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• A multi-channel model based on recurrent variational autoencoders was proposed to capture spatial and temporal evolution of AD using multimodal data. • Proposed model was evaluated on synthetic and real datasets. • Model outperforms a set of baselines for missing data reconstruction across modalities. [Display omitted] The progression of neurodegenerative diseases, such as Alzheimer's Disease, is the result of complex mechanisms interacting across multiple spatial and temporal scales. Understanding and predicting the longitudinal course of the disease requires harnessing the variability across different data modalities and time, which is extremely challenging. In this paper, we propose a model based on recurrent variational autoencoders that is able to capture cross-channel interactions between different modalities and model temporal information. These are achieved thanks to its multi-channel architecture and its shared latent variational space, parametrized with a recurrent neural network. We evaluate our model on both synthetic and real longitudinal datasets, the latter including imaging and non-imaging data, with N = 897 subjects. Results show that our multi-channel recurrent variational autoencoder outperforms a set of baselines (KNN, random forest, and group factor analysis) for the task of reconstructing missing modalities, reducing the mean absolute error by 5 % (w.r.t. the best baseline) for both subcortical volumes and cortical thickness. Our model is robust to missing features within each modality and is able to generate realistic synthetic imaging biomarkers trajectories from cognitive scores. [ABSTRACT FROM AUTHOR]

Colorectal cancer (CRC) is classified as the third leading cancer globally and one of the major causes of morbidity and mortality around the world. The interaction of the immune system with the cancer cells plays a vital role in CRC progression. Regulatory T cells (Tregs) are a form of T cells, which regulate and suppress unwanted activation of the immune system and play a major role in preventing autoimmune diseases. Tregs exhibit a significant role in immune modulation during CRC progression through accumulation in the tumor microenvironment (TME) and suppression of immunity against tumor specific antigens promoting tumor progression. The role of Tregs in CRC progression and its interaction with other immune cells within CRC TME and current clinical trials were reviewed in this paper. [Display omitted] • Discusses the role of Tregs in immune modulation during CRC progression. • Explores the role of Tregs in CRC tumor microenvironment. • Highlights the mechanism of Tregs in CRC growth and metastasis. • Identifies and discusses current clinical trials targeting Tregs in CRC therapy. [ABSTRACT FROM AUTHOR]