While previous research has linked cognitive function with resistance exercise, the nuanced links between muscle strength, mass, and neuroelectric function are less understood. Therefore, this study investigated the association of muscle strength and mass with inhibitory control (IC), working memory (WM), and related neuroelectric activity. A total of 123 18-50-year-old adults completed maximal aerobic capacity and strength tests, a body composition scan, and IC and WM tasks while the N2 and P3 components of event-related potentials were recorded. Bivariate correlations revealed aerobic fitness, strength, and mass were associated with behavioral and neuroelectric outcomes. After accounting for age, sex, and aerobic fitness, strength was associated with intra-individual response time variability, accuracy, and P3 latency during WM. Muscle mass was associated with N2 latency during IC. While relationships with behavioral outcomes did not persist after controlling for the opposite muscle outcome, greater strength and mass were related to shorter P3 latency during WM and shorter N2 latency during IC, respectively. These results provide initial evidence that muscle outcomes are associated with executive function and neuroelectric processing speed, suggesting distinct contributions of strength and mass to cognition. This work highlights the significance of maintaining muscle strength and mass alongside aerobic fitness for optimal cognitive health.
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http://dx.doi.org/10.1016/j.bandc.2024.106139 | DOI Listing |
Pediatr Radiol
January 2025
Department of Radiology, Children's Hospital of Philadelphia, 3401 Civic Center Blvd, Philadelphia, PA, 19104, USA.
Background: Splenic stiffness is a potential imaging marker of portal hypertension. Normative spleen stiffness values are needed to define diagnostic thresholds.
Objective: To report stiffness measurements of the spleen in healthy children undergoing liver magnetic resonance (MR) elastography across MRI vendors and field strengths.
Proc Natl Acad Sci U S A
January 2025
Gene Expression Laboratory, Salk Institute, La Jolla, CA 92037-1002.
Nutritional status is a determining factor for growth during development and homeostatic maintenance in adulthood. In the context of muscle, growth hormone (GH) coordinates growth with nutritional status; however, the detailed mechanisms remain to be fully elucidated. Here, we show that the transcriptional repressor B cell lymphoma 6 (BCL6) maintains muscle mass by sustaining GH action.
View Article and Find Full Text PDFJ Proteome Res
January 2025
Institute of Pharmacy and Molecular Biotechnology, Heidelberg University, 69120 Heidelberg, Germany.
The first step in bottom-up proteomics is the assignment of measured fragmentation mass spectra to peptide sequences, also known as peptide spectrum matches. In recent years novel algorithms have pushed the assignment to new heights; unfortunately, different algorithms come with different strengths and weaknesses and choosing the appropriate algorithm poses a challenge for the user. Here we introduce PeptideForest, a semisupervised machine learning approach that integrates the assignments of multiple algorithms to train a random forest classifier to alleviate that issue.
View Article and Find Full Text PDFOrthop J Sports Med
January 2025
Department of Sports Medical Center, Anam Hospital, Korea University College of Medicine, Seoul, Republic of Korea.
Background: Graft selection is an important part of preoperative planning for anterior cruciate ligament reconstruction (ACLR). In addition, ACLR with the remnant preservation technique has recently gained attention due to potential benefit in bone-tendon healing, graft revascularization, and proprioceptive nerve remodeling. However, the ideal graft choice remains controversial, and there is limited research comparing autograft and allograft in ACLR with remnant preservation.
View Article and Find Full Text PDFDigit Health
January 2025
Department of Exercise Rehabilitation & Welfare, Gachon University, Incheon, Republic of Korea.
Objective: Sarcopenia, a condition characterized by the progressive loss of skeletal muscle mass and strength, poses significant challenges in research due to missing data. Incomplete datasets undermine the accuracy and reliability of studies, necessitating effective imputation techniques. This study conducts a comparative analysis of three advanced methods-multiple imputation by chained equations (MICE), support vector regression, and K-nearest neighbors (KNN)-to address data completeness issues in sarcopenia research.
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