Evidence map›Paper›PMID 37658187›Full record

ArticleScientific reports2023

Computational immunohistochemical mapping adds immune context to histological phenotypes in mouse models of colitis.

Soma Kobayashi, Christopher Sullivan, Agnieszka B Bialkowska, Joel H Saltz, Vincent W Yang

Abstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Soma KobayashiDepartment of Biomedical Informatics, Renaissance School of Medicine at Stony, Brook University, Stony Brook, NY, USA.
Christopher SullivanDepartment of Medicine, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, USA.
Agnieszka B BialkowskaDepartment of Medicine, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, USA.
Joel H SaltzDepartment of Biomedical Informatics, Renaissance School of Medicine at Stony, Brook University, Stony Brook, NY, USA.
Vincent W YangDepartment of Biomedical Informatics, Renaissance School of Medicine at Stony, Brook University, Stony Brook, NY, USA. Vincent.Yang@stonybrookmedicine.edu.

Funding

REGULATION OF INTESTINAL EPITHELIAL CELL PROLIFERATIONR01DK052230 · NIDDK · STATE UNIVERSITY NEW YORK STONY BROOK · PI Vincent W Yang · 1997 to 2026
$8.7M
NIDDK NIH HHS R01 DK052230
6 · The paper itself

Abstract

Inflammatory bowel disease (IBD) is characterized by chronic, dysregulated inflammation in the gastrointestinal tract. The heterogeneity of IBD is reflected through two major subtypes, Crohn's Disease (CD) and Ulcerative Colitis (UC). CD and UC differ across symptomatic presentation, histology, immune responses, and treatment. While colitis mouse models have been influential in deciphering IBD pathogenesis, no single model captures the full heterogeneity of clinical disease. The translational capacity of mouse models may be augmented by shifting to multi-mouse model studies that aggregate analysis across various well-controlled phenotypes. Here, we evaluate the value of histology in multi-mouse model characterizations by building upon a previous pipeline that detects histological disease classes in hematoxylin and eosin (H&E)-stained murine colons. Specifically, we map immune marker positivity across serially-sectioned slides to H&E histological classes across the dextran sodium sulfate (DSS) chemical induction model and the intestinal epithelium-specific, inducible Villin-CreER

Indexed as

ColitisColitis, UlcerativeCrohn DiseaseInflammatory Bowel DiseasesAnimalsDisease Models, AnimalInflammationMicePhenotype

Identifiers

PMID37658187
PMCPMC10474139

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.