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Record W4400659205 · doi:10.1186/s12967-024-05480-5

miR-223 accelerates lipid droplets clearance in microglia following spinal cord injury by upregulating ABCA1

2024· article· en· W4400659205 on OpenAlexaff
Zhilin Ou, Yongquan Cheng, Hao Ma, Kai Chen, Qiong Lin, Jiayu Chen, Zhiping Huang, Qixian Cheng, Nima Alaeiilkhchi, Qingàn Zhu, Zucheng Huang, Hui Jiang

Bibliographic record

VenueJournal of Translational Medicine · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLipid metabolism and biosynthesis
Canadian institutionsInternational Collaboration On Repair Discoveries
FundersNatural Science Foundation of Guangdong ProvinceNational Natural Science Foundation of China
KeywordsMicrogliaRemyelinationSpinal cord injuryABCA1Spinal cordLipid dropletHomeostasisLipid accumulationNeuroscienceMedicineCell biologyChemistryInflammationCentral nervous systemBiologyImmunologyBiochemistryInternal medicineMyelinTransporter

Abstract

fetched live from OpenAlex

BACKGROUND: Spinal cord injury (SCI) is characterized by extensive demyelination and inflammatory responses. Facilitating the clearance of lipid droplets (LDs) within microglia contributes to creating a microenvironment that favors neural recovery and provides essential materials for subsequent remyelination. Therefore, investigating MicroRNAs (miRNAs) that regulate lipid homeostasis after SCI and elucidating their potential mechanisms in promoting LDs clearance in microglia have become focal points of SCI research. METHODS: We established a subacute C5 hemicontusion SCI model in mice and performed transcriptomic sequencing on the injury epicenter to identify differentially expressed genes and associated pathways. Confocal imaging was employed to observe LDs accumulation. Multi-omics analyses were conducted to identify differentially expressed mRNA and miRNA post-SCI. Pathway enrichment analysis and protein-protein interaction network construction were performed using bioinformatics methods, revealing miR-223-Abca1 as a crucial miRNA-mRNA pair in lipid metabolism regulation. BV2 microglia cell lines overexpressing miR-223 were engineered, and immunofluorescence staining, western blot, and other techniques were employed to assess LDs accumulation, relevant targets, and inflammatory factor expression, confirming its role in regulating lipid homeostasis in microglia. RESULTS: Histopathological results of our hemicontusion SCI model confirmed LDs aggregation at the injury epicenter, predominantly within microglia. Our transcriptomic analysis during the subacute phase of SCI in mice implicated ATP-binding cassette transporter A1 (Abca1) as a pivotal gene in lipid homeostasis, cholesterol efflux and microglial activation. Integrative mRNA-miRNA multi-omics analysis highlighted the crucial role of miR-223 in the neuroinflammation process following SCI, potentially through the regulation of lipid metabolism via Abca1. In vitro experiments using BV2 cells overexpressing miR-223 demonstrated that elevated levels of miR-223 enhance ABCA1 expression in myelin debris and LPS-induced BV2 cells. This promotes myelin debris degradation and LDs clearance, and induces a shift toward an anti-inflammatory M2 phenotype. CONCLUSIONS: In summary, our study unveils the critical regulatory role of miR-223 in lipid homeostasis following SCI. The mechanism by which this occurs involves the upregulation of ABCA1 expression, which facilitates LDs clearance and myelin debris degradation, consequently alleviating the lipid burden, and inhibiting inflammatory polarization of microglia. These findings suggest that strategies to enhance miR-223 expression and target ABCA1, thereby augmenting LDs clearance, may emerge as appealing new clinical targets for SCI treatment.

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 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)0.001
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 score0.373
Threshold uncertainty score0.476

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.304
Teacher spread0.291 · 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 teacher head, 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

Citations13
Published2024
Admission routes1
Has abstractyes

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