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miR-155 Deletion in Mice Overcomes Neuron-Intrinsic and Neuron-Extrinsic Barriers to Spinal Cord Repair

2016· article· en· W2491292286 on OpenAlexfundno aff
Andrew D. Gaudet, S. Mandrekar-Colucci, Jodie C.E. Hall, David R. Sweet, Philipp Schmitt, Xiaoping Xu, Zhen Guan, Xiaokui Mo, Mireia Guerau‐de‐Arellano, Phillip G. Popovich

Bibliographic record

VenueJournal of Neuroscience · 2016
Typearticle
Languageen
FieldNeuroscience
TopicNerve injury and regeneration
Canadian institutionsnot available
FundersNational Institute of Neurological Disorders and StrokeNational Institute of Allergy and Infectious DiseasesCanadian Institutes of Health ResearchNational Institutes of HealthInternational Foundation for Research in Paraplegia
KeywordsAxonNeuroinflammationSpinal cordNeuroscienceDorsal root ganglionNeuronNeuriteSpinal cord injuryRegeneration (biology)BiologyLesionCell biologyInflammationMedicinePathologyImmunologyIn vitro

Abstract

fetched live from OpenAlex

UNLABELLED: Axon regeneration after spinal cord injury (SCI) fails due to neuron-intrinsic mechanisms and extracellular barriers including inflammation. microRNA (miR)-155-5p is a small, noncoding RNA that negatively regulates mRNA translation. In macrophages, miR-155-5p is induced by inflammatory stimuli and elicits a response that could be toxic after SCI. miR-155 may also independently alter expression of genes that regulate axon growth in neurons. Here, we hypothesized that miR-155 deletion would simultaneously improve axon growth and reduce neuroinflammation after SCI by acting on both neurons and macrophages. New data show that miR-155 deletion attenuates inflammatory signaling in macrophages, reduces macrophage-mediated neuron toxicity, and increases macrophage-elicited axon growth by ∼40% relative to control conditions. In addition, miR-155 deletion increases spontaneous axon growth from neurons; adult miR-155 KO dorsal root ganglion (DRG) neurons extend 44% longer neurites than WT neurons. In vivo, miR-155 deletion augments conditioning lesion-induced intraneuronal expression of SPRR1A, a regeneration-associated gene; ∼50% more injured KO DRG neurons expressed SPRR1A versus WT neurons. After dorsal column SCI, miR-155 KO mouse spinal cord has reduced neuroinflammation and increased peripheral conditioning-lesion-enhanced axon regeneration beyond the epicenter. Finally, in a model of spinal contusion injury, miR-155 deletion improves locomotor function at postinjury times corresponding with the arrival and maximal appearance of activated intraspinal macrophages. In miR-155 KO mice, improved locomotor function is associated with smaller contusion lesions and decreased accumulation of inflammatory macrophages. Collectively, these data indicate that miR-155 is a novel therapeutic target capable of simultaneously overcoming neuron-intrinsic and neuron-extrinsic barriers to repair after SCI. SIGNIFICANCE STATEMENT: Axon regeneration after spinal cord injury (SCI) fails due to neuron-intrinsic mechanisms and extracellular barriers, including inflammation. Here, new data show that deleting microRNA-155 (miR-155) affects both mechanisms and improves repair and functional recovery after SCI. Macrophages lacking miR-155 have altered inflammatory capacity, which enhances neuron survival and axon growth of cocultured neurons. In addition, independent of macrophages, adult miR-155 KO neurons show enhanced spontaneous axon growth. Using either spinal cord dorsal column crush or contusion injury models, miR-155 deletion improves indices of repair and recovery. Therefore, miR-155 has a dual role in regulating spinal cord repair and may be a novel therapeutic target for SCI and other CNS pathologies.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.031
GPT teacher head0.292
Teacher spread0.261 · 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".

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Citations94
Published2016
Admission routes1
Has abstractyes

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