Diaphragm assessment in mice overexpressing phospholamban in slow‐twitch type <scp>I</scp> muscle fibers
Bibliographic record
Abstract
AIMS: Phospholamban (PLN) and sarcolipin (SLN) are small inhibitory proteins that regulate the sarco(endo)plasmic reticulum Ca(2+)-ATPase (SERCA) pump. Previous work from our laboratory revealed that in the soleus and gluteus minimus muscles of mice overexpressing PLN (Pln (OE)), SERCA function was impaired, dynamin 2 (3-5 fold) and SLN (7-9 fold) were upregulated, and features of human centronuclear myopathy (CNM) were observed. Here, we performed structural and functional experiments to evaluate whether the diaphragm muscles of the Pln (OE) mouse would exhibit CNM pathology and muscle weakness. METHODS: Diaphragm muscles from Pln (OE) and WT mice were subjected to histological/histochemical/immunofluorescent staining, Ca(2+)-ATPase and Ca(2+) uptake assays, Western blotting, and in vitro electrical stimulation. RESULTS: Our results demonstrate that PLN overexpression reduced SERCA's apparent affinity for Ca(2+) but did not reduce maximal SERCA activity or rates of Ca(2+) uptake. SLN was upregulated 2.5-fold, whereas no changes in dynamin 2 expression were found. With respect to CNM, we did not observe type I fiber predominance, central nuclei, or central aggregation of oxidative activity in diaphragm, although type I fiber hypotrophy was present. Furthermore, in vitro contractility assessment of Pln (OE) diaphragm strips revealed no reductions in force-generating capacity, maximal rates of relaxation or force development, but did indicate that ½ relaxation time was prolonged. CONCLUSIONS: Therefore, the effects of PLN overexpression on skeletal muscle phenotype differ between diaphragm and the postural soleus and gluteus minimus muscles. Our findings here point to differences in SLN expression and type I fiber distribution as potential contributing factors.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".