MétaCan
Menu
Back to cohort

Suppressing CSPG/LAR/PTPσ Axis Facilitates Neuronal Replacement and Synaptogenesis by Human Neural Precursor Grafts and Improves Recovery after Spinal Cord Injury

2022· article· en· W4220813517 on OpenAlexafffund

Bibliographic record

VenueJournal of Neuroscience · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProteoglycans and glycosaminoglycans research
Canadian institutionsNew World LaboratoriesChildren's Hospital Research Institute of ManitobaUniversity of Manitoba
FundersCanadian Institutes of Health ResearchGovernment of CanadaUniversity of Manitoba
KeywordsSynaptogenesisNeurogenesisSpinal cord injuryNeural stem cellSpinal cordRegeneration (biology)GliogenesisBiological neural networkNeurodegeneration

Abstract

fetched live from OpenAlex

Traumatic spinal cord injury (SCI) is a leading cause of permanent neurologic disabilities in young adults. Functional impairments after SCI are substantially attributed to the progressive neurodegeneration. However, regeneration of spinal-specific neurons and circuit re-assembly remain challenging in the dysregulated milieu of SCI because of impaired neurogenesis and neuronal maturation by neural precursor cells (NPCs) spontaneously or in cell-based strategies. The extrinsic mechanisms that regulate neuronal differentiation and synaptogenesis in SCI are poorly understood. Here, we perform extensive in vitro and in vivo studies to unravel that SCI-induced upregulation of matrix chondroitin sulfate proteoglycans (CSPGs) impedes neurogenesis of NPCs through co-activation of two receptor protein tyrosine phosphatases, LAR and PTPσ. In adult female rats with SCI, systemic co-inhibition of LAR and PTPσ promotes regeneration of motoneurons and spinal interneurons by engrafted human directly reprogramed caudalized NPCs (drNPC-O2) and fosters their morphologic maturity and synaptic connectivity within the host neural network that culminate in improved recovery of locomotion and sensorimotor integration. Our transcriptomic analysis of engrafted human NPCs in the injured spinal cord confirmed that inhibition of CSPG receptors activates a comprehensive program of gene expression in NPCs that can support neuronal differentiation, maturation, morphologic complexity, signal transmission, synaptic plasticity, and behavioral improvement after SCI. We uncovered that CSPG/LAR/PTPσ axis suppresses neuronal differentiation in part by blocking Wnt/β-Catenin pathway. Taken together, we provide the first evidence that CSPGs/LAR/PTPσ axis restricts neurogenesis and synaptic integration of new neurons in NPC cellular therapies for SCI. We propose targeting LAR and PTPσ receptors offers a promising clinically-feasible adjunct treatment to optimize the efficacy and neurologic benefits of ongoing NPC-based clinical trials for SCI. SIGNIFICANCE STATEMENT Transplantation of neural precursor cells (NPCs) is a promising approach for replacing damaged neurons after spinal cord injury (SCI). However, survival, neuronal differentiation, and synaptic connectivity of transplanted NPCs within remain challenging in SCI. Here, we unravel that activation of chondroitin sulfate proteoglycan (CSPG)/LAR/PTPσ axis after SCI impedes the capacity of transplanted human NPCs for replacing functionally integrated neurons. Co-blockade of LAR and PTPσ is sufficient to promote re-generation of motoneurons and spinal V1 and V3 interneurons by engrafted human caudalized directly reprogramed NPCs (drNPC-O2) and facilitate their synaptic integration within the injured spinal cord. CSPG/LAR/PTPσ axis appears to suppress neuronal differentiation of NPCs by inhibiting Wnt/β-Catenin pathway. These findings identify targeting CSPG/LAR/PTPσ axis as a promising strategy for optimizing neuronal replacement, synaptic re-connectivity, and neurologic recovery in NPC-based strategies.

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 score0.001
Threshold uncertainty score0.003

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)0.0010.000

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 head0.018
GPT teacher head0.299
Teacher spread0.281 · 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

Citations27
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueJournal of NeuroscienceSame topicProteoglycans and glycosaminoglycans researchFrench-language works237,207