All Outputs (2)

Modelling a dynamic magneto-agglutination bioassay (2022)
Journal Article
Hughes, R., Fishman, A., Lamb-Riddell, K., Sleigh Muñoz, V., Champneys, A., Kiely, J., & Luxton, R. (2023). Modelling a dynamic magneto-agglutination bioassay. Biosensors and Bioelectronics, 222, 114745. https://doi.org/10.1016/j.bios.2022.114745

The process of developing an end-to-end model of a magneto-immunoassay is described, simulating the agglutination effect due to the specific binding of bacteria to paramagnetic particles. After establishing the properties of the dose-specific aggluti... Read More about Modelling a dynamic magneto-agglutination bioassay.

Shedding smart light on the effectiveness of chemotherapy: using Raman spectroscopy and machine learning to differentiate the effects of Cytarabine toxicity and crosstalk of leukaemic and bone marrow stromal cells (2021)
Journal Article
Gynn, L., Lamb-Riddell, K., Cox, T., Hansen, M., Conway, M., & May, J. (2021). Shedding smart light on the effectiveness of chemotherapy: using Raman spectroscopy and machine learning to differentiate the effects of Cytarabine toxicity and crosstalk of leukaemic and bone marrow stromal cells. British Journal of Haematology, 193(S1), 46-47

Mesenchymal stromal cells (MSC) protect leukaemic cells from drug-induced toxicity within the bone marrow niche, with increasing evidence of leukaemic impact on supportive stroma. The nucleoside analogue, cytarabine (ara-C), is a front-line agent for... Read More about Shedding smart light on the effectiveness of chemotherapy: using Raman spectroscopy and machine learning to differentiate the effects of Cytarabine toxicity and crosstalk of leukaemic and bone marrow stromal cells.