Classifying and Grouping Mammography Images into Communities Using Fisher Information Networks to Assist the Diagnosis of Breast Cancer

© 2020, Springer Nature Switzerland AG. The aim of this paper is to build a computer based clinical decision support tool using a semi-supervised framework, the Fisher Information Network (FIN), for visualization of a set of mammographic images. The FIN organizes the images into a similarity network from which, for any new image, reference images that are closely related can be identified. This enables clinicians to review not just the reference images but also ancillary information e.g. about response to therapy. The Fisher information metric defines a Riemannian space where distances reflect similarity with respect to a given probability distribution. This metric is informed about generative properties of data, and hence assesses the importance of directions in space of parameters. It automatically performs feature relevance detection. This approach focusses on the interpretability of the model from the standpoint of the clinical user. Model predictions were validated using the prevalence of classes in each of the clusters identified by the FIN

A genetic contribution from the Far East into Ashkenazi Jews via the ancient Silk Road

Contemporary Jews retain a genetic imprint from their Near Eastern ancestry, but obtained substantial genetic components from their neighboring populations during their history. Whether they received any genetic contribution from the Far East remains unknown, but frequent communication with the Chinese has been observed since the Silk Road period. To address this issue, mitochondrial DNA (mtDNA) variation from 55,595 Eurasians are analyzed. The existence of some eastern Eurasian haplotypes in eastern Ashkenazi Jews supports an East Asian genetic contribution, likely from Chinese. Further evidence indicates that this connection can be attributed to a gene flow event that occurred less than 1.4 kilo-years ago (kya), which falls within the time frame of the Silk Road scenario and fits well with historical records and archaeological discoveries. This observed genetic contribution from Chinese to Ashkenazi Jews demonstrates that the historical exchange between Ashkenazim and the Far East was not confined to the cultural sphere but also extended to an exchange of genes

Direct evidence for charge stripes in a layered cobalt oxide

Recent experiments indicate that static stripe-like charge order is generic to the hole-doped copper oxide superconductors and competes with superconductivity. Here we show that a similar type of charge order is present in La5/3 Sr1/3 CoO4 , an insulating analogue of the copper oxide superconductors containing cobalt in place of copper. The stripe phase we have detected is accompanied by short-range, quasi-one-dimensional, antiferromagnetic order, and provides a natural explanation for the distinctive hour- glass shape of the magnetic spectrum previously observed in neutron scattering mea- surements of La2−xSrx CoO4 and many hole-doped copper oxide superconductors. The results establish a solid empirical basis for theories of the hourglass spectrum built on short-range, quasi-static, stripe correlations

n-type chalcogenides by ion implantation.

Carrier-type reversal to enable the formation of semiconductor p-n junctions is a prerequisite for many electronic applications. Chalcogenide glasses are p-type semiconductors and their applications have been limited by the extraordinary difficulty in obtaining n-type conductivity. The ability to form chalcogenide glass p-n junctions could improve the performance of phase-change memory and thermoelectric devices and allow the direct electronic control of nonlinear optical devices. Previously, carrier-type reversal has been restricted to the GeCh (Ch=S, Se, Te) family of glasses, with very high Bi or Pb 'doping' concentrations (~5-11 at.%), incorporated during high-temperature glass melting. Here we report the first n-type doping of chalcogenide glasses by ion implantation of Bi into GeTe and GaLaSO amorphous films, demonstrating rectification and photocurrent in a Bi-implanted GaLaSO device. The electrical doping effect of Bi is observed at a 100 times lower concentration than for Bi melt-doped GeCh glasses.This work was supported by the UK EPSRC grants EP/I018417/1, EP/I019065/1 and EP/I018050/1.This is the author accepted manuscript. The final version is available from NPG via http://dx.doi.org/10.1038/ncomms634

Prediction of the yield of grains through artificial intelligence

Grass turns out to be an appropriate food for cattle, mainly in tropical climate countries such as Latin American countries. This is due to the high number of species that can be used, the possibility of growing them year-round, the ability of the ruminant to use fibrous supplies and be an economic source (Sánchez et al., Data mining and big data. DMBD 2018. Lecture notes in computer science, vol 10943. Springer, Cham, 2018, [1]). In this work, an application of neural networks was carried out in the forecasting of more accurate values of production and quality of grasslands

Chemotherapy-Response Monitoring of Breast Cancer Patients Using Quantitative Ultrasound-Based Intra-Tumour Heterogeneities

© 2017 The Author(s). Anti-cancer therapies including chemotherapy aim to induce tumour cell death. Cell death introduces alterations in cell morphology and tissue micro-structures that cause measurable changes in tissue echogenicity. This study investigated the effectiveness of quantitative ultrasound (QUS) parametric imaging to characterize intra-tumour heterogeneity and monitor the pathological response of breast cancer to chemotherapy in a large cohort of patients (n = 100). Results demonstrated that QUS imaging can non-invasively monitor pathological response and outcome of breast cancer patients to chemotherapy early following treatment initiation. Specifically, QUS biomarkers quantifying spatial heterogeneities in size, concentration and spacing of acoustic scatterers could predict treatment responses of patients with cross-validated accuracies of 82 ± 0.7%, 86 ± 0.7% and 85 ± 0.9% and areas under the receiver operating characteristic (ROC) curve of 0.75 ± 0.1, 0.80 ± 0.1 and 0.89 ± 0.1 at 1, 4 and 8 weeks after the start of treatment, respectively. The patients classified as responders and non-responders using QUS biomarkers demonstrated significantly different survivals, in good agreement with clinical and pathological endpoints. The results form a basis for using early predictive information on survival-linked patient response to facilitate adapting standard anti-cancer treatments on an individual patient basis

Initiating head development in mouse embryos: integrating signalling and transcriptional activity

The generation of an embryonic body plan is the outcome of inductive interactions between the progenitor tissues that underpin their specification, regionalization and morphogenesis. The intercellular signalling activity driving these processes is deployed in a time- and site-specific manner, and the signal strength must be precisely controlled. Receptor and ligand functions are modulated by secreted antagonists to impose a dynamic pattern of globally controlled and locally graded signals onto the tissues of early post-implantation mouse embryo. In response to the WNT, Nodal and Bone Morphogenetic Protein (BMP) signalling cascades, the embryo acquires its body plan, which manifests as differences in the developmental fate of cells located at different positions in the anterior–posterior body axis. The initial formation of the anterior (head) structures in the mouse embryo is critically dependent on the morphogenetic activity emanating from two signalling centres that are juxtaposed with the progenitor tissues of the head. A common property of these centres is that they are the source of antagonistic factors and the hub of transcriptional activities that negatively modulate the function of WNT, Nodal and BMP signalling cascades. These events generate the scaffold of the embryonic head by the early-somite stage of development. Beyond this, additional tissue interactions continue to support the growth, regionalization, differentiation and morphogenesis required for the elaboration of the structure recognizable as the embryonic head

High Speed Simulation Analytics

Simulation, especially Discrete-event simulation (DES) and Agent-based simulation (ABS), is widely used in industry to support decision making. It is used to create predictive models or Digital Twins of systems used to analyse what-if scenarios, perform sensitivity analytics on data and decisions and even to optimise the impact of decisions. Simulation-based Analytics, or just Simulation Analytics, therefore has a major role to play in Industry 4.0. However, a major issue in Simulation Analytics is speed. Extensive, continuous experimentation demanded by Industry 4.0 can take a significant time, especially if many replications are required. This is compounded by detailed models as these can take a long time to simulate. Distributed Simulation (DS) techniques use multiple computers to either speed up the simulation of a single model by splitting it across the computers and/or to speed up experimentation by running experiments across multiple computers in parallel. This chapter discusses how DS and Simulation Analytics, as well as concepts from contemporary e-Science, can be combined to contribute to the speed problem by creating a new approach called High Speed Simulation Analytics. We present a vision of High Speed Simulation Analytics to show how this might be integrated with the future of Industry 4.0