Browse Articles

Using Artificial Intelligence to Forecast Continuous Glucose Monitor(CGM) readings for Type One Diabetes

Jalla et al. | Aug 07, 2024

Using Artificial Intelligence to Forecast Continuous Glucose Monitor(CGM) readings for Type One Diabetes
Image credit: The authors

People with Type One diabetes often rely on Continuous Blood Glucose Monitors (CGMs) to track their blood glucose and manage their condition. Researchers are now working to help people with Type One diabetes more easily monitor their health by developing models that will future blood glucose levels based on CGM readings. Jalla and Ghanta tackle this issue by exploring the use of AI models to forecast blood glucose levels with CGM data.

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Optical anisotropy of crystallized vanillin thin film: the science behind the art

Wang et al. | Jul 09, 2024

Optical anisotropy of crystallized vanillin thin film: the science behind the art
Image credit: The authors

Microscopic beauty is hiding in common kitchen ingredients - even vanillin flavoring can be turned into mesmerizing artwork by crystallizing the vanillin and examining it under a polarizing microscope. Wang and Pang explore this hidden beauty by determining the optimal conditions to grow crystalline vanillin films and by creating computer simulations of chemical interactions between vanillin molecules.

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Impact of carbon number and atom number on cc-pVTZ Hartree-Fock Energy and program runtime of alkanes

Pan et al. | Mar 06, 2024

Impact of carbon number and atom number on cc-pVTZ Hartree-Fock Energy and program runtime of alkanes
Image credit: The authors

It's time-consuming to complete the calculations that are used to study nuclear reactions and energy. To uncover which computational chemistry tools are useful for this challenge, Pan, Vaiyakarnam, Li, and McMahan investigated whether the Python-based Simulations of Chemistry Framework’s Hartree-Fock (PySCF) method is an efficient and accurate way to assess alkane molecules.

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Contribution of environmental factors to genetic variation in the Pacific white-sided dolphin

Talwar et al. | Jan 23, 2024

Contribution of environmental factors to genetic variation in the Pacific white-sided dolphin
Image credit: Flavio

Here the authors sought to understand the effects of different variables that may be tied to pollution and climate change on genetic variation of Pacific white-sided dolphins, a species that is currently threatened by water pollution. Based on environmental data collected alongside a genetic distance matrix, they found that ocean currents had the most significant impact on the genetic diversity of Pacific white-sided dolphins along the Japanese coast.

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Applying centrality analysis on a protein interaction network to predict colorectal cancer driver genes

Saha et al. | Nov 18, 2023

Applying centrality analysis on a protein interaction network to predict colorectal cancer driver genes

In this article the authors created an interaction map of proteins involved in colorectal cancer to look for driver vs. non-driver genes. That is they wanted to see if they could determine what genes are more likely to drive the development and progression in colorectal cancer and which are present in altered states but not necessarily driving disease progression.

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Fractal dimensions of crumpled paper

Zhou et al. | Aug 10, 2023

Fractal dimensions of crumpled paper
Image credit: Richard Dykes

Here, beginning from an interest in fractals, infinitely complex shapes. The authors investigated the fractal object that results from crumpling a sheet of paper. They determined its fractal dimension using continuous Chi-squared analysis, thereby testing and validating their model against the more conventional least squares analysis.

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From trash to treasure: A sustainable approach to oil spill clean-up

Kathir et al. | Aug 02, 2023

From trash to treasure: A sustainable approach to oil spill clean-up

In this study the authors looked at sustainable ways to clean up oil spills that harm marine life. Using water spangle leaves and milk week the authors looked at the ability to recovery oil from both fresh and salt water and the ability to reuse the organic material to clean up spills. Their results show promise to help find a sustainable, eco-friendly way to clean up oil spills and protect marine life and habitats.

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Blockchain databases: Encrypted for efficient and secure NoSQL key-store

Mehrota et al. | Mar 18, 2023

Blockchain databases: Encrypted for efficient and secure NoSQL key-store
Image credit: Ayushi Mehrota & David Kim

Although commonly associated with cryptocurrency, blockchains offer security that other databases could benefit from. These student authors tested a blockchain database framework, and by tracking runtime of four independent variables, they prove this framework is feasible for application.

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The sweetened actualities of neural membrane proteins: A computational structural analysis

Chauhan et al. | Nov 03, 2022

The sweetened actualities of neural membrane proteins: A computational structural analysis

Here, seeking to better understand the roles of glycans in the receptors of active sites of neuronal cells, the authors used molecular dynamics simulations to to uncover the dynamic nature of N-glycans on membrane proteins. The authors suggest the study of theinteractions of these membrane poreins could provide future potential therapeutic targets to treat mental diseases.

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Development of a novel machine learning platform to identify structural trends among NNRTI HIV-1 reverse transcriptase inhibitors

Ashok et al. | Jun 24, 2022

Development of a novel machine learning platform to identify structural trends among NNRTI HIV-1 reverse transcriptase inhibitors

With advancements in machine learning a large data scale, high throughput virtual screening has become a more attractive method for screening drug candidates. This study compared the accuracy of molecular descriptors from two cheminformatics Mordred and PaDEL, software libraries, in characterizing the chemo-structural composition of 53 compounds from the non-nucleoside reverse transcriptase inhibitors (NNRTI) class. The classification model built with the filtered set of descriptors from Mordred was superior to the model using PaDEL descriptors. This approach can accelerate the identification of hit compounds and improve the efficiency of the drug discovery pipeline.

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