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Record W4386475150 · doi:10.1007/s12015-023-10618-x

ST2-Conditioned Medium Fosters Dorsal Horn Cell Excitability and Synaptic Transmission in Cultured Mouse Spinal Cord

2023· article· en· W4386475150 on OpenAlexaff
Esri H. Juárez, Chelsea R. Wood, Rebecca Davies, Oksana Kehoe, William E. Johnson, Adalberto Merighi, Francesco Ferrini

Bibliographic record

VenueStem Cell Reviews and Reports · 2023
Typearticle
Languageen
FieldMedicine
TopicSpinal Cord Injury Research
Canadian institutionsUniversité Laval
FundersUniversity of GalwayUniversità degli Studi di TorinoNational University of Ireland
KeywordsSpinal cordNeuroscienceMesenchymal stem cellExcitatory postsynaptic potentialNeurotransmissionPremovement neuronal activityChemistryNeuronCell biologyBiologyReceptorInhibitory postsynaptic potentialBiochemistry

Abstract

fetched live from OpenAlex

Conditioned medium obtained from bone marrow-derived stem cells has been proposed as a novel cell-free therapy in spinal cord injury and neuropathic pain, yet the direct effect on spinal neuron function has never been investigated. Here, we adopted spinal cord organotypic cultures (SCOCs) as an experimental model to probe the effect of ST2 murine mesenchymal stem cells-conditioned medium (ST2-CM) on dorsal horn (DH) neuron functional properties. Three days of SCOC exposure to ST2-CM increased neuronal activity measured by Fos expression, as well as spontaneous or induced firing. We showed that the increase in neuronal excitability was associated with changes in both intrinsic membrane properties and an enhanced excitatory drive. The increased excitability at the single-cell level was substantiated at the network level by detecting synchronous bursts of calcium waves across DH neurons. Altogether, SCOCs represent a viable tool to probe mesenchymal cells' effect on intact neuronal networks. Our findings indicate that ST2-CM enhances neuronal activity and synaptic wiring in the spinal dorsal horn. Our data also support the trophic role of mesenchymal cells CM in maintaining network activity in spinal circuits.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.496
Threshold uncertainty score0.672

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.050
GPT teacher head0.352
Teacher spread0.302 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

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