Rho protein GTPases and their interactions with NFκB: crossroads of inflammation and matrix biology
Bibliographic record
Abstract
The RhoGTPases, with RhoA, Cdc42 and Rac being major members, are a group of key ubiquitous proteins present in all eukaryotic organisms that subserve such important functions as cell migration, adhesion and differentiation. The NFκB (nuclear factor κB) is a family of constitutive and inducible transcription factors that through their diverse target genes, play a major role in processes such as cytokine expression, stress regulation, cell division and transformation. Research over the past decade has uncovered new molecular links between the RhoGTPases and the NFκB pathway, with the RhoGTPases playing a positive or negative regulatory role on NFκB activation depending on the context. The RhoA-NFκB interaction has been shown to be important in cytokine-activated NFκB processes, such as those induced by TNFα (tumour necrosis factor α). On the other hand, Rac is important for activating the NFκB response downstream of integrin activation, such as after phagocytosis. Specific residues of Rac1 are important for triggering NFκB activation, and mutations do obliterate this response. Other upstream triggers of the RhoGTPase-NFκB interactions include the suppressive p120 catenin, with implications for skin inflammation. The networks described here are not only important areas for further research, but are also significant for discovery of targets for translational medicine.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".