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The most common atopic disease of the upper respiratory tract is allergic rhinitis. It is defined as a chronic inflammatory condition of nasal mucosa due to the effects of one or more allergens and is usually a long-term problem. The purpose of our study was to test the efficiency of apitherapy in allergic rhinitis healing by the application of honey bee pollen. Apitherapy is a branch of alternative medicine that uses honey bee products. Honey bee pollen can act as an allergen and cause new allergy attacks for those who suffer from allergic rhinitis. Conversely, we hoped to prove that smaller ingestion of honey bee pollen on a daily basis would desensitize participants to pollen and thus reduce the severity of allergic rhinitis.

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.

Parkinson's disease is a neurodegenerative disorder that affects over 10 million people worldwide. It is caused by destruction of dopamine-producing neurons, which results in severe motor and movement symptoms. In this study, the authors investigated the anti-Parkinsonian effects of two natural compounds curcumin and nicotinamide using C. elegans as a model organism.

Insulin infusion patches are a common way for diabetics to receive medication. The durability of two different patch adhesives was compared on artificial skin with and without artificial sweat.

Here seeking to develop a method to diagnose, hypertrophic cardiomyopathy which can cause sudden cardiac death, the authors investigated the use of a convolutional neural network (CNN) and long short-term memory (LSTM) models to classify cardiac magnetic resonance and heart electrocardiogram scans. They found that the CNN model had a higher accuracy and precision and better other qualities, suggesting that machine learning models could be valuable tools to assist physicians in the diagnosis of hypertrophic cardiomyopathy.

Skin cancer is a common and potentially deadly form of cancer. This study’s purpose was to develop an automated approach for early detection for skin cancer. We hypothesized that convolutional neural network-based models using transfer learning could accurately differentiate between benign and malignant moles using natural images of human skin.

In this study, the authors identify transcripts and gene networks that are changed after infection with the Middle East Respiratory Syndrome-related coronavirus (MERS-CoV).