The authors looked at how vocabulary is impacted in Alzheimer's disease and whether it could be used a predictor of disease onset.
Read More...Decline in vocabulary richness in individuals with Alzheimer's disease
The authors looked at how vocabulary is impacted in Alzheimer's disease and whether it could be used a predictor of disease onset.
Read More...Analysis of ultraviolet light as a bactericide of gram-negative bacteria in Cladophora macroalgae extracts
Here, the authors sought to use Cladophora macroalgae as a possible antibiotic to address the growing threat of antibiotic resistance in pathogenic bacteria. However, when they observed algae extracts to be greatly contaminated with gram-negative bacteria, they adapted to explore the ability to use ultraviolet light as a bactericide. They found that treatment with ultraviolet light had a significant effect.
Read More...The effects of Helianthus Annuus on Amyotrophic Lateral Sclerosis using Drosophila Melanogaster
Amyotrophic lateral sclerosis (ALS) affects nearly 200,000 people worldwide and there is currently no cure. The purpose of the study was to determine if Helianthus annuus seeds helped reduce nerve degeneration and increase locomotion using Drosophila melanogaster as the model organism. Through this experiment, we found a general trend suggesting that H. annuus helped increase the mobility of the D. melanogaster suggesting it could be a viable supplement for patients with ALS.
Read More...String analysis of exon 10 of the CFTR gene and the use of Bioinformatics in determination of the most accurate DNA indicator for CF prediction
Cystic fibrosis is a genetic disease caused by mutations in the CFTR gene. In this paper, the authors attempt to identify variations in stretches of up to 8 nucleotides in the protein-coding portions of the CFTR gene that are associated with disease development. This would allow screening of newborns or even fetuses in utero to determine the likelihood they develop cystic fibrosis.
Read More...Predicting sickle cell vaso-occlusion by microscopic imaging and modeling
The authors use blood smears from individuals with sickle cell disease to correlate sickle cell frequency with the occurrence of vaso-occlusive crises.
Read More...Quantitative analysis and development of alopecia areata classification frameworks
This article discusses Alopecia areata, an autoimmune disorder causing sudden hair loss due to the immune system mistakenly attacking hair follicles. The article introduces the use of deep learning (DL) techniques, particularly convolutional neural networks (CNN), for classifying images of healthy and alopecia-affected hair. The study presents a comparative analysis of newly optimized CNN models with existing ones, trained on datasets containing images of healthy and alopecia-affected hair. The Inception-Resnet-v2 model emerged as the most effective for classifying Alopecia Areata.
Read More...Investigating the impact of electrocardiography biofeedback on POTS symptom management
The authors test electrocardiography biofeedback as a treatment for individuals with Postural Orthostatic Tachycardia Syndrome.
Read More...Aberrant response to dexamethasone suppression test associated with inflammatory response in MDD patients
Major depressive disorder (MDD) is a prevalent mood disorder. The direct causes and biological mechanisms of depression still elude understanding, though genetic factors have been implicated. This study looked to identify the mechanism behind the aberrant response to the dexamethasone suppression test (DST) displayed by MDD patients, in which they display a lack of cortisol suppression. Analysis revealed several pro-inflammatory genes that were significant and differentially expressed between affected and non-affected groups in response to the DST. Looking at ways to decrease the inflammatory response could have implications for treatment and may explain why some people treated for depression still display symptoms or may lead researchers to different classes of drugs for treatment.
Read More...Using a Risk Assessment Questionnaire to Identify Prediabetics and Diabetics in Tandag, Philippines
Diabetes is a growing health concern in the developing world. This study aimed to develop a questionnaire that uses factors including age, blood pressure, BMI, and family history to predict whether Filipino participants are at risk for diabetes.
Read More...Study of neural network parameters in detecting heart disease
The authors looked at the ability to detect heart disease before the onset of severe clinical symptoms.
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