Evidence map›Paper›PMID 26204522›Full record

ArticlePhysical chemistry chemical physics : PCCP2015

Mass partitioning effects in diffusion transport.

Milos Kojic, Miljan Milosevic, Suhong Wu, Elvin Blanco, Mauro Ferrari, Arturas Ziemys

Abstract read
In one paragraph

Article in Physical chemistry chemical physics : PCCP, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. A modeling platform for the lymphatic system.Journal of theoretical biology · 2020
    Article
  4. Article
  5. Article
  6. Article
  7. Article
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

6 authors.

Milos KojicHouston Methodist Research Institute, 6670 Bertner Ave., R7-116, Houston, TX 77030, USA. aziemys@houstonmethodist.org.
Miljan Milosevic
Suhong Wu
Elvin Blanco
Mauro Ferrari
Arturas Ziemys

Funding

Texas Center for Cancer NanomedicineU54CA151668 · NCI · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI FERRARI, MAURO · 2010 to 2014
$12.4M
TRANS-NETWORK PROJECTSU54CA143837 · NCI · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI FERRARI, MAURO · 2009 to 2014
$10.8M
NCI NIH HHS U54 CA143837NCI NIH HHS U54CA143837NCI NIH HHS U54 CA151668NCI NIH HHS U54CA151668
6 · The paper itself

Abstract

Frequent mass exchange takes place in a heterogeneous environment among several phases, where mass partitioning may occur at the interface of phases. Analytical and computational methods for diffusion do not usually incorporate molecule partitioning masking the true picture of mass transport. Here we present a computational finite element methodology to calculate diffusion mass transport with a partitioning phenomenon included and the analysis of the effects of partitioning. Our numerical results showed that partitioning controls equilibrated mass distribution as expected from analytical solutions. The experimental validation of mass release from drug-loaded nanoparticles showed that partitioning might even dominate in some cases with respect to diffusion itself. The analysis of diffusion kinetics in the parameter space of partitioning and diffusivity showed that partitioning is an extremely important parameter in systems, where mass diffusivity is fast and that the concentration of nanoparticles can control payload retention inside nanoparticles. The computational and experimental results suggest that partitioning and physiochemical properties of phases play an important, if not crucial, role in diffusion transport and should be included in the studies of mass transport processes.

Indexed as

Molecular Dynamics SimulationDiffusionMolecular StructureNanoparticles

Identifiers

PMID26204522
PMCPMC4527522

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.