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Record W4388133835 · doi:10.1080/15548627.2023.2276639

CKLF induces microglial activation via triggering defective mitophagy and mitochondrial dysfunction

2023· article· en· W4388133835 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAutophagy · 2023
Typearticle
Languageen
FieldMedicine
TopicAutophagy in Disease and Therapy
Canadian institutionsUniversity of Toronto
FundersNational Key Research and Development Program of ChinaNational Natural Science Foundation of China
KeywordsMitophagyPINK1Cell biologyAutophagyBiologyMicrogliaNeuroinflammationLysosomeParkinAutophagosomeMitochondrionProinflammatory cytokineInflammationImmunologyBiochemistryApoptosis

Abstract

fetched live from OpenAlex

Although microglial activation is induced by an increase in chemokines, the role of mitophagy in this process remains unclear. This study aimed to elucidate the role of microglial mitophagy in CKLF/CKLF1 (chemokine-like factor 1)-induced microglial activation and neuroinflammation, as well as the underlying molecular mechanisms following CKLF treatment. This study determined that CKLF, an inducible chemokine in the brain, leads to an increase in mitophagy markers, such as DNM1L, PINK1 (PTEN induced putative kinase 1), PRKN, and OPTN, along with a simultaneous increase in autophagosome formation, as evidenced by elevated levels of BECN1 and MAP1LC3B (microtubule-associated protein 1 light chain 3 beta)-II. However, SQSTM1, a substrate of autophagy, was also accumulated by CKLF treatment, suggesting that mitophagy flux was reduced and mitophagosomes accumulated. These findings were confirmed by transmission electron microscopy and confocal microscopy. The defective mitophagy observed in our study was caused by impaired lysosomal function, including mitophagosome-lysosome fusion, lysosome generation, and acidification, resulting in the accumulation of damaged mitochondria in microglial cells. Further analysis revealed that pharmacological blocking or gene-silencing of mitophagy inhibited CKLF-mediated microglial activation, as evidenced by the expression of the microglial marker AIF1 (allograft inflammatory factor 1) and the mRNA of proinflammatory cytokines (Tnf and Il6). Ultimately, defective mitophagy induced by CKLF results in microglial activation, as observed in the brains of adult mice. In summary, CKLF induces defective mitophagy, microglial activation, and inflammation, providing a potential approach for treating neuroinflammatory diseases.Abbreviation: 3-MA: 3-methyladenine; AIF1: allograft inflammatory factor 1; ANOVA: analysis of variance; BAF: bafilomycin A1; BSA: bovine serum albumin; CCCP: carbonyl cyanide m-chlorophenyl hydrazone; cGAMP: cyclic GMP-AMP; CGAS: cyclic GMP-AMP synthase; CKLF/CKLF1: chemokine-like factor 1; CNS: central nervous system; DMEM: Dulbecco’s Modified Eagle Medium; DNM1L: dynamin 1 like; GAPDH: glyceraldehyde-3-phosphate dehydrogenase; GFP: green fluorescence protein; IRF3: interferon regulatory factor 3; IgG: immunoglobulin G; LAMP1: lysosomal-associated membrane protein 1; LAPTM4A: lysosomal-associated protein transmembrane 4A; MAP1LC3B: microtubule-associated protein 1 light chain 3 beta; Mdivi-1: mitochondrial division inhibitor 1; mRFP: monomeric red fluorescent protein; mtDNA: mitochondrial DNA; MTORC1: mechanistic target of rapamycin kinase complex 1; OPTN: optineurin; PBS: phosphate-buffered saline; PCR: polymerase chain reaction; PINK1: PTEN induced putative kinase 1; PLL: poly-L-lysine; PRKN: parkin RBR E3 ubiquitin protein ligase; qPCR: quantitative polymerase chain reaction; ROS: reactive oxygen species; SQSTM1: sequestosome 1; TBK1: TANK-binding kinase 1; TFEB: transcription factor EB; VDAC: voltage-dependent anion channel

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.110
Threshold uncertainty score0.872

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.014
GPT teacher head0.270
Teacher spread0.256 · 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