Cellular senescence plays a key role in aging cells and is attributed to a number of disease and pathology. These authors find that genetic editing of both RPS6KB1 and PPARGC1A revitalizes a human skin fibroblast cell line.

In this study, the authors investigate the demographic indicators for voter shift between the 2016 and 2020 presidential elections based on demographic data put through a K-nearest neighbors classification algorithm and Principal Component Analysis.

Ashley Moulton & Joseph Rasmus investigate 9 controversial categories of intelligence as predicted by Multiple Intelligence Theory, originally proposed in the mid-1980s. By collecting data from 56 participants, they record that there may not actually be a correlation between these categorical types when it comes to workplace atmosphere and project efficiency.

Kashyap Jha et al. look at the formulation of MAT20, a crude extract of the moringa, amla, and tulsi leaves, as a potential complementary and alternative medicine. Using HeLa cells, they find MAT20 up-regulates expression of inflammation and cell cytotoxicity markers. Their data is important for understanding the anti-cancer and anti-inflammatory properties of MAT20.

The facial integument, or external skin tissues, were assessed on set of dinosaurs from the Allosauroidea clade to test whether dermal patterns served specific functions.

In this study, the ability of arbuscular mycorrhizal fungi to limit the growth of an agricultural weed Cirsium arvense is tested. This has important implications for developing natural herbicides.

Head injuries are common in American football and the facemasks found on football helmets receive a lot of impact during contacts. This study investigates how effective they are at reducing concussion risk.

In order to determine whether unmarked soybeans in the market were genetically modified crops, the authors developed a polymerase chain reaction (PCR) screen for DNA lectin.

Seeking to investigate the effects of ambient pollutants on human respiratory health, here the authors used machine learning to examine asthma in Lost Angeles County, an area with substantial pollution. By using machine learning models and classification techniques, the authors identified that nitrogen dioxide and ozone levels were significantly correlated with asthma hospitalizations. Based on an identified seasonal surge in asthma hospitalizations, the authors suggest future directions to improve machine learning modeling to investigate these relationships.

In this study, the authors conduct a bibliometric analysis to understand the recent growth in and current state of peripheral nerve regeneration research. They also explored potential future studies.