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siRNA-dependent KCNMB2 silencing inhibits lung cancer cell proliferation and promotes cell death

Jeong et al. | Nov 01, 2022

siRNA-dependent KCNMB2 silencing inhibits lung cancer cell proliferation and promotes cell death

Here, seeking to better understand the genetic associations underlying non-small cell lung cancer, the authors screened hundreds of genes, identifying that KCNMB2 upregulation was significantly correlated with poor prognoses in lung cancer patients. Based on this, they used small interfering RNA to decrease the expression of KCNMB2 in A549 lung cancer cells, finding decreased cell proliferation and increased lung cancer cell death. They suggest this could lead to a new potential target for lung cancer therapies.

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Impact of light intensity and electrolyte volume on performance of photo-electrochemical (PEC) solar cell

Patel et al. | Mar 14, 2022

Impact of light intensity and electrolyte volume on performance of photo-electrochemical (PEC) solar cell

Here, seeking to develop more efficient solar cells, the authors investigated photo-electrochemical (PEC) solar cells, specifically molybdenum diselenide (MoSe2) based on its high resistance to corrosion. They found that the percentage efficiency of these PEC solar cells was proportional to light intensity–0.9 and that performance was positively influenced by increasing the electrolyte volume. They suggest that studies such as these can lead to new insight into reaction-based solar cells.

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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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Effects of Prolonged Azithromycin Therapy on Bacterial Resistance to Functionally Analogous Antibiotics

Gibbs et al. | Dec 04, 2020

Effects of Prolonged Azithromycin Therapy on Bacterial Resistance to Functionally Analogous Antibiotics

In this study, the authors investigate a potential case of cross antibiotic-resistance. Using swabs from an individual who received long-term treatments of azithromycin, they addressed the question of whether any bacteria in this individual might develop resistance to not only azithromycin, but also other antibiotics with similar structures. This study cleverly addresses the important issue of antibiotic resistance from a new and thoughtful approach.

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Assigning Lightning Seasons to Different Regions in the United States

Hawkins et al. | Sep 07, 2020

Assigning Lightning Seasons to Different Regions in the United States

Climate change is predicted to increase the frequency of severe thunderstorm events in coming years. In this study, the authors hypothesized that (i) the majority of severe thunderstorm events will occur in the summer months in all states examined for all years analyzed, (ii) climate change will cause an unusual number of severe thunderstorm events in winter months in all states, (iii) thundersnow would be observed in Colorado, and (iv.) there would be no difference in the number of severe thunderstorm events between states in any given year examined. They classified lightning seasons in all states observed, with the most severe thunderstorm events occurring in May, June, July, and August. Colorado, New Jersey, Washington, and West Virginia were found to have severe thunderstorm events in the winter, which could be explained by increased winter storms due to climate change (1). Overall, they highlight the importance of quantifying when lightning seasons occur to avoid lightning-related injuries or death.

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LawCrypt: Secret Sharing for Attorney-Client Data in a Multi-Provider Cloud Architecture

Zhang et al. | Jul 19, 2020

LawCrypt: Secret Sharing for Attorney-Client Data in a Multi-Provider Cloud Architecture

In this study, the authors develop an architecture to implement in a cloud-based database used by law firms to ensure confidentiality, availability, and integrity of attorney documents while maintaining greater efficiency than traditional encryption algorithms. They assessed whether the architecture satisfies necessary criteria and tested the overall file sizes the architecture could process. The authors found that their system was able to handle larger file sizes and fit engineering criteria. This study presents a valuable new tool that can be used to ensure law firms have adequate security as they shift to using cloud-based storage systems for their files.

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Honey Bee Pollen in Allergic Rhinitis Healing

Bjelajac et al. | Jun 24, 2020

Honey Bee Pollen in Allergic Rhinitis Healing

The most common atopic disease of the upper respiratory tract is allergic rhinitis. It is defined as a chronic inflammatory condition of nasal mucosa due to the effects of one or more allergens and is usually a long-term problem. The purpose of our study was to test the efficiency of apitherapy in allergic rhinitis healing by the application of honey bee pollen. Apitherapy is a branch of alternative medicine that uses honey bee products. Honey bee pollen can act as an allergen and cause new allergy attacks for those who suffer from allergic rhinitis. Conversely, we hoped to prove that smaller ingestion of honey bee pollen on a daily basis would desensitize participants to pollen and thus reduce the severity of allergic rhinitis.

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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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The Bioactive Ingredients in Niuli Lactucis Agrestibus Possess Anticancer Effects

Zhu et al. | Sep 17, 2019

The Bioactive Ingredients in Niuli Lactucis Agrestibus Possess Anticancer Effects

In​ the​ field​ of​ medicine,​ natural​ treatments​ are​ becoming ​increasingly ​vital ​towards ​the ​cure ​of ​cancer. Zhu et al. wanted to investigate the effects of lettuce extract on cancer cell survival and proliferation. They used an adenocarcinoma cell line, COLO320DM, to determine whether crude extract from a lettuce species called Niuli​ Lactucis Agrestibus​ would affect cancer cell survival, migration, and proliferation. They found that Niuli extract inhibited cancer cell survival, increased expression of cell cycle inhibitors p21 and p27, and inhibited migration. However, Niuli extract did not have these effects on healthy cells. This work reveals important findings about a potential new source of anti-colorectal cancer compounds.

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Covalently Entrapping Catalase into Calcium Alginate Worm Pieces Using EDC Carbodiimide as a Crosslinker.

Suresh et al. | Mar 31, 2019

Covalently Entrapping Catalase into Calcium Alginate Worm Pieces Using EDC Carbodiimide as a Crosslinker.

Catalase is a biocatalyst used to break down toxic hydrogen peroxide into water and oxygen in industries such as cheese and textiles. Improving the efficiency of catalase would help us to make some industrial products, such as cheese, less expensively. The best way to maintain catalase’s conformation, and thus enhance its activity, is to immobilize it. The primary goal of this study was to find a new way of immobilizing catalase.

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