Bibliographic record
Abstract
In this issue of the Biochemical Journal, Zhang et al. reveal a new strategy for modifying the regulated function of CFTR (cystic fibrosis transmembrane conductance regulator) on the apical surface of epithelial cells. Simply stated, these authors tested the idea that the cAMP-dependent channel activity of CFTR could be effectively enhanced by disruption of a protein-protein interaction which is normally inhibitory for the production of cAMP. This particular protein-protein interaction [between the PDZ motif of LPA2 (type 2 lysophosphatidic acid receptor) and the scaffold protein Nherf2 (Na+/H+ exchanger regulatory factor 2)] is localized in the CFTR interactome on the apical membrane of epithelial cells. Hence disruption of the LPA2-Nherf2 interaction should lead to a localized elevation in cAMP and, consequently, increased cAMP-dependent CFTR activity on the surface of epithelial cells. Zhang et al. confirmed these expectations for a small-molecule compound targeting the LPA2-Nherf2 interaction using relevant cultures and tissues thought to model the human respiratory epithelium. The success of this strategy depended on previous knowledge regarding the role for multiple PDZ-motif-mediated interactions in signalling (directly or indirectly) to CFTR. Given the number and diversity of such PDZ-mediated interactions, future structural and computational studies will be essential for guiding the design of specific pharmacological interventions.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".