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Record W4393471979 · doi:10.3389/fcell.2024.1343962

The role of the Pin1-cis P-tau axis in the development and treatment of vascular contribution to cognitive impairment and dementia and preeclampsia

2024· article· en· W4393471979 on OpenAlexafffund
Chenxi Qiu, Zhixiong Li, David A. Leigh, Bingbing Duan, Joseph E. Stucky, Na‐Mi Kim, George Xie, Kun Ping Lu, Xiao Zhen Zhou

Bibliographic record

VenueFrontiers in Cell and Developmental Biology · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSignaling Pathways in Disease
Canadian institutionsLawson Health Research InstituteWestern University
FundersCanadian Institutes of Health Research
KeywordsTauopathyPIN1NeurodegenerationDementiaNeuroscienceDiseaseVascular dementiaMedicineFrontotemporal dementiaCognitionPsychologyBioinformaticsInternal medicineBiologyGenetics

Abstract

fetched live from OpenAlex

Tauopathies are neurodegenerative diseases characterized by deposits of abnormal Tau protein in the brain. Conventional tauopathies are often defined by a limited number of Tau epitopes, notably neurofibrillary tangles, but emerging evidence suggests structural heterogeneity among tauopathies. The prolyl isomerase Pin1 isomerizes cis P-tau to inhibit the development of oligomers, tangles and neurodegeneration in multiple neurodegenerative diseases such as Alzheimer’s disease, traumatic brain injury, vascular contribution to cognitive impairment and dementia (VCID) and preeclampsia (PE). Thus, cis P-tau has emerged as an early etiological driver, blood marker and therapeutic target for multiple neurodegenerative diseases, with clinical trials ongoing. The discovery of cis P-tau and other tau pathologies in VCID and PE calls attention for simplistic classification of tauopathy in neurodegenerative diseases. These recent advances have revealed the exciting novel role of the Pin1- cis P-tau axis in the development and treatment of vascular contribution to cognitive impairment and dementia and preeclampsia.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.620
Threshold uncertainty score0.291

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 head0.005
GPT teacher head0.213
Teacher spread0.208 · 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 designObservational
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

Citations5
Published2024
Admission routes2
Has abstractyes

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