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Record W2112677777 · doi:10.1126/scisignal.3147pe41

Control of Breathing by “Nerve Glue”

2010· article· en· W2112677777 on OpenAlexafffund
Klaus Ballanyi, Bogdan Panaitescu, Araya Ruangkittisakul

Bibliographic record

VenueScience Signaling · 2010
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience of respiration and sleep
Canadian institutionsUniversity of Alberta
FundersCanadian Institutes of Health Research
KeywordsBrainstemNeuroscienceGlutamate receptorBiologyNeuromodulationControl of respirationElectrophysiologySlice preparationStimulationCell biologyRespiratory systemAnatomyReceptorBiochemistry

Abstract

fetched live from OpenAlex

Long regarded as mere structural support for neurons, neuroglial cells are now considered pivotal for brain metabolism, the blood-brain barrier, cerebral hemodynamics, and neuronal function. Multitasking by glia involves numerous signaling and effector pathways that control various processes, including neurotransmitter uptake and release of gliotransmitters, such as glutamate or adenosine 5'-triphosphate (ATP). Acidosis of cerebrospinal fluid causes ATP release from astrocytic glia at the ventral brainstem surface, which excites neighboring brainstem neurons that stimulate neurons in the pre-Bötzinger complex (preBötC), which controls inspiratory breathing movements. New insights into glial regulation of complex behavior, and particularly into respiratory circuit function, are evolving from application of genetically engineered optical stimulation and Ca(2+) imaging tools, combined with other molecular and electrophysiological approaches. These advances in technology will enable direct analyses of respiratory-related neuron-glia interactions not only at the ventral brainstem surface but also within the preBötC, which generates a vital brain rhythm.

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 score0.002
Threshold uncertainty score0.006

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 communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.018
GPT teacher head0.275
Teacher spread0.257 · 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

Citations16
Published2010
Admission routes2
Has abstractyes

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