Regulatory volume increase in single mouse soleus muscle fibres assessed simultaneously using intracellular fluorescence and fibre width
Bibliographic record
Abstract
Mammalian skeletal muscle cells have the ability to regulate volume in response to increases or decreases in extracellular osmolarity. In the present study we measured the time course of change in single fibre intracellular calcein fluorescence (volume indicastor) and width in response to varied 200 mosmol/L increase in extracellular osmolarity using NaCl or sucrose. Adult mouse EDL single fibres were isolated using collagenase and incubated in DMEM prior to and during experimentation. Fibres were loaded with calcein‐AM for 30 min, and triple‐rinsed with calcein‐free DMEM. After obtaining baseline images NaCl or sucrose solution was added. Fibre images were obtained at 3–6 s intervals for up to 60 min. Fibre images were analyzed for intensity and width at 2–3 sites. Increased osmolarity resulted in a rapid increase in fibre fluorescence and decrease in fibre width. Both variables gradually recovered to baseline values within ~45 min. Bumetanide, an inhibitor of the sodium‐potassium‐2 chloride cotransporter (NKCC) impaired recovery. There was a linear relationship between increases in fibre fluorescent intensity and decreases in fibre width. It is concluded that the NKCC is involved in regulatory volume increase in skeletal muscle, and that changes in fluorescence intensity can be used as an indicator of changes in cell volume. Supported by NSERC of Canada.
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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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".