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Record W2094309691 · doi:10.1038/ncomms5980

Kainate receptor activation induces glycine receptor endocytosis through PKC deSUMOylation

2014· article· en· W2094309691 on OpenAlexaff
Hao Sun, Li Lu, Yong Zuo, Yan Wang, Yingfu Jiao, Wei-Zheng Zeng, Chao Huang, Michael X. Zhu, Gerald W. Zamponi, Tong Zhou, Tian-Le Xu, Jinke Cheng, Yong Li

Bibliographic record

VenueNature Communications · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicUbiquitin and proteasome pathways
Canadian institutionsUniversity of Calgary
FundersNational Key Research and Development Program of ChinaMajor Research PlanNational Natural Science Foundation of China
KeywordsGlycine receptorSUMO proteinKainate receptorCell biologyEndocytosisProtein kinase CBiologyExcitatory postsynaptic potentialInhibitory postsynaptic potentialReceptorNMDA receptorNeuroscienceAMPA receptorBiochemistryGlycineKinaseUbiquitinAmino acid

Abstract

fetched live from OpenAlex

Surface expression and regulated endocytosis of glycine receptors (GlyRs) play a critical function in balancing neuronal excitability. SUMOylation (SUMO modification) is of critical importance for maintaining neuronal function in the central nervous system. Here we show that activation of kainate receptors (KARs) causes GlyR endocytosis in a calcium- and protein kinase C (PKC)-dependent manner, leading to reduced GlyR-mediated synaptic activity in cultured spinal cord neurons and the superficial dorsal horn of rat spinal cord slices. This effect requires SUMO1/sentrin-specific peptidase 1 (SENP1)-mediated deSUMOylation of PKC, indicating that the crosstalk between KARs and GlyRs relies on the SUMOylation status of PKC. SENP1-mediated deSUMOylation of PKC is involved in the kainate-induced GlyR endocytosis and thus plays an important role in the anti-homeostatic regulation between excitatory and inhibitory ligand-gated ion channels. Altogether, we have identified a SUMOylation-dependent regulatory pathway for GlyR endocytosis, which may have important physiological implications for proper neuronal excitability.

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)0.001
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 score0.386
Threshold uncertainty score0.639

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0010.000
Research integrity0.0000.001
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 head0.026
GPT teacher head0.297
Teacher spread0.270 · 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

Citations50
Published2014
Admission routes1
Has abstractyes

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