To explore the parent-child relationship during college planning, authors surveyed high school juniors from two private schools (boarding school vs. non-boarding parochial school). After coding, survey answers indicate students at boarding schools were found to have greater fear of parental control and disappointment, while students at non-boarding parochial schoolexpressed a greater need for parental assistance.

Cholesterol is a major component of neuronal cell membrane and myelin sheath. In this study, the authors either transfected Neuro 2A cells with CYP46A1 cDNA or treated the cells with 24SHC. Cells expressing CYP46A1 had significantly less viability compared to the negative control. Up to 55% reduction in cell viability was also observed in 24S-HC-treated cells. This work supports that CYP46A1 and 24S-HC could directly trigger cell death. The direct involvement of 24S-HC in cell death provides further evidence that 24S-HC can be a promising biomarker for diagnosing brain damage severity.

Mainstream cancer treatments, which include radiotherapy and chemotherapeutic drugs, are known to induce oxidative damage to healthy somatic cells due to the liberation of harmful free radicals. In order to avert this, physiological antioxidants must be complemented with external antioxidants. Here the authors performed a preliminary phytochemical screen to identify alkaloids, saponins, flavonoids, polyphenols, and tannins in all parts of the Amaranthus spinosus Linn. plant. This paper describes the preparation of this crude extract and assesses its antioxidant properties for potential use in complementary cancer treatment.

In this article, Harvell and Nicholson hypothesized that increased ocean acidity would decrease the photosynthetic ability of Chaetoceros gracilis, a diatom prolific in Monterey Bay, because of the usually corrosive effects of carbonic acid on both seashells and cells’ internal structures. They altered pH of algae environments and measured the photosynthetic ability of diatoms over four days by spectrophotometer. Overall, their findings indicate that C. gracilis may become more abundant in Monterey Bay as the pH of the ocean continues to drop, potentially contributing to harmful algal blooms.

Understanding the relationships between temperature, MEI, SPI, and CO2 concentration is important as they measure the major influencers of California’s regional climate: temperature, ENSO, precipitation, and atmospheric CO2. In this article, the authors analyzed temperature, Multivariate El Niño-Southern Oscillation Index (MEI), and Standard Precipitation Index (SPI) data from the San Francisco Bay Area from 1971 to 2016. They also analyzed CO2 records from Mauna Loa, HI for the same time period, along with the annual temperature anomalies for the Bay Area.

In this study, the authors sample water at different points closer and closer to two different airports to determine if these airports may be contributing to water pollution, specifically by measuring metals, nitrates, and pH.

In this study, the authors investigate whether a new compound has anti-cancer properties. Using the crude extract from the Amaranthus spinosus plant, HeLa cancer cells were assessed for cell death. Findings reveal that the extract (AS20) has cytotoxic effects on HeLa cells. Their findings introduce a new compound to potentially pursue in the hunt for novel cancer treatments.

This study uses neuroimaging to investigate cognitive set-shifting, a type of executive function that involves shifting from one task to another. This study tested whether cortical gray-white matter contrast in subregions of the prefrontal cortex (PFC) was associated with set-shifting abilities in adults.

Pandemics involve the high transmission of a disease that impacts global and local health and economic patterns. Epidemiological models help propose pandemic control strategies based on non-pharmaceutical interventions such as social distancing, curfews, and lockdowns, reducing the economic impact of these restrictions. In this research, we utilized an epidemiological Susceptible, Exposed, Infected, Recovered, Deceased (SEIRD) model – a compartmental model for virtually simulating a pandemic day by day.

Machine learning and deep learning techniques can be used to predict the early onset of breast cancer. The main objective of this analysis was to determine whether machine learning algorithms can be used to predict the onset of breast cancer with more than 90% accuracy. Based on research with supervised machine learning algorithms, Gaussian Naïve Bayes, K Nearest Algorithm, Random Forest, and Logistic Regression were considered because they offer a wide variety of classification methods and also provide high accuracy and performance. We hypothesized that all these algorithms would provide accurate results, and Random Forest and Logistic Regression would provide better accuracy and performance than Naïve Bayes and K Nearest Neighbor.