ArticlePLoS computational biology2016
Modeling of Kidney Hemodynamics: Probability-Based Topology of an Arterial Network.
Article in PLoS computational biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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.
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.
Who cites it
15 citing papers in PubMed.
- The nephron arterial network and its interactions: nonlinear and information theoretic analyses.Frontiers in network physiology · 2026Article
- Assessment, molecular mechanisms and therapeutic targets for renal functional reserve.Renal failure · 2025Review
- Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.Npj imaging · 2025Article
- Response of the Nephron Arterial Network and Its Interactions to Acute Hypertension: A Simulation.Function (Oxford, England) · 2025Article
- High-Speed Clearing and High-Resolution Staining for Analysis of Various Markers for Neurons and Vessels.Tissue engineering and regenerative medicine · 2024Article
- Mapping the blood vasculature in an intact human kidney using hierarchical phase-contrast tomography.bioRxiv : the preprint server for biology · 2024Article
- Resting-state MRI reveals spontaneous physiological fluctuations in the kidney and tracks diabetic nephropathy in rats.American journal of physiology. Renal physiology · 2024Article
- A hybrid approach to full-scale reconstruction of renal arterial network.Scientific reports · 2023Article
- Interacting information streams on the nephron arterial network.Frontiers in network physiology · 2023Article
- Synchronization in renal microcirculation unveiled with high-resolution blood flow imaging.eLife · 2022Article
- Parallel generation of extensive vascular networks with application to an archetypal human kidney model.Royal Society open science · 2021Article
- An in silico validation framework for quantitative DCE-MRI techniques based on a dynamic digital phantom.Medical image analysis · 2021Article
- Article
- Vessel network extraction and analysis of mouse pulmonary vasculature via X-ray micro-computed tomographic imaging.PLoS computational biology · 2021Article
- Architecture of the rat nephron-arterial network: analysis with micro-computed tomography.American journal of physiology. Renal physiology · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Through regulation of the extracellular fluid volume, the kidneys provide important long-term regulation of blood pressure. At the level of the individual functional unit (the nephron), pressure and flow control involves two different mechanisms that both produce oscillations. The nephrons are arranged in a complex branching structure that delivers blood to each nephron and, at the same time, provides a basis for an interaction between adjacent nephrons. The functional consequences of this interaction are not understood, and at present it is not possible to address this question experimentally. We provide experimental data and a new modeling approach to clarify this problem. To resolve details of microvascular structure, we collected 3D data from more than 150 afferent arterioles in an optically cleared rat kidney. Using these results together with published micro-computed tomography (μCT) data we develop an algorithm for generating the renal arterial network. We then introduce a mathematical model describing blood flow dynamics and nephron to nephron interaction in the network. The model includes an implementation of electrical signal propagation along a vascular wall. Simulation results show that the renal arterial architecture plays an important role in maintaining adequate pressure levels and the self-sustained dynamics of nephrons.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.