Evidence map›Paper›PMID 39633071›Full record

ArticleMolecular imaging and biology2025

In Vivo Mouse Abdominal Oxygen Imaging And Assessment of Subcutaneously Implanted Beta Cell Replacement Devices.

Irene Canavesi, Navin Viswakarma, Boris Epel, Mrignayani Kotecha

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Article in Molecular imaging and biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

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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

6 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Accelerated EPR imaging using deep learning denoising.Magnetic resonance in medicine · 2025
    Article
  5. Article
  6. Review
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

4 authors.

Irene CanavesiOxygen Measurement Core, O2M Technologies, Chicago, IL, 60612, USA.
Navin ViswakarmaOxygen Measurement Core, O2M Technologies, Chicago, IL, 60612, USA.
Boris EpelOxygen Measurement Core, O2M Technologies, Chicago, IL, 60612, USA.
Mrignayani KotechaOxygen Measurement Core, O2M Technologies, Chicago, IL, 60612, USA. mk@oxygenimaging.com.ORCID http://orcid.org/0000-0003-2264-0247

Funding

Juvenile Diabetes Research Foundation International 3-SRA-2020-883-M-B
6 · The paper itself

Abstract

purposeType 1 diabetes (T1D) is an autoimmune disease that leads to the loss of insulin-producing pancreatic beta cells. Beta cell replacement devices or bioartificial pancreas (BAP) have shown promise in curing T1D and providing long-term insulin independence without the need for immunosuppressants. Hypoxia in BAP devices damages cells and imposes limitations on device dimensions. Noninvasive in vivo oxygen imaging assessment of implanted BAP devices will provide the necessary feedback and improve the chances of success. Pulse-mode electron paramagnetic resonance (EPR) oxygen imaging (EPROI) using injectable trityl OX071 as the oxygen-sensitive agent is an excellent technique for obtaining partial oxygen pressure (pO

methodsAll EPROI experiments were performed using a 25 mT EPROI instrument, JIVA-25®. For in vivo EPROI experiments, trityl OX071, a whole-body mouse resonator (∅32 mm × 35 mm), C57BL6 mice, and the inversion recovery electron spin echo (IRESE) pulse sequence were utilized. We investigated the signal amplitude and pO

resultsWe established that mouse abdominal pO

conclusionsIn vivo EPROI is a reliable technique for mouse abdominal oxygen imaging and longitudinal assessment of subcutaneously implanted BAP devices noninvasively. This work reports abdominal oxygen imaging in the mouse model and demonstrates its application for the assessment of BAP devices. Even though the application focus of this work was on cell therapy, the techniques developed will have a much broader use in the biomedical field.

Indexed as

AbdomenInsulin-Secreting CellsOxygenAnimalsElectron Spin Resonance SpectroscopyMiceMice, Inbred C57BLOxygenCell transplantation devicesEPR oxygen imagingHypoxiaTissue oxygenationType I diabetes

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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.