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Record W4306855783 · doi:10.1126/sciadv.abm4295

Numb regulates Tau levels and prevents neurodegeneration in tauopathy mouse models

2022· article· en· W4306855783 on OpenAlexaff
Marine Lacomme, Sarah C. Hales, Thomas W. Brown, Katarina Stevanovic, Christine Jolicoeur, Jenny Cai, Thérence Bois, Mélissa Desrosiers, Deniz Dalkara, Michel Cayouette

Bibliographic record

VenueScience Advances · 2022
Typearticle
Languageen
FieldNeuroscience
TopicNerve injury and regeneration
Canadian institutionsMcGill UniversityUniversité de MontréalMontreal Clinical Research Institute
FundersAgence Nationale de la Recherche
KeywordsNUMBTauopathyNeurodegenerationNeuroscienceBiologyCell biologyIntracellularMedicinePathologyDisease

Abstract

fetched live from OpenAlex

Accumulation of the microtubule-associated protein Tau is linked to neuronal cell death in tauopathies, but how intraneuronal Tau levels are regulated in health and disease remains unclear. Here, we show that conditional inactivation of the trafficking adaptor protein Numb in retinal ganglion cells (RGCs) increases Tau levels and leads to axonal blebbing, which is followed by neuronal cell loss in aged mice. In the TauP301S mouse model of tauopathy, conditional inactivation of Numb in RGCs and spinal motoneurons accelerates neurodegeneration, and loss of Numb in motoneurons also leads to precocious hindlimb paralysis. Conversely, overexpression of the long isoform of Numb (Numb-72) decreases intracellular Tau levels and reduces axonal blebbing in TauP301S RGCs, leading to improved electrical activity in cultured neurons and improves performance in a visually guided behavior test in vivo. These results uncover Numb as a key regulator of intracellular Tau levels and identify Numb-72 as a potential therapeutic factor for tauopathies.

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)0.001
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 score0.062
Threshold uncertainty score0.686

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.002
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 head0.037
GPT teacher head0.289
Teacher spread0.252 · 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

Citations17
Published2022
Admission routes1
Has abstractyes

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