Evidence map›Paper›PMID 36718155›Full record

ArticleHeliyon2023

Reduced volume of diabetic pancreatic islets in rodents detected by synchrotron X-ray phase-contrast microtomography and deep learning network.

Qingqing Guo, Abdulla AlKendi, Xiaoping Jiang, Alberto Mittone, Linbo Wang, Emanuel Larsson, Alberto Bravin, Erik Renström, Xianyong Fang, Enming Zhang

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.3field-weighted citation impact, top 22% 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

3 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
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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

10 authors at 5 institutions in 5 countries.

Qingqing GuoSchool of Computer Science and Technology, Anhui University, Hefei, China.
Abdulla AlKendiIslet Pathophysiology, Department of Clinical Science, Lund University Diabetes Centre, Malmö, Sweden.
Xiaoping JiangIslet Pathophysiology, Department of Clinical Science, Lund University Diabetes Centre, Malmö, Sweden.
Alberto MittoneAdvanced Photon Source, Argonne National Laboratory, Lemont, IL, United States.
Linbo WangSchool of Computer Science and Technology, Anhui University, Hefei, China.
Emanuel LarssonDivision of Solid Mechanics & LUNARC, Department of Construction Sciences, Lund University, Lund, Sweden.
Alberto BravinBiomedical Beamline ID17, European Synchrotron Radiation Facility, Grenoble Cedex, France.
Erik RenströmIslet Pathophysiology, Department of Clinical Science, Lund University Diabetes Centre, Malmö, Sweden.
Xianyong FangSchool of Computer Science and Technology, Anhui University, Hefei, China.
Enming ZhangIslet Pathophysiology, Department of Clinical Science, Lund University Diabetes Centre, Malmö, Sweden.
Lund University · SEAnhui University · CNArgonne National Laboratory · USEuropean Synchrotron Radiation Facility · FRSouthwest University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The pancreatic islet is a highly structured micro-organ that produces insulin in response to rising blood glucose. Here we develop a label-free and automatic imaging approach to visualize the islets

Indexed as

AAM, affinity-aware moduleAA-Net, Affinity-Aware NetworkDeep learningDiabetesPancreatic isletsPCI, phase contrast imagingSF, Shortcut-FreeSRμCT, synchrotron radiation X-ray phase-contrast microtomographySTZ, streptozotocinSynchrotron radiationT1D, type-1 diabetesT2D, type-2 diabetesX-ray microtomographyX-ray phase-contrast

Identifiers

PMID36718155
PMCPMC9883183
OpenAlexW4317470367

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.