1, Packaged foods and beverages representation that leveraged pre-trained model in Natural Language Processing (NLP)

[1] Hu, G., Ahmed, M., & L’Abbé, M. (2023). Natural language processing and machine learning approaches for food categorization and nutrition quality prediction compared to traditional methods. The American Journal of Clinical Nutrition, 117(3), 449-450. (Editor’s Choice)

[2] Hu, G., Flexner, N., Tiscornia, M., & L’Abbé, M. (2023). Accelerating classification of food processing levels using a fine-tuned language model: a multi-country study. (working paper ready to submit)


2, Pathomics, metabolomics and lipidomics (Well-nourished vs Malnourished induced liver metabolic dysfunction)

[1] Hu, G., Ling, C., Chi, L., Thind, M. K., Furse, S., … & Bandsma, R. (2022). The role of the tryptophan-NAD + pathway in a mouse model of severe malnutrition induced liver dysfunction. Nature Communications, 13(1), 1-16.

[2] Arvidsson Kvissberg, M. E., Hu, G., Chi, L., Bourdon, C., Ling, C., ChenMi, Y., … & Bandsma, R. (2022). Inhibition of mTOR improves malnutrition induced hepatic metabolic dysfunction. Scientific Reports, 12(1), 1-12.


3, Food Processing

[1] Hu, G., Zheng, Y., Liu, Z., Deng, Y., & Zhao, Y. (2016). Structure and IgE-binding properties of α-casein treated by high hydrostatic pressure, UV-C, and far-IR radiations. Food Chemistry, 204, 46-55.

[2] Hu, G., Zheng, Y., Liu, Z., Xiao, Y., Deng, Y., & Zhao, Y. (2017). Effects of high hydrostatic pressure, ultraviolet light-C, and far-infrared treatments on the digestibility, antioxidant and antihypertensive activity of α-casein. Food Chemistry, 221, 1860-1866.