Bibliographic record
Abstract
This seminar, delivered to the UBC Cell and Developmental Biology Graduate Program Seminar Series on June 18, 2020, presents unpublished electrophysiological and computational work characterizing the functional role of phenylalanine 431 (F431), a conserved S6 residue in the pore domain of mouse HCN2 channels. Whole-cell patch clamp recordings of wild-type and F431A mutant channels were used to characterize the voltage-dependence and kinetics of activation and deactivation. F431A was found to slow and reduce the voltage-dependence of channel closing. A four-state allosteric model (Chen et al., 2007; Flynn & Zagotta, 2018) was fitted to the data using numerical optimization, with identifiability analysis demonstrating that deactivation protocols are necessary to constrain model parameters. Model fitting revealed that F431A alters both voltage-dependent and voltage-independent gating transitions, resulting in reduced total channel opening. Structural analysis using the Shintre et al. (2019) mouse HCN2 cryo-EM structure suggests that F431 may stabilize the closed-activated (CA) state through hydrophobic contacts with Ile344. This work was conducted in the Accili Lab, Department of Cellular and Physiological Sciences, University of British Columbia. Data are unpublished; access is available upon reasonable request.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".