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Record W4415535640 · doi:10.1016/j.xpro.2025.104158

Protocol for immunodetection of α-synuclein pathology in paraffin-embedded liver tissues from murine models of Parkinson’s disease

2025· article· en· W4415535640 on OpenAlexaff
Martin Hallbeck, Maria Ntzouni, Martin Ingelsson, Juan F. Reyes

Bibliographic record

VenueSTAR Protocols · 2025
Typearticle
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsUniversity Health Network
FundersÅhlén-stiftelsenVetenskapsrådetSwedish Brain PowerHjärnfondenÅke Wiberg Stiftelse
KeywordsGenetically modified mouseDiseaseImmunohistochemistryExperimental pathologyAntibodyHuman PathologyTransgeneHuman liver

Abstract

fetched live from OpenAlex

The accumulation of α-synuclein (α-Syn) pathology in peripheral tissues of Parkinson’s disease (PD) has attracted growing scientific interest in recent years. Here, we present a protocol for the immunodetection of α-Syn pathology in murine liver tissue from models of PD using fluorescence microscopy. We describe steps for liver isolation, fixation, embedding, and immunodetection using an array of antibodies targeting α-Syn. This approach offers valuable applications for studying PD in transgenic mouse models and could be adapted for human liver tissue. For complete details on the use and execution of this protocol, please refer to Hallbeck et al. 1

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)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: none
Teacher disagreement score0.044
Threshold uncertainty score0.149

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.002
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0440.017

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 head0.044
GPT teacher head0.358
Teacher spread0.314 · 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 designNot applicable
Domainnot available
GenreProtocol

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
Published2025
Admission routes1
Has abstractyes

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