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Who is at Risk for a Spinal Fracture? – A Comparative Study of National Health and Nutrition Examination Survey Data

He et al. | Mar 01, 2018

Who is at Risk for a Spinal Fracture? – A Comparative Study of National Health and Nutrition Examination Survey Data

One common age-related health problem is the loss of bone mineral density (BMD), which can lead to a variety of negative health outcomes, including increased risk of spinal fracture. In this study, the authors investigate risk factors that may be predictive of an individual's risk of spinal fracture. Their findings provide valuable information that clinicians can use in patient evaluations.

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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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Optimizing AI-generated image detection using a Convolutional Neural Network model with Fast Fourier Transform

Gupta et al. | Oct 24, 2025

Optimizing AI-generated image detection using a Convolutional Neural Network model with Fast Fourier Transform

Recent advances in generative AI have made it increasingly hard to distinguish real images from AI-generated ones. Traditional detection models using CNNs or U-net architectures lack precision because they overlook key spatial and frequency domain details. This study introduced a hybrid model combining Convolutional Neural Networks (CNN) with Fast Fourier Transform (FFT) to better capture subtle edge and texture patterns.

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Increased carmine red exposure periods yields a higher number of vacuoles formed in Tetrahymena pyriformis

Shah et al. | Nov 18, 2022

Increased carmine red exposure periods yields a higher number of vacuoles formed in <em>Tetrahymena pyriformis</em>

T. pyriformis can use phagocytosis to create vacuoles of carmine red, a dye which is made using crushed insects and is full of nutrients. Establishing a relationship between vacuole formation and duration of exposure to food can demonstrate how phagocytosis occurs in T. pyriformis. We hypothesized that if T. pyriformis was incubated in a carmine red solution, then more vacuoles would form over time in each cell.

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