Differential regulation of components of the apoptotic and ubiquitin-mediated proteolytic pathway in slow- and fast- twitch muscle type in lambs receiving increasing amounts of dietary non-structural carbohydrate
Bibliographic record
Abstract
Non-fibre carbohydrate (NFC) rich diets are commonly fed in ruminant production systems. The objective was to determine whether NFC challenge affects proteasome activity, or messenger ribonucleic acid (mRNA) expression of proteasome subunits or apoptotic Bcl-2 proteins, in slow- or fast- twitch muscle of sheep. For 12 d prior to slaughter, lambs (n = 8) received either a control diet (28.4% of dry matter as grain), or a diet of increasing amounts of grain up to 79.1% of dry matter. A decrease in urinary pH (P = 0.01), base excess of blood and extracellular fluid (P = 0.01), bicarbonate (P = 0.03) and total carbon dioxide (P = 0.04), and an increase in anion gap (P = 0.07) in NFC lambs are indicative of metabolic acidosis. NFC lambs had significantly lower mRNA expression of the 20S -β subunit (P = 0.05), and a tendency toward lower mRNA expression of the 20S-α subunit (P = 0.11) and the 19S isoform (P = 0.15) in soleus, but not to the same extent in extensor digitorum longus (EDL) muscle. Downregulation of Bad mRNA expression occurred in both soleus (P = 0.10) and EDL (P = 0.08) muscle as a result of NFC challenge. These results indicate that NFC challenge does affect mRNA expression of genes related to the proteasome and apoptosis in a muscle specific manner. Key words: Ubiquitin-mediated proteolytic pathway, non-fibre carbohydrate, apoptosis, sheep
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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 | 0.000 |
| 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".