Evidence map›Paper›PMID 28356733›Full record

ArticleInternational journal of nanomedicine2017

A novel selective VPAC2 agonist peptide-conjugated chitosan modified selenium nanoparticles with enhanced anti-type 2 diabetes synergy effects.

Shao-Jun Zhao, De-Hua Wang, Yan-Wei Li, Lei Han, Xing Xiao, Min Ma, David Chi-Cheong Wan, An Hong, Yi Ma

Open access · goldAbstract read
In one paragraph

Article in International journal of nanomedicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.4field-weighted citation impact, top 22% 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

8 citing papers in PubMed, 28 citations in OpenAlex.

  1. Review
  2. Review
  3. Review
  4. Review
  5. Trends of nanotechnology in type 2 diabetes mellitus treatment.Asian journal of pharmaceutical sciences · 2021
    Review
  6. Review
  7. Article
  8. 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

9 authors at 1 institution in 1 country.

Shao-Jun ZhaoInstitute of Biomedicine, Department of Cellular Biology, Jinan University; National Engineering Research Center of Genetic Medicine, Key Laboratory of Bioengineering Medicine of Guangdong Province, Jinan University.
De-Hua WangInstitute of Biomedicine, Department of Cellular Biology, Jinan University; National Engineering Research Center of Genetic Medicine, Key Laboratory of Bioengineering Medicine of Guangdong Province, Jinan University.
Yan-Wei LiInstitute of Biomedicine, Department of Cellular Biology, Jinan University; National Engineering Research Center of Genetic Medicine, Key Laboratory of Bioengineering Medicine of Guangdong Province, Jinan University.
Lei HanInstitute of Biomedicine, Department of Cellular Biology, Jinan University; National Engineering Research Center of Genetic Medicine, Key Laboratory of Bioengineering Medicine of Guangdong Province, Jinan University.
Xing XiaoInstitute of Biomedicine, Department of Cellular Biology, Jinan University; National Engineering Research Center of Genetic Medicine, Key Laboratory of Bioengineering Medicine of Guangdong Province, Jinan University.
Min MaCollege of traditional Chinese Medicine, Institute of Integrated Traditional Chinese and Western Medicine, Jinan University, Guangdong.
David Chi-Cheong WanSchool of Biomedical Sciences, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, People's Republic of China.
An HongInstitute of Biomedicine, Department of Cellular Biology, Jinan University; National Engineering Research Center of Genetic Medicine, Key Laboratory of Bioengineering Medicine of Guangdong Province, Jinan University.
Yi MaInstitute of Biomedicine, Department of Cellular Biology, Jinan University; National Engineering Research Center of Genetic Medicine, Key Laboratory of Bioengineering Medicine of Guangdong Province, Jinan University.
Chinese University of Hong Kong · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A novel neuroendocrine peptide, pituitary adenylate cyclase activating peptide (PACAP), was found to have an important role in carbohydrate or lipid metabolism and was susceptible to dipeptidyl peptidase IV degradation. It can not only mediate glucose-dependent insulin secretion and lower blood glucose by activating VPAC2 receptor, but also raise blood glucose by promoting glucagon production by VPAC1 receptor activation. Therefore, its therapeutic application is restricted by the exceedingly short-acting half-life and the stimulatory function for glycogenolysis. Herein, we generated novel peptide-conjugated selenium nanoparticles (SeNPs; named as SCD), comprising a 32-amino acid PACAP-derived peptide DBAYL that selectively binds to VPAC2, and chitosan-modified SeNPs (SeNPs-CTS, SC) as slow-release carrier. The circulating half-life of SCD is 14.12 h in mice, which is 168.4-and 7.1-fold longer than wild PACAP (~5 min) and DBAYL (~1.98 h), respectively. SCD (10 nmol/L) significantly promotes INS-1 cell proliferation, glucose uptake, insulin secretion, insulin receptor expression and also obviously reduces intracellular reactive oxygen species levels in H

Indexed as

AnimalsBlood GlucoseCell ProliferationChitosanDiabetes Mellitus, Type 2Drug LiberationExenatideFastingGlucoseHalf-LifeHydrogen PeroxideInsulinInsulin ResistanceMaleMiceNanoparticlesBlood GlucoseChitosanExenatideGlucoseHydrogen PeroxideInsulinPeptidesReactive Oxygen SpeciesReceptor, InsulinReceptors, Vasoactive Intestinal Peptide, Type IIRNA, MessengerSeleniumVenomsnano-seleniumpituitary adenylate cyclase activating peptide (PACAP)-derived peptidesynergy effecttype 2 diabetes (T2D)VPAC2 receptor

Identifiers

PMID28356733
PMCPMC5367579
OpenAlexW2602617292

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.