Characterizing SERCA function in murine skeletal muscles after 35-37 days of spaceflight
Bibliographic record
Abstract
Abstract It is well established that microgravity exposure causes significant muscle weakness and atrophy via muscle unloading. On Earth, muscle unloading leads to a disproportionate loss in muscle force and size with the loss in muscle force occurring at a faster rate. Though the exact mechanisms are unknown, a role for Ca 2+ dysregulation has been suggested. The sarco(endo)plasmic reticulum Ca 2+ ATPase (SERCA) pump actively brings cytosolic Ca 2+ into the SR, eliciting muscle relaxation and maintaining low intracellular Ca 2+ ([Ca 2+ ] i ). SERCA dysfunction contributes to elevations in [Ca 2+ ] i , leading to cellular damage and thus may contribute to the muscle weakness and atrophy observed with spaceflight. Here, we investigated SERCA function, SERCA regulatory protein content (sarcolipin, phospholamban, and neuronatin), and reactive oxygen/nitrogen species (RONS) protein adduction in murine skeletal muscle after 35-37 days of spaceflight. In male and female soleus muscles, spaceflight led to drastic impairments in Ca 2+ uptake despite significant increases in SERCA1a protein content. We attribute this impairment to an increase in RONS production and elevated total protein tyrosine (T) nitration and cysteine (S) nitrosylation. Contrarily, in the tibialis anterior (TA) we observed an enhancement in Ca 2+ uptake, which we attribute to a shift towards a faster muscle fiber type (i.e., increased myosin heavy chain IIb and SERCA1a) without elevated total protein T-nitration and S-nitrosylation. Thus, spaceflight affects SERCA function differently between the soleus and TA. As the soleus is severely affected by spaceflight, future studies should determine whether improving SERCA function in this muscle can mitigate muscle atrophy and weakness.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".