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Cell cytotoxicity and pro-apoptosis on MCF-7 cells using polyherbal formulation, MAT20

Tarigopula et al. | Feb 17, 2023

Cell cytotoxicity and pro-apoptosis on MCF-7  cells using polyherbal formulation, MAT20

The purpose of this study was to test the anti-cancer properties and pro-apoptotic effects of the polyherbal formulation MAT20 as a complementary treatment. Moringa oleifera (Moringa), Phyllanthus emblica (Amla) and Ocimum sanctum (Tulsi), these 3 herbs were used to formulate MAT20, which contain phytochemicals that are known to display anti-cancer properties. In this study, we hypothesized that MCF-7 breast cancer cells treated with MAT20 would show increased cytotoxicity compared to its individual plant extracts.

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The Effect of Concentration on the Pressure of a Sodium Chloride Solution Inside Dialysis Tubing

Dye et al. | Nov 13, 2018

The Effect of Concentration on the Pressure of a Sodium Chloride Solution Inside Dialysis Tubing

In this study, the authors investigate the effects of sodium levels on blood pressure, one of the most common medical problems worldwide. They used a simulated blood vessel constructed from dialysis tubing to carefully analyze pressure changes resulting from various levels of sodium in the external solution. They found that when the sodium concentration in the simulated blood vessel was higher than the external fluid, internal pressure increased, while the reverse was true when the sodium concentration was lower than in the surrounding environment. These results highlight the potential for sodium concentration to have a significant effect on blood pressure in humans by affecting the rate of osmosis across the boundaries of actual blood vessels.

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Time-Efficient and Low-Cost Neural Network to detect plant disease on leaves and reduce food loss and waste

Singh et al. | Apr 24, 2023

Time-Efficient and Low-Cost Neural Network to detect plant disease on leaves and reduce food loss and waste

About 25% of the food grown never reaches consumers due to spoilage, and 11.5 billion pounds of produce from gardens are wasted every year. Current solutions involve farmers manually looking for and treating diseased crops. These methods of tending crops are neither time-efficient nor feasible. I used a convolutional neural network to identify signs of plant disease on leaves for garden owners and farmers.

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Utilizing meteorological data and machine learning to predict and reduce the spread of California wildfires

Bilwar et al. | Jan 15, 2024

Utilizing meteorological data and machine learning to predict and reduce the spread of California wildfires
Image credit: Pixabay

This study hypothesized that a machine learning model could accurately predict the severity of California wildfires and determine the most influential meteorological factors. It utilized a custom dataset with information from the World Weather Online API and a Kaggle dataset of wildfires in California from 2013-2020. The developed algorithms classified fires into seven categories with promising accuracy (around 55 percent). They found that higher temperatures, lower humidity, lower dew point, higher wind gusts, and higher wind speeds are the most significant contributors to the spread of a wildfire. This tool could vastly improve the efficiency and preparedness of firefighters as they deal with wildfires.

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