Evidence map›Paper›PMID 37128309›Full record

ArticleHeliyon2023

Facile construction of irinotecan loaded mesoporous nano-formulation with surface-initiated polymerization to improve stimuli-responsive drug delivery for breast cancer therapy.

Zheng Nie, Daoliang Wang, Shuangyan Wang, Linling Wang

Open access · goldAbstract read
In one paragraph

Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
2.4field-weighted citation impact, top 12% 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

7 citing papers in PubMed, 24 citations in OpenAlex.

  1. Article
  2. Article
  3. Stimuli-responsive bioengineered platforms for precision cancer therapy.Frontiers in bioengineering and biotechnology · 2026
    Review
  4. Article
  5. Article
  6. Article
  7. 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

4 authors at 3 institutions in 1 country.

Zheng NieDepartment of Breast Surgery, The First People's Hospital of Jingzhou, Jingzhou, 434000, China.
Daoliang WangDepartment of Breast Surgery, The First People's Hospital of Jingzhou, Jingzhou, 434000, China.
Shuangyan WangDepartment of Thyroid and Breast Surgery, The First People's Hospital of Wenling, Wenling, 317500, China.
Linling WangDepartment of Ultrasonography, The First Hospital of Hunan University of Chinese Medicine, Changsha, 410000, China.
First People's Hospital of Jingzhou · CNFirst Affiliated Hospital of Hunan University of Traditional Chinese Medicine · CNThe First People's Hospital of Wenling · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This work uses rice husk to fabricate mesoporous silica nanoparticles (D-RMN) for breast cancer therapy. The biocompatible dual-responsive (DAN-RMN) was developed by polymerizing acrylic acid (AA) and n-isopropyl acrylamide (NIPAM) on the DV-RMN surface monomeric ratio to increase drug delivery efficiency after vinyl groups were added to the surface of nanoparticles (DAN-RMN). Various analytical and spectroscopical methods characterized the fabricated nanoparticles. Additionally, further encapsulation with SN-38 into the DAN-RMN enhances anticancer efficiency. The in-vitro controlled SN-38 release displayed remarkable temperature and pH response. The MTT assay established the biocompatibility and cytotoxicity of natural sources of silica and DAN-RMN. The fabricated SN-38@DAN-RMN nanoparticles effectively killed the MDA-MB-231 and 4T1 cancerous cells, confirmed by the MTT assay. The IC

Indexed as

ApoptosisBreast cancerIrinotecanMesoporous silicaNanotherapy

Identifiers

PMID37128309
PMCPMC10148107
OpenAlexW4362455836

What OpenQuestion holds

Textmetadata
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.