Here, recognizing the difficulty associated with tracking the progression of dementia, the authors used machine learning models to predict between the presence of cognitive normalcy, mild cognitive impairment, and Alzheimer's Disease, based on blood DNA methylation levels, sex, and age. With four machine learning models and two dataset dimensionality reduction methods they achieved an accuracy of 53.33%.
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Prediction of preclinical Aβ deposit in Alzheimer’s disease mice using EEG and machine learning
Alzheimer’s disease (AD) is a common disease affecting 6 million people in the U.S., but no cure exists. To create therapy for AD, it is critical to detect amyloid-β protein in the brain at the early stage of AD because the accumulation of amyloid-β over 20 years is believed to cause memory impairment. However, it is difficult to examine amyloid-β in patients’ brains. In this study, we hypothesized that we could accurately predict the presence of amyloid-β using EEG data and machine learning.
Read More...A Novel Alzheimer's Disease Therapeutic Model: Attenuating Hyperphosphorylated Tau and Amyloid β (Aβ) Aggregates by Characterizing Antioxidative, Anti-Inflammatory, and Neuroprotective Properties of Natural Extracts
Oxidative damage and neuro-inflammation were the key pathways implicated in the pathogenesis of Alzheimer’s disease. In this study, 30 natural extracts from plant roots and leaves with extensive anti-inflammatory and anti-oxidative properties were consumed by Drosophila melanogaster. Several assays were performed to evaluate the efficacy of these combinational extracts on delaying the progression of Alzheimer’s disease. The experimental group showed increased motor activity, improved associative memory, and decreased lifespan decline relative to the control group.
Read More...Rubik’s cube: What separates the fastest solvers from the rest?
In this study, the authors assess the factors that allow some speedcubers to solve Rubik's Cubes faster than others.
Read More...A novel approach for early detection of Alzheimer’s disease using deep neural networks with magnetic resonance imaging
In the battle against Alzheimer's disease, early detection is critical to mitigating symptoms in patients. Here, the authors use a collection of MRI scans, layering with deep learning computer modeling, to investigate early stages of AD which can be hard to catch by human eye. Their model is successful, able to outperform previous models, and detected regions of interest in the brain for further consideration.
Read More...Luteolin's positive inhibition of melanoma cell lines.
Luteolin (3′,4′,5,7-tetrahydroxyflavone) is a flavonoid that occurs in fruits, vegetables, and herbs. Research suggests that luteolin is effective against various forms of cancer by triggering apoptosis pathways. This experiment analyzes the effects of luteolin on the cell viability of malignant melanoma cells using an in vitro experiment to research alternative melanoma treatments and hopefully to help further cancer research as a whole.
Read More...Machine Learning Algorithm Using Logistic Regression and an Artificial Neural Network (ANN) for Early Stage Detection of Parkinson’s Disease
Despite the prevalence of PD, diagnosing PD is expensive, requires specialized testing, and is often inaccurate. Moreover, diagnosis is often made late in the disease course when treatments are less effective. Using existing voice data from patients with PD and healthy controls, the authors created and trained two different algorithms: one using logistic regression and another employing an artificial neural network (ANN).
Read More...Using the COmplex PAthway SImulator, Stage Analysis, and Chemical Kinetics to Develop a Novel Solution to Lower Tau Concentrations in Alzheimer’s Disease
In this study, the authors ask whether a Tau immunotherapy treatment, Hsp70 protein treatment, or dual treatment approach of both the Tau imunotherapy treatment and Hsp70 protein treatment leads to a greater reduction in Tau protein concentration in Alzheimer's disease. Overall, they conclude that the effectiveness of the treatment ultimately relies on the stage of Alzheimer’s.
Read More...People’s Preference to Bet on Home Teams Even When Losing is Likely
In this study, the authors investigate situations in which people make sports bets that seem to go against their better judgement. Using surveys, individuals were asked to bet on which team would win in scenarios when their home team was involved and others when they were not to determine whether fandom for a team can overshadow fans’ judgment. They found that fans bet much more on their home teams than neutral teams when their team was facing a large deficit.
Read More...Potential Multifunctional Agents for Dual Therapy of Age-Related and Associated Diseases: Alzheimer’s Disease and Type 2 Diabetes Mellitus
Studies show an age-related link between Alzheimer’s Disease and Type 2 Diabetes Mellitus with oxidative stress a characteristic of both. Here, methanolic fractionations and extracts of four Ayurvedic plants were assessed for their protective abilities using a number of in vitro assays. Extracts inhibited oxidative stress and reduced activity of key enzymes involved in the pathogenesis of both diseases in neuroblastoma cells.
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