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Record W4385978374 · doi:10.3390/biom13081263

Alpha-Synuclein in Peripheral Tissues as a Possible Marker for Neurological Diseases and Other Medical Conditions

2023· review· en· W4385978374 on OpenAlexaff
Félix Javier Jiménez‐Jiménez, Hortensia Alonso‐Navarro, Elena García‐Martín, Diego Santos‐García, Iván Martínez-Valbuena, José A. G. Agúndez

Bibliographic record

VenueBiomolecules · 2023
Typereview
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsOccupational Cancer Research CentreUniversity of Toronto
FundersEuropean Regional Development Fund
KeywordsSalivaSynucleinopathiesPathologyCerebrospinal fluidMedicineSalivary glandAlpha-synucleinBiologyParkinson's diseaseDiseaseInternal medicine

Abstract

fetched live from OpenAlex

The possible usefulness of alpha-synuclein (aSyn) determinations in peripheral tissues (blood cells, salivary gland biopsies, olfactory mucosa, digestive tract, skin) and in biological fluids, except for cerebrospinal fluid (serum, plasma, saliva, feces, urine), as a marker of several diseases, has been the subject of numerous publications. This narrative review summarizes data from studies trying to determine the role of total, oligomeric, and phosphorylated aSyn determinations as a marker of various diseases, especially PD and other alpha-synucleinopathies. In summary, the results of studies addressing the determinations of aSyn in its different forms in peripheral tissues (especially in platelets, skin, and digestive tract, but also salivary glands and olfactory mucosa), in combination with other potential biomarkers, could be a useful tool to discriminate PD from controls and from other causes of parkinsonisms, including 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 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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.981
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.058
GPT teacher head0.387
Teacher spread0.330 · 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 designNot applicable
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

Citations29
Published2023
Admission routes1
Has abstractyes

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