Sarcomere length measurement reliability in single myofibrils
Bibliographic record
Abstract
Sarcomere length non-uniformities occur at all structural levels of skeletal muscles and have been associated with important mechanical properties. Changes in sarcomere length non-uniformities in the nano- and sub-nanometer range have been used to explain muscle properties and contractile mechanisms. Typically, these measurements rely on light microscopy with a limited spatial resolution. One critical aspect in sarcomere length determination is the relatively arbitrary choice of intensity thresholds used to delineate sarcomere structures, such as A-bands or Z-lines. In experiments, these structures are typically distorted, intensity profiles vary, and baselines drift, resulting in asymmetric intensity patterns, causing changes in the centroid location of these structures depending on threshold choice, resulting in changes of sarcomere lengths. The purpose of this study was to determine the changes in (half-) sarcomere lengths associated with small changes in the A-band threshold choice. Sarcomere and half-sarcomere length changes for minute variations in A-band threshold were 28 nm (±28 nm) and 18 nm (±22 nm), respectively, and for the entire feasible range of thresholds across A-bands were 123 nm (±88 nm) and 99 nm (±105 nm), respectively. We conclude from these results that (half-) sarcomere lengths in the nanometer range obtained with light microcopy are noise, and the functional implications associated with such data should be discarded. We suggest that a functional resolution for sarcomere length of 100 nm (0.1 µm) is reasonable and 50 nm (0.05 µm) might be possible under ideal conditions.
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 | 0.008 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".