AI Article Synopsis

  • Mitochondrial oxidative stress contributes to heart dysfunction after burn injuries, and the AMPK-sirtuin 1-PGC1α-NFE2L2-ARE signaling pathway plays a key role in this process.
  • Male Sprague-Dawley rats with burn injuries showed decreased levels of AMPK, sirtuin 1, and PGC1, which were linked to increased oxidative stress and impaired heart function.
  • Treating cardiac cells with AMPK and PGC1α activators improved mitochondrial function, suggesting these could be potential therapies for heart issues following burn injuries.

Article Abstract

Background: Mitochondrial oxidative stress plays a prominent role in the development of burn-induced cardiac dysfunction. AMP-activated kinase (AMPK), an energy sensor, has a central role in the pathogenesis of heart failure. However, its role in cardiac dysfunction after burn injury is unclear. Our hypothesis is that burn injury acts through the AMPK-sirtuin 1-PGC1α-nuclear factor erythroid 2-related factor 2 (NFE2L2)-ARE signaling pathway, leading to cardiac mitochondrial impairment, resulting in cardiac dysfunction.

Study Design: Male Sprague-Dawley rats underwent sham procedure or 60% total body surface area full-thickness burn. Echocardiograms were performed 24 hours post burn. Heart tissue was harvested at 24 hours post burn for biochemistry/molecular biologic analysis. AC16 cardiomyocytes were treated with either sham or burned rat serum (±AMPK inhibitor/AMPK activator/PGC1α activator) for evaluation of cardiomyocyte mitochondrial function by using seahorse in vitro.

Results: Burn injury-induced cardiac dysfunction was measured by echocardiogram. Burn injury suppressed cardiac AMPK, sirtuin 1, and PGC1 expression, leading to acetylation of cardiomyocyte proteins. In addition, burn injury caused NFE2L2 and NFE2L2 regulated antioxidants (heme oxygenase 1, NADH quinone oxidoreductase 1, glutamatecysteine ligase catalytic subunit, manganese superoxide dismutase, and glutathione peroxidase) to decrease, resulting in cardiac oxidative stress. In vitro, AMPK1 activator and PGC1α agonist treatment improved Ac16 cell mitochondrial dysfunction, and AMPK1 inhibitor treatment worsened Ac16 cellular damage.

Conclusions: Burn-induced cardiac dysfunction and cardiac mitochondrial damage occur via the AMPK-sirtuin 1-PGC1α-NFE2L2-ARE signaling pathway. AMPK and PGC1α agonists might be promising therapeutic agents to reverse cardiac dysfunction after burn injury.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8495903PMC
http://dx.doi.org/10.1016/j.jamcollsurg.2019.12.029DOI Listing

Publication Analysis

Top Keywords

cardiac dysfunction
24
burn injury
24
dysfunction burn
12
cardiac
11
burn
10
oxidative stress
8
burn-induced cardiac
8
signaling pathway
8
cardiac mitochondrial
8
hours post
8

Similar Publications

Outcomes for Children With Congenital Heart Disease Undergoing Ventricular Assist Device Implantation: An ACTION Registry Analysis.

J Am Coll Cardiol

December 2024

Division of Cardiology, Department of Pediatrics, University of Pennsylvania Perelman School of Medicine, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.

Background: There are no contemporary reports that highlight the national outcomes for children with congenital heart disease (CHD) undergoing ventricular assist device (VAD) implantation.

Objectives: This study sought to evaluate differences in VAD outcomes for children with CHD to those with non-CHD as well as those with univentricular CHD to those with biventricular CHD.

Methods: Data for CHD and non-CHD patients from the multicenter ACTION (Advanced Cardiac Therapies Improving Outcomes Network) undergoing VAD implantation from April 2018 to February 2023 were included.

View Article and Find Full Text PDF

Background: Myocardial fibrosis is a key healing response after myocardial infarction driven by activated fibroblasts. Gallium-68-labeled fibroblast activation protein inhibitor ([Ga]-FAPI) is a novel positron-emitting radiotracer that binds activated fibroblasts.

Objectives: The aim of this study was to investigate the intensity, distribution, and time-course of fibroblast activation after acute myocardial infarction.

View Article and Find Full Text PDF

Wearable Solutions Using Physiological Signals for Stress Monitoring on Individuals with Autism Spectrum Disorder (ASD): A Systematic Literature Review.

Sensors (Basel)

December 2024

REMIT (Research on Economics, Management and Information Technologies), IJP (Instituto Jurídico Portucalense), Universidade Portucalense, Rua Dr. António Bernardino de Almeida, 541-619, 4200-072 Porto, Portugal.

Some previous studies have focused on using physiological signals to detect stress in individuals with ASD through wearable devices, yet few have focused on how to design such solutions. Wearable technology may be a valuable tool to aid parents and caregivers in monitoring the emotional states of individuals with ASD who are at high risk of experiencing very stressful situations. However, effective wearable devices for individuals with ASD may need to differ from solutions for those without ASD.

View Article and Find Full Text PDF

Coronary artery stenosis detection remains a challenging task due to the complex vascular structure, poor quality of imaging pictures, poor vessel contouring caused by breathing artifacts and stenotic lesions that often appear in a small region of the image. In order to improve the accuracy and efficiency of detection, a new deep-learning technique based on a coronary artery stenosis detection framework (DCA-YOLOv8) is proposed in this paper. The framework consists of a histogram equalization and canny edge detection preprocessing (HEC) enhancement module, a double coordinate attention (DCA) feature extraction module and an output module that combines a newly designed loss function, named adaptive inner-CIoU (AICI).

View Article and Find Full Text PDF

Electrocardiogram (ECG) signals contain complex and diverse features, serving as a crucial basis for arrhythmia diagnosis. The subtle differences in characteristics among various types of arrhythmias, coupled with class imbalance issues in datasets, often hinder existing models from effectively capturing key information within these complex signals, leading to a bias towards normal classes. To address these challenges, this paper proposes a method for arrhythmia classification based on a multi-branch, multi-head attention temporal convolutional network (MB-MHA-TCN).

View Article and Find Full Text PDF

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!