Evidence map›Paper›PMID 34349500›Full record

ArticleDrug design, development and therapy2021

Dual-Functional Peptide Driven Liposome Codelivery System for Efficient Treatment of Doxorubicin-Resistant Breast Cancer.

Kamel S Ahmed, Shenhuan Liu, Jing Mao, Jie Zhang, Lipeng Qiu

Open access · goldAbstract read
In one paragraph

Article in Drug design, development and therapy, 2021. 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
1.0field-weighted citation impact, top 27% 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

10 citing papers in PubMed, 20 citations in OpenAlex.

  1. Strategies for Targeting Mitochondria in the Treatment of Breast Cancer.ACS pharmacology & translational science · 2026
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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

5 authors at 2 institutions in 2 countries.

Kamel S Ahmed *School of Pharmaceutical Sciences, Jiangnan University, Wuxi, 214122, Jiangsu, People's Republic of China.ORCID 0000-0003-4333-6324
Shenhuan Liu *School of Pharmaceutical Sciences, Jiangnan University, Wuxi, 214122, Jiangsu, People's Republic of China.
Jing MaoSchool of Pharmaceutical Sciences, Jiangnan University, Wuxi, 214122, Jiangsu, People's Republic of China.
Jie ZhangThe Jiaxing Key Laboratory of Oncological Photodynamic Therapy and the Targeted Drug Research, College of Medicine, Jiaxing University, Jiaxing, Zhejiang, 314001, People's Republic of China.
Lipeng QiuSchool of Pharmaceutical Sciences, Jiangnan University, Wuxi, 214122, Jiangsu, People's Republic of China.ORCID 0000-0001-7546-7420
Jiangnan University · CNJiaxing University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe active-targeted drug delivery systems had attracted more and more attention to efficiently overcome multidrug resistance (MDR) in cancer treatments. The aim of the work was to develop a multifunctional nano-structured liposomal system for co-delivery of doxorubicin hydrochloride (DOX) and celecoxib (CEL) to overcome doxorubicin resistance in breast cancer.

methodsA functional hybrid peptide (MTS-R

resultsDOX/CEL-MTS-R

conclusionThe study suggested that the DOX/CEL-MTS-R

Indexed as

Drug Delivery SystemsATP Binding Cassette Transporter, Subfamily B, Member 1Breast NeoplasmsCelecoxibDoxorubicinDrug LiberationDrug Resistance, NeoplasmDrug StabilityFemaleHumansLiposomesMCF-7 CellsPeptidesReactive Oxygen SpeciesATP Binding Cassette Transporter, Subfamily B, Member 1CelecoxibDoxorubicinLiposomesPeptidesReactive Oxygen Speciescelecoxibco-deliverydoxorubicin hydrochloridemultidrug resistancetargeting liposomes

Identifiers

PMID34349500
PMCPMC8326382
OpenAlexW3184776254

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.