Evidence map›Paper›PMID 32679837›Full record

ArticleMolecules (Basel, Switzerland)2020

Synthesis and Antitumor Activity of Doxycycline Polymeric Nanoparticles: Effect on Tumor Apoptosis in Solid Ehrlich Carcinoma.

Ahmed R Gardouh, Mohammed A Attia, Eman T Enan, Alaaeldeen M Elbahaie, Rania A Fouad, Mohamed El-Shafey, Amal M Youssef, Suliman Y Alomar, Zinab Abd-Elhady Ali, Sawsan A Zaitone and 1 more

Open access · goldAbstract read
In one paragraph

Article in Molecules (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
1.3field-weighted citation impact, top 22% 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

13 citing papers in PubMed, 25 citations in OpenAlex.

  1. Review
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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

11 authors at 6 institutions in 3 countries.

Ahmed R GardouhDepartment of Pharmaceutics and Industrial Pharmacy, Faculty of Pharmacy, Suez Canal University, Ismailia 41522, Egypt.ORCID 0000-0002-5387-1614
Mohammed A AttiaDepartment of Clinical Pharmacology, Faculty of Medicine, Mansoura University, Mansoura 35516, Egypt.
Eman T EnanDepartment of Pathology, Faculty of Medicine, Mansoura University, Mansoura 35516, Egypt.ORCID 0000-0001-8425-8946
Alaaeldeen M ElbahaieDepartment of Clinical Oncology and Nuclear Medicine, Faculty of Medicine, Suez Canal University, Ismailia 41522, Egypt.
Rania A FouadMedical Biochemistry Department, Faculty of Medicine, Zagazig University, Zagazig 44519, Egypt.ORCID 0000-0002-6741-1897
Mohamed El-ShafeyPhysiological Sciences Department, Fakeeh College for Medical Sciences, 2537 Jeddah, Saudi Arabia.
Amal M YoussefDepartment of Physiology, Faculty of Medicine, Suez Canal University, Ismailia 41522, Egypt.
Suliman Y AlomarDoping Research Chair, Department of Zoology, College of Science, King Saud University, Riyadh 11495, Saudi Arabia.
Zinab Abd-Elhady AliClinical Skills Lab Department, College of Medicine, Imam Abdulrahman Bin Faisal University, P.O. 1982, Dammam 31441, Saudi Arabia.
Sawsan A ZaitoneDepartment of Pharmacology and Toxicology, Faculty of Pharmacy, Suez Canal University, Ismailia 41522, Egypt.ORCID 0000-0002-9688-7683
Mona K E QushawyDepartment of Pharmaceutics, Faculty of Pharmacy, University of Tabuk, Tabuk 71491, Saudi Arabia.ORCID 0000-0001-8733-1168
Suez Canal University · EGAlfaisal University · SAMansoura University · EGImam Abdulrahman Bin Faisal University · SAKing Saud University · SASinai University · EG

Funding

Almaarefa University, Riyadh, Saudi Arabia Almaarefa University provided financial support of this article
6 · The paper itself

Abstract

objectivesThe aim of this study was to prepare doxycycline polymeric nanoparticles (DOXY-PNPs) with hope to enhance its chemotherapeutic potential against solid Ehrlich carcinoma (SEC).

methodsThree DOXY-PNPs were formulated by nanoprecipitation method using hydroxypropyl methyl cellulose (HPMC) as a polymer. The prepared DOXY-PNPs were evaluated for the encapsulation efficiency (EE%), the drug loading capacity, particle size, zeta potential (ZP) and the in-vitro release for selection of the best formulation. PNP number 3 was selected for further biological testing based on the best pharmaceutical characters. PNP3 (5 and 10 mg/kg) was evaluated for the antitumor potential against SEC grown in female mice by measuring the tumor mass as well as the expression and immunohistochemical staining for the apoptosis markers; caspase 3 and BAX.

resultsThe biological study documented the greatest reduction in tumor mass in mice treated with PNP3. Importantly, treatment with 5 mg/kg of DOXY-PNPs produced a similar chemotherapeutic effect to that produced by 10 mg/kg of free DOXY. Further, a significant elevation in mRNA expression and immunostaining for caspase 3 and BAX was detected in mice group treated with DOXY-PNPs.

conclusionsThe DOXY-PNPs showed greater antitumor potential against SEC grown in mice and greater values for Spearman's correlation coefficients were detected when correlation with tumor mass or apoptosis markers was examined; this is in comparison to free DOXY. Hence, DOXY-PNPs should be tested in other tumor types to further determine the utility of the current technique in preparing chemotherapeutic agents and enhancing their properties.

Indexed as

AnimalsAntineoplastic AgentsCaspase 3DoxycyclineDrug CarriersDrug Delivery SystemsFemaleImmunohistochemistryMiceNanoparticlesParticle SizePolymersStructure-Activity RelationshipAntineoplastic AgentsCaspase 3DoxycyclineDrug CarriersPolymersapoptosisdoxycyclinefemale micehydroxypropyl methyl cellulose (HPMC), polymeric nanoparticlessolid Ehrlich carcinoma

Identifiers

PMID32679837
PMCPMC7396998
OpenAlexW3043179187

What OpenQuestion holds

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LicenceCC BY
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.