Evidence map›Paper›PMID 29657506›Full record

ArticleJournal of pharmacy & bioallied sciences

Mayson H Alkhatib, Wafa S Alshehri, Faiza B Abdu

Open access · goldAbstract read
In one paragraph

Article in Journal of pharmacy & bioallied sciences. 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
0.4field-weighted citation impact, top 43% 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, 12 citations in OpenAlex.

  1. Article
  2. Article
  3. Enhanced antitumor efficacy of lapachol-loaded nanoemulsion in breast cancer tumor model.Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie · 2021
    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

3 authors at 1 institution in 1 country.

Mayson H AlkhatibDepartment of Biochemistry, King Abdulaziz University, Jeddah, Saudi Arabia.
Wafa S AlshehriDepartment of Biochemistry, King Abdulaziz University, Jeddah, Saudi Arabia.
Faiza B AbduDepartment of Biological Sciences, King Abdulaziz University, Jeddah, Saudi Arabia.
King Abdulaziz University · SA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

contextDoxorubicin (DOX) and gemcitabine (GEM) are anticancer drugs that were combined in a nanoemulsion (NE) to reduce their adverse side effects.

aimTo detect the antitumor activity of the combination formulas of GEM and DOX, loaded either in water (GEM+DOX-Sol) or in NEs (GEM-DOX combination/loaded NE [GEM+DOX/LNE]), in female Swiss albino mice inoculated with Ehrlich ascites carcinoma (EAC). SETTINGS AND

designThe anticancer assessment of the NE formulas was implemented in 200 mice, which were divided into 10 groups. MATERIALS AND

methodsIt includes the detection of the change in body weight, analysis of the hematological and serum biochemical profiles, and study of the histopathologic alterations of the heart tissues. STATISTICAL ANALYSIS: One-factor analysis of variance was used.

resultsMice treated with GEM + DOX/LNE, which have an z-average of 155.38±2.33nm and zeta potential of -38.5±1.3 mV, recorded a considerable improvement in the mean survival time (MST), which was 60 days, as compared to the EAC control group, which has an MST of 28 days. It also restored the hematological and serum biochemical parameters toward normal values.

conclusionsThe combination of GEM and DOX in NE has significantly diminished the cardiotoxicity of DOX and hematotoxicity of GEM while improving their antitumor properties.

Indexed as

Cardiotoxicitychemotherapeutic agentsmean survival timez-average diameterzeta potential

Identifiers

PMID29657506
PMCPMC5887650
OpenAlexW2791774802

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.