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Record W2265706621 · doi:10.1161/str.44.suppl_1.awp92

Abstract WP92: Human Neural Stem Cells Enhance Synaptic Structural Remodeling in the Ischemic Brain.

2013· article· en· W2265706621 on OpenAlexaff
Takeshi Hiu, Tonya Bliss, Nathan C. Manley, Eric H. Wang, Gordon Wang, Kristina D. Micheva, Andrew Olson, Stephen J Smith, Gary K. Steinberg

Bibliographic record

VenueStroke · 2013
Typearticle
Languageen
FieldNeuroscience
TopicAnesthesia and Neurotoxicity Research
Canadian institutionsStuart Olson (Canada)
Fundersnot available
KeywordsTransplantationMedicineNeural stem cellNeuroscienceGlutamatergicStem cellNeuroplasticityProgenitor cellStroke (engine)Synaptic plasticityGlutamate receptorCortex (anatomy)Internal medicineBiologyReceptorCell biology

Abstract

fetched live from OpenAlex

Introduction: Stem cell transplantation has emerged as a promising new experimental treatment for stroke; understanding its mechanism of action will facilitate the translation of stem cell therapy to the clinic. Previous work from our lab and others suggests that transplanted stem cells function by enhancing endogenous brain repair processes including structural brain plasticity. The ultimate change in brain plasticity is manifested at the synaptic level and thus we hypothesize that stem cells will enhance synaptic structural remodeling in the post-ischemic brain. To test this we use array tomography, a new high-resolution proteomic imaging method, to determine a) the number and subtype of glutamate and GABA synapses after stroke, and b) how these parameters are affected by transplantation of human neural progenitor cells (hNPCs). Method: Vehicle or hNPCs derived from fetal cortex were transplanted into the ischemic cortex of Nude rats at 7 days after distal middle cerebral artery occlusion. Neurological recovery was assessed weekly using a battery of behavioral tests. Small tissue was removed from the peri-infarct cortex at 4 weeks post-transplantation. The tissue was processed and ribbons, or arrays, of serial ultrathin sections (70 nm) were obtained using an ultramicrotome. Ribbons were stained with antibodies for the synaptic markers Synapsin1, VGlut1, VGlut2, PSD-95, GAD, VGAT, GABAAR-α1, and images taken in cortical layer 2/3 and layer 5. Computational analysis of the resultant staining pattern was used to identify and quantify subtypes of glutamatergic and GABAergic synapses. Results: Transplantation of hNPCs significantly improved behavioral recovery after stroke compared to vehicle-treated rats (4 weeks; p<0.01, n=9). There was an increase in the density and proportion of glutamatergic synapses expressing VGluT2 in layer5 at 4 weeks post-transplantation (Density: 0.090 vs 0.057 synapses/μm3. Proportion: 27.0 vs 22.6 %, n=4). No detectable differences in the density of GABAergic synapses were observed. Conclusions: These results suggest that stem cells alter synaptic remodeling after stroke and this is coincident with stem cell-induced functional recovery.

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)0.000
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 score0.015
Threshold uncertainty score0.549

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.043
GPT teacher head0.308
Teacher spread0.265 · 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

Citations0
Published2013
Admission routes1
Has abstractyes

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