Hepatic alterations during the development and progression of cancer cachexia
Bibliographic record
Abstract
Cancer-associated bodyweight loss (cachexia) is a hallmark of many cancers and is associated with decreased quality of life and increased mortality. Hepatic function can dramatically influence whole-body energy expenditure and may therefore significantly influence whole-body health during cancer progression. The purpose of this study was to examine alterations in markers of hepatic metabolism and physiology during cachexia progression. Male C57BL/6J mice were injected with 1 × 106 Lewis Lung Carcinoma cells dissolved in 100 μL PBS and cancer was allowed to develop for 1, 2, 3, or 4 weeks. Control animals were injected with an equal volume of phosphate-buffered saline. Livers were analyzed for measures of metabolism, collagen deposition, protein turnover, and mitochondrial quality. Animals at 4 weeks had ∼30% larger livers compared with all other groups. Cancer progression was associated with altered regulators of fat metabolism. Additionally, longer duration of cancer development was associated with ∼3-fold increased regulators of collagen deposition as well as phenotypic collagen content, suggesting increased liver fibrosis. Mitochondrial quality control regulators appeared to be altered before any phenotypic alterations to collagen deposition. While induction of Akt was noted, downstream markers of protein synthesis were not altered. In conclusions, cancer cachexia progression is associated with hepatic pathologies, specifically liver fibrosis. Alterations to mitochondrial quality control mechanisms appear to precede this fibrotic phenotype, potentially suggesting mitochondrial mechanisms for the development of hepatic pathologies during the development and progression of cancer cachexia. Novelty Cachexia progression results in liver collagen deposition and fibrosis. Alterations in mitochondrial quality control may precede liver pathologies during cachexia.
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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 | 0.001 |
| 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".