ArticleIntravital2016
An intravital microscopy model to study early pancreatic inflammation in type 1 diabetes in NOD mice.
Article in Intravital, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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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.
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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.
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Who cites it
2 citing papers in PubMed, 2 citations in OpenAlex.
- Real-Time Imaging of Immune Modulation by Cannabinoids Using Intravital Fluorescence Microscopy.Cannabis and cannabinoid research · 2021Review
- Real-time, high-resolution imaging of tumor cells in genetically engineered and orthotopic models of thyroid cancer.Endocrine-related cancer · 2020Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Intravital microscopy (IVM) of the pancreas has been proven to be an invaluable tool in pancreatitis, transplantation and ischemia/reperfusion research. Also in type 1 diabetes (T1D) pancreatic IVM offers unique advantages for the elucidation of the disease process. Female non-obese diabetic (NOD) mice develop T1D spontaneously by 40 weeks of age. Our goal was to establish an IVM-based method to study early pancreatic inflammation in NOD mice, which can be used to screen novel medications to prevent or delay T1D in future studies. This included evaluation of leukocyte-endothelial interactions as well as disturbances of capillary perfusion in the pancreatic microcirculation.
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Registered trials
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.