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Cyclic azapeptide CD36 ligand attenuates cardiac injury and reduces long‐chain fatty acid accumulation after myocardial ischemia–reperfusion in mice

FEBS Open Bio, EarlyView.
In a murine model of myocardial ischemia and reperfusion (MI/R), the CD36 azapeptide ligand MPE‐298 reduces cardiac injury and transiently lowers left ventricular long‐chain fatty acids (LCFAs) accumulation 3 h after reperfusion, accompanied by a decrease of oxidative stress and inflammation‐associated genes' expression in the heart and adipose tissue.
Jade Gauvin +12 more
wiley +1 more source

Cracking the Code: Genotype–Phenotype Correlation Models in Sarcoglycanopathies

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Sarcoglycanopathies are among the most severe limb‐girdle muscular dystrophies (LGMD), though milder presentations have been described. These diseases are primarily caused by missense variants, but the limited predictability of their effect on protein maturation, complex formation, and transport has hindered reliable genotype ...
Leonela Luce +72 more
wiley +1 more source

Temperature and energy-aware consolidation algorithms in cloud computing

Journal of Cloud Computing: Advances, Systems and Applications, 2019
Cloud computing provides access to shared resources through Internet. It provides facilities such as broad access, scalability and cost savings for users. However, cloud data centers consume a significant amount of energy because of inefficient resources
Maede Yavari +2 more
doaj +1 more source

Prognostic Value of Neurofilament Light Chain and Glial Fibrillary Acidic Protein in ALD‐Related Myelopathy

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background X‐linked adrenoleukodystrophy (X‐ALD) is a neurometabolic disorder caused by pathogenic variants in ABCD1, leading to slowly progressive spinal cord disease in nearly all affected men. Sensitive biomarkers to quantify disease severity and predict progression are needed for clinical care and trial design.
Eda G. Kabak +4 more
wiley +1 more source

Does Long‐Term Lower Extremity Strength Training in Adults With Knee Osteoarthritis and Varus Alignment Reduce Knee Joint Loading During Gait?

Arthritis Care &Research, EarlyView.
Objective We examined whether 18 months of strength training in individuals with knee varus alignment and medial tibiofemoral osteoarthritis (OA) reduced knee joint loads during walking compared to an attention control group. Methods This study was a secondary analysis of a randomized clinical trial that compared the effects of strength training to a ...
Stephen P. Messier +12 more
wiley +1 more source

An Energy Aware Unified Ant Colony System for Dynamic Virtual Machine Placement in Cloud Computing

Energies, 2017
Energy efficiency is a significant topic in cloud computing. Dynamic consolidation of virtual machines (VMs) with live migration is an important method to reduce energy consumption.
Xiao-Fang Liu, Zhi-Hui Zhan, Jun Zhang
doaj +1 more source

A Comprehensive Review of Cloud Computing Virtual Machine Consolidation

IEEE Access, 2023
In the last decade, users have been able to access their applications, data, and services via the cloud from any location with an internet connection.
Jaspreet Singh, Navpreet Kaur Walia
doaj +1 more source

Cumulative Social Disadvantage and Disease Activity in Juvenile Idiopathic Arthritis: A Childhood Arthritis and Rheumatology Research Alliance Registry Study

Arthritis Care &Research, EarlyView.
Objective Social determinants of health (SDOH) contribute to juvenile idiopathic arthritis (JIA) disparities, but most studies have assessed SDOH independently rather than cumulatively across individual, family, and neighborhood levels. Using a socioecological framework, we investigated the relationship among cumulative social disadvantage ...
William Daniel Soulsby +448 more
wiley +1 more source

Energy-aware VM placement algorithms for the OpenStack Neat consolidation framework

Journal of Cloud Computing: Advances, Systems and Applications, 2019
One of the main challenges in cloud computing is an enormous amount of energy consumed in data-centers. Several researches have been conducted on Virtual Machine(VM) consolidation to optimize energy consumption.
Fikru Feleke Moges, Surafel Lemma Abebe
doaj +1 more source

BHyPreC: A Novel Bi-LSTM Based Hybrid Recurrent Neural Network Model to Predict the CPU Workload of Cloud Virtual Machine

IEEE Access, 2021
With the advancement of cloud computing technologies, there is an ever-increasing demand for the maximum utilization of cloud resources. It increases the computing power consumption of the cloud’s systems.
Md. Ebtidaul Karim +3 more
doaj +1 more source

7. clean energy
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virtual machine consolidation

energy efficiency
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dynamic vm consolidation

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