Metabolism of the Branched‐Chain Amino Acids are Disrupted by Chemotherapy Drugs
Bibliographic record
Abstract
Cachexia is a devastating muscle‐wasting condition found in many diseases, including cancer, chronic kidney disease and heart failure. Aside from both tumour burden and disease‐related malnutrition, the development of cachexia is associated with chemotherapy treatment. Branched‐ chain amino acids (BCAA: leucine, isoleucine and valine) are critical regulators of skeletal muscle protein anabolism due to their activation of the mammalian/mechanistic target of rapamycin complex 1 (mTORC1). However, BCAA supplementation/nutritional support does not fully reverse chemotherapy‐induced cachexia. Therefore, we investigated whether breakdown of BCAAs is affected by chemotherapy drugs. On day 4 of differentiation, L6 myotubes were treated with vehicle (1.4μL/mL DMSO) or a common chemotherapy drug cocktail, folfiri (a mixture of CPT‐11 (20μg/mL), leucovorin (10μg/mL), and 5‐fluorouracil (50μg/mL)) for 24‐48h. Myotubes treated with folfiri exhibited ~30% reductions in myotube diameter (p < 0.05, n=3) and ~50% reductions in abundance of myofibrillar proteins myosin heavy chain‐1 (MHC) and troponin (p < 0.05). Protein content of branched‐chain alpha‐ketoacid dehydrogenase complex (BCKD), the enzyme responsible for the irreversible decarboxylation of the BCAA ketoacids, was unchanged following folfiri treatment. However, the activity of this enzyme complex was significantly decreased (~20%) 24 and 48h following treatment with folfiri (p < 0.05). Branched‐chain alpha‐ketoacid dehydrogenase complex kinase (BDK), a negative regulator of BCKD, was increased 24h (~20%), but unchanged at 48h following folfiri treatment. Compared to vehicle, folfiri‐treated myotubes showed a non‐significant reduction (~30%) in phenylalanine incorporation into proteins. In line with studies showing a link between impaired BCAA catabolism and insulin resistance, our data suggest a link between chemotherapy‐induced muscle atrophy and altered BCAA catabolism.
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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) | 0.002 | 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".