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Record W2418152902 · doi:10.5498/wjp.v5.i3.260

Role of presynaptic phosphoprotein synapsin II in schizophrenia

2015· article· en· W2418152902 on OpenAlexaff
Luke Molinaro, Patricia Hui, Mattea Tan, Ram K. Mishra

Bibliographic record

VenueWorld Journal of Psychiatry · 2015
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neuropharmacology Research
Canadian institutionsMcMaster University
Fundersnot available
KeywordsSynapsinSynapsin ISchizophrenia (object-oriented programming)NeurosciencePrefrontal cortexNeurotransmitterPhosphoproteinPsychiatrySynaptogenesisMedicineBioinformaticsPsychologyBiologyCognitionGeneticsGeneSynaptic vesicleCentral nervous system

Abstract

fetched live from OpenAlex

Synapsin II is a member of the neuronal phosphoprotein family. These phosphoproteins are evolutionarily conserved across many organisms and are important in a variety of synaptic functions, including synaptogenesis and the regulation of neurotransmitter release. A number of genome-wide scans, meta-analyses, and genetic susceptibility studies have implicated the synapsin II gene (3p25) in the etiology of schizophrenia (SZ) and other psychiatric disorders. Further studies have found a reduction of synapsin II mRNA and protein in the prefrontal cortex in post-mortem samples from schizophrenic patients. Disruptions in the expression of this gene may cause synaptic dysfunction, which can result in neurotransmitter imbalances, likely contributing to the pathogenesis of SZ. SZ is a costly, debilitating psychiatric illness affecting approximately 1.1% of the world's population, amounting to 51 million people today. The disorder is characterized by positive (hallucinations, paranoia), negative (social withdrawal, lack of motivation), and cognitive (memory impairments, attention deficits) symptoms. This review provides a comprehensive summary of the structure, function, and involvement of the synapsin family, specifically synapsin II, in the pathophysiology of SZ and possible target for therapeutic intervention/implications.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.020
Threshold uncertainty score0.501

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.031
GPT teacher head0.313
Teacher spread0.282 · 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

Citations17
Published2015
Admission routes1
Has abstractyes

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