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Impact of <i>Sim1</i> gene dosage on the development of the paraventricular and supraoptic nuclei of the hypothalamus

2009· article· en· W1519823454 on OpenAlexafffund
Sabine Michaëlle Duplan, Francine Boucher, Lubomir Alexandrov, Jacques L. Michaud

Bibliographic record

VenueEuropean Journal of Neuroscience · 2009
Typearticle
Languageen
FieldPsychology
TopicNeuroendocrine regulation and behavior
Canadian institutionsUniversité de MontréalCentre Hospitalier Universitaire Sainte-Justine
FundersCanadian Institutes of Health Research
KeywordsSupraoptic nucleusHypothalamusVasopressinEndocrinologyInternal medicineOxytocinHomeostasisNucleusNeuropeptideBiologyHaploinsufficiencyChemistryNeuroscienceGeneMedicinePhenotypeReceptorBiochemistry

Abstract

fetched live from OpenAlex

The bHLH-PAS transcription SIM1 is required for the development of all neurons of the paraventricular nucleus (PVN) and supraoptic nucleus (SON) of the hypothalamus. Mice with a loss of Sim1 die within a few days of birth, presumably because of the lack of a PVN and SON. In contrast, mice with a decrease of Sim1 survive, are hyperphagic and become obese. The mechanism by which Sim1 controls food intake remains unclear. Here we show that the development of specific PVN and SON cell types is sensitive to Sim1 gene dosage. Sim1 haploinsufficiency reduces the number of vasopressin (AVP)- and oxytocin-producing cells in the PVN by about 50 and 80%, respectively, but does not affect the development of Crh, Trh and Ss neurons. A decrease of AVP-producing cells increases the sensitivity of Sim1 heterozygous mice to chronic dehydration. Moreover, retrograde labelling showed a 70% reduction of PVN neurons projecting to the dorsal vagal complex, raising the possibility that a decrease of these axons contributes to the hyperphagia of Sim1(+/-) mice. Sim1 haploinsufficiency is thus associated with a decrease of several PVN/SON cell types, which has the potential of affecting distinct homeostatic processes.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.928
Threshold uncertainty score0.192

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 science0.0010.000
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 head0.043
GPT teacher head0.304
Teacher spread0.260 · 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

Citations43
Published2009
Admission routes2
Has abstractyes

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