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Record W2110958561 · doi:10.3389/fneur.2014.00049

Maladaptive Plasticity in Levodopa-Induced Dyskinesias and Tardive Dyskinesias: Old and New Insights on the Effects of Dopamine Receptor Pharmacology

2014· review· en· W2110958561 on OpenAlexaff
Antonio Cerasa, Alfonso Fasano, Francesca Morgante, Giacomo Koch, Aldo Quattrone

Bibliographic record

VenueFrontiers in Neurology · 2014
Typereview
Languageen
FieldMedicine
TopicNeurological disorders and treatments
Canadian institutionsToronto Western HospitalUniversity Health NetworkUniversity of Toronto
Fundersnot available
KeywordsDopamineNeuroscienceTardive dyskinesiaLevodopaDopamine receptor D2Dopamine receptorPharmacologyPsychologyDopamine receptor D3MedicinePsychiatrySchizophrenia (object-oriented programming)Internal medicineParkinson's diseaseDisease

Abstract

fetched live from OpenAlex

Maladaptive plasticity can be defined as behavioral loss or even development of disease symptoms resulting from aberrant plasticity changes in the human brain. Hyperkinetic movement disorders, in the neurological or psychiatric realms, have been associated with maladaptive neural plasticity that can be expressed by functional changes such as an increase in transmitter release, receptor regulation, and synaptic plasticity or anatomical modifications such as axonal regeneration, sprouting, synaptogenesis, and neurogenesis. Recent evidence from human and animal models provided support to the hypothesis that these phenomena likely depend on altered dopamine turnover induced by long-term drug treatment. However, it is still unclear how and where these altered mechanisms of cortical plasticity may be localized. This study provides an up-to-date overview of these issues together with some reflections on future studies in the field, particularly focusing on two specific disorders (levodopa-induced dyskinesias in Parkinson's disease patients and tardive dyskinesias in schizophrenic patients) where the modern neuroimaging approaches have recently provided new fundamental insights.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.902
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.027
GPT teacher head0.283
Teacher spread0.256 · 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.

Study designOther design
Domainnot available
GenreReview

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

Citations45
Published2014
Admission routes1
Has abstractyes

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