In this study, the authors investigate whether Eisenia Fetida nerve signal speed correlates with Withania somnifera ingestion, a possible way to protect against demyelination.
Read More...Effects of Withania Somnifera on Charcot-Marie-Tooth Disease Type 1A in the model organism Eisenia Fetida
In this study, the authors investigate whether Eisenia Fetida nerve signal speed correlates with Withania somnifera ingestion, a possible way to protect against demyelination.
Read More...The effect of nicotine and lead on neuron morphology, function, and ɑ-Synuclein levels in a C. elegans model
E-cigarettes are often considered a healthier alternative to traditional cigarettes. This team of high school authors investigated the impact of common e-cigarette compounds on C. elegans, and found a number of harmful effects ultimately resulting in injury and neuronal damage.
Read More...Impact of gadodiamide (Omniscan) on a beef liver catalase ex vivo model
Here, seeking to better understand the effects of gadolinium-based contrast agents, dyes typically used for MRI scans, the authors evaluated the activity of catalase found in beef liver both with and without gadodiamide when exposed to hydrogen peroxide. They found that gadioamide did not significantly inhibit catalase's activity, attributing this lack of effects to the chelating agent found in gadodiamide.
Read More...Collaboration beats heterogeneity: Improving federated learning-based waste classification
Based on the success of deep learning, recent works have attempted to develop a waste classification model using deep neural networks. This work presents federated learning (FL) for a solution, as it allows participants to aid in training the model using their own data. Results showed that with less clients, having a higher participation ratio resulted in less accuracy degradation by the data heterogeneity.
Read More...Groundwater prediction using artificial intelligence: Case study for Texas aquifers
Here, in an effort to develop a model to predict future groundwater levels, the authors tested a tree-based automated artificial intelligence (AI) model against other methods. Through their analysis they found that groundwater levels in Texas aquifers are down significantly, and found that tree-based AI models most accurately predicted future levels.
Read More...Molecular Dynamics Simulations of Periplasmic Proteins Interacting With the Peptidoglycan Layer of Escherichia coli
Molecular dynamics (MD) simulations are a great tool to model and study complex biological systems. In this paper, the authors use MD simulations to construct and simulate a model of the periplasmic space, the peptidoglycan layer and its associated proteins, in an Escherichia coli cell.
Read More...The Effect of the Human MeCP2 gene on Drosophila melanogaster behavior and p53 inhibition as a model for Rett Syndrome
In this study, the authors observe if the symptoms of Rett Syndrome, a neurodegenerative disease in humans, are reflected in Drosophila melanogaster. This was achieved by differentiating the behavior and physical aspects of wild-type flies from flies expressing the full-length MeCP2 gene and the mutated MeCP2 gene (R106W). After conducting these experiments, some of the Rett Syndrome symptoms were recapitulated in Drosophila, and a subset of those were partially ameliorated by the introduction of pifithrin-alpha.
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...Development of Diet-Induced Insulin Resistance in Drosophila melanogaster and Characterization of the Anti-Diabetic Effects of Resveratrol and Pterostilbene
Dhar and colleagues established a Type II diabetes mellitus (T2DM) model in fruit flies, using this model to induce insulin resistance and characterize the effects Resveratrol and Pterostilbene on a number of growth and activity metrics. Resveratrol and Pterostilbene treatment notably overturned the weight gain and glucose levels. The results of this study suggest that Drosophila can be utilized as a model organism to study T2DM and novel pharmacological treatments.
Read More...Differential privacy in machine learning for traffic forecasting
In this paper, we measured the privacy budgets and utilities of different differentially private mechanisms combined with different machine learning models that forecast traffic congestion at future timestamps. We expected the ANNs combined with the Staircase mechanism to perform the best with every value in the privacy budget range, especially with the medium high values of the privacy budget. In this study, we used the Autoregressive Integrated Moving Average (ARIMA) and neural network models to forecast and then added differentially private Laplacian, Gaussian, and Staircase noise to our datasets. We tested two real traffic congestion datasets, experimented with the different models, and examined their utility for different privacy budgets. We found that a favorable combination for this application was neural networks with the Staircase mechanism. Our findings identify the optimal models when dealing with tricky time series forecasting and can be used in non-traffic applications like disease tracking and population growth.
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