Millions of people are affected by neurodegenerative diseases worldwide. They occur due to the loss of brain functions or peripheral nervous system dysfunction. If untreated, prolonged condition ultimately leads to death. Mostly they are associated with stress, altered cholesterol metabolism, inflammation and organelle dysfunction. Endogenous cholesterol and phospholipids in brain undergo auto-oxidation by enzymatic as well as non-enzymatic modes leading to the formation of by-products such as 4-hydroxynonenal and oxysterols.
More than a century has passed since pathological protein aggregates were first identified in the brains of patients with neurodegenerative diseases (NDDs). Yet, we still do not have effective therapies to treat or slow the progression of these devastating diseases or diagnostics for early detection and monitoring disease progression.
Background: Alzheimer's disease (AD) is a progressive neurodegenerative disorder of the brain that ultimately results in the death of neurons and dementia. The prevalence of the disease in the world is increasing rapidly. In recent years, many studies have been done to automatically detect this disease from brain signals. Method: In this paper, the Hjorth parameters are used along with other common features to improve the AD detection accuracy from EEG signals in early stages.
Elsevier, Measurement: Journal of the International Measurement Confederation, Volume 171, February 2021
In the recent past, biomedical domain has become popular due to digital image processing of accurate and efficient diagnosis of clinical patients using Computer-Aided Diagnosis (CAD). Appropriate and punctual disease identification and treatment arrangement directs to enhance superiority of life and improved life hope in Alzheimer Disease (AD) patients. The cutting-edge approaches that believe multimodal analysis have been shown to be efficient and accurate are improved compared with manual analysis.
The enormous social and economic cost of Alzheimer's disease (AD) has driven a number of neuroimaging investigations for early detection and diagnosis. Towards this end, various computational approaches have been applied to longitudinal imaging data in subjects with Mild Cognitive Impairment (MCI), as serial brain imaging could increase sensitivity for detecting changes from baseline, and potentially serve as a diagnostic biomarker for AD. However, current state-of-the-art brain imaging diagnostic methods have limited utility in clinical practice due to the lack of robust predictive power.
Objective: Many studies evaluated how the Magnetic Resonance Imaging (MRI) field strength affects the effectiveness to detect neurodegenerative changes of Alzheimer's disease (AD), derived from atrophy or thickness. To the best of our knowledge, no study evaluated before how tissue texture changes are affected. In this research, hippocampus texture features extracted from 1.5 T and 3 T MRI are evaluated how are affected by the magnetic field strength.
Background: Evidences of infectious pathogens in Alzheimer's disease (AD) brains may suggest a deteriorated innate immune system in AD pathophysiology. We previously demonstrated reduced salivary lactoferrin (Lf) levels, one of the major antimicrobial proteins, in AD patients. Methods: To assess the clinical utility of salivary Lf for AD diagnosis, we examine the relationship between salivary Lf and cerebral amyloid-β (Aβ) load using amyloid-Positron-Emission Tomography (PET) neuroimaging, in two different cross-sectional cohorts including patients with different neurodegenerative disorders.
Traumatic brain injury (TBI) is one the most common human afflictions, contributing to long-term disability in survivors. Emerging data indicate that functional improvement or deterioration can occur years after TBI. In this regard, TBI is recognized as risk factor for late-life neurodegenerative disorders. TBI encompasses a heterogeneous disease process in which diverse injury subtypes and multiple molecular mechanisms overlap.
Dementia can disturb the circadian rhythm more than in normal ageing people. And their biological clock is often not enough stimulated by light. Sleep disturbances form a high burden for informal caregivers and is the main reason for institutionalization. The effect of biodynamic lighting with varying intensity and colour resembling a daylight curve has hardly been objectively researched. In this study, we evaluate the exposure to biodynamic lighting on circadian functioning of 13 patients with dementia admitted to a psychiatric hospital.
