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In this study, a deep learning model is used to classify post-traumatic stress disorder patients through novel markers to assist in finding candidate biomarkers for the disorder.

Since cancer cells inhibit T-cell activity, the authors investigated a method to reverse T-cell disfunction with gene therapy, so that the T-cells would become effective once again in fighting cancer cells. They used the inhibition of proprotein convertases (PCSK1) in T cells and programmed death-ligand 1 (CD274) in cancer cells. They observed the recovery of IL-2 expression in Jurkat cells, with increased recovery noted in a co-culture sample. This study suggests a novel strategy to reactivate T cells.

Wearing face masks has become a common occurrence in everyday life and during athletics due to the spread of diseases. This study tested if masks would affect blood percent saturation of hemoglobin (SpO₂) during treadmill exercise. The data analysis showed that mask type, time, and the interaction of mask type and time were significant results, regardless of physical ability. These results may assist athletes in understanding the differences between training and competing with and without a mask.

To best identify tuberculosis and pneumonia diagnoses in chest x-rays, the authors compare different deep learning convolution neural networks.

The diagnosis of malaria remains one of the major hurdles to eradicating the disease, especially among poorer populations. Here, the authors use machine learning to improve the accuracy of deep learning algorithms that automate the diagnosis of malaria using images of blood smears from patients, which could make diagnosis easier and faster for many.

Free radical chain reactions result when atoms containing unpaired electrons bind with biomolecules and alter their biological functions, contributing to the progression of diseases such as atherosclerosis, cancer, and diabetes. Antioxidants, such as vitamin E and sulforaphane, are effective neutralizers of free radicals and prevent cellular damage. This present study is conducted to determine the relative effectiveness of sulforaphane against free radicals generated by hydrogen peroxide (H2O2) compared with the known antioxidant vitamin E.

Cannabidiol (CBD) is a chemical extracted from cannabis and shown by some studies to alleviate the symptoms of many mental disorders, especially major depressive disorder. The authors hypothesized that chronic treatments with purified CBD through oral administration would relieve depression-associated behaviors in normal healthy rats under adverse conditions. A statistical analysis of the experimental data suggested that long-term consumption of CBD could elicit depression associated symptoms in normal rats without depression. The results imply that people should consume CBD-containing products with extreme caution and highlight the need to carefully monitor the use of CBD in health care products.

In this study, the authors seek to improve a machine learning algorithm used for image classification: identifying male and female images. In addition to fine-tuning the classification model, they investigate how accuracy is affected by their changes (an important task when developing and updating algorithms). To determine accuracy, a set of images is used to train the model and then a separate set of images is used for validation. They found that the validation accuracy was close to the training accuracy. This study contributes to the expanding areas of machine learning and its applications to image identification.

Resveratrol is a type of stillbenoid, a phenolic compound produced in plants, that is known for its anti-inflammatory and anticancer effects. Many oligomers of resveratrol have recently been isolated their bioactivities remain unknown. Here, authors compared the bioactivities of resveratrol with natural dimers (ε-viniferin and gnetin H) and trimers (suffruticosol B and C). Results provide preliminary evidence that resveratrol oligomers could be potential preventive or therapeutic agents for cancers and other immune-related diseases

In this article, the authors identify the characteristics that make a book a best-seller. Knowing what, besides content, predicts the success of a book can help publishers maximize the success of their print products.