Evidence map›Paper›PMID 32218241›Full record

ArticleMaterials (Basel, Switzerland)2020

Microfluidic-Assisted Preparation of 5-Fluorouracil-Loaded PLGA Nanoparticles as a Potential System for Colorectal Cancer Therapy.

Mahtab Ghasemi Toudeshkchouei, Payam Zahedi, Amin Shavandi

Abstract read
In one paragraph

Article in Materials (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Mechanisms and Strategies to Overcome Drug Resistance in Colorectal Cancer.International journal of molecular sciences · 2025
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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.

Mahtab Ghasemi ToudeshkchoueiDepartment of Polymer, School of Chemical Engineering, College of Engineering, University of Tehran, P. O. Box: 11155-4563, Tehran 1417613131, Iran.
Payam ZahediDepartment of Polymer, School of Chemical Engineering, College of Engineering, University of Tehran, P. O. Box: 11155-4563, Tehran 1417613131, Iran.ORCID 0000-0001-6636-4534
Amin ShavandiBioMatter Unit-Biomass Transformation Lab (BTL), École Interfacultaire de Bioingénieurs (EIB), École Polytechnique de Bruxelles, Université Libre de Bruxelles, Avenue F.D. Roosevelt, 50-CP 165/61, 1050 Brussels, Belgium.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This work aims at fabricating 5-fluorouracil (5-FU)-loaded poly (lactic-co-glycolic) acid nanoparticles (PLGA NPs) using a microfluidic (MF) technique, with potential for use in colorectal cancer therapy. In order to achieve 5-FU-loaded NPs with an average diameter of approximately 119 nm, the parameters of MF process with fork-shaped patterns were adjusted as follows: the ratio of polymer to drug solutions flow rates was equal to 10 and the solution concentrations of PLGA as carrier, 5-FU as anti-cancer drug and poly (vinyl alcohol) (PVA) as surfactant were 0.2 (% w/v), 0.01 (% w/v) and 0.15 (% w/v), respectively. In this way, a drug encapsulation efficiency of approximately 95% into the PLGA NPs was obtained, due to the formation of a hydrodynamic flow focusing phenomenon through the MF chip. A performance evaluation of the NP samples in terms of the drug release, cytotoxicity and cell death was carried out. Finally, by analyzing the results after induction of cell death and 4', 6-diamidino-2-phenylin-dole (DAPI) staining, MF-fabricated NPs containing 5-FU [0.2 (% w/v) of PLGA] revealed the dead cell amounts of 10 and 1.5-fold higher than the control sample for Caco2 and SW-480, respectively.

Indexed as

Caco2cell deathfluorouracilmicrofluidicsnanoparticlePLGA

Identifiers

PMID32218241
PMCPMC7177286

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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.