Balancing selection is potentially an important biological force for maintaining advantageous genetic diversity in populations, including variation that is responsible for long-term adaptation to the environment. By serving as a means to maintain genetic variation, it may be particularly relevant to maintaining phenotypic variation in natural populations. Nevertheless, its prevalence and specific targets in the human genome remain largely unknown. We have analyzed the patterns of diversity and divergence of 13,400 genes in two human populations using an unbiased single-nucleotide polymorphism data set, a genome-wide approach, and a method that incorporates demography in neutrality tests. We identified an unbiased catalog of genes with signatures of long-term balancing selection, which includes immunity genes as well as genes encoding keratins and membrane channels; the catalog also shows enrichment in functional categories involved in cellular structure. Patterns are mostly concordant in the two populations, with a small fraction of genes showing population-specific signatures of selection. Power considerations indicate that our findings represent a subset of all targets in the genome, suggesting that although balancing selection may not have an obvious impact on a large proportion of human genes, it is a key force affecting the evolution of a number of genes in humans.
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http://dx.doi.org/10.1093/molbev/msp190 | DOI Listing |
Curr Obes Rep
January 2025
Metabolism and Body Composition, Pennington Biomedical Research Center, Baton Rouge, LA, 70808, USA.
Background: Recent technological advances have introduced novel methods for measuring body composition, each with unique benefits and limitations. The choice of method often depends on the trade-offs between accuracy, cost, participant burden, and the ability to measure specific body composition compartments.
Objective: To review the considerations of cost, accuracy, portability, and participant burden in reference and emerging body composition assessment methods, and to evaluate their clinical applicability.
J Clin Med
December 2024
Pető András Faculty, Semmelweis University, 1125 Budapest, Hungary.
Cerebral palsy (CP) manifests with abnormal posture and impaired selective motor control, notably affecting trunk control and dynamic balance coordination, leading to inadequate postural control. Previous research has indicated the benefits of pulsed electromagnetic field (PEMF) therapy for various musculoskeletal and neurological conditions. Therefore, we conducted a randomized pilot study to assess the feasibility of our preliminary research design and examine the effect of the PEMF treatment among children with CP.
View Article and Find Full Text PDFSensors (Basel)
January 2025
National Key Laboratory of Multispectral Information Intelligent Processing Technology, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430000, China.
Despite rapid progress in UAV-based infrared vehicle detection, achieving reliable target recognition remains challenging due to dynamic viewpoint variations and platform instability. The inherent limitations of infrared imaging, particularly low contrast ratios and thermal crossover effects, significantly compromise detection accuracy. Moreover, the computational constraints of edge computing platforms pose a fundamental challenge in balancing real-time processing requirements with detection performance.
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December 2024
The College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China.
Software-defined networking (SDN) offers an effective solution for flexible management of Wireless Sensor Networks (WSNs) by separating control logic from sensor nodes. This paper tackles the challenge of timely recovery from SDN controller failures and proposes a game theoretic model for multi-domain controllers. A game-enhanced autonomous fault recovery algorithm for SDN controllers is proposed, which boasts fast fault recovery and low migration costs.
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December 2024
IT Research Institute, Chosun University, Gwangju 61452, Republic of Korea.
The high mobility and dynamic nature of unmanned aerial vehicles (UAVs) pose significant challenges to clustering and routing in flying ad hoc networks (FANETs). Traditional methods often fail to achieve stable networks with efficient resource utilization and low latency. To address these issues, we propose a hybrid bio-inspired algorithm, HMAO, combining the mountain gazelle optimizer (MGO) and the aquila optimizer (AO).
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