Evidence map›Paper›PMID 28751653›Full record

ArticleScientific reports2017

Biochemical profiling of diabetes disease progression by multivariate vibrational microspectroscopy of the pancreas.

Christoffer Nord, Maria Eriksson, Andrea Dicker, Anna Eriksson, Eivind Grong, Erwin Ilegems, Ronald Mårvik, Bård Kulseng, Per-Olof Berggren, András Gorzsás and 1 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
1.8field-weighted citation impact, top 12% 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

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Review
  4. Review
  5. Article
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

11 authors at 4 institutions in 2 countries.

Christoffer NordUmeå Centre for Molecular Medicine, Umeå University, Umeå, Sweden.
Maria ErikssonUmeå Centre for Molecular Medicine, Umeå University, Umeå, Sweden.
Andrea DickerThe Rolf Luft Research Center for Diabetes and Endocrinology, Karolinska Institutet, Stockholm, Sweden.
Anna ErikssonUmeå Centre for Molecular Medicine, Umeå University, Umeå, Sweden.
Eivind GrongCentre for Obesity, Department of Surgery, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway.
Erwin IlegemsThe Rolf Luft Research Center for Diabetes and Endocrinology, Karolinska Institutet, Stockholm, Sweden.
Ronald MårvikCentre for Obesity, Department of Surgery, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway.
Bård KulsengCentre for Obesity, Department of Surgery, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway.
Per-Olof BerggrenThe Rolf Luft Research Center for Diabetes and Endocrinology, Karolinska Institutet, Stockholm, Sweden.
András GorzsásDepartment of Chemistry, Umeå University, Umeå, Sweden.
Ulf AhlgrenUmeå Centre for Molecular Medicine, Umeå University, Umeå, Sweden. Ulf.Ahlgren@umu.se.
Umeå University · SEKarolinska Institutet · SESt Olav's University Hospital · NONorwegian University of Science and Technology · NO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite the dramatic increase in the prevalence of diabetes, techniques for in situ studies of the underlying pancreatic biochemistry are lacking. Such methods would facilitate obtaining mechanistic understanding of diabetes pathophysiology and aid in prognostic and/or diagnostic assessments. In this report we demonstrate how a multivariate imaging approach (orthogonal projections to latent structures - discriminant analysis) can be applied to generate full vibrational microspectroscopic profiles of pancreatic tissues. These profiles enable extraction of known and previously unrecorded biochemical alterations in models of diabetes, and allow for classification of the investigated tissue with regards to tissue type, strain and stage of disease progression. Most significantly, the approach provided evidence for dramatic alterations of the pancreatic biochemistry at the initial onset of immune-infiltration in the Non Obese Diabetic model for type 1 diabetes. Further, it enabled detection of a previously undocumented accumulation of collagen fibrils in the leptin deficient ob/ob mouse islets. By generating high quality spectral profiles through the tissue capsule of hydrated human pancreata and by in vivo Raman imaging of pancreatic islets transplanted to the anterior chamber of the eye, we provide critical feasibility studies for the translation of this technique to diagnostic assessments of pancreatic biochemistry in vivo.

Indexed as

AnimalsDiabetes Mellitus, Type 1Disease Models, AnimalDisease ProgressionFemaleHumansLeptinMiceMice, Inbred C57BLMice, Mutant StrainsPancreasSpectrum AnalysisLeptin

Identifiers

PMID28751653
PMCPMC5532280
OpenAlexW2739446947

What OpenQuestion holds

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LicenceCC BY
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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.