Unfolding ARF and ARL GTPases: from biophysics to systems-level insights
Bibliographic record
Abstract
Advanced technologies to study protein biophysics, mRNA expression and protein-protein interactions at high throughput in physiological or pathological contexts are reshaping our view of the ARF family of GTPases. Most current knowledge arises from work on the classical members ARF1 and ARF6, with many ARF-like proteins (ARLs) remaining poorly characterized. Recent findings suggest that several ARLs deviate from the binary molecular switch paradigm, instead exhibiting atypical biochemical properties, highly restricted tissue-specific expression patterns, specialized subcellular localizations, and unique interaction networks. These observations raise fundamental questions about the breadth of ARF family functions, mechanisms that regulate them, and their potential impact on cellular and organismal biology. In this review, we highlight emerging insights into atypical ARF members, outline unresolved questions, and discuss how expanding our understanding beyond the classical ARF members could shed light on their unique roles in health and disease.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".