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Record W4210565361 · doi:10.3390/biomedicines10020337

Somatostatin-Mediated Regulation of Retinoic Acid-Induced Differentiation of SH-SY5Y Cells: Neurotransmitters Phenotype Characterization

2022· article· en· W4210565361 on OpenAlexafffund
Sneha Singh, R.K. Somvanshi, Ujendra Kumar

Bibliographic record

VenueBiomedicines · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRetinal Development and Disorders
Canadian institutionsUniversity of British Columbia
FundersScience and Engineering Research BoardNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsSynaptophysinCholine acetyltransferaseRetinoic acidNeuriteNeurograninGlutamate decarboxylaseCell biologyBiologySH-SY5YTyrosine hydroxylaseChemistryEndocrinologyDopamineBiochemistrySignal transductionCholinergicNeuroblastomaCell cultureEnzymeIn vitro

Abstract

fetched live from OpenAlex

During brain development, neurite formation plays a critical role in neuronal communication and cognitive function. In the present study, we compared developmental changes in the expression of crucial markers that govern the functional activity of neurons, including somatostatin (SST), choline acetyltransferase (ChAT), tyrosine hydroxylase (TH), brain nitric oxide synthase (bNOS), gamma-aminobutyric acid (GABA), glutamic acid decarboxylase (GAD-65) and synaptic vesicle protein synaptophysin (SYP) in non-differentiated and retinoic acid (RA)-induced differentiated SH-SY5Y cells. We further determined the role of SST in regulating subcellular distribution and expression of neurotransmitters. Our results indicate that SST potentiates RA-induced differentiation of SH-SY5Y cells and involves regulating the subcellular distribution and expression of neurotransmitter markers and synaptophysin translocation to neurites in a time-dependent manner, anticipating the therapeutic implication of SST in neurodegeneration.

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 score0.186
Threshold uncertainty score0.391

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 science0.0000.000
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 head0.008
GPT teacher head0.210
Teacher spread0.201 · 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

Citations10
Published2022
Admission routes2
Has abstractyes

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