A multi-organ atlas of microcirculatory signatures for systemic profiling of diabetic and therapeutic states

Microcirculatory deterioration in diabetes mellitus causes severe organ-specific complications, yet a systemic understanding of its cross-organ pathophysiology remains elusive due to a lack of comprehensive data. To address this gap, we present a high-dimensional dataset mapping microhemodynamic and oxygenation profiles across six organs in murine models of health, pre-diabetes, and type 1 and 2 diabetes. Structured as a third-order tensor, the dataset comprises 10-parameter physio-signatures for each condition, documenting responses to insulin and the GLP-1 receptor agonist liraglutide at one- and two-week endpoints. Our resource enables direct deconvolution of disease- and organ-specific signatures and provides a quantitative platform for comparing therapeutic pharmacodynamics. We propose a vectorial and tensorial analytical framework to dissect systemic patterns, quantify disease perturbation, and identify significant drug-organ interactions. Our foundational dataset is intended to catalyze the development of system-level computational models for managing diabetic microvascular disease.

Authors

Institutions

Publication Details

Journal
Scientific Data
Published
2026-05-12
DOI
https://doi.org/10.1038/s41597-026-07430-w
Primary Topic
3D Printing in Biomedical Research
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A multi-organ atlas of microcirculatory signatures for systemic profiling of diabetic and therapeutic states

Bo Wang, Xi Zhang, Xiang Xu, Weiqi Liu et al.
Scientific Data
3D Printing in Biomedical Research
article

A multi-organ atlas of microcirculatory signatures for systemic profiling of diabetic and therapeutic states

Bo Wang, Xi Zhang, Xiang Xu, Weiqi Liu, Bingwei Li, Yuxing Wang, Yuan Li, Mingming Liu
article en

Abstract

Microcirculatory deterioration in diabetes mellitus causes severe organ-specific complications, yet a systemic understanding of its cross-organ pathophysiology remains elusive due to a lack of comprehensive data. To address this gap, we present a high-dimensional dataset mapping microhemodynamic and oxygenation profiles across six organs in murine models of health, pre-diabetes, and type 1 and 2 diabetes. Structured as a third-order tensor, the dataset comprises 10-parameter physio-signatures for each condition, documenting responses to insulin and the GLP-1 receptor agonist liraglutide at one- and two-week endpoints. Our resource enables direct deconvolution of disease- and organ-specific signatures and provides a quantitative platform for comparing therapeutic pharmacodynamics. We propose a vectorial and tensorial analytical framework to dissect systemic patterns, quantify disease perturbation, and identify significant drug-organ interactions. Our foundational dataset is intended to catalyze the development of system-level computational models for managing diabetic microvascular disease.

Scientific Data
Chinese Academy of Medical Sciences & Peking Union Medical College (CN), Peking University (CN), Peking University First Hospital (CN)
Natural Science Foundation of Beijing Municipality
Good health and well-being
Openalex Percentile: Top 8%
3D Printing in Biomedical Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.