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Record W4411438203 · doi:10.4103/nrr.nrr-d-24-01459

Mitochondrial damage-associated molecular patterns: Neuroimmunomodulators in central nervous system pathophysiology

2025· article· en· W4411438203 on OpenAlexaff
Ishvin Riar, Andis Klegeris

Bibliographic record

VenueNeural Regeneration Research · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMitochondrial Function and Pathology
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsMitochondrionBiologyNeuroinflammationCell biologyMicrogliaExtracellularNeuroscienceCentral nervous systemImmunologyInflammation

Abstract

fetched live from OpenAlex

Neuroinflammation contributes to a wide range of neurodegenerative diseases including Alzheimer's disease, Parkinson's disease, Huntington's disease, and multiple sclerosis. It is driven by non-neuronal glial cells, mainly microglia and astrocytes. Microglia are the resident immune cells of the central nervous system, while astrocytes are the main support cells for neuronal functions but can also participate in neuroimmune responses. Both these glial cell types can become reactive upon detection of certain endogenous intracellular molecules that appear in the extracellular space under specific circumstances; these can be pathology-associated abnormal structures, such as amyloid β proteins, or damage-associated molecular patterns released from injured cells, including their mitochondria. Once in the extracellular space, damage-associated molecular patterns act as ligands for specific pattern recognition receptors expressed by glia inducing their reactivity and neuroimmune responses. This review considers the following mitochondrial damage-associated molecular patterns: heme, cytochrome c, cardiolipin, adenosine triphosphate, mitochondrial DNA, mitochondrial transcription factor A, N-formyl peptides, and the tricarboxylic acid cycle metabolites: succinate, fumarate, and itaconate. We describe their well-established functions as damage-associated molecular patterns of the peripheral tissues before summarizing available evidence indicating these molecules may also play significant roles in the neuroimmune processes of the central nervous system. We highlight the pattern recognition receptors that mitochondrial damage-associated molecular patterns interact with and the cellular signaling mechanisms they modulate. Our review demonstrates that some mitochondrial damage-associated molecular patterns, such as cytochrome c, adenosine triphosphate, and mitochondrial transcription factor A, have already demonstrated significant effects on the central nervous system. In contrast, others including cardiolipin, mitochondrial DNA, N-formyl peptides, succinate, fumarate, and itaconate, will require additional studies corroborating their roles as damage-associated molecular patterns in the central nervous system. For all of the reviewed mitochondrial damage-associated molecular patterns, there is a shortage of studies using human cells and tissues, which is identified as a significant knowledge gap. We also assess the need for targeted research on the effects of mitochondrial damage-associated molecular patterns in the central nervous system pathologies where their roles are understudied. Such studies could identify novel treatment strategies for multiple neurodegenerative diseases, which are characterized by chronic neuroinflammation and currently lack effective therapies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.021
GPT teacher head0.308
Teacher spread0.287 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2025
Admission routes1
Has abstractyes

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