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Effects of Paan Extracts on Periodontal Ligament and Osteosarcoma Cells

Venkatachalam et al. | Sep 20, 2018

Effects of Paan Extracts on Periodontal Ligament and Osteosarcoma Cells

In South Asian countries, the major cause of oral cancer is reported to be chewing paan, which is comprised of betel leaf daubed with slaked lime paste and areca nut. To investigate how paan may contribute to the onset of cancer, the authors treated two immortalized cell lines with extracts of betel leaf, areca nut, and lime and evaluated how these treatments affected cell proliferation and cell death. Initial results indicate that while betel leaf alone may inhibit cell growth, areca nut promoted cancer cell survival and proliferation, even when co-treated with betel leaf. These data suggest that areca nut could exacerbate the progression of oral cancer in humans.

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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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Effect of Manuka Honey and Licorice Root Extract on the Growth of Porphyromonas gingivalis: An In Vitro Study

Chandran et al. | Apr 11, 2018

Effect of Manuka Honey and Licorice Root Extract on the Growth of Porphyromonas gingivalis: An In Vitro Study

Chronic bad breath, or halitosis, is a problem faced by nearly 50% of the general poluation, but existing treatments such as liquid mouthwash or sugar-free gum are imperfect and temporary solutions. In this study, the authors investigate potential alternative treatments using natural ingredients such as Manuka Honey and Licorice root extract. They found that Manuka honey is almost as effective as commercial mouthwashes in reducing the growth of P gingivalis (one of the main bacteria that causes bad breath), while Licorice root extract was largely ineffective. The authors' results suggest that Manuka honey is a promising candidate in the search for new and improved halitosis treatments.

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Green Tea Extract as an Environmentally Friendly Antibacterial Agent Against Pseudomonas syringae pv. tomato on Plants

Lo et al. | Oct 27, 2015

Green Tea Extract as an Environmentally Friendly Antibacterial Agent Against <i>Pseudomonas syringae pv. tomato </i>on Plants

Plant pathogens can cause significant crop loss each year, but controlling them with bactericides or antibiotics can be costly and may be harmful to the environment. Green tea naturally contains polyphenols, which have been shown to have some antimicrobial properties. In this study, the authors show that green tea extract can inhibit growth of the plant pathogen Pseudomonas syringae pv. tomato and may be useful as an alternative bactericide for crops.

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Efficacy of Rotten and Fresh Fruit Extracts as the Photosensitive Dye for Dye-Sensitized Solar Cells

Jayasankar et al. | Jan 16, 2019

Efficacy of Rotten and Fresh Fruit Extracts as the Photosensitive Dye for Dye-Sensitized Solar Cells

Dye-sensitized solar cells (DSSC) use dye as the photoactive material, which capture the incoming photon of light and use the energy to excite electrons. Research in DSSCs has centered around improving the efficacy of photosensitive dyes. A fruit's color is defined by a unique set of molecules, known as a pigment profile, which changes as a fruit progresses from ripe to rotten. This project investigates the use of fresh and rotten fruit extracts as the photoactive dye in a DSSC.

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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 Effects of Barley Straw (Hordeum vulgare) Extract and Barley Straw Pellets on Algal Growth and Water Quality

McHargue et al. | Oct 06, 2020

The Effects of Barley Straw (Hordeum vulgare) Extract and Barley Straw Pellets on Algal Growth and Water Quality

Algal overgrowth often threatens to clog irrigation pipes and drinking water lines when left unchecked, as well as releasing possible toxins that threaten plant and human health. It is thus important to find natural, non-harmful agents that can decrease algal growth without threatening the health of plants and humans. In this paper, the authors test the efficacy of barely extract in either liquid or pellet form in decreasing algal growth. While their results were inconclusive, the experimental set-up allows them to investigate a wider range of agents as anti-algal treatments that could potentially be adopted on a wider scale.

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The Role of a Mask - Understanding the Performance of Deep Neural Networks to Detect, Segment, and Extract Cellular Nuclei from Microscopy Images

Dasgupta et al. | Jul 06, 2021

The Role of a Mask - Understanding the Performance of Deep Neural Networks to Detect, Segment, and Extract Cellular Nuclei from Microscopy Images

Cell segmentation is the task of identifying cell nuclei instances in fluorescence microscopy images. The goal of this paper is to benchmark the performance of representative deep learning techniques for cell nuclei segmentation using standard datasets and common evaluation criteria. This research establishes an important baseline for cell nuclei segmentation, enabling researchers to continually refine and deploy neural models for real-world clinical applications.

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