Evidence map›Paper›PMID 27099493›Full record

ArticleInternational journal of nanomedicine2016

Hyaluronic acid reagent functional chitosan-PEI conjugate with AQP2-siRNA suppressed endometriotic lesion formation.

Meng-Dan Zhao, Jin-Lin Cheng, Jing-Jing Yan, Feng-Ying Chen, Jian-Zhong Sheng, Dong-Li Sun, Jian Chen, Jing Miao, Run-Ju Zhang, Cai-Hong Zheng and 1 more

Open access · goldAbstract read
In one paragraph

Article in International journal of nanomedicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed
7.0field-weighted citation impact, top 4% 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

31 citing papers in PubMed, 67 citations in OpenAlex.

  1. Tissue-specific gene delivery approaches.Bioengineering & translational medicine · 2026
    Review
  2. Three-dimensional patient-derived endometriosis model for drug evaluation.Acta obstetricia et gynecologica Scandinavica · 2026
    Article
  3. Review
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  14. Applications of nanomaterials in endometriosis treatment.Frontiers in bioengineering and biotechnology · 2023
    Review
  15. Article
  16. Review
  17. Article
  18. Article
  19. Article
  20. Nanomedicines for Endometriosis: Lessons Learned from Cancer Research.Small (Weinheim an der Bergstrasse, Germany) · 2021
    Review
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

11 authors at 2 institutions in 1 country.

Meng-Dan ZhaoWomen's Hospital, School of Medicine, Zhejiang University, Hangzhou, People's Republic of China.
Jin-Lin ChengState Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, People's Republic of China.
Jing-Jing YanWomen's Hospital, School of Medicine, Zhejiang University, Hangzhou, People's Republic of China.
Feng-Ying ChenWomen's Hospital, School of Medicine, Zhejiang University, Hangzhou, People's Republic of China.
Jian-Zhong ShengDepartment of Pathophysiology, School of Medicine, Zhejiang University, Hangzhou, People's Republic of China.
Dong-Li SunWomen's Hospital, School of Medicine, Zhejiang University, Hangzhou, People's Republic of China.
Jian ChenThe First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, People's Republic of China.
Jing MiaoThe First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, People's Republic of China.
Run-Ju ZhangWomen's Hospital, School of Medicine, Zhejiang University, Hangzhou, People's Republic of China.
Cai-Hong ZhengWomen's Hospital, School of Medicine, Zhejiang University, Hangzhou, People's Republic of China.
He-Feng HuangWomen's Hospital, School of Medicine, Zhejiang University, Hangzhou, People's Republic of China; International Peace Maternity and Child Health Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, People's Republic of China.
Women's Hospital, School of Medicine, Zhejiang University · CNZhejiang University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To identify a new drug candidate for treating endometriosis which has fewer side effects, a new polymeric nanoparticle gene delivery system consisting of polyethylenimine-grafted chitosan oligosaccharide (CSO-PEI) with hyaluronic acid (HA) and small interfering RNA (siRNA) was designed. There was no obvious difference in sizes observed between (CSO-PEI/siRNA)HA and CSO-PEI/siRNA, but the fluorescence accumulation in the endometriotic lesion was more significant for (CSO-PEI/siRNA)HA compared with CSO-PEI/siRNA due to the specific binding of HA to CD44. In addition, the (CSO-PEI/siRNA)HA nanoparticle gene therapy significantly decreased the endometriotic lesion sizes with atrophy and degeneration of the ectopic endometrium. The epithelial cells of ectopic endometrium from rat models of endometriosis showed a significantly lower CD44 expression than control after treatment with (CSO-PEI/siRNA)HA. Furthermore, observation under an electron microscope showed no obvious toxic effect on the reproductive organs. Therefore, (CSO-PEI/siRNA)HA gene delivery system can be used as an effective method for the treatment of endometriosis.

Indexed as

Gene Transfer TechniquesAnimalsChitosanFemaleGenetic TherapyHyaluronic AcidImmunoenzyme TechniquesNanoparticlesPolyethyleneiminePolymersRatsRats, Sprague-DawleyRNA, Small InterferingUterine DiseasesChitosanchitosan-graft-polyethylenimineHyaluronic AcidPolyethyleneiminePolymersRNA, Small InterferingAQP2-siRNAchitosan-PEIendometriosishyaluronic acidtargeted therapy

Identifiers

PMID27099493
PMCPMC4821386
OpenAlexW2333901123

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.