Fungal disease poses a growing threat to public health that our current antifungal therapies are not well equipped to meet. As the population of immunocompromised hosts expands, and ecological changes favor the emergence of fungal pathogens, the development of new antifungal agents, including vaccines, becomes a global priority. Here, we summarize recent advancements in the understanding of fungal pathogenesis, key features of the host antifungal immune response, and how these findings could be leveraged to design novel approaches to deadly fungal disease.
View Article and Find Full Text PDFIntroduction: We propose a novel approach for the non-invasive quantification of dynamic PET imaging data, focusing on the arterial input function (AIF) without the need for invasive arterial cannulation.
Methods: Our method utilizes a combination of three-dimensional depth-wise separable convolutional layers and a physically informed deep neural network to incorporatea priori knowledge about the AIF's functional form and shape, enabling precise predictions of the concentrations of [C]PBR28 in whole blood and the free tracer in metabolite-corrected plasma.
Results: We found a robust linear correlation between our model's predicted AIF curves and those obtained through traditional, invasive measurements.
Candida spp. are the fourth leading cause of bloodstream infections in hospitalized patients and the most common cause of invasive fungal infection. No vaccine against Candida spp.
View Article and Find Full Text PDFDeveloping anticancer drugs from preclinical to clinical takes approximately a decade in a cutting-edge biomedical lab and still 97% of most fail at clinical trials. Cell line usage is critical in expediting the advancement of anticancer therapies. Yet developing appropriate cell lines has been challenging and overcoming these obstacles whilst implementing a systematic approach of utilizing 3D models that recapitulate the tumour microenvironment is prudent.
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