The tumour microenvironment (TME) presents a major block to anti-tumour immune responses and to effective cancer immunotherapy. The inflammatory mediators such as cytokines, chemokines, growth factors and prostaglandins generated in the TME alter the phenotype and function of dendritic cells (DCs) that are critical for a successful adaptive immune response against the growing tumour. In this mini review we discuss how tumour cells and the surrounding stroma modulate DC maturation and trafficking to impact T cell function. Fibroblastic stroma and the associated extracellular matrix around tumours can also provide physical restrictions to infiltrating DCs and other leukocytes. We discuss interactions between the inflammatory TME and infiltrating immune cell function, exploring how the inflammatory TME affects generation of T cell-driven anti-tumour immunity. We discuss the open question of the relative importance of antigen-presentation site; locally within the TME versus tumour-draining lymph nodes. Addressing these questions will potentially increase immune surveillance and enhance anti-tumour immunity.

In this paper, a deep learning based fusion approach has been proposed to classify the emotions portrayed by image and corresponding text into discrete emotion classes. The proposed method first implements intermediate fusion on image and text inputs and then applies late fusion on image, text, and intermediate fusion's output. We have also come up with a way to handle the unavailability of labeled multimodal emotional data. We have prepared a new dataset built on Balanced Twitter for Sentiment Analysis dataset (B-T4SA) dataset containing an image, text, and emotion labels, i.e., 'happy,' 'sad,' 'hate' and 'anger.' The emotion recognition accuracy of 90.20% has been achieved by the proposed method. Along with multi-class emotion recognition, we've also compared the sentiment classification results and found the proposed method to perform better than the benchmark approaches.

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strand break (DSB) repair (53BP1, phospho-ATM and phospho-Histone H2A.X), vitality and cell cycling by performing high resolution 3D imaging (in fixed and live cells) using spinning disk microscopy. DSB were produced by X-ray irradiation. X-ray irradiated (6 Gy) Mia PaCa-2 cells in co-culture with unirradiated cells showed highly significantly less DSB relative to irradiated cells cultured alone. Intriguingly, the presence of unirradiated Mia PaCa-2 cells resulted in a rapid DBS repair in irradiated ATM -/fibroblasts down to levels of ATM þ/þ fibroblasts within 1 d after irradiation. Additionally, when irradiated Mia PaCa-2 cells were co-cultured with ATM -/fibroblasts or ATM þ/þ fibroblasts pretreated with an ATM inhibitor, the acceleration of DNA damage foci was completely abrogated similar to non-coculture conditions. Our findings suggest that ATM is a key transducer in cell-cell communication eliciting a rescue of neighboring cells from radiogenic DNA damage through a yet to be identified mechanism. Consequently, normal cells support each other in surviving radiogenic DNA damage, while cancer cells might be prone to develop resistances to current radiochemotherapies.