Ageing is a complex multifactorial process involving a progressive physiological decline that, ultimately, leads to the death of an organism. It involves multiple changes in many components that play fundamental roles under healthy and pathological conditions. Simultaneously, every organism undergoes accumulative 'wear and tear' during its lifespan, which confounds the effects of the ageing process. The scenario is complicated even further by the presence of both age-dependent and age-independent competing causes of death. Various manipulations have been shown to interfere with the ageing process. Calorie restriction, for example, has been reported to increase the lifespan of a wide range of organisms, which suggests a strong relation between energy metabolism and ageing. Such a link is also supported within the main theories for ageing: the free radical hypothesis, for instance, links oxidative damage production directly to energy metabolism. The Dynamic Energy Budgets (DEB) theory, which characterizes the uptake and use of energy by living organisms, therefore constitutes a useful tool for gaining insight into the ageing process. Here we compare the existing DEB-based modelling approaches and, then, discuss how new biological evidence could be incorporated within a DEB framework.
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http://dx.doi.org/10.1098/rstb.2010.0071 | DOI Listing |
Age Ageing
January 2025
Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China.
Background: A mobile cognition scale for community screening in cognitive impairment with rigorous validation is in paucity. We aimed to develop a digital scale that overcame low education for community screening for mild cognitive impairment (MCI) due to Alzheimer's disease (AD) and AD.
Methods: A mobile cognitive self-assessment scale (CogSAS) was designed through the Delphi process, which is feasible for the older population with low education.
STAR Protoc
January 2025
CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China. Electronic address:
Mammalian Dicer has been proved to be functional on double-stranded RNAs (dsRNAs) and involved in antiviral immunity or immune regulation. Here, we present a protocol for identifying Dicer as a dsRNA binding and cleaving factor to transfected dsRNA in cell lines, based on small RNA sequencing (RNA-seq) and dsRNA-immunoprecipitation (dsRNA-IP). We detail both experimental processes and analysis on small RNA-seq data.
View Article and Find Full Text PDFFront Biosci (Landmark Ed)
January 2025
Cardiometabolic and Endocrine Institute, North Brunswick, NJ 08902, USA.
Human skin is a physical and biochemical barrier that protects the internal body from the external environment. Throughout a person's life, the skin undergoes both intrinsic and extrinsic aging, leading to microscopic and macroscopic changes in its morphology. In addition, the repair processes slow with aging, making the older population more susceptible to skin diseases.
View Article and Find Full Text PDFJ Integr Neurosci
January 2025
Department of Brain Disease Center, The First Affiliated Hospital of Anhui University of Chinese Medicine, 230031 Hefei, Anhui, China.
Background: White matter (WM) is a principal component of the human brain, forming the structural basis for neural transmission between cortico-cortical and subcortical structures. The impairment of WM integrity is closely associated with the aging process, manifesting as the reorganization of brain networks based on graph theoretical analysis of complex networks and increased volume of white matter hyperintensities (WMHs) in imaging studies.
Methods: This study investigated changes in the robustness of WM brain networks during aging and assessed their correlation with WMHs.
Nutrients
January 2025
Department of Computer Engineering, Inje University, Gimhae 50834, Republic of Korea.
Background: Food image recognition, a crucial step in computational gastronomy, has diverse applications across nutritional platforms. Convolutional neural networks (CNNs) are widely used for this task due to their ability to capture hierarchical features. However, they struggle with long-range dependencies and global feature extraction, which are vital in distinguishing visually similar foods or images where the context of the whole dish is crucial, thus necessitating transformer architecture.
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