Van der Woude syndrome is a common birth defect caused by mutations in the gene Irf6. In this project, students used microarray expression analysis from wild-type and Irf6-deficient mice in order to identify gene networks or pathways differentially regulated due to the Irf6 mutation. They found NF-κB pathway to be activated in deficient mice.

In many cultures and for many centuries, the implications of birth order have been examined. Birth order has been shown to affect personality, accomplishments, and even career choice. This study investigated the impact of birth order and ethnicity on two measures of academic success in high school: a student’s grade point average (GPA) and the number of Advanced Placement (AP) classes he or she took.

In this manuscript the authors looked at current vaccine strategies against different strains of influenza. Looking at several factors they found that influenza strain as well as vaccinated age group, among other factors, impact vaccine effectiveness.

In this study, Donnellan and colleagues investigated how environmental pollution may be affecting honey samples from Chicago apiaries. They found no significant correlation between heavy metal concentration in honey to distance from local industries, suggesting a minimal effect of proximity to industrial pollution on honey contamination.

In this study, the authors study features of exoplanet 189733 b. This exoplanet, or planets that orbit stars other than the Sun, is found in the HD star system. Using a DSLR camera, they constructed a high caliber exoplanet transit detection tracker to study the orbital periods, radial velocity, and photometry of 189733 b. They then compared results from their system to data collected by other high precision studies. What they found was that their system produced results supporting previously published studies. These results are exciting results from the solar system demonstrating the importance of validating radial velocity and photometry data using high-precision studies.

Neural networks are used throughout modern society to solve many problems commonly thought of as impossible for computers. Fountain and Rasmus designed a convolutional neural network and ran it with varying levels of training to see if consistent, accurate, and precise changes or patterns could be observed. They found that training introduced and strengthened patterns in the weights and visualizations, the patterns observed may not be consistent between all neural networks.

Aloe vera and alpha-chymotrypsin have been used in are known for their various wound healing properties. Halder et al hypothesized that these treatments would enhance wound healing in Drosophila melanogaster larvae over 2 weeks by decreasing wound size more effectively compared to controls. The results of two of the treatment groups, Salep and Aloe vera, yielded wound sizes small enough to present a significant percent decrease when compared with the wound sizes of the control group. Their results show support that both Salep and Aloe vera were effective for enhancing wound healing in epithelial cells in D. melanogaster larvae.

Psoriasis is a heritable autoimmune disorder characterized by abnormal red and itchy skin patches. The authors study the family of a man with psoriasis. They explore whether the man's children, who do not show any symptoms of psoriasis, demonstrate gene expression consistent with the disease.

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.

The authors look at using publicly available data and machine learning to see if they can develop a criminal activity index for counties within the state of California.