FRET assessment of CFTR molecular assembly
Bibliographic record
Abstract
In spite of extensive studies, uncertainty exists regarding the number of CFTR molecules that come together to form a conducting pore. At present, findings point both to monomeric and multimeric assembly of CFTR protein. We evaluated the CFTR assembly by fluorescence resonance energy transfer imaging. FRET exploits the exquisite sensitivity of fluorescence measurements to detect molecular complexes with near angstrom resolution. We assayed for FRET between (i) N‐terminally tagged CFTRs (ECFP‐CFTR and EYFP‐CFTR); (ii) C‐terminally tagged CFTRs (CFTR‐ECFP and CFTR‐EYFP); and (iii) both N‐terminally and C‐terminally tagged CFTRs (ECFP‐CFTR and CFTR‐EYFP). We found no appreciable increase in CFP fluorescence after selective photobleaching of YFP, indicative of no FRET occurrence. Our findings show that the cytoplasmic tails of CFTR are not in sufficient proximity for the occurrence of FRET, suggestive of monomeric organization of CFTR. Supported by NIH 2RO1‐DK37206‐15, NIH P50 DK53090‐05, NIH RO1‐ DK075302 , CFF/CFFT.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".