Publications by authors named "Guochang Yang"
There is an evident requirement for a rapid, efficient, and simple method to screen the authenticity of milk products in the market. Fourier transform infrared (FTIR) spectroscopy stands out as a promising solution. This work employed FTIR spectroscopy and modern statistical machine learning algorithms for the identification and quantification of pasteurized milk adulteration.
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- The study addresses the issue of milk adulteration, where higher priced milks like buffalo, goat, and camel are mixed with cheaper cow milk or water, impacting consumer health and market dynamics.
- Using mid-infrared spectroscopy (MIRS) along with advanced statistical machine learning techniques, particularly support vector machines (SVM), the study successfully detected and quantified the levels of cow milk and water adulteration in various milk types.
- The research found that modern machine learning methods significantly outperformed traditional techniques like partial least squares (PLS), achieving high accuracy rates in classification and regression models for identifying and quantifying milk adulteration.
Cysteinyl leukotrienes (CysLTs) exert potent proinflammatory actions and contribute to many of the symptoms of asthma. Using a model of allergic sensitization and airway challenge with Aspergillus fumigatus (Af), we have found that Th2-type inflammation and airway hyperresponsiveness (AHR) to methacholine (MCh) were associated with increased LTD(4) responsiveness in mice. To explore the importance of increased CysLT signaling in airway smooth muscle function, we generated transgenic mice that overexpress the human CysLT1 receptor (hCysLT(1)R) via the alpha-actin promoter.
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