Assessment of Na+/K+ ATPase Activity in Small Rodent and Human Skeletal Muscle Samples
Bibliographic record
Abstract
INTRODUCTION: In skeletal muscle, the Na/K ATPase (NKA) plays essential roles in processes linked to muscle contraction, fatigue, and energy metabolism; however, very little information exists regarding the regulation of NKA activity. The scarcity of information regarding NKA function in skeletal muscle likely stems from methodological constraints, as NKA contributes minimally to total cellular ATP utilization, and therefore contamination from other ATPases prevents the assessment of NKA activity in muscle homogenates. Here we introduce a method that improves accuracy and feasibility for the determination of NKA activity in small rodent muscle samples (5-10 mg) and in human skeletal muscle. METHODS: Skeletal muscle homogenates from mice (n = 6) and humans (n = 3) were used to measure NKA and sarcoplasmic reticulum Ca ATPase (SERCA) activities with the addition of specific ATPase inhibitors to minimize "background noise." RESULTS: We observed that myosin ATPase activity was the major interfering factor for estimation of NKA activity in skeletal muscle homogenates, as the addition of 25 μM of blebbistatin, a specific myosin ATPase inhibitor, considerably minimized "background noise" (threefold) and enabled the determination of NKA maximal activity with values three times higher than previously reported. The specificity of the assay was demonstrated after the addition of 2 mM ouabain, which completely inhibited NKA. On the other hand, the addition of blebbistatin did not affect the ability to measure SERCA function. The coefficient of variation for NKA and SERCA assays were 6.2% and 4.4%, respectively. CONCLUSION: The present study has improved the methodology to determine NKA activity. We further show the feasibility of measuring NKA and SERCA activities from a common muscle homogenate. This methodology is expected to aid in our long-term understanding of how NKA affects skeletal muscle metabolic homeostasis and contractile function in diverse situations.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".