Bibliographic record
Abstract
From single and static organelles within the cell, the image of mitochondria has evolved to a dynamic cellular network in constant communication with other organelles. Indeed, their social nature allows their potential as signal transducer organelles which exert multiple functions beyond energy production. Recently, mitochondrial regulation of the innate immune response has become into a new functionality which determines cellular health. Mitochondria serve as platforms for the recruitment of complexes that forward signals to the nucleus in response to infections, with the aim of triggering inflammatory signaling pathways that, in turn, promote adequate immune responses. On the other hand, mitochondria act as a source of damage-associated molecular patterns (DAMPs), which initiate sterile inflammatory responses upon different stimuli. The mitochondrial genome (mtDNA), owing to its resemblance to a bacterial genome, is considered a mitochondrial DAMP (mtDAMP). The presence of mtDNA outside the mitochondrial compartment, either in the cytoplasm, inside endosomes or in the extracellular media, serves as an initial signal of mitochondrial dysfunction. Chronic mitochondrial damage leads to a robust activation of the innate immunity, triggering the expression of pro-inflammatory cytokines and interferon-related genes, impacting tissue and systemic homeostasis and potentially driving disease. In this chapter, we review the intracellular innate immune response mechanisms that can recognize mtDNA upon mitochondrial dysfunction, engaging aberrant sterile inflammation. We connect the state-of-the-art knowledge to the emerging role of inflammation as a common marker of age-related and mitochondria-associated diseases.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.059 | 0.029 |
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".