The authors compare neuroimaging datasets to identify potential new biomarkers for earlier detection of Alzheimer's disease.
Read More...Predictions of neural control deficits in elders with subjective memory complaints and Alzheimer’s disease
The authors compare neuroimaging datasets to identify potential new biomarkers for earlier detection of Alzheimer's disease.
Read More...Sex differences in confidence and memory
In this work, the authors sought to provide an original experiment to investigate the conflict over whether males or females tend to exhibit greater accuracy or confidence in their memories. By using an online portal to obtain a convenience sample, the authors found that their results suggest that though males tend to be more confident regarding their memories, they may in fact remember fewer details. The authors suggest that these findings merit further research before making systematic changes regarding crime scene recall settings.
Read More...Stock price prediction: Long short-term memory vs. Autoformer and time series foundation model
The authors looked the ability to predict future stock prices using various machine learning models.
Read More...Examining the impact of the sympathetic nervous system on short-term memory
The authors looked at how activation of the sympathetic nervous system impacts short-term memory.
Read More...The impact of culturally informed music therapy on visually impaired youth: A Jaffna, Sri Lanka study
The authors looked at the effect of music therapy on visually impaired youth. They found that culturally relevant curricula is an important consideration while also showing that broadly music therapy enhances working memory, emotional well-being and inhibitory control.
Read More...The study of technology and the use of individual cognitive effort
A trial study was performed in 2021 to investigate the link between technology and transactive memory. Transactive memory is shared knowledge in which members share the responsibility to encode, store, and retrieve certain tasks or assignments, leading to a successful and collective performance. We hypothesize that a participants’ expected access to an external source affects the recall rate and retrieval of information.
Read More...Diagnosing hypertrophic cardiomyopathy using machine learning models on CMRs and EKGs of the heart
Here seeking to develop a method to diagnose, hypertrophic cardiomyopathy which can cause sudden cardiac death, the authors investigated the use of a convolutional neural network (CNN) and long short-term memory (LSTM) models to classify cardiac magnetic resonance and heart electrocardiogram scans. They found that the CNN model had a higher accuracy and precision and better other qualities, suggesting that machine learning models could be valuable tools to assist physicians in the diagnosis of hypertrophic cardiomyopathy.
Read More...VISTA inhibitor CA170 combined with KRAS vaccine enhances immune response in lung cancer
Here the authors investigated a combination therapy to target the Kirsten rat sarcoma viral oncogene homolog mutation in lung cancer, by analyzing publicly available data. Their findings indicate that the combination therapy of CA170 and Kvax enhances helper T cell function and improves cytotoxic T lymphocyte infiltration, while Kvax alone drives plasma and memory B cell proliferation.
Read More...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.
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