The authors test the effects of the pesticide captan on the growth of gut microbiome bacteria including Bacillus coagulan and Escherichia coli.
Read More...Inhibitory effects of captan on growth of Escherichia coli and Bacillus coagulans
The authors test the effects of the pesticide captan on the growth of gut microbiome bacteria including Bacillus coagulan and Escherichia coli.
Read More...Extracellular vesicles derived from oxidatively stressed stromal cells promote cancer progression
This paper hypothesized that the tumor microenvironment mediates cancer’s response to oxidative stress by delivering extracellular vesicles to cancer cells. Breast and lung cancer cells were treated with EVs, reavealing that EVs extracted from oxidatively stressed adipocytes increased the cell proliferation of breast cancer cells. These findings present a novel way that the TME influences cancer progression.
Read More...Using explainable artificial intelligence to identify patient-specific breast cancer subtypes
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.
Read More...The characterization of quorum sensing trajectories of Vibrio fischeri using longitudinal data analytics
Quorum sensing (QS) is the process in which bacteria recognize and respond to the surrounding cell density, and it can be inhibited by certain antimicrobial substances. This study showed that illumination intensity data is insufficient for evaluating QS activity without proper statistical modeling. It concluded that modeling illumination intensity through time provides a more accurate evaluation of QS activity than conventional cross-sectional analysis.
Read More...Comparing the reducing sugars in avocados, soybeans, and cinnamon: A Benedict’s test experiment
The authors test the levels of reducing sugars in avocados, soybeans, and cinnamon as part of a diet for individuals managing Type II diabetes.
Read More...Varying levels of disinfectant resistance among invasive Klebsiella pneumoniae isolates
The authors identify disinfectant-resistant bacterial strains of infection-causing bacteria from samples collected at a hospital setting.
Read More...Heterotrophic culture of Spirulina platensis improved its growth and the study of its nutritional effect
The authors looked at the ability to grow S. platensis on a larger scale with reduced cost given that it is currently quite expensive to grow, but poses as an important food source in the future.
Read More...DNA repair protein mutations alter blood cancer sensitivity to cisplatin or gemcitabine in vitro
The authors investigate whether human blood cancers carrying mutations in DNA repair genes possess increased sensitivity to common chemotherapy drugs cisplatin or gemcitabine.
Read More...A novel approach for predicting Alzheimer’s disease using machine learning on DNA methylation in blood
Here, recognizing the difficulty associated with tracking the progression of dementia, the authors used machine learning models to predict between the presence of cognitive normalcy, mild cognitive impairment, and Alzheimer's Disease, based on blood DNA methylation levels, sex, and age. With four machine learning models and two dataset dimensionality reduction methods they achieved an accuracy of 53.33%.
Read More...Analysis of the lung microbiome in cystic fibrosis patients using 16S sequencing
In this article the authors look at the lung microbiome in patients with cystic fibrosis to determine what the major bacterial species present are.
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