Background: Skeletal muscle mass is determined predominantly by feeding-induced and activity-induced fluctuations in muscle protein synthesis (MPS). Older individuals display a diminished MPS response to protein ingestion, referred to as age-related anabolic resistance, which contributes to the progression of age-related muscle loss known as sarcopenia.

Objectives: We aimed to determine the impact of consuming higher-quality compared with lower-quality protein supplements above the recommended dietary allowance (RDA) on integrated MPS rates. We hypothesized that increasing total protein intake above the RDA, regardless of the source, would support higher integrated rates of myofibrillar protein synthesis.

Methods: Thirty-one healthy older males (72 ± 4 y) consumed a controlled diet with protein intake set at the RDA: control phase (days 1-7). In a double-blind, randomized controlled fashion, participants were assigned to consume an additional 50 g (2 × 25g) of whey (n = 10), pea (n = 11), or collagen (n = 10) protein each day (25 g at breakfast and lunch) during the supplemental phase (days 8-15). Deuterated water ingestion and muscle biopsies assessed integrated MPS and acute anabolic signaling. Postprandial blood samples were collected to determine feeding-induced aminoacidemia.

Results: Integrated MPS was increased during supplemental with whey (1.59 ± 0.11 %/d; P < 0.001) and pea (1.59 ± 0.14 %/d; P < 0.001) when compared with RDA (1.46 ± 0.09 %/d for the whey group; 1.46 ± 0.10 %/d for the pea group); however, it remained unchanged with collagen. Supplemental protein was sufficient to overcome anabolic signaling deficits (mTORC1 and rpS6), corroborating the greater postprandial aminoacidemia.

Conclusions: Our findings demonstrate that supplemental protein provided at breakfast and lunch over the current RDA enhanced anabolic signaling and integrated MPS in older males; however, the source of additional protein may be an important consideration in overcoming age-related anabolic resistance. This trial was registered clinicaltrials.gov as NCT04026607.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11291473PMC
http://dx.doi.org/10.1016/j.ajcnut.2024.05.009DOI Listing

Publication Analysis

Top Keywords

integrated mps
16
protein
12
older males
12
anabolic signaling
12
whey pea
8
pea collagen
8
collagen protein
8
recommended dietary
8
dietary allowance
8
myofibrillar protein
8

Similar Publications

The ever-increasing microplastics (MPs) and antibiotic-resistance genes (ARGs) in aquatic ecosystems has become a serious global challenging issue. However, the impact of different pollution sources on microbiome and antibiotic resistome in surface water (SW) and plastisphere (PS) remains largely elusive. Here, shotgun metagenomics was used to analyze microbiome structure and antibiotic resistome in SW and PS under the influence of different pollution sources.

View Article and Find Full Text PDF

Machine learning-integrated droplet microfluidic system for accurate quantification and classification of microplastics.

Water Res

January 2025

Department of Mechanical Engineering, Sogang University, Seoul, South Korea; Institute of Integrated Biotechnology, Sogang University, Seoul, South Korea; Department of Biomedical Engineering, Sogang University, Seoul, South Korea; Institute of Smart Biosensor, Sogang University, Seoul, South Korea. Electronic address:

Microplastic (MP) pollution poses serious environmental and public health concerns, requiring efficient detection methods. Conventional techniques have the limitations of labor-intensive workflows and complex instrumentation, hindering rapid on-site field analysis. Here, we present the Machine learning (ML)-Integrated Droplet-based REal-time Analysis of MP (MiDREAM) system.

View Article and Find Full Text PDF

Impact of Heterosigma akashiwo on the environmental behavior of microplastics: Aggregation, sinking, and resuspension dynamics.

J Hazard Mater

January 2025

Ecological Risk Research Department, KIOST, Geoje 53201, Republic of Korea; Department of Ocean Science, University of Science and Technology (UST), Daejeon 34113, Republic of Korea. Electronic address:

Aggregation processes of microalgae have significant effects on the vertical distribution of microplastics (MPs) in the marine environment. This study explored how the harmful microalga Heterosigma akashiwo affects the aggregation and sinking characteristics of four types of MPs: low and high-density polyethylene (PE) spheres, and small and large polypropylene (PP) fragments. The aggregation of MPs was primarily driven by extracellular polymeric substances (EPS) rather than direct attachment to the cells, contributing to their sinking.

View Article and Find Full Text PDF

Opioids have been the primary method used to manage pain for hundreds of years, however the increasing prescription rate of these drugs in the modern world has led to a public health crisis of overdose related deaths. Naloxone is the current standard treatment for opioid overdose rescue, but it has not been fully investigated for potential off-target toxicity effects. The current methods for pharmaceutical development do not correlate well with pre-clinical animal studies compared to clinical results, creating a need for improved methods for therapeutic evaluation.

View Article and Find Full Text PDF

Integrating machine learning, suspect and nontarget screening reveal the interpretable fates of micropollutants and their transformation products in sludge.

J Hazard Mater

January 2025

School of Environmental Studies, China University of Geosciences, Wuhan, Hubei 430074, China; National Engineering Research Center of Industrial Wastewater Detoxication and Resource Recovery, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China. Electronic address:

Activated sludge enriches vast amounts of micropollutants (MPs) when wastewater is treated, posing potential environmental risks. While standard methods typically focus on target analysis of known compounds, the identity, structure, and concentration of transformation products (TPs) of MPs remain less understood. Here, we employed a novel approach that integrates machine learning for the quantification of nontarget TPs with advanced target, suspect, and nontarget screening strategies.

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!