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Developing a Portable, Reusable, and Inexpensive Magnesium-Air Fuel Cell

Tota et al. | Mar 28, 2019

Developing a Portable, Reusable, and Inexpensive Magnesium-Air Fuel Cell

One of the greatest challenges we face today is the sustainable production, storage, and distribution of electrical power. One emerging technology with great promise in this area is that of metal-air fuel cells—a long-term and reusable electricity storage system made from a reactive metal anode and a saline solution. In this study the authors tested several different types of metal to determine which was the most suitable for this application. They found that a fuel cell with a magnesium anode was superior to fuel cells made from aluminum or zinc, producing a voltage and current sufficient for real-world applications such as charging a mobile phone.

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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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Societal awareness regarding viral Hepatitis in developed and developing countries

Srivastava et al. | Oct 03, 2022

Societal awareness regarding viral Hepatitis in developed and developing countries

Many cases of viral hepatitis are easily preventable if caught early; however, a lack of public awareness regarding often leads to diagnoses near the final stages of disease when it is most lethal. Thus, we wanted to understand to what extent an individual's sex, age, education and country of residence (India or Singapore) impacts disease identification. We sent out a survey and quiz to residents in India (n = 239) and Singapore (n = 130) with questions that test their knowledge and awareness of the disease. We hypothesized that older and more educated individuals would score higher because they are more experienced, but that the Indian population will not be as knowledgeable as the Singaporean population because they do not have as many resources, such as socioeconomic access to schools and accessibility to healthcare, available to them. Additionally, we predicted that there would not be any notable differences between make and females. The results revealed that the accuracy for all groups we looked at was primarily below 50%, demonstrating a severe knowledge gap. Therefore, we concluded that if more medical professionals discussed viral hepatitis during hospital visits and in schools, patients can avoid the end stages of the disease in notable cases.

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Effect of the Herbal Formulation HF1 on the Expression of PD-L1 in PC3 cells

Imani et al. | Nov 15, 2019

Effect of the Herbal Formulation HF1 on the Expression of PD-L1 in PC3 cells

In this study, Imani et al. investigate whether a new proprietary herbal formulation, HF1, can inhibit expression of immune suppressor protein PD-L1. PD-L1 is a transmembrane protein that can be expressed by cancer cells to assist in their ability to avoid attacks from the immune system. Work from this study demonstrates that HF1 treatment can reduce expression of PD-L1 in cultured cancer cells, implicating HF1 as a potential new cancer therapy.

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Machine Learning Algorithm Using Logistic Regression and an Artificial Neural Network (ANN) for Early Stage Detection of Parkinson’s Disease

Kar et al. | Oct 10, 2020

Machine Learning Algorithm Using Logistic Regression and an Artificial Neural Network (ANN) for Early Stage Detection of Parkinson’s Disease

Despite the prevalence of PD, diagnosing PD is expensive, requires specialized testing, and is often inaccurate. Moreover, diagnosis is often made late in the disease course when treatments are less effective. Using existing voice data from patients with PD and healthy controls, the authors created and trained two different algorithms: one using logistic regression and another employing an artificial neural network (ANN).

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