Inward Flux of Lactate- through Monocarboxylate Transporters Contributes to Regulatory Volume Increase in Mouse Muscle Fibres
Bibliographic record
Abstract
Mouse and rat skeletal muscles are capable of a regulatory volume increase (RVI) after they shrink (volume loss resultant from exposure to solutions of increased osmolarity) and that this RVI occurs mainly by a Na-K-Cl-Cotransporter (NKCC)-dependent mechanism. With high-intensity exercise, increased extracellular osmolarity is accompanied by large increases in extracellular [lactate⁻]. We hypothesized that large increases in [lactate⁻] and osmolarity augment the NKCC-dependent RVI response observed with a NaCl (or sucrose)-induced increase in osmolarity alone; a response that is dependent on lactate⁻ influx through monocarboxylate transporters (MCTs). Single mouse muscle fibres were isolated and visualized under light microscopy under varying osmolar conditions. When solution osmolarity was increased by adding NaLac by 30 or 60 mM, fibres lost significantly less volume and regained volume sooner compared to when NaCl was used. Phloretin (MCT1 inhibitor) accentuated the volume loss compared to both NaLac controls, supporting a role for MCT1 in the RVI response in the presence of elevated [lactate⁻]. Inhibition of MCT4 (with pCMBS) resulted in a volume loss, intermediate to that seen with phloretin and NaLac controls. Bumetanide (NKCC inhibitor), in combination with pCMBS, reduced the magnitude of volume loss, but volume recovery was complete. While combined phloretin-bumetanide also reduced the magnitude of the volume loss, it also largely abolished the cell volume recovery. In conclusion, RVI in skeletal muscle exposed to raised tonicity and [lactate⁻] is facilitated by inward flux of solute by NKCC- and MCT1-dependent mechanisms. This work demonstrates evidence of a RVI response in skeletal muscle that is facilitated by inward flux of solute by MCT-dependent mechanisms. These findings further expand our understanding of the capacities for skeletal muscle to volume regulate, particularly in instances of raised tonicity and lactate⁻ concentrations, as occurs with high intensity exercise.
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 | 0.000 |
| 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".