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Metformin Activates Neural Stem and Progenitor Cells in the Spinal Cord and Improves Functional Outcomes Following Injury

2019· article· en· W3174576027 on OpenAlexafffundabout
Emily Gilbert, Cindi M. Morshead

Bibliographic record

VenueThe FASEB Journal · 2019
Typearticle
Languageen
FieldMedicine
TopicSpinal Cord Injury Research
Canadian institutionsUniversity of Toronto
FundersKrembil FoundationAmerican Association of Anatomists
KeywordsNeurogenesisNeural stem cellProgenitor cellSpinal cord injurySpinal cordNeurosphereMedicineStem cellProgenitorNeuroscienceBiologyAdult stem cellCell biologyEndothelial stem cellIn vitro

Abstract

fetched live from OpenAlex

Across mammals, spinal cord injuries (SCI) result in devastating functional deficits with minimal treatment options. Neural stem and progenitor cells (NSPCs) exist within the spinal cord and are located in the periventricular region lining the central canal. Although normally relatively quiescent and non‐neurogenic, these NSPCs are activated in response to injury, however their response is not sufficient to support functional recovery. Enhancing the response of resident NSPCs is an innovative approach to improve structural and functional outcomes following SCI. The FDA‐approved drug metformin (MET) has demonstrated efficacy in promoting neural repair in the injured brain where it expands the size of the NSPC pool and promotes both oligogenesis and neurogenesis from NSPCs. Here, we seek to determine whether MET can influence NSPCs within the spinal cord prior to and following SCI. Using the in vitro colony‐forming assay (neurosphere assay) we examined the size of the neural stem cell (NSC) pool in the spinal cord following 7 days of in vivo MET treatment. Females, but not males, demonstrated a three‐fold increase in the size of the NSC pool in response to MET treatment. Conversely, the differentiation profile of male and female‐derived NSPCs was not sex dependent in the presence of MET. Our results show that MET exposure led to an increase in oligogenesis across both males and females, with no change in neurogenesis. Next, we evaluated whether MET administration would improve functional outcomes following SCI using a dorsal column lesion in the thoracic spinal cord. MET was delivered to animals immediately post‐SCI and treatment resulted in a significantly reduced impairment at 7 days post‐injury (DPI) on a skilled walking task, compared to vehicle‐treated SCI mice. Strikingly, MET‐treated mice recovered to baseline by 14 DPI. Our data reveals that MET has differential effects on spinal cord NSPCs across males and females and that MET administration reduces the severity of SCI and results in improves functional outcomes post‐injury. Taken together, our results support MET as a viable therapeutic strategy for enhancing neural repair and improving recovery following SCI. Support or Funding Information American Association of Anatomists Ontario Institute for Regeneration Medicine Krembil Foundation This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.047
GPT teacher head0.345
Teacher spread0.298 · 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

Citations1
Published2019
Admission routes3
Has abstractyes

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