MétaCan
Menu
← Back to cohort

Nesfatin‐1 influences the excitability of subfornical organ neurons

2013· article· en· W3167567029 on OpenAlexafffundabout
Markus Kuksis, Li Dai, Alastair V. Ferguson

Bibliographic record

VenueThe FASEB Journal · 2013
Typearticle
Languageen
FieldNeuroscience
TopicRegulation of Appetite and Obesity
Canadian institutionsQueen's University
FundersCanadian Institutes of Health Research
KeywordsSubfornical organDepolarizationThirstMembrane potentialHyperpolarization (physics)EndocrinologyNeuroscienceInternal medicineChemistryOsmoreceptorMedicineBiologyBlood pressure

Abstract

fetched live from OpenAlex

Nesfatin‐1, a centrally acting anorexigenic peptide, is produced in several brain areas involved in metabolic function and has been implicated in appetite and thirst reflexes. The present study was thus undertaken to determine the specific role of nesfatin‐1 in appetite and thirst regulation mediated by the subfornical organ (SFO). We first used RT‐PCR and were able to confirm the presence of nesfatin‐1 in SFO. We then used whole‐cell patch clamp recordings to investigate the influence of nesfatin‐1 on the membrane potential of dissociated SFO neurons. Approximately 68.8% (42 of 61) of neurons tested showed a response to nesfatin‐1 (10 nM and 1 nM). Of the responding neurons, 50% depolarized by a mean depolarization of 10.6 ± 1.64 mV (n=21) and 50% hyperpolarized by a mean hyperpolarization of −8.8 ± 2.2 mV (n=21). No effect was observed at a concentration of 100 pM (n=3). This study has demonstrated that nesfatin‐1 has the ability to change the membrane potential of SFO neurons, and therefore can be identified as a potential modulator of SFO function. Supported by the Canadian Institutes of Health Research

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 head0.031
GPT teacher head0.262
Teacher spread0.232 · 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

Citations0
Published2013
Admission routes3
Has abstractyes

Explore more

Same venueThe FASEB Journal→Same topicRegulation of Appetite and Obesity→French-language works237,207→