Evidence map›Paper›PMID 31186597›Full record

ArticleProceedings of SPIE--the International Society for Optical Engineering2019

Examining Structural Patterns and Causality in Diabetic Nephropathy using inter-Glomerular Distance and Bayesian Graphical Models.

Aurijoy Majumdar, Kuang-Yu Jen, Sanjay Jain, John E Tomaszewski, Pinaki Sarder

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

Article in Proceedings of SPIE--the International Society for Optical Engineering, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. 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 98% 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

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

5 authors at 3 institutions in 1 country.

Aurijoy MajumdarDepartments of Pathology and Anatomical Sciences, University at Buffalo.
Kuang-Yu JenDepartments of Pathology, University at California at Davis.
Sanjay JainDepartment of Medicine, Washington University School of Medicine in St. Louis.
John E TomaszewskiDepartments of Pathology and Anatomical Sciences, University at Buffalo.
Pinaki SarderDepartments of Pathology and Anatomical Sciences, University at Buffalo.
University at Buffalo, State University of New York · USUniversity of California, Davis · USWashington University in St. Louis · US

Funding

Coordinating and Bioinformatics Unit for the MMPC/DiaCompU24DK076169 · NIDDK · AUGUSTA UNIVERSITY · PI MCINDOE, RICHARD A. · 2006 to 2018
$42.4M
Computational Imaging of Renal Structures for Diagnosing DiabeticNephropathyR01DK114485 · NIDDK · UNIVERSITY OF FLORIDA · PI Michael Thomas Eadon, Avi Z Rosenberg · 2018 to 2026
$4.7M
NIDDK NIH HHS R01 DK114485NIDDK NIH HHS U24 DK076169
6 · The paper itself

Abstract

In diabetic nephropathy (DN), hyperglycemia drives a progressive thickening of glomerular filtration surfaces, increased cell proliferation as well as mesangial expansion and a constriction of capillary lumens. This leads to progressive structural changes inside the Glomeruli. In this work, we make a study of structural glomerular changes in DN from a graph-theoretic standpoint, using features extracted from Minimal Spanning Trees (MSTs) constructed over intercellular distances in order to classify the "packing signatures" of different DN stages. We further investigate the significance of the competing effects of Volume change measured here in 2Dimensional Pixel span area (Area) on one hand and increased cell proliferation on the other in determining the packing patterns. Towards that we formulate the problem as Dynamic Bayesian Network (DBN). From our preliminary results we do postulate that volume expansion caused by internal pressure as capillary lumens constriction has perhaps has a greater effect in the early stages.

Indexed as

Diabetic nephropathyDynamic Bayesian NetworkGraphical ModelsMedical Image processingMinimum Spanning TreeSupport Vector Machinewhole slide image analysis

Identifiers

PMID31186597
PMCPMC6557453
OpenAlexW2923299823

What OpenQuestion holds

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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.