Is EEG Entropy a Useful Measure for Alzheimer's Disease?

BACKGROUND: The number of individuals diagnosed with Alzheimer's disease (AD) has increased, and it is estimated to continue rising in the coming years. The diagnosis of this disease is challenging due to variations in onset and course, its diverse clinical manifestations, and the indications for measuring deposit biomarkers. Hence, there is a need to develop more precise and less invasive diagnostic tools. Multiple studies have considered using electroencephalography (EEG) entropy measures as an indicator of the onset and course of AD. Entropy is deemed suitable as a potential indicator based on the discovery that variations in its complexity can be associated with specific pathologies such as AD. METHODOLOGY: Following PRISMA guidelines, a literature search was conducted in 4 scientific databases, and 40 articles were analyzed after discarding and filtering. RESULTS: There is a diversity in entropy measures; however, Sample Entropy (SampEn) and Multiscale Entropy (MSE) are the most widely used (21/40). In general, it is found that when comparing patients with controls, patients exhibit lower entropy (20/40) in various areas. Findings of correlation with the level of cognitive decline are less consistent, and with neuropsychiatric symptoms (2/40) or treatment response less explored (2/40), although most studies show lower entropy with greater severity. Machine learning-based studies show good discrimination capacity. CONCLUSIONS: There is significant difficulty in comparing multiple studies due to their heterogeneity; however, changes in Multiscale Entropy (MSE) scales or a decrease in entropy levels are considered useful for determining the presence of AD and measuring its severity.

Effects of combined drought and pathogen stress on growth, resistance and gene expression in young Norway spruce trees.

Drought-induced mortality is a major direct effect of climate change on tree health, but drought can also affect trees indirectly by altering their susceptibility to pathogens. Here, we report how a combination of mild or severe drought and pathogen infection affected the growth, pathogen resistance and gene expression in potted 5-year-old Norway spruce trees [Picea abies (L.) Karst.]. After 5 weeks of drought, trees were inoculated with the fungal pathogen Endoconidiophora polonica. Combined drought-pathogen stress over the next 8 weeks led to significant reductions in the growth of drought-treated trees relative to well-watered trees and more so in trees subjected to severe drought. Belowground, growth of the smallest fine roots was most affected. Aboveground, shoot diameter change was most sensitive to the combined stress, followed by shoot length growth and twig biomass. Both drought-related and some resistance-related genes were upregulated in bark samples collected after 5 weeks of drought (but before pathogen infection), and gene expression levels scaled with the intensity of drought stress. Trees subjected to severe drought were much more susceptible to pathogen infection than well-watered trees or trees subjected to mild drought. Overall, our results show that mild drought stress may increase the tree resistance to pathogen infection by upregulating resistance-related genes. Severe drought stress, on the other hand, decreased tree resistance. Because drought episodes are expected to become more frequent with climate change, combined effects of drought and pathogen stress should be studied in more detail to understand how these stressors interactively influence tree susceptibility to pests and pathogens.