Subpixel tracking for the analysis of outer hair cell movements
Bibliographic record
Abstract
CONCLUSION: Videomicroscopy with subpixel analysis is an excellent system for quantification of outer hair cell (OHC) movements. The resolution of a few nanometers is accurate enough to show induced differences of electromotility. OBJECTIVE: Electromotility of OHCs is a voltage-dependent process resulting from a membrane protein named prestin. Voltage sensitivity is conferred to prestin by intracellular anions. Reduction of these anions reduces electromotility. Videomicroscopy and subpixel tracking combine video-based analysis with a resolution of few nanometers. The aim of this study was to show the feasibility of a system for quantification of OHC movements. MATERIALS AND METHODS: Electromotility was investigated under normal and reduced intracellular chloride conditions. Cells were stimulated by the patch-clamp technique. Voltage steps were 500 ms long, ranging from -170 to +30 mV in 10 mV steps. RESULTS: As in previous studies our results show the following. The direction of OHC movement depends on the polarity of voltage steps, length changes are not equal for symmetrical voltage steps of opposite polarity, average shortening for a depolarizing step (-70 mV to +30 mV) is about 13 nm/mV. Hyperpolarization (-70 mV to -170 mV) on average evokes elongations of about 3 nm/mV. Half maximal chloride concentration reduces motility by 14%; half maximal electromotility is reached by a 94% reduction of chloride.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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".