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The range of human neurodegenerative diseases continues to pose significant unmet medical needs for societies around the world. The progressive and terminal nature of these conditions places a considerable personal burden on the individual affected but also on public health systems and health services. Tens of millions of people are indiscriminately affected by various dementias, which are rising at an alarming rate. There are no cures for many conditions, and it is clear that treatments applied as early as possible could greatly improve outcomes for patients. Therefore, new disease classification and diagnostic tools should be a key priority. Metabolomics represents a relatively new field of analytical science, which can be extremely useful in the early diagnosis of disease. The relatively unique feature of metabolites is that they sit at the intersection between the genetic background of an organism and its environment. Because many neurodegenerative diseases are not genetically inherited (instead having a range of known genetic risk factors and also a large number of unknown environmental triggers) the field of metabolomics offers great promise for the discovery of new, biologically, and clinically relevant biomarkers for neurodegenerative disorders. It is already bringing forward new knowledge in terms of the mechanisms of neurodegenerative disease.
glutamic acid --- n/a --- direct mass spectrometry --- neurodegeneration --- 6-OHDA --- targeted mass spectrometry --- mitochondrial dysfunction --- myo-inositol --- metabolomics --- bile acids --- subacute mild traumatic brain injury --- age-related macular degeneration --- metabolic pathways --- energy metabolism --- midbrain --- Alzheimer’s disease --- biomarkers --- 1H NMR --- Parkinson’s disease dementia --- GC-MS --- pathogenesis --- tricarboxylic acid cycle --- micro-dialysis --- 13C-labeled succinate --- metabolism --- lipidomics --- dementia with Lewy bodies --- fatty acid --- prodromal Parkinson’s disease --- malonate --- cerebral ischemia --- mass spectrometry --- retinal pigment epithelium --- excitotoxicity --- endothelin-1 --- reperfusion --- C. elegans --- Streptomyces venezuelae --- ?-synuclein aggregates --- natural product --- fatty acid metabolism --- imaging mass spectrometry --- LC-MS --- drusen --- cerebral palsy --- plasma --- Parkinson’s disease --- Alzheimer's disease --- Parkinson's disease dementia --- prodromal Parkinson's disease --- Parkinson's disease
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It is important to prevent and manage the frailty of the elderly because their muscle strength and physical activity decrease in old age, making them prone to falling, depression, and social isolation. In the end, they need to be admitted to a hospital or a nursing home. When successful aging fails and motor ability declines due to illness, malnutrition, or reduced activity, frailty eventually occurs. Once frailty occurs, people with frailty do not have the power to exercise or the power to move. The functions of the heart and muscles are deteriorated more rapidly when they are not used. Consequently, frailty goes through a vicious cycle. As one’s physical fitness is deteriorated, the person has less power to exercise, poorer cognitive functions, and inferior nutrition intake. Consequently, the whole body of the person deteriorates. Therefore, in addition to observational studies to identify risk factors for preventing aging, various intervention studies have been conducted to develop exercise programs and apply them to communities, hospitals, and nursing homes for helping the elderly maintain healthy lives. Until now, most aging studies have focused on physical frailty. However, social frailty and cognitive frailty affect senile health negatively just as much as physical frailty. Nevertheless, little is known about social frailty and cognitive frailty. This special issue includes original experimental studies, reviews, systematic reviews, and meta-analysis studies on the prevention of senescence (physical senescence, cognitive senescence, social senescence), high-risk group detection, differentiation, and intervention.
Public health & preventive medicine --- brain stimulation --- dementia --- meta-analysis --- naming --- primary progressive aphasia --- qualitative evaluation --- cognitive function --- data mining --- Parkinson’s disease with mild cognitive impairment --- random forest --- neuropsychological test --- motoric cognitive risk syndrome --- fall --- gait speed --- three-item recall --- older adults --- mixing ability --- color-changing chewing gum --- frailty --- cross-sectional study --- spousal concordance --- aging --- aged --- accidental falls --- pain --- mild cognitive impairment --- depressive symptoms --- frailty profiles --- latent class analysis --- quality of life --- perceived health --- frailty syndrome --- physiotherapy --- exercise --- mood --- BDI --- STAI --- SWLS --- muscle strength --- community-dwelling older adults --- physical frailty --- prevalence --- risk factors --- non-robust --- FRAIL scale --- Tilburg Frailty Indicator --- determinants --- community-based --- sleep quality --- middle-aged and older adults --- SUNFRAIL --- psychometric properties --- screening tool --- social isolation --- social networks --- social support --- social participation --- Parkinson’s disease dementia --- instrumental activities of daily living --- clinical dementia rating --- convergence rate --- neuropsychological tests --- neuropsychiatric symptoms --- explainable artificial intelligence --- machine learning --- stacking ensemble --- Self-Rating Anxiety Scale --- multiple risk factors --- fall assessment sheet --- elderly patients --- hospitalization --- risk management --- driving cessation --- meaningful activities --- psychosomatic functions --- physical functional performance --- nursing homes --- physical fitness --- gait analysis --- indicators --- screening --- artificial intelligence --- healthcare --- frail --- Baduanjin --- strength training --- endurance training --- Explainable Artificial Intelligence
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