An Enhanced Immune Response of Mclk1+/− Mutant Mice Is Associated with Partial Protection from Fibrosis, Cancer and the Development of Biomarkers of Aging
Bibliographic record
Abstract
The immune response is essential for survival by destroying microorganisms and pre-cancerous cells. However, inflammation, one aspect of this response, can result in short- and long-term deleterious side-effects. Mclk1⁺/⁻ mutant mice can be long-lived despite displaying a hair-trigger inflammatory response and chronically activated macrophages as a result of high mitochondrial ROS generation. Here we ask whether this phenotype is beneficial or simply tolerated. We used models of infection by Salmonella serovars and found that Mclk1⁺/⁻ mutants mount a stronger immune response, control bacterial proliferation better, and are resistant to cell and tissue damage resulting from the response, including fibrosis and types of oxidative damage that are considered to be biomarkers of aging. Moreover, these same types of tissue damage were found to be low in untreated 23 months-old mutants. We also examined the initiation of tumour growth after transplantation of mouse LLC1 carcinoma cells into Mclk1⁺/⁻ mutants, as well as during spontaneous tumorigenesis in Mclk1⁺/⁻Trp53⁺/⁻ double mutants. Tumour latency was increased by the Mclk1⁺/⁻ genotype in both models. Furthermore, we used the transplantation model to show that splenic CD8⁺ T lymphocytes from Mclk1⁺/⁻ graft recipients show enhanced cytotoxicity against LLC1 cells in vitro. Mclk1⁺/⁻ mutants thus display an association of an enhanced immune response with partial protection from age-dependent processes and from pathologies similar to those that are found with increased frequency during the aging process. This suggests that the immune phenotype of these mutants might contribute to their longevity. We discuss how these findings suggest a broader view of how the immune response might impact the aging process.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".