Browse Articles

Assaying the Formation of Beneficial Biofilms by Lactic Acid Bacteria and the Effect of Ayurvedic Plant Extracts on Their Enhancement

Rajpal et al. | Oct 12, 2017

Assaying the Formation of Beneficial Biofilms by Lactic Acid Bacteria and the Effect of Ayurvedic Plant Extracts on Their Enhancement

This study aimed to obtain an optimal non-antibiotic method to suppress the growth of pathogenic bacteria within the body. The two-fold purpose of this project was to determine which combination of bacteria would result in the most biofilm formation and then to assess the effect of ayurvedic plant extracts on the biofilm. The results show that the addition of a plant extract can affect the biofilm growth of a bacteria combination. The applications of this study can be used to design probiotic supplements with added beneficial plant extracts.

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Mathematical modeling of plant community composition for urban greenery plans

Fang et al. | Jul 05, 2023

Mathematical modeling of plant community composition for urban greenery plans
Image credit: CHUTTERSNAP

Here recognizing the importance of urban green space for the health of humans and other organisms, the authors investigated if mathematical modeling can be used to develop an urban greenery management plan with high eco-sustainability by calculating the composition of a plant community. They optimized and tested their model against green fields in a Beijing city park. Although the compositions predicted by their models differed somewhat from the composition of testing fields, they conclude that by using a mathematical model such as this urban green space can be finely designed to be ecologically and economically sustainable.

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Hybrid Quantum-Classical Generative Adversarial Network for synthesizing chemically feasible molecules

Sikdar et al. | Jan 10, 2023

Hybrid Quantum-Classical Generative Adversarial Network for synthesizing chemically feasible molecules

Current drug discovery processes can cost billions of dollars and usually take five to ten years. People have been researching and implementing various computational approaches to search for molecules and compounds from the chemical space, which can be on the order of 1060 molecules. One solution involves deep generative models, which are artificial intelligence models that learn from nonlinear data by modeling the probability distribution of chemical structures and creating similar data points from the trends it identifies. Aiming for faster runtime and greater robustness when analyzing high-dimensional data, we designed and implemented a Hybrid Quantum-Classical Generative Adversarial Network (QGAN) to synthesize molecules.

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High-throughput virtual screening of novel dihydropyrimidine monastrol analogs reveals robust structure-activity relationship to kinesin Eg5 binding thermodynamics

Shern et al. | Jan 20, 2021

High-throughput virtual screening of novel dihydropyrimidine monastrol analogs reveals robust structure-activity relationship to kinesin Eg5 binding thermodynamics

As cancer continues to take millions of lives worldwide, the need to create effective therapeutics for the disease persists. The kinesin Eg5 assembly motor protein is a promising target for cancer therapeutics as inhibition of this protein leads to cell cycle arrest. Monastrol, a small dihydropyrimidine-based molecule capable of inhibiting the kinesin Eg5 function, has attracted the attention of medicinal chemists with its potency, affinity, and specificity to the highly targeted loop5/α2/α3 allosteric binding pocket. In this work, we employed high-throughput virtual screening (HTVS) to identify potential small molecule Eg5 inhibitors from a designed set of novel dihydropyrimidine analogs structurally similar to monastrol.

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Emotional and Psychological Effect of Music on People

Nolt et al. | Jan 03, 2019

Emotional and Psychological Effect of Music on People

Nolt and Elwonger examine how different types of music impact our emotional and physical states. They found that music can influence a subject's emotional state, with sad music inspiring sadness and exciting music bringing excitement. They were not able to find a clear relationship between heart rate and music type. Music's effect on emotional state can be useful when designing novel therapies for emotional and mental disorders.

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The Potential of Fibroblast Growth Factors to Stimulate Hair Growth In Vitro

Cheng et al. | Nov 07, 2021

The Potential of Fibroblast Growth Factors to Stimulate Hair Growth In Vitro

Identifying treatments that can stimulate hair growth use could help those struggling with undesirable hair loss. Here, the authors show that Fibroblast Growth Factors can stimulate the division of cells isolated from the mouse hair follicle. Their results suggest that this family of growth factors might be helpful in stimulating hair growth in living animals as well.

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Transfer Learning for Small and Different Datasets: Fine-Tuning A Pre-Trained Model Affects Performance

Gupta et al. | Oct 18, 2020

Transfer Learning for Small and Different Datasets: Fine-Tuning A Pre-Trained Model Affects Performance

In this study, the authors seek to improve a machine learning algorithm used for image classification: identifying male and female images. In addition to fine-tuning the classification model, they investigate how accuracy is affected by their changes (an important task when developing and updating algorithms). To determine accuracy, a set of images is used to train the model and then a separate set of images is used for validation. They found that the validation accuracy was close to the training accuracy. This study contributes to the expanding areas of machine learning and its applications to image identification.

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