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.
The authors here investigate the absorbency of two leading brands of diapers. They find that Huggies Little Snugglers absorb over 50% more salt water than Pampers Swaddlers, although both absorb significantly more fluid than what an average newborn can produce.
According to the World Health Organization, cancer is a leading cause of death globally. The disease’s prevalence is rapidly increasing in association with factors including the increased use of pesticides and herbicides, such as glyphosate, which is one of the most widely used herbicide ingredients. Natural antioxidants and phytochemicals are being tested as anti-cancer agents due to their antiproliferative, antioxidative, and pro-apoptotic properties. Thus, we aimed to investigate the potential role of S. amara extract as a therapeutic agent against glyphosate-induced toxicity and tumor-like morphologies in regenerating and homeostatic planaria (Dugesia dorotocephala).
Here, recognizing the recognizing the growing threat of non-biodegradable plastic waste, the authors investigated the ability to use a modified enzyme identified in bacteria to decompose polyethylene terephthalate (PET). They used simulations to screen and identify an optimized enzyme based on machine learning models. Ultimately, they identified a potential mutant PETases capable of decomposing PET with improved thermal stability.
The use of fertilizers is associated with an increase in soil degradation, which is predicted to lead to a decrease in crop production within the next decade. Thus, it is critical to find solutions to support crop production to sustain the robust global population. In this study, the authors investigate how probiotic bacteria, like Rhizobium leguminosarum, Bacillus subtilis and Pseudomonas fluorescens, can impact the growth of Arabidopsis thaliana when applied to the seeds.They hypothesized that solutions with multiple bacterial species compared to those with only a single bacterial species would promote seed germination more effectively.
Expanded polystyrene (EPS) is a plastic used to make food containers and packing materials that poses a threat to the environment. Mealworms can degrade EPS, but at a slow rate. Here, researchers assessed the impact of food waste compost and oats on the speed of EPS consumption by mealworms, superworms, and waxworms. A positive correlation was found between food waste compost supplementation and EPS consumption, especially by mealworms, indicating a potential industrial application.
This study hypothesized that sodium chloride was taken up through plant root structures to facilitate water transportation, and that sodium chloride accumulation was directly proportional to the soil salinity. Results showed that most cells within the “bulb” structures were isotonic at a concentration approximately twice as high as that of root tissue and ambient soil salinity, therefore supporting the presented hypothesis.
Breast cancer is the most common cancer in women, with approximately 300,000 diagnosed with breast cancer in 2023. It ranks second in cancer-related deaths for women, after lung cancer with nearly 50,000 deaths. Scientists have identified important genetic mutations in genes like BRCA1 and BRCA2 that lead to the development of breast cancer, but previous studies were limited as they focused on specific populations. To overcome limitations, diverse populations and powerful statistical methods like genome-wide association studies and whole-genome sequencing are needed. Explainable artificial intelligence (XAI) can be used in oncology and breast cancer research to overcome these limitations of specificity as it can analyze datasets of diagnosed patients by providing interpretable explanations for identified patterns and predictions. This project aims to achieve technological and medicinal goals by using advanced algorithms to identify breast cancer subtypes for faster diagnoses. Multiple methods were utilized to develop an efficient algorithm. We hypothesized that an XAI approach would be best as it can assign scores to genes, specifically with a 90% success rate. To test that, we ran multiple trials utilizing XAI methods through the identification of class-specific and patient-specific key genes. We found that the study demonstrated a pipeline that combines multiple XAI techniques to identify potential biomarker genes for breast cancer with a 95% success rate.