A PHP Error was encountered

Severity: Warning

Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests

Filename: helpers/my_audit_helper.php

Line Number: 176

Backtrace:

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1034
Function: getPubMedXML

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016

File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global

File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword

File: /var/www/html/index.php
Line: 316
Function: require_once

RNA interference targeting mu-opioid receptors reverses the inhibition of fentanyl on glucose-evoked insulin release of rat islets. | LitMetric

AI Article Synopsis

  • The study investigates the impact of fentanyl, a mu-opioid receptor agonist, on insulin release from rat pancreatic islets, aiming to understand the role of mu-opioid receptors in this process.
  • Researchers utilized siRNA to effectively reduce mu-opioid receptor expression in islet cells, finding that this knockdown led to a significant reversal of fentanyl's inhibitory effects on glucose-evoked insulin release.
  • The findings suggest that the inhibition of insulin release by fentanyl is mediated through mu-opioid receptors, indicating potential therapeutic implications for diabetes research using RNA interference techniques.

Article Abstract

Background: Mu opioid receptor plays an important role in many physiological functions. Fentanyl is a widely used opioid receptor agonist for analgesia. This study was conducted to test the role of mu-opioid receptor on insulin release by determining whether fentanyl affected insulin release from freshly isolated rat pancreatic islets and if small interfering RNAs (siRNA) targeting mu-opioid receptor in the islets could knock down mu-opioid receptor expression.

Methods: Islets were isolated from ripe SD rats' pancreas by common bile duct intraductal collagenase V digestion and purified by discontinuous Ficoll density gradient centrifugation. The siRNA knock-down of mu-opioid receptor mRNA and protein in islet cells was analyzed by semi-quantitative real time-PCR and Western blotting. After siRNA-transfection for 48 hours, the islets were co-cultured with fentanyl as follows: 0 ng/ml, 3 ng/ml and 30 ng/ml for 48 hours. Then glucose-evoked insulin release was performed. As a control, the insulin release was also analyzed in islets without siRNA-trasfection after being co-cultured with fentanyl for 48 hours.

Results: After 48 hours of transfections, specific siRNA targeting of mu-opioid receptors produced significant reduction of mu-opioid receptor mRNA and protein (P < 0.01). Fentanyl significantly inhibited glucose-evoked insulin release in islets in a concentration dependent manner (P < 0.01). But after siRNA-transfection for 48 hours, the inhibition on glucose-evoked insulin release was reversed (P < 0.01).

Conclusions: RNA interference specifically reduces mu-opioid receptor mRNA and protein expression, leading to reversal of the fentanyl-induced inhibition on glucose-evoked insulin release of rat islets. The activation of opioid receptor induced by fentanyl functions to inhibit insulin release. The use of RNAi presents a promising tool for future research in diabetic mechanisms and a novel therapy for diabetes.

Download full-text PDF

Source

Publication Analysis

Top Keywords

insulin release
36
mu-opioid receptor
24
glucose-evoked insulin
20
targeting mu-opioid
12
opioid receptor
12
receptor mrna
12
mrna protein
12
insulin
9
release
9
receptor
9

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!