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Record W4200180734 · doi:10.1177/10935266211053973

Characterization of the Transition Zone in Short Segment Hirschsprung Disease Using Calretinin Immunostaining

2021· article· en· W4200180734 on OpenAlexaff
Franziska Righini‐Grunder, Dorothée Bouron‐Dal Soglio, Lara Hart, Ann Aspirot, Christophe Fauré, Natacha Patey

Bibliographic record

VenuePediatric and Developmental Pathology · 2021
Typearticle
Languageen
FieldMedicine
TopicCongenital gastrointestinal and neural anomalies
Canadian institutionsMcMaster UniversityCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsCalretininGanglionImmunohistochemistryImmunostainingPathologyH&E stainAnatomySubmucosaWestern blotStainingMedicineHirschsprung's diseaseBiologyDisease

Abstract

fetched live from OpenAlex

Introduction: The detailed expression pattern of calretinin immunohistochemistry in the transition zone (TZ) of Hirschsprung disease (HSCR) has not yet been reported. This study aims to examine the value of calretinin immunohistochemistry for more accurately determining the distal and proximal border of the TZ in short segment HSCR. Methods: Specimens of pull-through surgery from 51 patients with short form of HSCR were analyzed on two longitudinal strips using hematoxylin and eosin (H&E) staining and calretinin immunohistochemistry. Results: In all but two patients, the first appearance of calretinin expression was seen on mucosal nerve fibers before the appearance of any ganglion cells, indicating the distal border of the TZ. The maximum distance between the distal border of the TZ and the proximal border of the TZ, defined by ganglion cells in a normal density on H&E stained sections, a strong calretinin expression on mucosal nerve fibers and in >80% of submucosal and myenteric ganglion cells, with no nerve hypertrophy and absence of ganglionitis was 60 mm. Conclusion: The distal border of the TZ is characterized by calretinin positive intramucosal neurites in nearly all of short form of HSCR and not by calretinin expression on ganglion cells.

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 score0.384
Threshold uncertainty score0.253

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 head0.017
GPT teacher head0.230
Teacher spread0.213 · 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
Published2021
Admission routes1
Has abstractyes

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