This project investigated whether previously identified genetic risk factors in non-Korean populations were associated with high gastric cancer incidence rates in Koreans.
Read More...Investigating the contribution of genetic risk factors to gastric cancer in Korean-ancestry populations
This project investigated whether previously identified genetic risk factors in non-Korean populations were associated with high gastric cancer incidence rates in Koreans.
Read More...Legacy mercury, reservoir dynamics, and dredging effects on methylmercury in San Francisco Bay
This study analyzes over two decades of monitoring data (1999-2022) to investigate how legacy mining, reservoir water releases, and dredging activities influence toxic methylmercury (MeHg) levels in San Francisco Bay. The findings reveal a significant delayed correlation between river flow and San Francisco Bay MeHg, and counter to the authors' hypothesis, a strong association between increased MeHg concentrations in the bay and both total annual dredging volume and beneficial sediment reuse / upland sediment disposal.
Read More...In silico design of an epitope-based vaccine for Rocio virus using phage display and E. coli expression system
The explored the potential of an epitope-based vaccine for Rocio virus using computational methods and M13 bacteriophage technology. Researchers identified 30 promising B- and T-cell epitopes and designed vaccine candidates using both phage display and E. coli expression systems.
Read More...Iron oxide nanoparticles coated with liposomes and chitosan pass a model blood–brain barrier to kill bacteria
This study explored using iron oxide nanoparticles embedded in liposomes and coated with antibacterial chitosan as a potential alternative to antibiotics for treating bacterial meningitis. The nanoparticles were tested for their ability to cross a model blood–brain barrier and kill E. coli, with and without magnetic guidance.
Read More...Lung region complexity affects Grad-CAM and Deep Taylor outcomes in pneumonia predictions
The authors studied the accuracy of two commonly used explainable AI techniques for detecting pneumonia in chest x-rays.
Read More...The development of FeO(OH) nanoparticles to extract synthetic motor oil from freshwater
This study aimed to combat widespread hydrocarbon residue persistently polluting global water sources by developing and testing the ability of modified iron(III) oxide-hydroxide (FeO(OH)) nanoparticles to remove small amounts of motor oil from freshwater
Read More...The relationship between meteorological factors and air quality in Washington D.C. metropolitan area
The authors studied the relationship between air quality and weather conditions (wind speed, precipitation, and temperature) in the Washington D.C. area.
Read More...A model for angle evolution in conical piles formed using the fixed funnel method
When granular materials are poured onto a surface, they form conical piles whose slopes increase before reaching a stable angle of repose. We found that this angle evolution follows a previously unrecognized two-phase exponential growth pattern that is conserved across granular materials with diverse particle properties. The parameters of this model correlate with particle friction and are influenced by deposition conditions, providing a quantitative framework for describing pile formation.
Read More...Integration of iron oxide nanoparticles into high-density polyethylene for sustainable cup coatings
Here the authors propose integrating magnetic iron (II) oxide nanoparticles into the high-density polyethylene linings of disposable paper cups to create a waterproof, magnetically responsive composite liner. Their findings demonstrate that these nanoparticles successfully bond with the plastic layer without disrupting its structural integrity, offering a viable method to improve plastic recovery through magnetic recycling and mitigate global microplastic pollution.
Read More...Distributional effects of residential energy tax credits: A machine learning approach
Tax incentives for sustainable technology are a key part of the push for a greener future. However, these incentives may not reach all income strata equally. Using a machine learning approach, this study analyzed the distributional effects of residential energy tax credits across different income levels in the United States.
Read More...