Bio-inspired Attentive Segmentation of Retinal OCT Imaging

Albeit optical coherence imaging (OCT) is widely used to assess ophthalmic pathologies, localization of intra-retinal boundaries suffers from erroneous segmentations due to image artifacts or topological abnormalities. Although deep learning-based methods have been effectively applied in OCT imaging, accurate automated layer segmentation remains a challenging task, with the flexibility and precision of most methods being highly constrained. In this paper, we propose a novel method to segment all retinal layers, tailored to the bio-topological OCT geometry. In addition to traditional learning of shift-invariant features, our method learns in selected pixels horizontally and vertically, exploiting the orientation of the extracted features. In this way, the most discriminative retinal features are generated in a robust manner, while long-range pixel dependencies across spatial locations are efficiently captured. To validate the effectiveness and generalisation of our method, we implement three sets of networks based on different backbone models. Results on three independent studies show that our methodology consistently produces more accurate segmentations than state-of-the-art networks, and shows better precision and agreement with ground truth. Thus, our method not only improves segmentation, but also enhances the statistical power of clinical trials with layer thickness change outcomes

Heralded single photon absorption by a single atom

The emission and absorption of single photons by single atomic particles is a fundamental limit of matter-light interaction, manifesting its quantum mechanical nature. At the same time, as a controlled process it is a key enabling tool for quantum technologies, such as quantum optical information technology [1, 2] and quantum metrology [3, 4, 5, 6]. Controlling both emission and absorption will allow implementing quantum networking scenarios [1, 7, 8, 9], where photonic communication of quantum information is interfaced with its local processing in atoms. In studies of single-photon emission, recent progress includes control of the shape, bandwidth, frequency, and polarization of single-photon sources [10, 11, 12, 13, 14, 15, 16, 17], and the demonstration of atom-photon entanglement [18, 19, 20]. Controlled absorption of a single photon by a single atom is much less investigated; proposals exist but only very preliminary steps have been taken experimentally such as detecting the attenuation and phase shift of a weak laser beam by a single atom [21, 22], and designing an optical system that covers a large fraction of the full solid angle [23, 24, 25]. Here we report the interaction of single heralded photons with a single trapped atom. We find strong correlations of the detection of a heralding photon with a change in the quantum state of the atom marking absorption of the quantum-correlated heralded photon. In coupling a single absorber with a quantum light source, our experiment demonstrates previously unexplored matter-light interaction, while opening up new avenues towards photon-atom entanglement conversion in quantum technology.Comment: 10 pages, 4 figure

Envelope: interactive software for modeling and fitting complex isotope distributions

<p>Abstract</p> <p>Background</p> <p>An important aspect of proteomic mass spectrometry involves quantifying and interpreting the isotope distributions arising from mixtures of macromolecules with different isotope labeling patterns. These patterns can be quite complex, in particular with <it>in vivo </it>metabolic labeling experiments producing fractional atomic labeling or fractional residue labeling of peptides or other macromolecules. In general, it can be difficult to distinguish the contributions of species with different labeling patterns to an experimental spectrum and difficult to calculate a theoretical isotope distribution to fit such data. There is a need for interactive and user-friendly software that can calculate and fit the entire isotope distribution of a complex mixture while comparing these calculations with experimental data and extracting the contributions from the differently labeled species.</p> <p>Results</p> <p>Envelope has been developed to be user-friendly while still being as flexible and powerful as possible. Envelope can simultaneously calculate the isotope distributions for any number of different labeling patterns for a given peptide or oligonucleotide, while automatically summing these into a single overall isotope distribution. Envelope can handle fractional or complete atom or residue-based labeling, and the contribution from each different user-defined labeling pattern is clearly illustrated in the interactive display and is individually adjustable. At present, Envelope supports labeling with ²H, ¹³C, and ¹⁵N, and supports adjustments for baseline correction, an instrument accuracy offset in the m/z domain, and peak width. Furthermore, Envelope can display experimental data superimposed on calculated isotope distributions, and calculate a least-squares goodness of fit between the two. All of this information is displayed on the screen in a single graphical user interface. Envelope supports high-quality output of experimental and calculated distributions in PNG or PDF format. Beyond simply comparing calculated distributions to experimental data, Envelope is useful for planning or designing metabolic labeling experiments, by visualizing hypothetical isotope distributions in order to evaluate the feasibility of a labeling strategy. Envelope is also useful as a teaching tool, with its real-time display capabilities providing a straightforward way to illustrate the key variable factors that contribute to an observed isotope distribution.</p> <p>Conclusion</p> <p>Envelope is a powerful tool for the interactive calculation and visualization of complex isotope distributions for comparison to experimental data. It is available under the GNU General Public License from <url>http://williamson.scripps.edu/envelope/</url>.</p

Definitions of recovery and outcomes of major depression: results from a 10-year follow-up

Furukawa TA, Fujita A, Harai H, Yoshimura R, Kitamura T, Takahashi K. Definitions of recovery and outcomes of major depression: results from a 10-year follow-up

COVID-19: protocol for observational studies utilizing near real-time electronic Australian general practice data to promote effective care and best-practice policy—a design thinking approach

Background: Health systems around the world have been forced to make choices about how to prioritize care, manage infection control and maintain reserve capacity for future disease outbreaks. Primary healthcare has moved into the front line as COVID-19 testing transitions from hospitals to multiple providers, where tracking testing behaviours can be fragmented and delayed. Pooled general practice data are a valuable resource which can be used to inform population and individual care decision-making. This project aims to examine the feasibility of using near real-time electronic general practice data to promote effective care and best-practice policy. Methods: The project will utilize a design thinking approach involving all collaborators (primary health networks [PHNs], general practices, consumer groups, researchers, and digital health developers, pathology professionals) to enhance the development of meaningful and translational project outcomes. The project will be based on a series of observational studies utilizing near real-time electronic general practice data from a secure and comprehensive digital health platform [POpulation Level Analysis and Reporting (POLAR) general practice data warehouse]. The study will be carried out over 1.5 years (July 2020–December 2021) using data from over 450 general practices within three Victorian PHNs and Gippsland PHN, Eastern Melbourne PHN and South Eastern Melbourne PHN, supplemented by data from consenting general practices from two PHNs in New South Wales, Central and Eastern Sydney PHN and South Western Sydney PHN. Discussion: The project will be developed using a design thinking approach, leading to the building of a meaningful near real-time COVID-19 geospatial reporting framework and dashboard for decision-makers at community, state and nationwide levels, to identify and monitor emerging trends and the impact of interventions/policy decisions. This will integrate timely evidence about the impact of the COVID-19 pandemic related to its diagnosis and treatment, and its impact across clinical, population and general practice levels

A Dynamic Model of Interactions of Ca^(2+), Calmodulin, and Catalytic Subunits of Ca^(2+)/Calmodulin-Dependent Protein Kinase II

During the acquisition of memories, influx of Ca^(2+) into the postsynaptic spine through the pores of activated N-methyl-D-aspartate-type glutamate receptors triggers processes that change the strength of excitatory synapses. The pattern of Ca^(2+) influx during the first few seconds of activity is interpreted within the Ca^(2+)-dependent signaling network such that synaptic strength is eventually either potentiated or depressed. Many of the critical signaling enzymes that control synaptic plasticity, including Ca^(2+)/calmodulin-dependent protein kinase II (CaMKII), are regulated by calmodulin, a small protein that can bind up to 4 Ca^(2+) ions. As a first step toward clarifying how the Ca^(2+)-signaling network decides between potentiation or depression, we have created a kinetic model of the interactions of Ca^(2+), calmodulin, and CaMKII that represents our best understanding of the dynamics of these interactions under conditions that resemble those in a postsynaptic spine. We constrained parameters of the model from data in the literature, or from our own measurements, and then predicted time courses of activation and autophosphorylation of CaMKII under a variety of conditions. Simulations showed that species of calmodulin with fewer than four bound Ca^(2+) play a significant role in activation of CaMKII in the physiological regime, supporting the notion that processing ofCa^(2+) signals in a spine involves competition among target enzymes for binding to unsaturated species of CaM in an environment in which the concentration of Ca^(2+) is fluctuating rapidly. Indeed, we showed that dependence of activation on the frequency of Ca^(2+) transients arises from the kinetics of interaction of fluctuating Ca^(2+) with calmodulin/CaMKII complexes. We used parameter sensitivity analysis to identify which parameters will be most beneficial to measure more carefully to improve the accuracy of predictions. This model provides a quantitative base from which to build more complex dynamic models of postsynaptic signal transduction during learning

Metabolomics to unveil and understand phenotypic diversity between pathogen populations

Visceral leishmaniasis is caused by a parasite called Leishmania donovani, which every year infects about half a million people and claims several thousand lives. Existing treatments are now becoming less effective due to the emergence of drug resistance. Improving our understanding of the mechanisms used by the parasite to adapt to drugs and achieve resistance is crucial for developing future treatment strategies. Unfortunately, the biological mechanism whereby Leishmania acquires drug resistance is poorly understood. Recent years have brought new technologies with the potential to increase greatly our understanding of drug resistance mechanisms. The latest mass spectrometry techniques allow the metabolome of parasites to be studied rapidly and in great detail. We have applied this approach to determine the metabolome of drug-sensitive and drug-resistant parasites isolated from patients with leishmaniasis. The data show that there are wholesale differences between the isolates and that the membrane composition has been drastically modified in drug-resistant parasites compared with drug-sensitive parasites. Our findings demonstrate that untargeted metabolomics has great potential to identify major metabolic differences between closely related parasite strains and thus should find many applications in distinguishing parasite phenotypes of clinical relevance

What traits are carried on mobile genetic elements, and why?

Although similar to any other organism, prokaryotes can transfer genes vertically from mother cell to daughter cell, they can also exchange certain genes horizontally. Genes can move within and between genomes at fast rates because of mobile genetic elements (MGEs). Although mobile elements are fundamentally self-interested entities, and thus replicate for their own gain, they frequently carry genes beneficial for their hosts and/or the neighbours of their hosts. Many genes that are carried by mobile elements code for traits that are expressed outside of the cell. Such traits are involved in bacterial sociality, such as the production of public goods, which benefit a cell's neighbours, or the production of bacteriocins, which harm a cell's neighbours. In this study we review the patterns that are emerging in the types of genes carried by mobile elements, and discuss the evolutionary and ecological conditions under which mobile elements evolve to carry their peculiar mix of parasitic, beneficial and cooperative genes

Novel roles of the chemorepellent axon guidance molecule RGMa in cell migration and adhesion

The repulsive guidance molecule A (RGMa) is a contact-mediated axon guidance molecule that has significant roles in central nervous system (CNS) development. Here we have examined whether RGMa has novel roles in cell migration and cell adhesion outside the nervous system. RGMa was found to stimulate cell migration from Xenopus animal cap explants in a neogenin-dependent and BMP-independent manner. RGMa also stimulated the adhesion of Xenopus animal cap cells, and this adhesion was dependent on neogenin and independent of calcium. To begin to functionally characterize the role of specific domains in RGMa, we assessed the migratory and adhesive activities of deletion mutants. RGMa lacking the partial von Willebrand factor type D (vWF) domain preferentially perturbed cell adhesion, while mutants lacking the RGD motif affected cell migration. We also revealed that manipulating the levels of RGMa in vivo caused major migration defects during Xenopus gastrulation. We have revealed here novel roles of RGMa in cell migration and adhesion and demonstrated that perturbations to the homeostasis of RGMa expression can severely disrupt major morphogenetic events. These results have implications for understanding the role of RGMa in both health and disease

Postcopulatory sexual selection

The female reproductive tract is where competition between the sperm of different males takes place, aided and abetted by the female herself. Intense postcopulatory sexual selection fosters inter-sexual conflict and drives rapid evolutionary change to generate a startling diversity of morphological, behavioural and physiological adaptations. We identify three main issues that should be resolved to advance our understanding of postcopulatory sexual selection. We need to determine the genetic basis of different male fertility traits and female traits that mediate sperm selection; identify the genes or genomic regions that control these traits; and establish the coevolutionary trajectory of sexes