Explainable Disease Classification via weakly-supervised segmentation

Deep learning based approaches to Computer Aided Diagnosis (CAD) typically pose the problem as an image classification (Normal or Abnormal) problem. These systems achieve high to very high accuracy in specific disease detection for which they are trained but lack in terms of an explanation for the provided decision/classification result. The activation maps which correspond to decisions do not correlate well with regions of interest for specific diseases. This paper examines this problem and proposes an approach which mimics the clinical practice of looking for an evidence prior to diagnosis. A CAD model is learnt using a mixed set of information: class labels for the entire training set of images plus a rough localisation of suspect regions as an extra input for a smaller subset of training images for guiding the learning. The proposed approach is illustrated with detection of diabetic macular edema (DME) from OCT slices. Results of testing on on a large public dataset show that with just a third of images with roughly segmented fluid filled regions, the classification accuracy is on par with state of the art methods while providing a good explanation in the form of anatomically accurate heatmap /region of interest. The proposed solution is then adapted to Breast Cancer detection from mammographic images. Good evaluation results on public datasets underscores the generalisability of the proposed solution

Simple method for sub-diffraction resolution imaging of cellular structures on standard confocal microscopes by three-photon absorption of quantum dots

This study describes a simple technique that improves a recently developed 3D sub-diffraction imaging method based on three-photon absorption of commercially available quantum dots. The method combines imaging of biological samples via tri-exciton generation in quantum dots with deconvolution and spectral multiplexing, resulting in a novel approach for multi-color imaging of even thick biological samples at a 1.4 to 1.9-fold better spatial resolution. This approach is realized on a conventional confocal microscope equipped with standard continuous-wave lasers. We demonstrate the potential of multi-color tri-exciton imaging of quantum dots combined with deconvolution on viral vesicles in lentivirally transduced cells as well as intermediate filaments in three-dimensional clusters of mouse-derived neural stem cells (neurospheres) and dense microtubuli arrays in myotubes formed by stacks of differentiated C2C12 myoblasts

The Complete Star Formation History of the Universe

The determination of the star-formation history of the Universe is a key goal of modern cosmology, as it is crucial to our understanding of how structure in the Universe forms and evolves. A picture has built up over recent years, piece-by-piece, by observing young stars in distant galaxies at different times in the past. These studies indicated that the stellar birthrate peaked some 8 billion years ago, and then declined by a factor of around ten to its present value. Here we report on a new study which obtains the complete star formation history by analysing the fossil record of the stellar populations of 96545 nearby galaxies. Broadly, our results support those derived from high-redshift galaxies elsewhere in the Universe. We find, however, that the peak of star formation was more recent - around 5 billion years ago. Our study also shows that the bigger the stellar mass of the galaxy, the earlier the stars were formed. This striking result indicates a very different formation history for high- and low-mass formation.Comment: Accepted by Nature. Press embargo until publishe

Placental syncytiotrophoblast constitutes a major barrier to vertical transmission of Listeria monocytogenes.

Listeria monocytogenes is an important cause of maternal-fetal infections and serves as a model organism to study these important but poorly understood events. L. monocytogenes can infect non-phagocytic cells by two means: direct invasion and cell-to-cell spread. The relative contribution of each method to placental infection is controversial, as is the anatomical site of invasion. Here, we report for the first time the use of first trimester placental organ cultures to quantitatively analyze L. monocytogenes infection of the human placenta. Contrary to previous reports, we found that the syncytiotrophoblast, which constitutes most of the placental surface and is bathed in maternal blood, was highly resistant to L. monocytogenes infection by either internalin-mediated invasion or cell-to-cell spread. Instead, extravillous cytotrophoblasts-which anchor the placenta in the decidua (uterine lining) and abundantly express E-cadherin-served as the primary portal of entry for L. monocytogenes from both extracellular and intracellular compartments. Subsequent bacterial dissemination to the villous stroma, where fetal capillaries are found, was hampered by further cellular and histological barriers. Our study suggests the placenta has evolved multiple mechanisms to resist pathogen infection, especially from maternal blood. These findings provide a novel explanation why almost all placental pathogens have intracellular life cycles: they may need maternal cells to reach the decidua and infect the placenta

Experimental bond behaviour of GFRP and masonry bricks under impulsive loading

Fibre Reinforced Polymers have become a popular material for strengthening of masonry structures. The performance of this technique is strongly dependent on the bond between the FRP and the substrate. Understanding the strain rate effect on these materials and strengthening techniques is important for proper design and proper modelling of these systems under impacts or blast loads. This work aims to study the behaviour of the bond between GFRP and brick at different strain rates. A Drop Weight Impact Machine specially developed for pull-off tests (single shear tests) is used with different masses and different heights introducing different deformation rates. The strain rate effect on the failure mode, shear capacity and effective bond length is determined from the experimental results. Empirical relations of dynamic increase factors (DIF) for these materials and techniques are also presented.This work was performed under Project CH-SECURE (PTDC/EMC/120118/2010) funded by the Portuguese Foundation of Science and Technology – FCT. The authors acknowledge the support. The first author also acknowledges the support from his PhD FCT grant with the reference SFRH/BD/45436/2008

Sequence and Phylogenetic Analysis of SSU rRNA Gene of Five Microsporidia

The complete small subunit rRNA (SSU rRNA) gene sequences of five microsporidia including Nosemaheliothidis, and four novel microsporidia isolated from Pieris rapae, Phyllobrotica armta, Hemerophila atrilineata, and Bombyx mori, respectively, were obtained by PCR amplification, cloning, and sequencing. Two phylogenetic trees based on SSU rRNA sequences had been constructed by using Neighbor-Joining of Phylip software and UPGMA of MEGA4.0 software. The taxonomic status of four novel microsporidia was determined by analysis of phylogenetic relationship, length, G+C content, identity, and divergence of the SSU rRNA sequences. The results showed that the microsporidia isolated from Pieris rapae, Phyllobrotica armta, and Hemerophila atrilineata have close phylogenetic relationship with the Nosema, while another microsporidium isolated from Bombyx mori is closely related to the Endoreticulatus. So, we temporarily classify three novel species of microsporidia to genus Nosema, as Nosema sp. PR, Nosema sp. PA, Nosema sp. HA. Another is temporarily classified into genus Endoreticulatus, as Endoreticulatus sp. Zhenjiang. The result indicated as well that it is feasible and valuable to elucidate phylogenetic relationships and taxonomic status of microsporidian species by analyzing information from SSU rRNA sequences of microsporidia

Controlling Cherenkov angles with resonance transition radiation

Cherenkov radiation provides a valuable way to identify high energy particles in a wide momentum range, through the relation between the particle velocity and the Cherenkov angle. However, since the Cherenkov angle depends only on material's permittivity, the material unavoidably sets a fundamental limit to the momentum coverage and sensitivity of Cherenkov detectors. For example, Ring Imaging Cherenkov detectors must employ materials transparent to the frequency of interest as well as possessing permittivities close to unity to identify particles in the multi GeV range, and thus are often limited to large gas chambers. It would be extremely important albeit challenging to lift this fundamental limit and control Cherenkov angles as preferred. Here we propose a new mechanism that uses constructive interference of resonance transition radiation from photonic crystals to generate both forward and backward Cherenkov radiation. This mechanism can control Cherenkov angles in a flexible way with high sensitivity to any desired range of velocities. Photonic crystals thus overcome the severe material limit for Cherenkov detectors, enabling the use of transparent materials with arbitrary values of permittivity, and provide a promising option suited for identification of particles at high energy with enhanced sensitivity.Comment: There are 16 pages and 4 figures for the manuscript. Supplementary information with 18 pages and 5 figures, appended at the end of the file with the manuscript. Source files in Word format converted to PDF. Submitted to Nature Physic

Supernova Remnants as Clues to Their Progenitors

Supernovae shape the interstellar medium, chemically enrich their host galaxies, and generate powerful interstellar shocks that drive future generations of star formation. The shock produced by a supernova event acts as a type of time machine, probing the mass loss history of the progenitor system back to ages of $\sim$ 10 000 years before the explosion, whereas supernova remnants probe a much earlier stage of stellar evolution, interacting with material expelled during the progenitor's much earlier evolution. In this chapter we will review how observations of supernova remnants allow us to infer fundamental properties of the progenitor system. We will provide detailed examples of how bulk characteristics of a remnant, such as its chemical composition and dynamics, allow us to infer properties of the progenitor evolution. In the latter half of this chapter, we will show how this exercise may be extended from individual objects to SNR as classes of objects, and how there are clear bifurcations in the dynamics and spectral characteristics of core collapse and thermonuclear supernova remnants. We will finish the chapter by touching on recent advances in the modeling of massive stars, and the implications for observable properties of supernovae and their remnants.Comment: A chapter in "Handbook of Supernovae" edited by Athem W. Alsabti and Paul Murdin (18 pages, 6 figures