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Phytochemical Analysis of Amaranthus spinosus Linn.: An in vitro Analysis

Sharma et al. | Mar 20, 2021

Phytochemical Analysis of <em>Amaranthus spinosus</em> Linn.: An <em>in vitro</em> Analysis

Mainstream cancer treatments, which include radiotherapy and chemotherapeutic drugs, are known to induce oxidative damage to healthy somatic cells due to the liberation of harmful free radicals. In order to avert this, physiological antioxidants must be complemented with external antioxidants. Here the authors performed a preliminary phytochemical screen to identify alkaloids, saponins, flavonoids, polyphenols, and tannins in all parts of the Amaranthus spinosus Linn. plant. This paper describes the preparation of this crude extract and assesses its antioxidant properties for potential use in complementary cancer treatment.

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Computational Structure-Activity Relationship (SAR) of Berberine Analogs in Double-Stranded and G-Quadruplex DNA Binding Reveals Both Position and Target Dependence

Sun et al. | Dec 18, 2020

Computational Structure-Activity Relationship (SAR) of Berberine Analogs in Double-Stranded and G-Quadruplex DNA Binding Reveals Both Position and Target Dependence

Berberine, a natural product alkaloid, and its analogs have a wide range of medicinal properties, including antibacterial and anticancer effects. Here, the authors explored a library of alkyl or aryl berberine analogs to probe binding to double-stranded and G-quadruplex DNA. They determined that the nature of the substituent, the position of the substituent, and the nucleic acid target affect the free energy of binding of berberine analogs to DNA and G-quadruplex DNA, however berberine analogs did not result in net stabilization of G-quadruplex DNA.

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Discovery of the Heart in Mathematics: Modeling the Chaotic Behaviors of Quantized Periods in the Mandelbrot Set

Golla et al. | Dec 14, 2020

Discovery of the Heart in Mathematics: Modeling the Chaotic Behaviors of Quantized Periods in the Mandelbrot Set

This study aimed to predict and explain chaotic behavior in the Mandelbrot Set, one of the world’s most popular models of fractals and exhibitors of Chaos Theory. The authors hypothesized that repeatedly iterating the Mandelbrot Set’s characteristic function would give rise to a more intricate layout of the fractal and elliptical models that predict and highlight “hotspots” of chaos through their overlaps. The positive and negative results from this study may provide a new perspective on fractals and their chaotic nature, helping to solve problems involving chaotic phenomena.

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A Juxtaposition of Airborne Microplastics and Fiber Contamination in Various Environments

Truong-Phan et al. | Dec 04, 2020

A Juxtaposition of Airborne Microplastics and Fiber Contamination in Various Environments

Microplastics can have detrimental effects on various wildlife, as well as pollute aquatic and atmospheric environments. This study focused on air samples collected from five locations to investigate microplastic concentrations in atmospheric fallout from indoor and outdoor settings, through a process utilizing a hand-held vacuum pump and a rotameter. The authors found that the difference between the average number of microplastic fragments and fibers collected from all locations was not large enough to be statistically significant. The results collected in this study will contribute to knowledge of the prevalence of airborne microplastics.

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Effect of Different Growth Media on Algae’s Ability for Carbon Dioxide Biofixation

Chaudhuri et al. | Oct 12, 2020

Effect of Different Growth Media on Algae’s Ability for Carbon Dioxide Biofixation

In this study, the authors investigate the effects of different algal growth media on algae's ability to perform carbon dioxide biofixation, or utilize carbon dioxide by fixing it into fatty acids within the cells. More specifically, carbon dioxide biofixation of Chlorella vulgaris was cultured in one of four media options and carbon dioxide was measured and compared to controls. The study results demonstrated that the use of media can enhance algae's capacity for biofixation and this has important implications for developing methods to reduce carbon dioxide in the environment.

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Population Forecasting by Population Growth Models based on MATLAB Simulation

Li et al. | Aug 31, 2020

Population Forecasting by Population Growth Models based on MATLAB Simulation

In this work, the authors investigate the accuracy with which two different population growth models can predict population growth over time. They apply the Malthusian law or Logistic law to US population from 1951 until 2019. To assess how closely the growth model fits actual population data, a least-squared curve fit was applied and revealed that the Logistic law of population growth resulted in smaller sum of squared residuals. These findings are important for ensuring optimal population growth models are implemented to data as population forecasting affects a country's economic and social structure.

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Creating a Phenology Trail Around Central Park Pond

Flynn et al. | Jul 16, 2020

Creating a Phenology Trail Around Central Park Pond

This study aimed to determine whether the life cycle stages, or phenophases, of some plants in the urban environment of Central Park, New York, differ from the typical phenophases of the same plant species. The authors hypothesized that the phenophases of the thirteen plants we studied would differ from their typical phenophases due to the urban heat island effect. Although the phenophases of five plants matched up with typical trends, there were distinct changes in the phenophases of the other eight, possibly resulting from the urban heat island effect.

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Trajectories Between Cigarette Smoking and Electronic Nicotine Delivery System Use Among Adults in the U.S.

Primack et al. | Apr 30, 2020

Trajectories Between Cigarette Smoking and Electronic Nicotine Delivery System Use Among Adults in the U.S.

In this study, the authors characterized the trends of cigarette use amongst people who do and don't use electronic nicotine delivery systems (or ENDS). This was done to help determine if the use of ENDS is aiding in helping smokers quit, as the data on this has been controversial. They found that use of ENDS among people either with or without previous cigarette usage were more likely to continue using cigarettes in the future. This is important information contributing to our understanding of ways to effectively (and not effectively) reduce cigarette use.

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Assessing and Improving Machine Learning Model Predictions of Polymer Glass Transition Temperatures

Ramprasad et al. | Mar 18, 2020

Assessing and Improving Machine Learning Model Predictions of Polymer Glass Transition Temperatures

In this study, the authors test whether providing a larger dataset of glass transition temperatures (Tg) to train the machine-learning platform Polymer Genome would improve its accuracy. Polymer Genome is a machine learning based data-driven informatics platform for polymer property prediction and Tg is one property needed to design new polymers in silico. They found that training the model with their larger, curated dataset improved the algorithm's Tg, providing valuable improvements to this useful platform.

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A Quantitative Analysis of the Proliferation of Microplastics in Williamston’s Waterways

Schafer et al. | Feb 17, 2019

A Quantitative Analysis of the Proliferation of Microplastics in Williamston’s Waterways

Plastic debris can disrupt marine ecosystems, spread contaminants, and take years to naturally degrade. In this study, Wu et al aim to establish an understanding of the scope of Williamston, Michigan’s microplastics problem, as well as to attempt to find the source of these plastics. Initially, the authors hypothesize that the Williamston Wastewater Treatment Plant was the primary contributor to Williamston’s microplastics pollution. Although they find a general trend of increasing concentrations of microplastics from upstream to downstream, they do not pinpoint the source of Williamston’s microplastics pollution in the present research.

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