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Record W1480193263 · doi:10.1002/ar.23192

Vagal Fibers Form Associations With Interstitial Cells of Cajal During Fetal Development

2015· article· en· W1480193263 on OpenAlexafffund
Kelly L. Hepworth, Xuan‐yu Wang, Jan D. Huizinga, Elyanne M. Ratcliffe

Bibliographic record

VenueThe Anatomical Record · 2015
Typearticle
Languageen
FieldMedicine
TopicGastrointestinal motility and disorders
Canadian institutionsMcMaster UniversityPopulation Health Research Institute
FundersCanadian Institutes of Health Research
KeywordsInterstitial cell of CajalPrenatal developmentMyenteric plexusFetusFree nerve endingPlexusVagus nerveAnatomyEnteric nervous systemBiologyNeurosciencePathologyMedicineSmooth muscleImmunohistochemistryEndocrinologyStimulationPregnancy

Abstract

fetched live from OpenAlex

Vagal intramuscular arrays (IMAs) have been shown to form complexes with intramuscular interstitial cells of Cajal (ICC). We tested the hypothesis that associations between vagal nerve endings and ICC arise in fetal development. Intraganglionic laminar endings (IGLEs) and IMAs were identified by applying 1,1'-dioctadecyl-3,3,3',3'-tetramethylindocarbocyanineperchlorate (DiI) to vagal nerve trunks and myenteric plexus (MP) and intramuscular (IM) ICC were immunolabeled with antibodies to c-Kit in fetal and early postnatal mice (E16-P7). At E16, c-Kit immunoreactive cells were abundant in the primordial smooth muscle, with early ICC networks discernable by E18 and ongoing organization at P1 and P7. The distribution of vagal endings was found to change during the course of development, with significantly more putative IGLEs in the prenatal compared to the postnatal period and less IMAs in the prenatal compared to postnatal period. Associations of ICC with both IGLEs and IMAs were detected as early as E16 and were maintained into postnatal life. These findings suggest that vagal fibers begin to associate with ICC during prenatal development. Future studies will be needed to determine the mechanisms through which vagal endings and ICC interact.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.243

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 science0.0000.000
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 head0.025
GPT teacher head0.252
Teacher spread0.228 · 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 designObservational
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

Citations2
Published2015
Admission routes2
Has abstractyes

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