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Protein 600 Is a Microtubule/Endoplasmic Reticulum-Associated Protein in CNS Neurons

2008· article· en· W2023179015 on OpenAlexafffund
Su Yeon Shim, Jian Wang, Naoyuki Asada, Gernot Neumayer, Hong Chi Tran, Kei‐ichiro Ishiguro, Kamon Sanada, Yoshihiro Nakatani, Minh Dang Nguyen

Bibliographic record

VenueJournal of Neuroscience · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEndoplasmic Reticulum Stress and Disease
Canadian institutionsUniversity of Calgary
FundersCanadian Institutes of Health ResearchFondation pour la Recherche MédicaleMinistry of Education, Culture, Sports, Science and Technology
KeywordsEndoplasmic reticulumCell biologyMicrotubuleBiologyNeuriteRNA interferenceCytoskeletonMicrotubule-associated proteinGene silencingGolgi apparatusNeuroscienceCellRNAGenetics

Abstract

fetched live from OpenAlex

There is an increasing body of literature pointing to cytoskeletal proteins as spatial organizers and interactors of organelles. In this study, we identified protein 600 (p600) as a novel microtubule-associated protein (MAP) developmentally regulated in neurons. p600 exhibits the unique feature to interact with the endoplasmic reticulum (ER). Silencing of p600 by RNA interference (RNAi) destabilizes neuronal processes in young primary neurons undergoing neurite extension and containing scarce staining of the ER marker Bip. Furthermore, in utero electroporation of p600 RNAi alters neuronal migration, a process that depends on synergistic actions of microtubule dynamics and ER functions. p600-depleted migrating neurons display thin, crooked, and "zigzag" leading process with very few ER membranes. Thus, p600 constitutes the only known MAP to associate with the ER in neurons, and this interaction may impact on multiple cellular processes ranging from neuronal development to neuronal maturation and plasticity.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.014
GPT teacher head0.242
Teacher spread0.228 · 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 source (direct Gemma or distilled Codex), 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

Citations54
Published2008
Admission routes2
Has abstractyes

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