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Record W7133087432

The Role of Exosomes in Spreading Pathology in Synucleinopathies

2022· dissertation· W7133087432 on OpenAlexfundno aff
Amir Mohammad Hamzeh

Bibliographic record

VenueTSpace · 2022
Typedissertation
Language
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsnot available
FundersCanadian Institutes of Health Research
KeywordsMicrovesiclesSynucleinopathiesDementia with Lewy bodiesAtrophyExtracellular vesiclesExosomeAlpha-synucleinBiomarkerExtracellular
DOInot available

Abstract

fetched live from OpenAlex

Parkinson’s disease, dementia with Lewy bodies and multiple system atrophy are neurodegenerative diseases classified as synucleinopathies due to the accumulation of misfolded and aggregated α-synuclein (α-syn). This misfolded α-syn is implicated in templating the misfolding of additional α-syn in a prion-like manner, contributing to the spread of synuclein pathology between brain regions. A purported mechanism of intercellular α-syn transmission is through small extracellular vesicles called exosomes which are comprised of a lipid bilayer enclosing proteins and nucleic acids. Here, we isolated and characterized exosomes from the brains of synucleinopathy-affected mice and intracerebrally inoculated healthy mice. We demonstrated that exosomes can induce progressive neurological dysfunction which correlates with the accumulation of insoluble and protease resistant α-syn inclusions. Furthermore, we measured peripheral blood α-syn to investigate its potential utility as a biomarker for aberrant α-syn. This work suggests that exosomes can transport α-syn across brain regions contributing to the progression of synucleinopathies.

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)0.000
metaresearch head score (Gemma)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.011
GPT teacher head0.312
Teacher spread0.301 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

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