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Record W3094080160 · doi:10.3233/jpd-202221

Treating Parkinson’s Disease with Antibodies: Previous Studies and Future Directions

2020· review· en· W3094080160 on OpenAlexaff
Anne-Marie Castonguay, Claude Gravel, Martin Lévesque

Bibliographic record

VenueJournal of Parkinson s Disease · 2020
Typereview
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsSubstantia nigraAlpha-synucleinDiseaseNeuroscienceParkinson's diseaseDopaminergicSynucleinopathiesBiologyMedicineDopaminePathology

Abstract

fetched live from OpenAlex

Parkinson's disease is a neurodegenerative disorder mainly characterized by the degeneration of dopaminergic neurons in the substantia nigra. Degenerating neurons contain abnormal aggregates called Lewy bodies, that are predominantly composed of the misfolded and/or mutated alpha-synuclein protein. Post-translational modifications, cellular stress, inflammation and gene mutations are thought to trigger its pathological misfolding and aggregation. With alpha-synuclein pathology being strongly associated with dopaminergic neuronal toxicity, strategies aimed to reduce its burden are expected to be beneficial in slowing disease progression. Moreover, multiple sources of evidence suggest a cell-to-cell transmission of pathological alpha-synuclein in a prion-like manner. Therefore, antibodies targeting extra- or intracellular alpha-synuclein could be efficient in limiting the aggregation and transmission. Several active and passive immunization strategies have been explored to target alpha-synuclein. Here, we summarize immunotherapeutic approaches that were tested in pre-clinical or clinical studies in the last two decades in an attempt to treat Parkinson's disease.

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 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 score0.937
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.040
GPT teacher head0.342
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.

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

Citations50
Published2020
Admission routes1
Has abstractyes

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