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Comparing the effects of electronic cigarette smoke and conventional cigarette smoke on lung cancer viability

Choe et al. | Sep 18, 2022

Comparing the effects of electronic cigarette smoke and conventional cigarette smoke on lung cancer viability

Here, recognizing the significant growth of electronic cigarettes in recent years, the authors sought to test a hypothesis that three main components of the liquid solutions used in e-cigarettes might affect lung cancer cell viability. In a study performed by exposing A549 cells, human lung cancer cells, to different types of smoke extracts, the authors found that increasing levels of nicotine resulted in improve lung cancer cell viability up until the toxicity of nicotine resulted in cell death. They conclude that these results suggest that contrary to conventional thought e-cigarettes may be more dangerous than tobacco cigarettes in certain contexts.

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The Impact of Age on Post-Concussive Symptoms: A Comparative Study of Symptoms Related and Not Related to the Default Mode Network

Wurscher et al. | Mar 05, 2017

The Impact of Age on Post-Concussive Symptoms: A Comparative Study of Symptoms Related and Not Related to the Default Mode Network

The Default Mode Network (DMN) is a network of connected brain regions that are active when the brain is not focused on external tasks. Minor brain injuries, such as concussions, can affect this network and manifest symptoms. In this study, the authors examined correlations between DMN age and post-concussion symptoms in previously concussed individuals and healthy controls.

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The Effect of Various Liquid Mediums on the Transport of Photonic Energy and its Impact on the Quantum Efficiency of Photovoltaic Cells

Payra et al. | May 05, 2015

The Effect of Various Liquid Mediums on the Transport of Photonic Energy and its Impact on the Quantum Efficiency of Photovoltaic Cells

A photovoltaic cell (PV cell), or solar cell, converts the energy of light into electricity and is the basis for solar power. In order to increase the efficiency of PV cells, the authors in this study used common household items as photon transmissions mediums and measured their effects on the temperature and voltage output of the PV cells.

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Machine learning on crowd-sourced data to highlight coral disease

Narayan et al. | Jul 26, 2021

Machine learning on crowd-sourced data to highlight coral disease

Triggered largely by the warming and pollution of oceans, corals are experiencing bleaching and a variety of diseases caused by the spread of bacteria, fungi, and viruses. Identification of bleached/diseased corals enables implementation of measures to halt or retard disease. Benthic cover analysis, a standard metric used in large databases to assess live coral cover, as a standalone measure of reef health is insufficient for identification of coral bleaching/disease. Proposed herein is a solution that couples machine learning with crowd-sourced data – images from government archives, citizen science projects, and personal images collected by tourists – to build a model capable of identifying healthy, bleached, and/or diseased coral.

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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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