A Robust Interpretable Deep Learning Classifier for Heart Anomaly Detection Without Segmentation

Traditionally, abnormal heart sound classification is framed as a three-stage process. The first stage involves segmenting the phonocardiogram to detect fundamental heart sounds; after which features are extracted and classification is performed. Some researchers in the field argue the segmentation step is an unwanted computational burden, whereas others embrace it as a prior step to feature extraction. When comparing accuracies achieved by studies that have segmented heart sounds before analysis with those who have overlooked that step, the question of whether to segment heart sounds before feature extraction is still open. In this study, we explicitly examine the importance of heart sound segmentation as a prior step for heart sound classification, and then seek to apply the obtained insights to propose a robust classifier for abnormal heart sound detection. Furthermore, recognizing the pressing need for explainable Artificial Intelligence (AI) models in the medical domain, we also unveil hidden representations learned by the classifier using model interpretation techniques. Experimental results demonstrate that the segmentation plays an essential role in abnormal heart sound classification. Our new classifier is also shown to be robust, stable and most importantly, explainable, with an accuracy of almost 100% on the widely used PhysioNet dataset

Holographic optical trapping Raman micro-spectroscopy for non-invasive measurement and manipulation of live cells

We present a new approach for combining holographic optical tweezers with confocal Raman spectroscopy. Multiple laser foci, generated using a liquid-crystal spatial light modulator, are individually used for both optical trapping and excitation of spontaneous Raman spectroscopy from trapped objects. Raman scattering from each laser focus is spatially filtered using reflective apertures on a digital micro-mirror device, which can be reconfigured with flexible patterns at video rate. We discuss operation of the instrument, and performance and viability considerations for biological measurements. We then demonstrate the capability of the instrument for fast, flexible, and interactive manipulation with molecular measurement of interacting live cell systems

Allergen recognition by innate immune cells: critical role of dendritic and epithelial cells

Allergy is an exacerbated response of the immune system against non-self-proteins called allergens and is typically characterized by biased type-2 T helper cell and deleterious IgE mediated immune responses. The allergic cascade starts with the recognition of allergens by antigen presenting cells, mainly dendritic cells (DCs), leading to Th2 polarization, switching to IgE production by B cells, culminating in mast cell sensitization and triggering. DCs have been demonstrated to play a crucial role in orchestrating allergic diseases. Using different C-type lectin receptors DCs are able to recognize and internalize a number of allergens from diverse sources leading to sensitization. Furthermore, there is increasing evidence highlighting the role of epithelial cells in triggering and modulating immune responses to allergens. As well as providing a physical barrier, epithelial cells can interact with allergens and influence DCs behavior through the release of a number of Th2 promoting cytokines. In this review we will summarize current understanding of how allergens are recognized by DCs and epithelial cells and what are the consequences of such interaction in the context of allergic sensitization and downstream events leading to allergic inflammation. Better understanding of the molecular mechanisms of allergen recognition and associated signaling pathways could enable developing more effective therapeutic strategies that target the initial steps of allergic sensitization hence hindering development or progression of allergic diseases

Microfluidics for Advanced Drug Delivery Systems.

Considerable efforts have been devoted towards developing effective drug delivery methods. Microfluidic systems, with their capability for precise handling and transport of small liquid quantities, have emerged as a promising platform for designing advanced drug delivery systems. Thus, microfluidic systems have been increasingly used for fabrication of drug carriers or direct drug delivery to a targeted tissue. In this review, the recent advances in these areas are critically reviewed and the shortcomings and opportunities are discussed. In addition, we highlight the efforts towards developing smart drug delivery platforms with integrated sensing and drug delivery components