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Modular mimics of neuroactive alkaloids - design, synthesis, and cholinesterase inhibitory activity of rivastigmine analogs

Yu et al. | Sep 12, 2022

Modular mimics of neuroactive alkaloids - design, synthesis, and cholinesterase inhibitory activity of rivastigmine analogs

Naturally occurring neuroactive alkaloids are often studied for their potential to treat Neurological diseases. This team of students study Rivastigmine, a potent cholinesterase inhibitor that is a synthetic analog of physostigmine, which comes from the Calabar bean plant Physostigma venenosum. By comparing the effects of optimized synthetic analogs to the naturally occurring alkaloid, they determine the most favorable analog for inhibition of acetylcholinesterase (AChE), the enzyme that breaks down the neurotransmitter acetylcholine (ACh) to terminate neuronal transmission and signaling between synapses.

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How Ethanol Concentration Affects Catalase Catalysis of Hydrogen Peroxide

Liu et al. | Nov 15, 2021

How Ethanol Concentration Affects Catalase Catalysis of Hydrogen Peroxide

Catalase is a critical enzyme in the human body because it is capable of converting potentially dangerous hydrogen peroxide into water and oxygen. This work asks whether ethanol affects catalase activity, as alcohol consumption has been often linked to hepatitis occurring in the liver, where catalase level is especially high, and ethanol is known to be capable of denaturing proteins. Testing different concentrations of ethanol found that higher concentrations reduced the activity of catalase. This work has important implications on the negative effects of ethanol on metabolism, in which catalase plays an important role, and protein function more broadly.

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Comparison of three large language models as middle school math tutoring assistants

Ramanathan et al. | May 02, 2024

Comparison of three large language models as middle school math tutoring assistants
Image credit: Thirdman

Middle school math forms the basis for advanced mathematical courses leading up to the university level. Large language models (LLMs) have the potential to power next-generation educational technologies, acting as digital tutors to students. The main objective of this study was to determine whether LLMs like ChatGPT, Bard, and Llama 2 can serve as reliable middle school math tutoring assistants on three tutoring tasks: hint generation, comprehensive solution, and exercise creation.

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Combating Insulin Resistance Using Medicinal Plants as a Supplementary Therapy to Metformin in 3T3-L1 Adipocytes: Improving Early Intervention-Based Diabetes Treatment

Jayram et al. | Apr 08, 2019

Combating Insulin Resistance Using Medicinal Plants as a Supplementary Therapy to Metformin in 3T3-L1 Adipocytes: Improving Early Intervention-Based Diabetes Treatment

A primary cause of diabetes is insulin resistance, which is caused by disruption of insulin signal transduction. The objective of this study was to maximize insulin sensitivity by creating a more effective, early intervention-based treatment to avert severe T2D. This treatment combined metformin, “the insulin sensitizer”, and medicinal plants, curcumin, fenugreek, and nettle.

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Can the nucleotide content of a DNA sequence predict the sequence accessibility?

Balachandran et al. | Mar 10, 2023

Can the nucleotide content of a DNA sequence predict the sequence accessibility?
Image credit: Warren Umoh

Sequence accessibility is an important factor affecting gene expression. Sequence accessibility or openness impacts the likelihood that a gene is transcribed and translated into a protein and performs functions and manifests traits. There are many potential factors that affect the accessibility of a gene. In this study, our hypothesis was that the content of nucleotides in a genetic sequence predicts its accessibility. Using a machine learning linear regression model, we studied the relationship between nucleotide content and accessibility.

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Propagation of representation bias in machine learning

Dass-Vattam et al. | Jun 10, 2021

Propagation of representation bias in machine learning

Using facial recognition as a use-case scenario, we attempt to identify sources of bias in a model developed using transfer learning. To achieve this task, we developed a model based on a pre-trained facial recognition model, and scrutinized the accuracy of the model’s image classification against factors such as age, gender, and race to observe whether or not the model performed better on some demographic groups than others. By identifying the bias and finding potential sources of bias, his work contributes a unique technical perspective from the view of a small scale developer to emerging discussions of accountability and transparency in AI.

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Two Wrongs Could Make a Right: Food Waste Compost Accelerated Polystyrene Consumption of Tenebrio molitor

Fu et al. | Jul 13, 2020

Two Wrongs Could Make a Right: Food Waste Compost Accelerated Polystyrene Consumption of <em>Tenebrio molitor</em>

Expanded polystyrene (EPS) is a plastic used to make food containers and packing materials that poses a threat to the environment. Mealworms can degrade EPS, but at a slow rate. Here, researchers assessed the impact of food waste compost and oats on the speed of EPS consumption by mealworms, superworms, and waxworms. A positive correlation was found between food waste compost supplementation and EPS consumption, especially by mealworms, indicating a potential industrial application.

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Reactivity-informed design, synthesis, and Michael addition kinetics of C-ring andrographolide analogs

Zhou et al. | Nov 17, 2022

Reactivity-informed design, synthesis, and Michael addition kinetics of C-ring andrographolide analogs

Here, based on the identification of androgapholide as a potential therapeutic treatment against cancer, Alzheimer's disease, diabetes, and multiple sclerosis, due to its ability to inhibit a signaling pathway in immune system function, the authors sought ways to optimize the natural product human systems by manipulating its chemical structure. Through the semisynthesis of a natural product along with computational studies, the authors developed an understanding of the kinetic mechanisms of andrographolide and semisynthetic analogs in the context of Michael additions.

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