The authors compare RNA expression profiles across three human cell types following infection with MERS-CoV
Read More...Differential MERS-CoV response in different cell types
The authors compare RNA expression profiles across three human cell types following infection with MERS-CoV
Read More...Gene expression profiling of MERS-CoV-London strain
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).
Read More...A bibliometric analysis of the use of biomimetic silk conduits for treating peripheral nerve injuries
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.
Read More...Testing HCN1 channel dysregulation in the prefrontal cortex using a novel piezoelectric silk neuromodulator
Although no comprehensive characterization of schizophrenia exists, there is a general consensus that patients have electrical dysfunction in the prefrontal cortex. The authors designed a novel piezoelectric silk-based implant and optimized electrical output through the addition of conductive materials zinc oxide (ZnO) and aluminum nitride (AlN). With further research and compatibility studies, this implant could rectify electrical misfiring in the infralimbic prefrontal cortex.
Read More...The impact of timing and magnitude of the El Niño- Southern Oscillation on local precipitation levels and temperatures in the Bay Area
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.
Read More...Reducing PMA-induced COX-2 expression using a herbal formulation in MCF-7 breast cancer cells
In this study, the authors investigate the effect of a herbal formulation on Cyclooxygenase-2 (COX-2) expression in cancer cells. High levels of COX-2 correlates with worsened cancer outcomes and the authors hypothesize that the formulation will inhibit COX-2 levels.
Read More...Evaluation of in vitro anti-inflammatory effect of PLAY® on UC-MSCs: A COX-2 expression study
The authors seek to accelerate wound healing by reducing inflammation with a cocktail containing growth factors and bioactive modulators.
Read More...Investigating Hydrogen as a Potential Alternative to Kerosene in Fueling Commercial Aircraft
Growing climate concerns have intensified research into zero-emission transportation fuels, notably hydrogen. Hydrogen is considered a clean fuel because its only major by-product is water. This project analyzes how hydrogen compares to kerosene as a commercial aircraft fuel with respect to cost, CO2 emissions, and flight range.
Read More...Utilizing a novel T1rho method to detect spinal degeneration via magnetic resonance imaging
Spinal degeneration has been linked to critical conditions such as osteoarthritis in adults aged 40+; while this condition is considered to be irreversible, we took interest in magnetic resonance imaging (MRI) for early detection of the condition. Ultimately, our purpose was to determine the effectiveness of a relatively novel T1rho method in the early detection of spinal degeneration, and we hypothesized that the early to mild progression of spinal degeneration would affect T1rho values following an MRI scan.
Read More...A novel approach for predicting Alzheimer’s disease using machine learning on DNA methylation in blood
Here, recognizing the difficulty associated with tracking the progression of dementia, the authors used machine learning models to predict between the presence of cognitive normalcy, mild cognitive impairment, and Alzheimer's Disease, based on blood DNA methylation levels, sex, and age. With four machine learning models and two dataset dimensionality reduction methods they achieved an accuracy of 53.33%.
Read More...Search articles by title, author name, or tags