Development of Automated Patch Clamp Technique to Investigate CFTR Chloride Channel Function
Bibliographic record
Abstract
The chloride channel Cystic Fibrosis Transmembrane conductance Regulator (CFTR) is defective in Cystic Fibrosis (CF) and mutation of its encoding gene leads to various defects such as retention of the misfolded protein in the endoplasmic reticulum, reduced stability at the plasma membrane, abnormal channel gating with low open probability, and thermal instability which leads to inactivation of the channel at physiological temperature. Pharmacotherapy is one major therapeutic approach in the CF field and needs sensible and fast tools to identify promising compounds. The high throughput screening assays available are often fast and sensible techniques but with lack of specificity. Few works used automated patch clamp for CFTR recording and none have compared conventional and planar techniques and demonstrated their capabilities for different types of experiments. In this study we evaluated the use of planar parallel automated patch clamp technique for pharmacological search of CFTR trafficking correctors and CFTR function modulators. Using optimized conditions, we recorded both wt- and corrected F508del-CFTR chloride currents with automated whole cell patch clamp and compared the data to results obtained with conventional manual whole cell patch clamp. We found no significant difference in patch clamp parameters such as cell capacitance and series resistance between automated and manual patch clamp. Also, the results showed good similarities of CFTR currents recording between the two methods. We showed that similar stimulation protocols could be used in both manual and automatic technics allowing precise control of temperature, classic I/V relationship, monitoring of current stability in time. In conclusion, parallel patch clamp recording allows rapid and efficient investigation of CFTR currents with a variety of tests available and could be considered as new tool for medium throughput screening in CF pharmacotherapy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".