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Record W4411755358 · doi:10.32388/9acjg4

Synuclein Aggregation: Critical Role of Water in Entropy-Driven, Temperature-Responsive Aggregations of Macromolecules and Cells

2025· preprint· en· W4411755358 on OpenAlexafffund
Donald R. Forsdyke

Bibliographic record

VenueQeios · 2025
Typepreprint
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsQueen's University
FundersQueen's University
KeywordsMacromoleculeEntropy (arrow of time)Statistical physicsBiophysicsChemistryPhysicsThermodynamicsBiologyBiochemistry

Abstract

fetched live from OpenAlex

The change from monomeric α-synuclein to aggregated forms plays a fundamental role in the initiation of Parkinson’s diseases that include its genetic subtypes. The biophysics of the homo-aggregation of whole cells (erythrocyte rouleaux) shares many features of the homo-aggregation of macromolecules such as α-synuclein. Evidence from both reveals that the aggregation pressure is determined as much by concentrations of surrounding macromolecules and water, as that of α-synuclein. Such entropic, rather than enthalmic, considerations predict that aggregation pressures would be less if measures were taken to prevent transient small increases in body temperature.

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 score0.008

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 studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.300
Teacher spread0.289 · 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
Published2025
Admission routes2
Has abstractyes

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