In this article the authors look at the lung microbiome in patients with cystic fibrosis to determine what the major bacterial species present are.

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.

Reimagize, a role-playing with decision-making, was conjured, implementing social psychological concepts like counter-stereotyping and perspective-taking. As the game works implicitly to influence body image, it even counters image issues beyond personal body dissatisfaction. This study explored whether a digital role-playing card game, incorporating some of the most common prejudices of body image (like size prejudice, prejudices from the media, etc.) as identified by a digital survey/questionnaire completed by Indian girls aged 11-21, could counter these issues and reduce personal body dissatisfaction.

Smoking generates free radicals and reactive oxygen species which induce cell damage and lipid peroxidation. This is linked to the development of oral cancer in chronic smokers. The authors of this study developed Quitpuff, simple colorimetric test to measure the extent of lipid peroxidation in saliva samples. This test detected salivary lipid peroxidation with 96% accuracy in test subjects and could serve as an inexpensive, non-invasive test for smokers to measure degree of salivary lipid peroxidation and potential risk of oral cancer.

While serving as an immediate address for psychological safety and stability, psychological first aid (PFA) currently lacks the incorporation of triage. Without triage, patients cannot be prioritized in correspondence to condition severity that is often called for within emergency conditions. To disentangle the relevance of a potential triage system to PFA, the authors of this paper have developed a method to quantify resilience - a prominent predictor of the capability to recover from a disaster. With this resilience index, they have quantified resilience of differing age, race, and sex demographics to better inform the practice of PFA and potential demographic prioritization via a triage system.

Staphylococcus aureus (S. aureus) has a mortality rate of up to 30% in developing countries. The purpose of this experiment was to determine if enzymatic and volatile compound-based approaches would perform more quickly in comparison to existing S. aureus diagnostic methods and to evaluate these novel methods on accuracy. Ultimately, this device provided results in less than 30 seconds, which is much quicker than existing methods that take anywhere from 10 minutes to 48 hours based on approach. Statistical analysis of accuracy provides preliminary confirmation that the device based on enzymatic and volatile compound-based approaches can be an accurate and time-efficient tool to detect pathogenic S. aureus.

The authors test the durability of synthetic versus non-synthetic fabrics though loose thread counts, color fade over time, and shrinkage tests.

In this study, the authors conduct a survey to evaluate the impact of household socioeconomic status on effectiveness of distance learning for students.

In this article the authors created an interaction map of proteins involved in colorectal cancer to look for driver vs. non-driver genes. That is they wanted to see if they could determine what genes are more likely to drive the development and progression in colorectal cancer and which are present in altered states but not necessarily driving disease progression.

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.