MétaCan
Menu
← Back to cohort

Hydrogen Sulphide Influences the Excitability of Neurons in the Paraventricular Nucleus of the Hypothalamus

2012· article· en· W3173142672 on OpenAlexaff
C. Sahara Khademullah, Alastair V. Ferguson

Bibliographic record

VenueThe FASEB Journal · 2012
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience of respiration and sleep
Canadian institutionsQueen's University
Fundersnot available
KeywordsParvocellular cellHypothalamusNucleusChemistryEndocrinologyInternal medicineNeuronNeuroscienceBiologyMedicine

Abstract

fetched live from OpenAlex

Hydrogen sulphide (H2S) has been observed as having a protective role against gastro‐intestinal inflammation. H2S‐catalyzing enzymes are expressed in the paraventricular nucleus of the hypothalamus (PVN). Previous findings suggest that, if stimulated, the PVN can produce inflammatory responses in the GI tract. To understand the effects of H2S in the PVN, we examined the effects of the H2S donor, sodium hydrogen sulphide (NaHS) on the excitability of PVN neurons. Whole‐cell current clamp recordings from rat PVN neurons in slice preparations were performed. Bath application of 50 μM NaHS influenced 90% (9/10) of cells tested within approximately 45s. of administration. 100% of the responsive cells exhibited a hyperpolarizing response (n=9, −15.42 ± 2.55mV). Of these cells, 89% returned to baseline after approximately 15 mins. Four these neurons were identified as parvocellular neurons and 5 were identified as magnocellular neurons, both displayed similar responses to NaHS. These findings shed light on the role that NaHS plays in the PVN to modify the membrane potential of neurons and in turn, may affect the possible pathways associated with the PVN that are involved in inflammatory effects. Support CIHR

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 head0.048
GPT teacher head0.275
Teacher spread0.227 · 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
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueThe FASEB Journal→Same topicNeuroscience of respiration and sleep→French-language works237,207→