![Post-Traumatic Stress Disorder (PTSD) biomarker identification using a deep learning model](/rails/active_storage/representations/proxy/eyJfcmFpbHMiOnsibWVzc2FnZSI6IkJBaHBBczhMIiwiZXhwIjpudWxsLCJwdXIiOiJibG9iX2lkIn19--5dc18d2a26a53e84e94f5947b270b49ddf9da907/eyJfcmFpbHMiOnsibWVzc2FnZSI6IkJBaDdCem9MWm05eWJXRjBTU0lJYW5CbkJqb0dSVlE2QzNKbGMybDZaVWtpRFRZd01IZzJNREErQmpzR1ZBPT0iLCJleHAiOm51bGwsInB1ciI6InZhcmlhdGlvbiJ9fQ==--a3b53ba1a0f83efef18f6e75a8d4ce784384bee2/JEI-21-161_Fig1.jpg)
In this study, a deep learning model is used to classify post-traumatic stress disorder patients through novel markers to assist in finding candidate biomarkers for the disorder.
Read More...Post-Traumatic Stress Disorder (PTSD) biomarker identification using a deep learning model
In this study, a deep learning model is used to classify post-traumatic stress disorder patients through novel markers to assist in finding candidate biomarkers for the disorder.
Read More...A machine learning approach for abstraction and reasoning problems without large amounts of data
While remarkable in its ability to mirror human cognition, machine learning and its associated algorithms often require extensive data to prove effective in completing tasks. However, data is not always plentiful, with unpredictable events occurring throughout our daily lives that require flexibility by artificial intelligence utilized in technology such as personal assistants and self-driving vehicles. Driven by the need for AI to complete tasks without extensive training, the researchers in this article use fluid intelligence assessments to develop an algorithm capable of generalization and abstraction. By forgoing prioritization on skill-based training, this article demonstrates the potential of focusing on a more generalized cognitive ability for artificial intelligence, proving more flexible and thus human-like in solving unique tasks than skill-focused algorithms.
Read More...Uncovering mirror neurons’ molecular identity by single cell transcriptomics and microarray analysis
In this study, the authors use bioinformatic approaches to characterize the mirror neurons, which are active when performing and seeing certain actions. They also investigated whether mirror neuron impairment was connected to neural degenerative diseases and psychiatric disorders.
Read More...Machine learning on crowd-sourced data to highlight coral disease
Triggered largely by the warming and pollution of oceans, corals are experiencing bleaching and a variety of diseases caused by the spread of bacteria, fungi, and viruses. Identification of bleached/diseased corals enables implementation of measures to halt or retard disease. Benthic cover analysis, a standard metric used in large databases to assess live coral cover, as a standalone measure of reef health is insufficient for identification of coral bleaching/disease. Proposed herein is a solution that couples machine learning with crowd-sourced data – images from government archives, citizen science projects, and personal images collected by tourists – to build a model capable of identifying healthy, bleached, and/or diseased coral.
Read More...Effect of Increasing Concentrations of Cannabidiol (CBD) on Hatching, Survival and Development of Artemia salina
Cannabidiol, or CBD, is a widely available over the counter treatment used for various medical conditions. However, CBD exerts its effects on the endocannabinoid system, which is involved in neural maturation, and could potentially have adverse effects on brain development. Here, the impact of CBD on the development of brine shrimp (Artemia salina) was assessed. Differences in dose responses were observed.
Read More...Similarity Graph-Based Semi-supervised Methods for Multiclass Data Classification
The purpose of the study was to determine whether graph-based machine learning techniques, which have increased prevalence in the last few years, can accurately classify data into one of many clusters, while requiring less labeled training data and parameter tuning as opposed to traditional machine learning algorithms. The results determined that the accuracy of graph-based and traditional classification algorithms depends directly upon the number of features of each dataset, the number of classes in each dataset, and the amount of labeled training data used.
Read More...The non-nutritive sweeteners acesulfame potassium and neotame slow the regeneration rate of planaria
The consumption of sugar substitute non-nutritive sweeteners (NNS) has dramatically increased in recent years. Despite being advertised as a healthy alternative, NNS have been linked to adverse effects on the body, such as neurodegenerative diseases (NDs). In NDs, neural stem cell function is impaired, which inhibits neuron regeneration. The purpose of this study was to determine if the NNS acesulfame potassium (Ace-K) and neotame affect planaria neuron regeneration rates. Since human neurons may regenerate, planaria, organisms with extensive regenerative capabilities due to stem cells called neoblasts, were used as the model organism. The heads of planaria exposed to either a control or non-toxic concentrations of NNS were amputated. The posterior regions of the planaria were observed every 24 hours to see the following regeneration stages: (1) wound healing, (2) blastema development, (3) growth, and (4) differentiation. The authors hypothesized that exposure to the NNS would slow planaria regeneration rates. The time it took for the planaria in the Ace-K group and the neotame group to reach the second, third, and fourth regeneration stage was significantly greater than that of the control. The results of this study indicated that exposure to the NNS significantly slowed regeneration rates in planaria. This suggests that the NNS may adversely impact neoblast proliferation rates in planaria, implying that it could impair neural stem cell proliferation in humans, which plays a role in NDs. This study may provide insight into the connection between NNS, human neuron regeneration, and NDs.
Read More...Linear and non-linear summation of responses to visual and olfactory cues in male Drosophila melanogaster
In this study, the authors investigate whether phototaxis and odortaxis in Drosophila melanogaster occurs through linear summation of cues including light and attractive odorants.
Read More...Activated NF-κB Pathway in an Irf6-Deficient Mouse Model for Van der Woude Syndrome
Van der Woude syndrome is a common birth defect caused by mutations in the gene Irf6. In this project, students used microarray expression analysis from wild-type and Irf6-deficient mice in order to identify gene networks or pathways differentially regulated due to the Irf6 mutation. They found NF-κB pathway to be activated in deficient mice.
Read More...A Statistical Comparison of the Simultaneous Attack/ Persistent Pursuit Theory Against Current Methods in Counterterrorism Using a Stochastic Model
Though current strategies in counterterrorism are somewhat effective, the Simultaneous Attack/Persistent Pursuit (SAPP) Theory may be superior alternative to current methods. The authors simulated five attack strategies (1 SAPP and 4 non-SAPP), and concluded that the SAPP model was significantly more effective in reducing the final number of terrorist attacks. This demonstrates the comparative advantage of utilizing the SAPP model, which may prove to be critical in future efforts in counterterrorism.
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