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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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Effect of hypervitaminosis A in regenerating planaria: A potential model for teratogenicity testing

Bennet et al. | Dec 12, 2022

Effect of hypervitaminosis A in regenerating planaria: A potential model for teratogenicity testing

This unique research study evaluated the potential use of the flatworm, brown planaria (Dugesia tigrine), as an alternative model for teratogenicity testing. In this study, we exposed amputated planaria to varying concentrations of a known teratogen, vitamin A (retinol), for approximately 2 weeks, and evaluated multiple parameters including the formation of blastema and eyes. The results from this study demonstrated that high concentrations of retinol caused defects in head and eye formation in regenerating planaria, with similarities to vitamin A related teratogenicity findings in mammals. Based on these results, regenerating brown planaria are a promising alternative model for teratogenicity testing, which can potentially be paradigm shifting as it can reduce cost, time, and pregnant animal use in research.

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Predicting the factors involved in orthopedic patient hospital stay

D’Souza et al. | Dec 13, 2023

Predicting the factors involved in orthopedic patient hospital stay
Image credit: Pixabay

Long hospital stays can be stressful for the patient for many reasons. We hypothesized that age would be the greatest predictor of hospital stay among patients who underwent orthopedic surgery. Through our models, we found that severity of illness was indeed the highest factor that contributed to determining patient length of stay. The other two factors that followed were the facility that the patient was staying in and the type of procedure that they underwent.

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Analysis of ultraviolet light as a bactericide of gram-negative bacteria in Cladophora macroalgae extracts

Newell et al. | Nov 07, 2022

Analysis of ultraviolet light as a bactericide of gram-negative bacteria in <em>Cladophora</em> macroalgae extracts

Here, the authors sought to use Cladophora macroalgae as a possible antibiotic to address the growing threat of antibiotic resistance in pathogenic bacteria. However, when they observed algae extracts to be greatly contaminated with gram-negative bacteria, they adapted to explore the ability to use ultraviolet light as a bactericide. They found that treatment with ultraviolet light had a significant effect.

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The knowledge and perception of opioid abuse and its long-term effects among high schoolers

Shroff et al. | Nov 27, 2021

The knowledge and perception of opioid abuse and its long-term effects among high schoolers

Due to the susceptibility of adolescent age groups to opioid misuse, here the authors sought to determine if there was a difference in the perception and knowledge between 9th and 12th graders regarding the opioid crisis. An educational intervention trial was done with the 9th graders and surveys were used to identify its effects. Although the authors acknowledge a small sample size, their results suggest that their are gaps within the knowledge of adolescents in regards to opioid misuse and its long-term effects that could be addressed with further education.

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A novel encoding technique to improve non-weather-based models for solar photovoltaic forecasting

Ahmed et al. | Jun 09, 2023

A novel encoding technique to improve non-weather-based models for solar photovoltaic forecasting

Several studies have applied different machine learning (ML) techniques to the area of forecasting solar photovoltaic power production. Most of these studies use weather data as inputs to predict power production; however, there are numerous practical issues with the procurement of this data. This study proposes models that do not use weather data as inputs, but rather use past power production data as a more practical substitute to weather-based models. Our proposed models demonstrate a better, cheaper, and more reliable alternatives to current weather models.

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Using machine learning to develop a global coral bleaching predictor

Madireddy et al. | Feb 21, 2023

Using machine learning to develop a global coral bleaching predictor
Image credit: Madireddy, Bosch, and McCalla

Coral bleaching is a fatal process that reduces coral diversity, leads to habitat loss for marine organisms, and is a symptom of climate change. This process occurs when corals expel their symbiotic dinoflagellates, algae that photosynthesize within coral tissue providing corals with glucose. Restoration efforts have attempted to repair damaged reefs; however, there are over 360,000 square miles of coral reefs worldwide, making it challenging to target conservation efforts. Thus, predicting the likelihood of bleaching in a certain region would make it easier to allocate resources for conservation efforts. We developed a machine learning model to predict global locations at risk for coral bleaching. Data obtained from the Biological and Chemical Oceanography Data Management Office consisted of various coral bleaching events and the parameters under which the bleaching occurred. Sea surface temperature, sea surface temperature anomalies, longitude, latitude, and coral depth below the surface were the features found to be most correlated to coral bleaching. Thirty-nine machine learning models were tested to determine which one most accurately used the parameters of interest to predict the percentage of corals that would be bleached. A random forest regressor model with an R-squared value of 0.25 and a root mean squared error value of 7.91 was determined to be the best model for predicting coral bleaching. In the end, the random model had a 96% accuracy in predicting the percentage of corals that would be bleached. This prediction system can make it easier for researchers and conservationists to identify coral bleaching hotspots and properly allocate resources to prevent or mitigate bleaching events.

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Effects of Ocean Acidification on the Photosynthetic Ability of Chaetoceros gracilis in the Monterey Bay

Harvell et al. | Jan 16, 2020

Effects of Ocean Acidification on the Photosynthetic Ability of <i>Chaetoceros gracilis</i> in the Monterey Bay

In this article, Harvell and Nicholson hypothesized that increased ocean acidity would decrease the photosynthetic ability of Chaetoceros gracilis, a diatom prolific in Monterey Bay, because of the usually corrosive effects of carbonic acid on both seashells and cells’ internal structures. They altered pH of algae environments and measured the photosynthetic ability of diatoms over four days by spectrophotometer. Overall, their findings indicate that C. gracilis may become more abundant in Monterey Bay as the pH of the ocean continues to drop, potentially contributing to harmful algal blooms.

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Integrated Ocean Cleanup System for Sustainable and Healthy Aquatic Ecosystems

Anand et al. | Nov 14, 2020

Integrated Ocean Cleanup System for Sustainable and Healthy Aquatic Ecosystems

Oil spills are one of the most devastating events for marine life. Finding ways to clean up oil spills without the need for harsh chemicals could help decrease the negative impact of such spills. Here the authors demonstrate that using a combination of several biodegradable substances can effectively adsorb oil in seawater in a laboratory setting. They suggest further exploring the potential of such a combination as a possible alternative to commonly-used non-biodegradable substances in oil spill management.

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