Evidence map›Paper›PMID 29463999›Full record

ReviewTheranostics2018

Stimuli-Responsive Nanomedicines for Overcoming Cancer Multidrug Resistance.

Lei Zhou, Hao Wang, Yaping Li

Abstract readReview
In one paragraph

Review in Theranostics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 68 papers.

0numbers the graph read from it
0cells of the map it votes in
68citing papers in PubMed
–field-weighted citation impact
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

68 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Theranostics in nuclear medicine: the era of precision oncology.Medical oncology (Northwood, London, England) · 2025
    Review
  5. Review
  6. Review
  7. Review
  8. Review
  9. Review
  10. Review
  11. Review
  12. Review
  13. Chemical science · 2024
    Article
  14. Review
  15. Review
  16. Article
  17. Article
  18. Article
  19. Article
  20. Review

8 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

3 authors.

Lei ZhouState Key Laboratory of Drug Research & Center of Pharmaceutics, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China.
Hao WangChina State Institute of Pharmaceutical Industry, Shanghai 201203, China.
Yaping LiState Key Laboratory of Drug Research & Center of Pharmaceutics, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chemotherapy is still a main option for cancer therapy, but its efficacy is often unsatisfying due to multidrug resistance (MDR). The tumor microenvironment is considered a dominant factor causing MDR. Stimuli-responsive nanomedicines exhibit many superiorities for reversal of MDR. As smart systems, stimuli-responsive nanomedicines are desirable for achieving site-specific accumulation and triggered drug release in response to slight changes in physicochemical properties in pathological conditions or to exogenous stimuli. In this review, we highlight the current progress of various nanomedicines with different stimuli-responsive capabilities for overcoming MDR. The materials, design, construction as well as efficacy in overcoming MDR of these nanomedicines are discussed. Eventually, we look forward to forthcoming intelligent nanoparticle systems with new mechanisms to deliver drugs for practical applications in conquering cancer MDR.

Indexed as

Drug Resistance, MultipleAnimalsDisease Models, AnimalDrug Delivery SystemsHumansMolecular Targeted TherapyNanomedicineNeoplasmscancerchemotherapymultidrug resistancenanomedicinesstimuli-responsivetumor microenvironment

Identifiers

PMID29463999
PMCPMC5817110

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.