The purpose of our study was to determine if direct administration of CXCL1/KC to cardiomyocytes causes negative changes to cell density or proliferation. This molecule has been shown to reduce inflammation in certain instances. Homocysteine models the direct effect of an inflammatory agent on cardiomyocytes. Our question was whether these molecules directly impact cell density through an interaction with the cell proliferation process. We hypothesized that cells treated with CXCL1/KC would maintain the same cell density as untreated cells. In contrast, cells treated with Homocysteine or both Homocysteine and CXCL1/KC, were expected to have a higher cell density that than that of untreated cells.

Control of voluntary and involuntary movements is one of the most important aspects of human neurological function, but the mechanisms of motor control are not completely understood. In this study, the authors use transcranial magnetic stimulation (TMS) to stimulate a portion of the motor cortex while subjects performed either discrete (e.g. throwing) or rhythmic (e.g. walking) movements. By recording electrical activity in the muscles during this process, the authors showed that motor evoked potentials (MEPs) measured in the muscles during TMS stimulation are larger in amplitude for discrete movements than for rhythmic movements. Interestingly, they also found that MEPs during transitions between rhythmic and discrete movements were nearly identical and larger in amplitude than those recorded during either rhythmic or discrete movements. This research provides important insights into the mechanisms of neurological control of movement and will serve as the foundation for future studies to learn more about temporal variability in neural activity during different movement types.

This study is centered around developing biofortification methods: the authors test whether the amount of calcium available to growing crops translates into more calcium present in the crops.

In this study, the authors engineer a cost-effective and bio-friendly water purification system using limestone, denitrifying bacteria, and sulfate-reducing bacteria. They evaluated its efficacy with samples from Eastern PA industrial sites.

Cross country is a popular sport in the U.S. Both athletes and coaches are interested in the factors that make runners successful. In this study, the authors explore the relationship between runners' physical attributes and their race performance.

In this study, the authors identify transcripts and gene networks that are changed after infection with the Middle East Respiratory Syndrome-related coronavirus (MERS-CoV).

In this study, the authors utilize an infrared camera to visualize and investigate the exothermic reaction of polyurethane foam, which has many everyday uses including automotive seats, bedding, and insulation.

In this research, a novel bioplastic inclusive of bamboo tannins and chitosan is selected from more than 60 trial formula variations based on resulting strength, fatigue, and transparency attributes. The biodegradability of the finalized bioplastic is compared to that of conventional polyethylene, in addition to investigating its solubility and water absorbance. This research displays the potential of a legitimate, fully biodegradable plastic alternative to current marketplace bioplastics.

Disruptions to the microbiome, specifically the imbalance in the two major phyla, the Firmicutes and the Bacteroidetes, have been linked to the development of obesity. This study explored whether or not Fage plain total 0% Greek yogurt, which contains live and active bacterial cultures belonging to the Firmicute phylum, could decrease the numbers of Bacteroides thetaiotaomicron, an organism found in the human gut that belongs to the Bacteroidetes phylum.

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.