Evidence map›Paper›PMID 32550189›Full record

ArticleJournal of diabetes and metabolic disorders2020

Trisected pancreas model for testing tissue dissociation enzyme combinations: a novel methodology for improving human islet yield for clinical islet transplantation.

Gopalakrishnan Loganathan, Subhashree Venugopal, Appakalai N Balamurugan

Erratum issuedOpen access · greenAbstract read
In one paragraph

Article in Journal of diabetes and metabolic disorders, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. 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, top 94% of its field
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, 0 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors at 3 institutions in 2 countries.

Gopalakrishnan LoganathanDepartment of Surgery, Clinical islet cell laboratory, Cardiovascular Innovation Institute, University of Louisville, Louisville, KY USA.
Subhashree VenugopalSchool of Biosciences and Technology, Vellore Institute of Technology, Vellore, India.
Appakalai N BalamuruganDepartment of Surgery, Clinical islet cell laboratory, Cardiovascular Innovation Institute, University of Louisville, Louisville, KY USA.
Cardiovascular Innovation Institute · USUniversity of Louisville · USVellore Institute of Technology University · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeHuman islet isolation requires a defined collagenase-protease enzyme combination for obtaining a successful islet yield. While different islet laboratories use different enzyme combinations, a systematic methodology to identify optimal enzyme combinations and their concentrations within a single donor pancreas has not been tested. In this study, we designed a trisected pancreas model to test efficacy of three clinical grade enzyme blends (VitaCyte, Roche, SERVA) within a single pancreas.

methodsIslet isolations were performed using brain-dead donor pancreases (

resultsUtilizing the trisected model, we identified that the collagenase dose from three different vendors did not affect the pancreas digestion and islet yield, but islet morphology after isolation with the neutral protease and BP-protease was better than thermolysin. In addition, the head lobe yielded a lower islet mass and higher tissue volume compared to other two lobes, irrespective of enzyme combination used.

conclusionsThis study demonstrates that the trisected model is a promising methodology in assessing donor and isolation associated parameters. Based on this study, we conclude that the donor characteristics and an optimal enzyme dose play a critical role in achieving higher islet yields.

Indexed as

BP-proteaseCollagenaseIslet isolationIslet transplantationNeutral proteaseThermolysinTrisected pancreas model

Identifiers

PMID32550189
PMCPMC7271336
OpenAlexW3017357686

What OpenQuestion holds

Textmetadata
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Registered trials

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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.