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Record W2098858769 · doi:10.1002/bies.201400131

<i>Atlas stumbled</i>: Kinesin light chain‐1 variant E triggers a vicious cycle of axonal transport disruption and amyloid‐β generation in Alzheimer's disease

2014· article· en· W2098858769 on OpenAlexaff
Kathlyn J. Gan, Takashi Morihara, Michael Silverman

Bibliographic record

VenueBioEssays · 2014
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsUniversity of British ColumbiaSimon Fraser University
Fundersnot available
KeywordsNeurodegenerationAxoplasmic transportKinesinAmyloid precursor proteinCell biologyNeuroscienceBiologyAmyloid (mycology)Alzheimer's diseaseDiseaseMedicineMicrotubuleInternal medicine

Abstract

fetched live from OpenAlex

Substantial evidence implicates fast axonal transport (FAT) defects in neurodegeneration. In Alzheimer's disease (AD), it is controversial whether transport defects cause or arise from amyloid-β (Aβ)-induced toxicity. Using a novel, unbiased genetic screen, Morihara et al. identified kinesin light chain-1 splice variant E (KLC1vE) as a modifier of Aβ accumulation. Here, we propose three mechanisms to explain this causal role. First, KLC1vE reduces APP transport, leading to Aβ accumulation. Second, reduced transport of APP by KLC1vE triggers an ER stress response that activates the amyloidogenic pathway. Third, KLC1vE impairs transport of other KLC1 cargos that regulate amyloidogenesis, promoting Aβ retention within the secretory pathway. Collectively, KLC1vE perpetuates a vicious cycle of Aβ generation, kinase dysregulation, and global FAT impairment that inevitably leads to cellular toxicity. These concepts implicate alternative splicing of KLC1 in AD and suggest that the reciprocal influence of transport mechanisms on disease states contributes to neurodegeneration.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.081
Threshold uncertainty score0.722

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 head0.022
GPT teacher head0.280
Teacher spread0.258 · 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

Citations18
Published2014
Admission routes1
Has abstractyes

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