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The authors looked at the impacts of short-chain fatty acids on muscle fiber formation as well as insulin sensitivity using a model of mouse myoblasts.

The authors looked at whether traditional Chinese medicine remedies that target the lungs and liver would reduce inflammation in a planaria model. They found that the two active compounds they tested were able to decrease induced inflammation by 97-98%.

The authors looked at whether CBD and THC would decrease reproductive rates in a Drosophila melanogaster model. They found that CBD had a greater impact on reducing hatching rates than THC, and that THC resulted in unexpected mortalities.

Here, the authors sought to develop a new metric to evaluate the efficacy of baseball pitchers using machine learning models. They found that the frequency of balls, was the most predictive feature for their walks/hits allowed per inning (WHIP) metric. While their machine learning models did not identify a defining trait, such as high velocity, spin rate, or types of pitches, they found that consistently pitching within the strike zone resulted in significantly lower WHIPs.

Long hospital stays can be stressful for the patient for many reasons. We hypothesized that age would be the greatest predictor of hospital stay among patients who underwent orthopedic surgery. Through our models, we found that severity of illness was indeed the highest factor that contributed to determining patient length of stay. The other two factors that followed were the facility that the patient was staying in and the type of procedure that they underwent.

Here the authors investigated alternative treatments for Parkinson's disease tremors, this study tested whether replacing the traditional carbidopa component with lovastatin in a levodopa combination would improve symptom reduction in a Drosophila melanogaster model. The findings revealed that the lovastatin–levodopa combination was more optimal at reducing tremors than the standard treatment, pointing to a potentially superior therapeutic approach for future investigation.

Using county-level epidemiological data from the Texas Department of State Health Services, this study implemented an SIRV model in Python to simulate measles transmission in Gaines County under different vaccination scenarios.

The authors looked at ways that autonomous vehicles could be trained to better perform in adverse weather without the use of actual images taken during adverse weather events. They were able to improve performance, but models using actual images still perform the best.

Machine learning offers a powerful way to analyze large astronomical datasets and identify stars with unusual properties. In this study, students used Extreme Gradient Boosting and Isolation Forest models to investigate why some red clump stars deviate from their expected luminosities. Their results show that stellar age plays a much stronger role than metallicity in driving luminosity variation, and the models successfully detected outlier stars that may affect distance measurements in galactic studies.

This study investigated whether soursop, a ketogenic diet-related compound called BHB, and circadian synchronization could reduce seizure recovery time in fruit flies used as a model for epilepsy.