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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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Anonymity Reduces Generosity in High School Students

Vargas-Guerrero et al. | Nov 25, 2019

Anonymity Reduces Generosity in High School Students

The disinterested willingness a person has for helping others is known as altruism. But is this willingness to help others dependent on external factors that make you more or less inclined to be generous? We hypothesized that generosity in adolescents would depend on external factors and that these factors would change the amount of help given. To evaluate altruism and generosity, we conducted non-anonymous and anonymous variations of the dictator game and ultimatum game experiments and explored the role of anonymity, fairness, and reciprocity in high school students.

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The Effect of Ultraviolet Radiation and the Antioxidant Curcumin on the Longevity, Fertility, and Physical Structure of Drosophila melanogaster: Can We Defend Our DNA?

Lateef et al. | May 18, 2019

The Effect of Ultraviolet Radiation and the Antioxidant Curcumin on the Longevity, Fertility, and Physical Structure of <em>Drosophila melanogaster</em>: Can We Defend Our DNA?

Ultraviolet (UV) radiation is known to alter DNA structure and impair cellular function in all living organisms. In this study, Lateef et al examine the effects of UV radiation to determine whether antioxidant-enriched nutrition can combat the potential deleterious effects of UV radiation on Drosophila melanogaster. They found that UVB (320nm) radiation caused a 59% decrease in the Drosophila lifespan and mutagenic effects on flies' physical appearance, but did not significantly affect fertility. Curcumin significantly prolonged lifespan and enhanced fertility for both UV- and non-UV-exposed flies. The research demonstrates the positive potential of natural antioxidants as weapons against radiation-induced diseases including cancer.

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Molecular Alterations in a High-Fat Mouse Model Before the Onset of Diet–Induced Nonalcoholic Fatty Liver Disease

Lee et al. | Sep 20, 2016

Molecular Alterations in a High-Fat Mouse Model Before the Onset of Diet–Induced Nonalcoholic Fatty Liver Disease

Nonalcoholic fatty liver disease (NAFLD) is one of the most prevalent chronic liver diseases worldwide, but there are few studied warning signs for early detection of the disease. Here, researchers study alterations that occur in a mouse model of NAFLD, which indicate the onset of NAFLD sooner. Earlier detection of diseases can lead to better prevention and treatment.

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Aberrant response to dexamethasone suppression test associated with inflammatory response in MDD patients

Ulery et al. | Nov 06, 2023

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.

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The Effects of Post-Consumer Waste Polystyrene on the Rate of Mealworm Consumption

Green et al. | Nov 29, 2018

The Effects of Post-Consumer Waste Polystyrene on the Rate of Mealworm Consumption

In a world where plastic waste accumulation is threatening both land and sea life, Green et al. investigate the ability of mealworms to breakdown polystyrene, a non-recyclable form of petrochemical-based polymer we use in our daily lives. They confirm that these organisms, can degrade various forms of polystyrene, even after it has been put to use in our daily lives. Although the efficiency of the degradation process still requires improvement, the good news is, the worms are tiny and themselves are biodegradable, so we can use plenty of them without worrying about space and how to get rid of them. This is very promising and certainly good news for the planet.

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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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