Resistance training is the most effective strategy to modify muscle architecture, enhancing sport performance and reducing injury risk. The aim of this study was to compare the effects of high loads (HL) versus lower loads (LL), maximal versus submaximal efforts, and high frequency (HF) versus low frequency (LF) on quadriceps architectural adaptations in team sports players. Five databases were searched. Vastus lateralis thickness, fascicle length and pennation angle, and rectus femoris thickness were analyzed as main outcomes. Overall, resistance training significantly improved muscle thickness and pennation angle, but not fascicle length. LL led to greater fascicle length adaptations in the vastus lateralis compared to HL (p=0.01), while no substantial differences were found for other load comparisons. Degree of effort and training frequency did not show meaningful differences (p>0.05). In conclusion, LL lengthen the fascicle to a greater extent than HL, and training with LL twice a week could maximize architectural adaptations, whereas the degree of effort does not appear to be a determinant variable on quadriceps architectural adaptations.
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http://dx.doi.org/10.1055/a-2369-5900 | DOI Listing |
Curr Med Imaging
January 2025
School of Life Sciences, Tiangong University, Tianjin 300387, China.
Objective: The objective of this research is to enhance pneumonia detection in chest X-rays by leveraging a novel hybrid deep learning model that combines Convolutional Neural Networks (CNNs) with modified Swin Transformer blocks. This study aims to significantly improve diagnostic accuracy, reduce misclassifications, and provide a robust, deployable solution for underdeveloped regions where access to conventional diagnostics and treatment is limited.
Methods: The study developed a hybrid model architecture integrating CNNs with modified Swin Transformer blocks to work seamlessly within the same model.
Adv Sci (Weinh)
January 2025
Department of Electrical Engineering, City University of Hong Kong, Kowloon, Hong Kong, 999077, China.
Optical edge detection is a crucial optical analog computing method in fundamental artificial intelligence, machine vision, and image recognition, owing to its advantages of parallel processing, high computing speed, and low energy consumption. Field-of-view-tunable edge detection is particularly significant for detecting a broader range of objects, enhancing both practicality and flexibility. In this work, a novel approach-adaptive optical spatial differentiation is proposed for field-of-view-tunable edge detection.
View Article and Find Full Text PDFSci Rep
January 2025
School of Chemical, Petroleum and Gas Engineering, Iran University of Science and Technology, P.O. Box: 16765-163, Tehran, Iran.
In this study, Response Surface Methodology (RSM) and Artificial Neural Networks (ANN) were developed to estimate the equilibrium solubility and partial pressure of CO in blended aqueous solutions of diisopropanolamine (DIPA) and 2-amino-2-methylpropanol (AMP). In this study, several key parameters were analyzed to understand the behavior of the aqueous DIPA/AMP system for CO capture. Including DIPA (9-21 wt%), AMP (9-21 wt%), temperature (323.
View Article and Find Full Text PDFProg Biophys Mol Biol
January 2025
Department of Cell Biology and Histology, Faculty of Medicine and Nursing, University of the Basque Country, UPV/EHU, Leioa 48940, Spain.
One of the most important goals of contemporary biology is to understand the principles of the molecular order underlying the complex dynamic architecture of cells. Here, we present an overview of the main driving forces involved in the cellular molecular complexity and in the emergent functional dynamic structures, spanning from the most basic molecular organization levels to the complex emergent integrative systemic behaviors. First, we address the molecular information processing which is essential in many complex fundamental mechanisms such as the epigenetic memory, alternative splicing, regulation of transcriptional system, and the adequate self-regulatory adaptation to the extracellular environment.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
January 2025
Department of Psychology, University of Pennsylvania, Philadelphia, PA 19104.
Human brain evolution is marked by a disproportionate expansion of cortical regions associated with advanced perceptual and cognitive functions. While this expansion is often attributed to the emergence of novel specialized brain areas, modifications to evolutionarily conserved cortical regions also have been linked to species-specific behaviors. Distinguishing between these two evolutionary outcomes has been limited by the ability to make direct comparisons between species.
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