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Dephosphorylation Targeting Chimaera (DEPTAC): Targeting Tau Proteinsin Tauopathies

2022· article· en· W4281263045 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCurrent Protein and Peptide Science · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Degradation and Inhibitors
Canadian institutionsMcGill UniversityMontreal Neurological Institute and Hospital
Fundersnot available
KeywordsNeurodegenerationDephosphorylationTau proteinCell biologyTauopathyNeurosciencePhosphorylationChimera (genetics)ChemistryBiologyPhosphataseBiochemistryAlzheimer's diseaseMedicinePathology

Abstract

fetched live from OpenAlex

One salient hallmark of neurodegeneration is the accumulation of toxic protein aggregates in neuronal cells. This proteotoxicity culminates in the deterioration of neuronal function. In AD and related tauopathies, the microtubule-associated protein tau becomes hyperphosphorylated. Hyperphosphorylated tau forms neurofibrillary tangles (NFTs) within neurons, which constitute a unique feature of tauopathies, including AD. A recent study has exploited a novel molecular strategy to counteract hyperphosphorylated tau and enhance its degradation. Analogous to the PROTAC methodology, a novel dephosphorylation targeting chimera (DEPTAC) was designed to promote the molecular interaction between tau and phosphatase, which, in turn, augments its degradation. Herein, we briefly discuss this novel finding and its potential therapeutic implications.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
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 score0.197
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.010
GPT teacher head0.251
Teacher spread0.241 · 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