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Record W3104370277 · doi:10.1021/acs.biochem.0c00450

Post-Translational Modifications of Platelet-Derived Amyloid Precursor Protein by Coagulation Factor XIII-A*

2020· article· en· W3104370277 on OpenAlexafffund
Woosuk S. Hur, Lih Jiin Juang, Nima Mazinani, Lonna Munro, Wilfred A. Jefferies, Christian J. Kastrup

Bibliographic record

VenueBiochemistry · 2020
Typearticle
Languageen
FieldMedicine
TopicBlood properties and coagulation
Canadian institutionsCanada's Michael Smith Genome Sciences CentreUniversity of British Columbia
FundersBritish Columbia Knowledge Development FundNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchMichael Smith Health Research BCCanada Foundation for InnovationWeston Brain Institute
KeywordsPlateletAmyloid precursor proteinChemistryCoagulationProteasesFactor XIIIPlatelet activationTissue transglutaminaseBiochemistryFibrinCovalent bondNicastrinPlatelet factor 4Cell biologyEnzymeAlzheimer's diseaseFibrinogenImmunologyHeparinBiologyMedicineInternal medicineDisease

Abstract

fetched live from OpenAlex

The physiological function of amyloid β precursor protein (APP) in platelets has remained elusive. Upon platelet activation, APP localizes to the platelet surface and is proteolytically processed by proteases to release various metabolites, including amyloid β (Aβ) and soluble APP. Synthetic Aβ is a substrate of activated coagulation factor XIII (FXIII-A*), a transglutaminase that is active both inside and on the surface of platelets. Here we tested if platelet APP and its fragments are covalently modified by FXIII-A*. Platelet-derived FXIII-A* and fibrin(ogen) bound to APP, and their bound fractions increased 7- and 11-fold upon platelet activation, respectively. The processing of platelet APP was enhanced when FXIII-A* was inhibited. Soluble APPβ was covalently cross-linked by FXIII-A*. This mechanism regulating APP processing is significant, because controlling the processing of APP, such as by inhibiting specific secretases that cleave APP, is a therapeutic target for Alzheimer's disease.

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 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 score0.005
Threshold uncertainty score0.460

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 head0.023
GPT teacher head0.238
Teacher spread0.215 · 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.

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

Citations6
Published2020
Admission routes2
Has abstractyes

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