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Scientific project in physics "Carbonated liquids and carbonation level"

Irina et al. | Jan 21, 2024

Scientific project in physics "Carbonated liquids and carbonation level"

In our work we followed the formation of gas bubbles on the surface of the vessel walls in different carbonated liquids, over different time intervals, at different temperatures and in vessels made of different materials. Our results made it possible to identify patterns affecting the process of formation and disappearance of carbon dioxide bubbles.

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Quantitative NMR spectroscopy reveals solvent effects in the photochemical degradation of thymoquinone

Mandava et al. | Dec 16, 2023

Quantitative NMR spectroscopy reveals solvent effects in the photochemical degradation of thymoquinone

Thymoquinone is a compound of great therapeutic potential and scientific interest. However, its clinical administration and synthetic modifications are greatly limited by its instability in the presence of light. This study employed quantitative 1H nuclear magnetic resonance (NMR) spectroscopy to identify the effect of solvation on the degradation of thymoquinone under ultraviolet light (UV). It found that the rate of degradation is highly solvent dependent occurs maximally in chloroform.

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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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Tomato disease identification with shallow convolutional neural networks

Trinh et al. | Mar 03, 2023

Tomato disease identification with shallow convolutional neural networks

Plant diseases can cause up to 50% crop yield loss for the popular tomato plant. A mobile device-based method to identify diseases from photos of symptomatic leaves via computer vision can be more effective due to its convenience and accessibility. To enable a practical mobile solution, a “shallow” convolutional neural networks (CNNs) with few layers, and thus low computational requirement but with high accuracy similar to the deep CNNs is needed. In this work, we explored if such a model was possible.

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Machine learning-based enzyme engineering of PETase for improved efficiency in plastic degradation

Gupta et al. | Jan 31, 2023

 Machine learning-based enzyme engineering of PETase for improved efficiency in plastic degradation
Image credit: Markus Spiske

Here, recognizing the recognizing the growing threat of non-biodegradable plastic waste, the authors investigated the ability to use a modified enzyme identified in bacteria to decompose polyethylene terephthalate (PET). They used simulations to screen and identify an optimized enzyme based on machine learning models. Ultimately, they identified a potential mutant PETases capable of decomposing PET with improved thermal stability.

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Using economic indicators to create an empirical model of inflation

Kasera et al. | Dec 01, 2022

Using economic indicators to create an empirical model of inflation

Here, seeking to understand the correlation of 50 of the most important economic indicators with inflation, the authors used a rolling linear regression to identify indicators with the most significant correlation with the Month over Month Consumer Price Index Seasonally Adjusted (CPI). Ultimately the concluded that the average gasoline price, U.S. import price index, and 5-year market expected inflation had the most significant correlation with the CPI.

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Photometric analysis and light curve modeling of apparent transient 2020pni

Arora et al. | Oct 07, 2022

Photometric analysis and light curve modeling of apparent transient 2020pni

Supernovas are powerful explosions that result from gravitational collapse of a massive star. Using photometric analysis Arora et al. set out to investigate whether 2020pni (located in galaxy UGC 9684) was a supernova. They were ultimately able to identify 2020pni as a Type II-L supernova and determine it's distance from earth.

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Survival of Escherichia coli K-12 in various types of drinking water

Hanna et al. | Sep 25, 2022

Survival of <i>Escherichia coli</i> K-12 in various types of drinking water

For public health, drinking water should be free of bacterial contamination. The objective of this research is to identify the fate of bacteria if drinking water becomes contaminated and inform consumers on which water type enables the least bacteria to survive. We hypothesized that bottled mineral water would provide the most sufficient conditions for E. coli to survive. We found that if water becomes contaminated, the conditions offered by the three water types at room temperature allow E. coli to survive up to three days. At 72 hours, the bottled spring water had the highest average colony forming units (CFUs), with tap and mineral water CFU values statistically lower than spring water but not significantly different from each other. The findings of this research highlight the need of implementing accessible quality drinking water for the underserved population and for the regulation of water sources.

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String analysis of exon 10 of the CFTR gene and the use of Bioinformatics in determination of the most accurate DNA indicator for CF prediction

Carroll et al. | Jul 12, 2020

String analysis of exon 10 of the CFTR gene and the use of Bioinformatics in determination of the most accurate DNA indicator for CF prediction

Cystic fibrosis is a genetic disease caused by mutations in the CFTR gene. In this paper, the authors attempt to identify variations in stretches of up to 8 nucleotides in the protein-coding portions of the CFTR gene that are associated with disease development. This would allow screening of newborns or even fetuses in utero to determine the likelihood they develop cystic fibrosis.

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