Evidence map›Paper›PMID 36925576›Full record

ReviewFrontiers in network physiology2021

A Graph-Based Framework for Multiscale Modeling of Physiological Transport.

M Deepa Maheshvare, Soumyendu Raha, Debnath Pal

Open access · goldFull text readReview
In one paragraph

Review in Frontiers in network physiology, 2021. 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
0.7field-weighted citation impact, top 32% 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, 5 citations in OpenAlex.

  1. Article
  2. Simulation and Modeling of the Adhesion ofPathogens (Basel, Switzerland) · 2024
    Article
  3. Review
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

3 authors at 1 institution in 1 country.

M Deepa MaheshvareDepartment of Computational and Data Sciences, Indian Institute of Science, Bangalore, India.
Soumyendu RahaDepartment of Computational and Data Sciences, Indian Institute of Science, Bangalore, India.
Debnath PalDepartment of Computational and Data Sciences, Indian Institute of Science, Bangalore, India.
Indian Institute of Science Bangalore · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Trillions of chemical reactions occur in the human body every second, where the generated products are not only consumed locally but also transported to various locations in a systematic manner to sustain homeostasis. Current solutions to model these biological phenomena are restricted in computability and scalability due to the use of continuum approaches in which it is practically impossible to encapsulate the complexity of the physiological processes occurring at diverse scales. Here, we present a discrete modeling framework defined on an interacting graph that offers the flexibility to model multiscale systems by translating the physical space into a metamodel. We discretize the graph-based metamodel into functional units composed of well-mixed volumes with vascular and cellular subdomains; the operators defined over these volumes define the transport dynamics. We predict glucose drift governed by advective-dispersive transport in the vascular subdomains of an islet vasculature and cross-validate the flow and concentration fields with finite-element-based COMSOL simulations. Vascular and cellular subdomains are coupled to model the nutrient exchange occurring in response to the gradient arising out of reaction and perfusion dynamics. The application of our framework for modeling biologically relevant test systems shows how our approach can assimilate both multi-omics data from

Indexed as

biophysical interactionsdiscrete network modelfunctional networkshierarchical modelingmicrovasculature and microenvironmentsolute transportspatio-temporal dynamicssystems biology

Identifiers

PMID36925576
PMCPMC10013063
OpenAlexW4226321578

What OpenQuestion holds

Textfull text, public
LicenceCC BY
reference markers read1
measurements read24
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.