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Record W2123906424 · doi:10.5430/jbgc.v3n2p30

Neurotransmitter visualization in schizophrenia

2013· article· en· W2123906424 on OpenAlexvenueno aff
James Robert Brašić

Bibliographic record

VenueJournal of Biomedical Graphics and Computing · 2013
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neuropharmacology Research
Canadian institutionsnot available
Fundersnot available
KeywordsDopamineDopamine hypothesis of schizophreniaNeuroscienceSchizophrenia (object-oriented programming)NeuroimagingPsychologyDopaminergicPsychosisPsychiatryPopulationMedicine

Abstract

fetched live from OpenAlex

Background: Although the history, interview, and examination of the patient provide the foundation for the diagnosis of schizophrenia, nuclear neuroimaging investigations constitute promising tools to elucidate the pathophysiology of schizophrenia and other neuropsychiatric disorders. Imaging studies of neuroreceptors constitute research tools to investigate the role of dysfunction of the acetylcholinergic, dopaminergic, glutamatergic, serotonergic, cannabinoid, opioid, and nicotinic systems in the pathogenesis and pathophysiology of schizophrenia and related conditions. People with the phenotype of the clinical syndrome of schizophrenia likely represent multiple distinct genotypes with poorly characterized biological traits. Thus, the population of people manifesting the clinical syndrome of schizophrenia likely contains several heterogeneous biological subgroups yet to be specified. The dopamine hypothesis of schizophrenia proposes that the positive symptoms result from an excess of intrasynaptic dopamine, an excitatory neurotransmitter, and the negative symptoms result from a deficit of intrasynaptic dopamine. Accordingly, a group of people with schizophrenia likely have reduced intrasynaptic dopamine in the tonic, resting, basal state, and increased intrasynaptic dopamine in the excited, aroused, phasic state. Additionally, the glutamate hypothesis of schizophrenia suggests that dysfunction of glutamate, another excitatory neurotransmitter, in the prefrontal region results in excessive concentrations of dopamine in the striata resulting in the positive symptoms of schizophrenia. Methodology/Principal Findings: Published research about the nuclear neuroimaging techniques to identify neurotrans- mitters in people with schizophrenia are reviewed. Conclusions/Significance: Future research including neuronuclear imaging and genetic evaluations is needed to characterize the biological subgroups of people with the clinical syndrome of schizophrenia. Neuronuclear imaging studies will likely refine the measurement of neurotransmitters in the presynaptic, synaptic, and postsynaptic regions in people with schizophrenia and healthy people. Imaging studies of neuroreceptors during the administration of putative therapeutic agents for schizophrenia will help determine the optimal dose. In the future the research findings summarized in this article will likely be translated into clinical practice.

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)0.001
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.327
Teacher spread0.296 · 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

Citations2
Published2013
Admission routes1
Has abstractyes

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