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Caenorhabditis elegans is an exceptionally valuable model for aging research because of many advantages, including its genetic tractability, short lifespan, and clear age‐dependent physiological changes. Aged C. elegans display a decline in their anatomical and functional features, including tissue integrity, motility, learning and memory, and immunity. Caenorhabditis elegans also exhibit many age‐associated changes in the expression of microRNAs and stress‐responsive genes and in RNA and protein quality control systems. Many of these age‐associated changes provide information on the health of the animals and serve as valuable biomarkers for aging research. Here, we review the age‐dependent changes in C. elegans and their utility as aging biomarkers indicative of the physiological status of aging.

Aging is associated with gradual deterioration of physiological and biochemical functions, including cognitive decline. Transcriptome profiling of brain samples from individuals of varying ages has identified the whole-transcriptome changes that underlie age-associated cognitive declines. In this review, we discuss transcriptome-based research on human brain aging performed by using microarray and RNA sequencing analyses. Overall, decreased synaptic function and increased immune function are prevalent in most regions of the aged brain. Age-associated gene expression changes are also cell dependent and region dependent and are affected by genotype. In addition, the transcriptome changes that occur during brain aging include different splicing events, intersample heterogeneity, and altered levels of various types of noncoding RNAs. Establishing transcriptome-based hallmarks of human brain aging will improve the understanding of cognitive aging and neurodegenerative diseases and eventually lead to interventions that delay or prevent brain aging.Brain aging: RNA profiling to elucidate cognitive declineExtensive exploration of RNA changes in the human brain over time should provide hallmarks for cognitive decline and neurodegenerative diseases. Changes in the messenger RNA profile, the ‘transcriptome’, of individual cells play a key role in brain aging, and could influence the progression of neurodegenerative diseases. Seung-Jae V. Lee and Seokjin Ham at the Korea Advanced Institute of Science and Technology, Daejeon, South Korea, reviewed current understanding of brain aging gained via transcriptomic profiling. Most aging brain regions display decreased synaptic function and plasticity, together with increased expression of immune response genes. Individual genotypes influence specific regional and cellular transcriptomic changes. The role of RNA-binding proteins and changes in expression of non-coding RNAs are of particular interest. The researchers call for widespread research in all ethnic groups, as most studies involve mainly Caucasian participants.

Low temperatures delay aging and promote longevity in many organisms. However, the metabolic and homeostatic aspects of low-temperature-induced longevity remain poorly understood. Here, we show that lipid homeostasis regulated by Caenorhabditis elegans Mediator 15 (MDT-15 or MED15), a transcriptional coregulator, is essential for low-temperature-induced longevity and proteostasis. We find that inhibition of mdt-15 prevents animals from living long at low temperatures. We show that MDT-15 up-regulates fat-7, a fatty acid desaturase that converts saturated fatty acids (SFAs) to unsaturated fatty acids (UFAs), at low temperatures. We then demonstrate that maintaining a high UFA/SFA ratio is essential for proteostasis at low temperatures. We show that dietary supplementation with a monounsaturated fatty acid, oleic acid (OA), substantially mitigates the short life span and proteotoxicity in mdt-15(-) animals at low temperatures. Thus, lipidostasis regulated by MDT-15 appears to be a limiting factor for proteostasis and longevity at low temperatures. Our findings highlight the crucial roles of lipid regulation in maintaining normal organismal physiology under different environmental conditions.

Microgrid is becoming an essential part of the power grid regarding reliability, economy, and environment. Renewable energies are main sources of energy in microgrids. Long-term solar generation forecasting is an important issue in microgrid planning and design from an engineering point of view. Solar generation forecasting mainly depends on solar radiation forecasting. Long-term solar radiation forecasting can also be used for estimating the degradation-rate-influenced energy potentials of photovoltaic (PV) panel. In this paper, a comparative study of different deep learning approaches is carried out for forecasting one year ahead hourly and daily solar radiation. In the proposed method, state of the art deep learning and machine learning architectures like gated recurrent units (GRUs), long short term memory (LSTM), recurrent neural network (RNN), feed forward neural network (FFNN), and support vector regression (SVR) models are compared. The proposed method uses historical solar radiation data and clear sky global horizontal irradiance (GHI). Even though all the models performed well, GRU performed relatively better compared to the other models. The proposed models are also compared with traditional state of the art methods for long-term solar radiation forecasting, i.e., random forest regression (RFR). The proposed models outperformed the traditional method, hence proving their efficiency.

Magnetic torques generated through spin–orbit coupling1–8 promise energy-efficient spintronic devices. For applications, it is important that these torques switch films with perpendicular magnetizations without an external magnetic field9–14. One suggested approach15 to enable such switching uses magnetic trilayers in which the torque on the top magnetic layer can be manipulated by changing the magnetization of the bottom layer. Spin currents generated in the bottom magnetic layer or its interfaces transit the spacer layer and exert a torque on the top magnetization. Here we demonstrate field-free switching in such structures and show that its dependence on the bottom-layer magnetization is not consistent with the anticipated bulk effects15. We describe a mechanism for spin-current generation16,17 at the interface between the bottom layer and the spacer layer, which gives torques that are consistent with the measured magnetization dependence. This other-layer-generated spin–orbit torque is relevant to energy-efficient control of spintronic devices.

Transcriptome analysis has become increasingly utilized in aging research. However, the identification of the key molecular changes underlying aging processes and longevity‐promoting regimens from transcriptome data remains challenging. Here, we present Transcriptomic CLassification via Adaptive learning of Signature States (T‐CLASS), an online tool that identifies, from transcriptome data, gene sets of several hundred genes that provide an optimal representation of longevity and aging paradigms. We systematically evaluated the effectiveness of T‐CLASS with diverse datasets, including longevity‐promoting regimens in Caenorhabditis elegans, cellular senescence by different means in both cultured mouse primary cells and cultured human cells, and human sarcopenia. We found that T‐CLASS exhibited robust and high classification performance across datasets compared to preexisting machine/deep learning‐based gene selection tools. By focusing our further analysis on longevity‐promoting regimens in C. elegans, we showed that T‐CLASS successfully classified transcriptomic changes caused by ten lifespan‐extending small molecules, among which we experimentally validated the effect of rifampicin and atracurium as a proof of principle. Overall, T‐CLASS is an effective and practical tool for uncovering and classifying physiological changes caused by genetic and pharmacological interventions that affect aging. T‐CLASS is a web‐based tool that selects an optimal gene set to categorize and classify transcriptomic changes associated with aging and longevity.

Trehalose is a non-reducing disaccharide with two glucose molecules linked through an α, α-1,1-glucosidic bond. Trehalose has received attention for the past few decades for its role in neuroprotection especially in animal models of various neurodegenerative diseases, such as Parkinson and Huntington diseases. The mechanism underlying the neuroprotective effects of trehalose remains elusive. The prevailing hypothesis is that trehalose protects neurons by inducing autophagy, thereby clearing protein aggregates. Some of the animal studies showed activation of autophagy and reduced protein aggregates after trehalose administration in neurodegenerative disease models, seemingly supporting the autophagy induction hypothesis. However, results from cell studies have been less certain; although many studies claim that trehalose induces autophagy and reduces protein aggregates, the studies have their weaknesses, failing to provide sufficient evidence for the autophagy induction theory. Furthermore, a recent study with a thorough examination of autophagy flux showed that trehalose interfered with the flux from autophagosome to autolysosome, raising controversy on the direct effects of trehalose on autophagy. This review summarizes the fundamental properties of trehalose and the studies on its effects on neurodegenerative diseases. We also discuss the controversy related to the autophagy induction theory and seek to explain how trehalose works in neuroprotection.

Insulin/IGF-1 signaling (IIS) regulates various physiological aspects in numerous species. In Caenorhabditis elegans , mutations in the daf-2 /insulin/IGF-1 receptor dramatically increase lifespan and immunity, but generally impair motility, growth, and reproduction. Whether these pleiotropic effects can be dissociated at a specific step in insulin/IGF-1 signaling pathway remains unknown. Through performing a mutagenesis screen, we identified a missense mutation daf-18(yh1) that alters a cysteine to tyrosine in DAF-18/PTEN phosphatase, which maintained the long lifespan and enhanced immunity, while improving the reduced motility in adult daf-2 mutants. We showed that the daf-18(yh1) mutation decreased the lipid phosphatase activity of DAF-18/PTEN, while retaining a partial protein tyrosine phosphatase activity. We found that daf-18(yh1) maintained the partial activity of DAF-16/FOXO but restricted the detrimental upregulation of SKN-1/NRF2, contributing to beneficial physiological traits in daf-2 mutants. Our work provides important insights into how one evolutionarily conserved component, PTEN, can coordinate animal health and longevity. Mutations in daf-2 /insulin/IGF-1 receptor impair the growth and reproduction of C. elegans but conversely enhance immunity and lifespan. Here, the authors show that a missense mutation in the gene retains the effects on lifespan and immunity and improves motility.

Parkinson’s disease (PD) and Multiple System Atrophy (MSA) are clinically distinctive diseases that feature a common neuropathological hallmark of aggregated α-synuclein. Little is known about how differences in α-synuclein aggregate structure affect disease phenotype. Here, we amplified α-synuclein aggregates from PD and MSA brain extracts and analyzed the conformational properties using fluorescent probes, NMR spectroscopy and electron paramagnetic resonance. We also generated and analyzed several in vitro α-synuclein polymorphs. We found that brain-derived α-synuclein fibrils were structurally different to all of the in vitro polymorphs analyzed. Importantly, there was a greater structural heterogeneity among α-synuclein fibrils from the PD brain compared to those from the MSA brain, possibly reflecting on the greater variability of disease phenotypes evident in PD. Our findings have significant ramifications for the use of non-brain-derived α-synuclein fibrils in PD and MSA studies, and raise important questions regarding the one disease-one strain hypothesis in the study of α-synucleinopathies. Parkinson’s disease (PD) and Multiple System Atrophy (MSA) are characterized by the pathological accumulation of α-synuclein. Here the authors employ fluorescent probes, electron microscopy and NMR spectroscopy to study the properties of α-synuclein aggregates that were amplified from patient brain extracts and observe a greater structural diversity among PD patients compared to MSA patients.

Ageing is marked by physical decline. Caenorhabditis elegans is a valuable model for identifying genetic regulatory mechanisms of ageing and longevity. Here we report a simple method to assess C. elegans ’ maximum physical ability based on the worms’ maximum movement velocity. We show maximum velocity declines with age, correlates well with longevity, accurately reports movement ability and, if measured in mid-adulthood, is predictive of maximal lifespan. Contrary to recent findings, we observe that maximum velocity of worm with mutations in daf-2(e1370) insulin/IGF-1 signalling scales with lifespan. Because of increased odorant receptor expression, daf-2(e1370) mutants prefer food over exploration, causing previous on-food motility assays to underestimate movement ability and, thus, worm health. Finally, a disease-burden analysis of published data reveals that the daf-2(e1370) mutation improves quality of life, and therefore combines lifespan extension with various signs of an increased healthspan. Increases in lifespan do not necessarily translate into prolonged healthspan. Here, the authors devise a simple metric, maximum velocity, to study ageing in C. elegans and, using this metric, show that reduced insulin signalling improves physical healthspan as well as worm lifespan.