Evidence map›Paper›PMID 34992370›Full record

ArticleInternational journal of nanomedicine2021

Folic Acid Decorated Zeolitic Imidazolate Framework (ZIF-8) Loaded with Baicalin as a Nano-Drug Delivery System for Breast Cancer Therapy.

Xiao Mi, Meigeng Hu, Mingran Dong, Zhihong Yang, Xia Zhan, Xinyue Chang, Juan Lu, Xi Chen

Open access · goldAbstract read
In one paragraph

Article in International journal of nanomedicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
62citing papers in PubMed, 1 pooled it
6.3field-weighted citation impact, top 2% 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

62 citing papers in PubMed, 1 synthesis or guideline pooled it, 127 citations in OpenAlex.

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2 more citing papers are in PubMed but not listed here.

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

8 authors at 2 institutions in 1 country.

Xiao MiInstitute of Medicinal Plant Development, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100094, People's Republic of China.
Meigeng HuInstitute of Medicinal Plant Development, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100094, People's Republic of China.
Mingran DongInstitute of Medicinal Plant Development, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100094, People's Republic of China.
Zhihong YangInstitute of Medicinal Plant Development, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100094, People's Republic of China.
Xia ZhanKey Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing, 100048, People's Republic of China.
Xinyue ChangInstitute of Medicinal Plant Development, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100094, People's Republic of China.
Juan LuInstitute of Medicinal Plant Development, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100094, People's Republic of China.
Xi ChenInstitute of Medicinal Plant Development, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100094, People's Republic of China.
Chinese Academy of Medical Sciences & Peking Union Medical College · CNBeijing Technology and Business University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBaicalin (BAN) has attracted widespread attention due to its low-toxicity and efficient antitumor activity, but its poor water solubility and low bioavailability severely limit its clinical application. Development of a targeted drug delivery system is a good strategy to improve the antitumor activity of baicalin.

methodsWe prepared a BAN nano-drug delivery system PEG-FA@ZIF-8@BAN with a zeolite imidazole framework-8 (ZIF-8) as a carrier, which can achieve the response of folate receptor (FR). We characterized this system in terms of morphology, particle size, zeta-potential, infrared (IR), ultraviolet (UV), x-ray diffraction (XRD), and Brunel-Emmett-Teller (BET), and examined the in vitro cytotoxicity and cellular uptake properties of PEG-FA@ZIF-8@BAN using MCF-7 cells. Lastly, we established a 4T1 tumor-bearing mouse model and evaluated its in vivo anti-mammary cancer activity.

resultsThe PEG-FA@ZIF-8@BAN nano-delivery system had good dispersion with a BAN loading efficiency of 41.45 ± 1.43%, hydrated particle size of 176 ± 8.1 nm, Zeta-potential of -23.83 ± 1.1 mV, and slow and massive drug release in an acidic environment (pH 5.0), whereas release was 11.03% in a neutral environment (pH 7.4). In vitro studies showed that PEG-FA@ZIF-8@BAN could significantly enhance the killing effect of BAN on MCF-7 cells, and the folic acid-mediated targeting could lead to better uptake of nanoparticles by tumor cells and thus better killing of cancer cells. In vivo studies also showed that PEG-FA@ZIF-8@BAN significantly increased the inhibition of the proliferation of solid breast cancer tumors (

conclusionThe PEG-FA@ZIF-8@BAN nano-drug delivery system significantly enhanced the anti-breast cancer effect of baicalin both in vivo and in vitro, providing a more promising drug delivery system for the clinical applications and tumor management.

Indexed as

Breast NeoplasmsNanoparticlesZeolitesAnimalsCell Line, TumorDrug CarriersDrug Delivery SystemsFemaleFlavonoidsFolic AcidHumansMiceNanoparticle Drug Delivery SystembaicalinDrug CarriersFlavonoidsFolic AcidNanoparticle Drug Delivery SystemZeolitesbaicalinbreast cancer therapyfolic acid responsemetal-organic framework

Identifiers

PMID34992370
PMCPMC8714011
OpenAlexW4200615556

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.