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Record W4211191701 · doi:10.3410/f.717970786.793469274

Faculty Opinions recommendation of Age-dependent microRNA control of synaptic plasticity in 22q11 deletion syndrome and schizophrenia.

2013· dataset· en· W4211191701 on OpenAlexaff
Alan Fine

Bibliographic record

VenueFaculty Opinions – Post-Publication Peer Review of the Biomedical Literature · 2013
Typedataset
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCongenital heart defects research
Canadian institutionsDalhousie University
Fundersnot available
KeywordsHaploinsufficiencyLong-term potentiationSchizophrenia (object-oriented programming)Synaptic plasticityEndoplasmic reticulummicroRNANeuroscienceHippocampal formationBiologyDISC1Cell biologyPsychologyGeneticsPsychiatryGenePhenotype

Abstract

fetched live from OpenAlex

The 22q11 deletion syndrome (22q11DS) is characterized by multiple physical and psychiatric abnormalities and is caused by the hemizygous deletion of a 1.5-3 Mb region of chromosome 22. It constitutes one of the strongest known genetic risks for schizophrenia; schizophrenia arises in as many as 30% of patients with 22q11DS during adolescence or early adulthood. A mouse model of 22q11DS displays an age-dependent increase in hippocampal long-term potentiation (LTP), a form of synaptic plasticity underlying learning and memory. The sarco(endo)plasmic reticulum Ca(2+) ATPase (SERCA2), which is responsible for loading Ca(2+) into the endoplasmic reticulum (ER), is elevated in this mouse model. The resulting increase in ER Ca(2+) load leads to enhanced neurotransmitter release and increased LTP. However, the mechanism by which the 22q11 microdeletion leads to SERCA2 overexpression and LTP increase has not been determined. Screening of multiple mutant mouse lines revealed that haploinsufficiency of Dgcr8, a microRNA (miRNA) biogenesis gene in the 22q11DS disease-critical region, causes age-dependent, synaptic SERCA2 overexpression and increased LTP. We found that miR-25 and miR-185, regulators of SERCA2, are depleted in mouse models of 22q11DS. Restoration of these miRNAs to presynaptic neurons rescues LTP in Dgcr8(+/-) mice. Finally, we show that SERCA2 is elevated in the brains of patients with schizophrenia, providing a link between mouse model findings and the human disease. We conclude that miRNA-dependent SERCA2 dysregulation is a pathogenic event in 22q11DS and schizophrenia. PMID: 23055483 Funding information This work was supported by: NIMH NIH HHS, United States Grant ID: R01 MH095810 NIMH NIH HHS, United States Grant ID: R24 MH068855 NIMH NIH HHS, United States Grant ID: R01MH095810 NIMH NIH HHS, United States Grant ID: R01 MH079079 NIMH NIH HHS, United States Grant ID: R01MH079079 NIMH NIH HHS, United States Grant ID: R24MH068855 NCI NIH HHS, United States Grant ID: R25 CA023944 NCI NIH HHS, United States Grant ID: 5R25CA023944 More Less keyboard_arrow_down

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.318
Threshold uncertainty score0.972

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0060.003
Insufficient payload (model declined to judge)0.3180.178

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 head0.020
GPT teacher head0.323
Teacher spread0.303 · 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.

Study designNot applicable
Domainnot available
GenreDataset

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

Citations0
Published2013
Admission routes1
Has abstractyes

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