Bibliographic record
Abstract
The cystic fibrosis transmembrane conductance regulator (CFTR) Cl -channel uses positively charged amino-acid side-chains to form binding sites for permeating anions.These binding sites have been investigated experimentally using a number of anionic probes.Mutations that alter the distribution of positive and negative charges within the pore have differential effects on the binding of monovalent versus divalent anions.This study uses patch clamp recording from wild-type and pore-mutant forms of CFTR to investigate small trivalent anions (Co(NO 2 ) 6 3-, Co(CN) 6 3-and IrCl 6 3-) as potential probes of anion binding sites.These anions caused weak block of Cl -permeation in wild-type CFTR (Kd ≥ 700 μM) when applied to the intracellular side of the membrane.Mutations that increase the density of positive charge within the pore (E92Q, I344K, S1141K) increased the binding affinity of these anions 80-280-fold, and also greatly increased the voltage-dependence of block, consistent with fixed charges in the pore affecting monovalent : multivalent anion selectivity.However, high-affinity pore block by Co(NO 2 ) 6 3-apparently did not alter channel gating, a hallmark of high-affinity binding of divalent Pt(NO 2 ) 4 2-ions within the pore.This work increases the arsenal of probes available to investigate anion binding sites within Cl -channel pores.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".