TWIST with TCF-4 was also seen using standard immunoprecipitation assays. CONCLUSION: Our study demonstrates the presence of two putative NLS motifs in H-TWIST and suggests that these NLS sequences are functional. Furthermore, we identified and confirmed the interaction of TWIST with a novel protein candidate TCF-4.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it