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Development of Diet-Induced Insulin Resistance in Drosophila melanogaster and Characterization of the Anti-Diabetic Effects of Resveratrol and Pterostilbene

Dhar et al. | Jul 02, 2018

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.

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Differential privacy in machine learning for traffic forecasting

Vinay et al. | Dec 21, 2022

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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Development of a Novel Treatment Strategy to Treat Parkinsonian Neurodegeneration by Targeting Both Lewy Body Aggregation and Dopaminergic Neuronal Degradation in a Drosophila melanogaster Model

Sama et al. | Sep 25, 2019

Development of a Novel Treatment Strategy to Treat Parkinsonian Neurodegeneration by Targeting Both Lewy Body Aggregation and Dopaminergic Neuronal Degradation in a <em>Drosophila melanogaster</em> Model

In this article the authors address the complex and life quality-diminishing neurodegenerative disease known as Parkinson's. Although genetic and/or environmental factors contribute to the etiology of the disease, the diagnostic symptoms are the same. By genetically modifying fruit flies to exhibit symptoms of Parkinson's disease, they investigate whether drugs that inhibit mitochondrial calcium uptake or activate the lysosomal degradation of proteins could improve the symptoms of Parkinson's these flies exhibit. The authors report the most promising outcome to be that when both types of drugs were used together. Their data provides encouraging evidence to support further investigation of the utility of such drugs in the treatment of human Parkinson's patients.

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Quantitative definition of chemical synthetic pathway complexity of organic compounds

Baranwal et al. | Jun 19, 2023

Quantitative definition of chemical synthetic pathway complexity of organic compounds

Irrespective of the final application of a molecule, synthetic accessibility is the rate-determining step in discovering and developing novel entities. However, synthetic complexity is challenging to quantify as a single metric, since it is a composite of several measurable metrics, some of which include cost, safety, and availability. Moreover, defining a single synthetic accessibility metric for both natural products and non-natural products poses yet another challenge given the structural distinctions between these two classes of compounds. Here, we propose a model for synthetic accessibility of all chemical compounds, inspired by the Central Limit Theorem, and devise a novel synthetic accessibility metric assessing the overall feasibility of making chemical compounds that has been fitted to a Gaussian distribution.

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Contrasting role of ASCC3 and ALKBH3 in determining genomic alterations in Glioblastoma Multiforme

Sriram et al. | Sep 27, 2022

Contrasting role of <i>ASCC3</i> and <i>ALKBH3</i> in determining genomic alterations in Glioblastoma Multiforme

Glioblastoma Multiforme (GBM) is the most malignant brain tumor with the highest fraction of genome alterations (FGA), manifesting poor disease-free status (DFS) and overall survival (OS). We explored The Cancer Genome Atlas (TCGA) and cBioportal public dataset- Firehose legacy GBM to study DNA repair genes Activating Signal Cointegrator 1 Complex Subunit 3 (ASCC3) and Alpha-Ketoglutarate-Dependent Dioxygenase AlkB Homolog 3 (ALKBH3). To test our hypothesis that these genes have correlations with FGA and can better determine prognosis and survival, we sorted the dataset to arrive at 254 patients. Analyzing using RStudio, both ASCC3 and ALKBH3 demonstrated hypomethylation in 82.3% and 61.8% of patients, respectively. Interestingly, low mRNA expression was observed in both these genes. We further conducted correlation tests between both methylation and mRNA expression of these genes with FGA. ASCC3 was found to be negatively correlated, while ALKBH3 was found to be positively correlated, potentially indicating contrasting dysregulation of these two genes. Prognostic analysis showed the following: ASCC3 hypomethylation is significant with DFS and high ASCC3 mRNA expression to be significant with OS, demonstrating ASCC3’s potential as disease prediction marker.

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Pressure and temperature influence the efficacy of metal-organic frameworks for carbon capture and conversion

Lin et al. | May 07, 2023

Pressure and temperature influence the efficacy of metal-organic frameworks for carbon capture and conversion

Metal-organic frameworks (MOFs) are promising new nanomaterials for use in the fight against climate change that can efficiently capture and convert CO2 to other useful carbon products. This research used computational models to determine the reaction conditions under which MOFs can more efficiently capture and convert CO2. In a cost-efficient manner, this analysis tested the hypothesis that pressure and temperature affect the efficacy of carbon capture and conversion, and contribute to understanding the optimal conditions for MOF performance to improve the use of MOFs for controlling greenhouse CO2 emissions.

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Effect of the Herbal Formulation HF1 on the Expression of PD-L1 in PC3 cells

Imani et al. | Nov 15, 2019

Effect of the Herbal Formulation HF1 on the Expression of PD-L1 in PC3 cells

In this study, Imani et al. investigate whether a new proprietary herbal formulation, HF1, can inhibit expression of immune suppressor protein PD-L1. PD-L1 is a transmembrane protein that can be expressed by cancer cells to assist in their ability to avoid attacks from the immune system. Work from this study demonstrates that HF1 treatment can reduce expression of PD-L1 in cultured cancer cells, implicating HF1 as a potential new cancer therapy.

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Predicting the factors involved in orthopedic patient hospital stay

D’Souza et al. | Dec 13, 2023

Predicting the factors involved in orthopedic patient hospital stay
Image credit: Pixabay

Long hospital stays can be stressful for the patient for many reasons. We hypothesized that age would be the greatest predictor of hospital stay among patients who underwent orthopedic surgery. Through our models, we found that severity of illness was indeed the highest factor that contributed to determining patient length of stay. The other two factors that followed were the facility that the patient was staying in and the type of procedure that they underwent.

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