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Record W2932093126 · doi:10.1155/2019/4050796

The Role of Mitochondrial Damage-Associated Molecular Patterns in Chronic Neuroinflammation

2019· review· en· W2932093126 on OpenAlexafffund
Ekta Bajwa, Caitlin B. Pointer, Andis Klegeris

Bibliographic record

VenueMediators of Inflammation · 2019
Typereview
Languageen
FieldNeuroscience
TopicNeuroinflammation and Neurodegeneration Mechanisms
Canadian institutionsOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsNeuroinflammationNeurodegenerationBiologyMicrogliaTFAMMitochondrionProinflammatory cytokineDNAJA3NeuroscienceCell biologymitochondrial fusionInflammationDiseaseImmunologyMitochondrial DNAMedicineMitochondrial biogenesisPathology

Abstract

fetched live from OpenAlex

Mitochondrial dysfunction has been established as a common feature of neurodegenerative disorders that contributes to disease pathology by causing impaired cellular energy production. Mitochondrial molecules released into the extracellular space following neuronal damage or death may also play a role in these diseases by acting as signaling molecules called damage-associated molecular patterns (DAMPs). Mitochondrial DAMPs have been shown to initiate proinflammatory immune responses from nonneuronal glial cells, including microglia and astrocytes; thereby, they have the potential to contribute to the chronic neuroinflammation present in these disorders accelerating the degeneration of neurons. In this review, we highlight the mitochondrial DAMPs cytochrome c (CytC), mitochondrial transcription factor A (TFAM), and cardiolipin and explore their potential role in the central nervous system disorders including Alzheimer’s disease and Parkinson’s disease, which are characterized by neurodegeneration and chronic neuroinflammation.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.022
GPT teacher head0.281
Teacher spread0.259 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations113
Published2019
Admission routes2
Has abstractyes

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