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Record W2752602007 · doi:10.1007/s13167-017-0114-6

The BSSG rat model of Parkinson’s disease: progressing towards a valid, predictive model of disease

2017· review· en· W2752602007 on OpenAlexafffund
Jackalina M. Van Kampen, H.A. Robertson

Bibliographic record

VenueThe EPMA Journal · 2017
Typereview
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsDalhousie UniversityUniversity of Prince Edward Island
FundersCanadian Institutes of Health ResearchWeston Brain Institute
KeywordsNeuropathologyNeuroscienceDopaminergicDopamineMPTPParkinson's diseaseNeuroprotectionDiseaseLevodopaMedicineOxidopaminePsychologySubstantia nigraPathology

Abstract

fetched live from OpenAlex

ABSTRACT: Parkinson's disease (PD) is a neurodegenerative disorder, classically considered a movement disorder. A great deal is known about the anatomical connections and neuropathology and pharmacological changes of PD, as they relate to the loss of dopaminergic function and the appearance of cardinal motor symptoms. Our understanding of the role of dopamine in PD has led to the development of effective pharmacological treatments of the motor symptoms in the form of dopamine replacement therapy using levodopa and dopaminergic agonists. Much of the information concerning these drug treatments has been obtained using classical neurotoxic models that mimic dopamine depletion (e.g., 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine or MPTP, 6-hydroxydopamine, reserpine). However, PD is more than a disorder of the nigrostriatal dopamine pathway. Our understanding of the neuropathology of PD has undergone massive changes, with the discovery that mutations in α-synuclein cause a familial form of PD and that PD pathology may spread, affecting multiple neurotransmitter systems and brain regions. These new developments in our understanding of PD demand that we reconsider our animal models. While classic neurotoxin models have been useful for the development of effective symptomatic treatments for motor manifestations, the paucity of a valid animal model exhibiting the progressive development of multiple key features of PD pathophysiology and phenotype has impeded the search for neuroprotective therapies, capable of slowing or halting disease progression. RELEVANCE OF THE ARTICLE FOR PREDICTIVE PREVENTIVE AND PERSONALISED MEDICINE: What characteristics would a good animal model of human PD have? In so much as is possible, a good model would exhibit as many behavioral, anatomical, biochemical, immunological, and pathological changes as are observed in the human condition, developing progressively, with clear, identifiable biomarkers along the way. Here, we review the BSSG rat model of PD, a novel environmental model of PD, with strong construct, face, and predictive validity. This model offers an effective tool for the screening of preventive therapies that may prove to be more predictive of their effects in human patients.

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)0.000
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 score0.984
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.144
GPT teacher head0.390
Teacher spread0.246 · 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

Citations40
Published2017
Admission routes2
Has abstractyes

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