MétaCan
Menu
Back to cohort
Record W4211089092 · doi:10.1186/s40035-022-00284-3

Adenosine A1 receptor ligands bind to α-synuclein: implications for α-synuclein misfolding and α-synucleinopathy in Parkinson’s disease

2022· article· en· W4211089092 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueTranslational Neurodegeneration · 2022
Typearticle
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsUniversity of ReginaUniversity of Saskatchewan
FundersNational Institute of General Medical SciencesNatural Sciences and Engineering Research Council of CanadaNational Institutes of HealthParkinson Society CanadaCanada Foundation for InnovationUniversity of SaskatchewanCanadian Institutes of Health ResearchParkinson CanadaSaskatchewan Health Research FoundationHeart and Stroke Foundation of Canada
KeywordsNeurodegenerationAdenosineSynucleinopathiesAdenosine A1 receptorChemistryAdenosine receptorPharmacologyAgonistParkinson's diseaseAlpha-synucleinReceptorNeuroscienceBiochemistryBiologyInternal medicineMedicine

Abstract

fetched live from OpenAlex

Abstract Background Accumulating α-synuclein (α-syn) aggregates in neurons and glial cells are the staples of many synucleinopathy disorders, such as Parkinson’s disease (PD). Since brain adenosine becomes greatly elevated in ageing brains and chronic adenosine A1 receptor (A1R) stimulation leads to neurodegeneration, we determined whether adenosine or A1R receptor ligands mimic the action of known compounds that promote α-syn aggregation (e.g., the amphetamine analogue 2-aminoindan) or inhibit α-syn aggregation (e.g., Rasagiline metabolite 1-aminoindan). In the present study, we determined whether adenosine, A1R receptor agonist N 6 -Cyclopentyladenosine (CPA) and antagonist 8-cyclopentyl-1,3-dipropylxanthine (DPCPX) could directly interact with α-syn to modulate α-syn aggregation and neurodegeneration of dopaminergic neurons in the substantia nigra (SN). Methods Nanopore analysis and molecular docking were used to test the binding properties of CPA and DPCPX with α-syn in vitro. Sprague–Dawley rats were administered with 7-day intraperitoneal injections of the A1R ligands and 1- and 2-aminoindan, and levels of α-syn aggregation and neurodegeneration were examined in the SN pars compacta and hippocampal regions using confocal imaging and Western blotting. Results Using nanopore analysis, we showed that the A1R agonists (CPA and adenosine) interacted with the N-terminus of α-syn, similar to 2-aminoindan, which is expected to promote a “knot” conformation and α-syn misfolding. In contrast, the A1R antagonist DPCPX interacted with the N- and C-termini of α-syn, similar to 1-aminoindan, which is expected to promote a “loop” conformation that prevents α-syn misfolding. Molecular docking studies revealed that adenosine, CPA and 2-aminoindan interacted with the hydrophobic core of α-syn N-terminus, whereas DPCPX and 1-aminoindan showed direct binding to the N- and C-terminal hydrophobic pockets. Confocal imaging and Western blot analyses revealed that chronic treatments with CPA alone or in combination with 2-aminoindan increased α-syn expression/aggregation and neurodegeneration in both SN pars compacta and hippocampus. In contrast, DPCPX and 1-aminoindan attenuated the CPA-induced α-syn expression/aggregation and neurodegeneration in SN and hippocampus. Conclusions The results indicate that A1R agonists and drugs promoting a “knot” conformation of α-syn can cause α-synucleinopathy and increase neuronal degeneration, whereas A1R antagonists and drugs promoting a “loop” conformation of α-syn can be harnessed for possible neuroprotective therapies to decrease α-synucleinopathy in PD.

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.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.572
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.029
GPT teacher head0.272
Teacher spread0.243 · 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