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Record W2327922059 · doi:10.1097/pas.0b013e3182035fb6

Immunohistochemical Staining for Smoothelin in the Duplicated Versus the True Muscularis Mucosae of Barrett Esophagus

2010· article· en· W2327922059 on OpenAlexaff
Hala Faragalla, Norman E. Marcon, George M. Yousef, Catherine Streutker

Bibliographic record

VenueThe American Journal of Surgical Pathology · 2010
Typearticle
Languageen
FieldMedicine
TopicEsophageal Cancer Research and Treatment
Canadian institutionsSt. Michael's HospitalUniversity of Toronto
Fundersnot available
KeywordsMuscularis mucosaePathologyImmunohistochemistryLamina propriaEsophagusMedicineStainingCarcinomaBiopsyMuscular layerAnatomyEpithelium

Abstract

fetched live from OpenAlex

BACKGROUND: The muscularis mucosa underlying the metaplastic mucosa of Barrett esophagus is frequently duplicated, with an intervening layer of lamina propria between the superficial or neomuscularis mucosa (NMM) and the deep/true muscularis mucosa (TMM). This duplication causes difficulties with accurate staging of superficially invasive carcinoma in biopsy specimens and endoscopic mucosal resections (EMRs), as invasion underneath the superficial muscle layers may be mistaken for submucosal invasion. Mucosal resections or other ablative nonsurgical therapies can be curative in patients with esophageal intramucosal carcinoma, whereas patients with submucosal invasion are recommended for esophagectomy. Therefore, the accurate staging of such specimens is crucial. Smoothelin is a novel smooth muscle protein expressed only by fully differentiated smooth muscle cells and not by proliferative or noncontractile smooth muscle cells and fibroblasts. It has been suggested that in the bladder, immunohistochemistry for smoothelin may help separate hyperplastic muscularis mucosa from the true muscularis propria. We hypothesized that in the esophagus, immunohistochemistry for smoothelin would differentiate the NMM from the TMM. DESIGN: Thirty cases of EMRs for Barrett esophagus-related neoplasia were retrieved from the archives of the pathology department, St Michael's Hospital. Immunohistochemical staining for smoothelin was performed to evaluate differential staining in the TMM versus NMM. Fifteen cases were stained for smooth muscle actin and smooth muscle myosin. The staining score was evaluated on a scale from 0 to 3 according to the percentage and intensity of staining. RESULTS: Immunohistochemical staining results for smoothelin were as follows: the NMM showed weak focal staining (+1) in 23 of 30 cases (82%), and moderate staining (+2) in 7 of 30 cases (12%), and the TMM showed very strong and diffuse staining (+3) in 30 of 30 cases. No cases showed negative (0) staining in the NMM. With smooth muscle actin and myosin, strong and diffuse staining was observed with similar intensity in both the TMM and NMM in 15 of 15 cases. CONCLUSIONS: In our study, smoothelin staining in the NMM is significantly weaker than that seen in the true/deep muscularis mucosa. This pattern is similar to that reported for the muscularis mucosae of the urinary bladder. Although smoothelin can readily distinguish the 2 layers, its value might be limited by the need to simultaneously compare the 2 layers. Although this might be of use in EMR specimens in which both layers are visible, use in biopsies may be limited as the residual staining in the NMM may inhibit definitive evaluation. This issue may be resolved by the use of appropriate standard controls, individual optimization of the antibody, and the use of an automated digital assessment.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.020
GPT teacher head0.344
Teacher spread0.324 · 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 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

Citations9
Published2010
Admission routes1
Has abstractyes

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