Phase-Diverse Coherent Diffractive Imaging: High Sensitivity with Low Dose

This Letter demonstrates that coherent diffractive imaging (CDI), in combination with phase-diversity methods, provides reliable and artefact free high-resolution images. Here, using x rays, experimental results show a threefold improvement in the available image contrast. Furthermore, in conditions requiring low imaging dose, it is demonstrated that phase-diverse CDI provides a factor of 2 improvement in comparison to previous CDI techniques

Wettability Switching Techniques on Superhydrophobic Surfaces

The wetting properties of superhydrophobic surfaces have generated worldwide research interest. A water drop on these surfaces forms a nearly perfect spherical pearl. Superhydrophobic materials hold considerable promise for potential applications ranging from self cleaning surfaces, completely water impermeable textiles to low cost energy displacement of liquids in lab-on-chip devices. However, the dynamic modification of the liquid droplets behavior and in particular of their wetting properties on these surfaces is still a challenging issue. In this review, after a brief overview on superhydrophobic states definition, the techniques leading to the modification of wettability behavior on superhydrophobic surfaces under specific conditions: optical, magnetic, mechanical, chemical, thermal are discussed. Finally, a focus on electrowetting is made from historical phenomenon pointed out some decades ago on classical planar hydrophobic surfaces to recent breakthrough obtained on superhydrophobic surfaces

Drug-target identification in COVID-19 disease mechanisms using computational systems biology approaches

Introduction: The COVID-19 Disease Map project is a large-scale community effort uniting 277 scientists from 130 Institutions around the globe. We use high-quality, mechanistic content describing SARS-CoV-2-host interactions and develop interoperable bioinformatic pipelines for novel target identification and drug repurposing. Methods: Extensive community work allowed an impressive step forward in building interfaces between Systems Biology tools and platforms. Our framework can link biomolecules from omics data analysis and computational modelling to dysregulated pathways in a cell-, tissue- or patient-specific manner. Drug repurposing using text mining and AI-assisted analysis identified potential drugs, chemicals and microRNAs that could target the identified key factors. Results: Results revealed drugs already tested for anti-COVID-19 efficacy, providing a mechanistic context for their mode of action, and drugs already in clinical trials for treating other diseases, never tested against COVID-19. Discussion: The key advance is that the proposed framework is versatile and expandable, offering a significant upgrade in the arsenal for virus-host interactions and other complex pathologies.Peer Reviewe

Introducing PIONEER: a project to harness big data in prostate cancer research

Prostate Cancer Diagnosis and Treatment Enhancement Through the Power of Big Data in Europe (PIONEER) is a European network of excellence for big data in prostate cancer, consisting of 32 private and public stakeholders from 9 countries across Europe. Launched by the Innovative Medicines Initiative 2 and part of the Big Data for Better Outcomes Programme (BD4BO), the overarching goal of PIONEER is to provide high-quality evidence on prostate cancer management by unlocking the potential of big data. The project has identified critical evidence gaps in prostate cancer care, via a detailed prioritization exercise including all key stakeholders. By standardizing and integrating existing high-quality and multidisciplinary data sources from patients with prostate cancer across different stages of the disease, the resulting big data will be assembled into a single innovative data platform for research. Based on a unique set of methodologies, PIONEER aims to advance the field of prostate cancer care with a particular focus on improving prostate-cancer-related outcomes, health system efficiency by streamlining patient management, and the quality of health and social care delivered to all men with prostate cancer and their families worldwide.Prostate Cancer Diagnosis and Treatment Enhancement Through the Power of Big Data in Europe (PIONEER) is a European network of excellence for big data in prostate cancer, consisting of 32 private and public stakeholders from 9 countries across Europe. In this Perspectives article, the authors introduce the PIONEER project and describe its aims and plans for ultimately improving prostate cancer care through the use of big data

Drug-target identification in COVID-19 disease mechanisms using computational systems biology approaches

IntroductionThe COVID-19 Disease Map project is a large-scale community effort uniting 277 scientists from 130 Institutions around the globe. We use high-quality, mechanistic content describing SARS-CoV-2-host interactions and develop interoperable bioinformatic pipelines for novel target identification and drug repurposing. MethodsExtensive community work allowed an impressive step forward in building interfaces between Systems Biology tools and platforms. Our framework can link biomolecules from omics data analysis and computational modelling to dysregulated pathways in a cell-, tissue- or patient-specific manner. Drug repurposing using text mining and AI-assisted analysis identified potential drugs, chemicals and microRNAs that could target the identified key factors.ResultsResults revealed drugs already tested for anti-COVID-19 efficacy, providing a mechanistic context for their mode of action, and drugs already in clinical trials for treating other diseases, never tested against COVID-19. DiscussionThe key advance is that the proposed framework is versatile and expandable, offering a significant upgrade in the arsenal for virus-host interactions and other complex pathologies

A computational framework for complex disease stratification from multiple large-scale datasets.

BACKGROUND: Multilevel data integration is becoming a major area of research in systems biology. Within this area, multi-'omics datasets on complex diseases are becoming more readily available and there is a need to set standards and good practices for integrated analysis of biological, clinical and environmental data. We present a framework to plan and generate single and multi-'omics signatures of disease states. METHODS: The framework is divided into four major steps: dataset subsetting, feature filtering, 'omics-based clustering and biomarker identification. RESULTS: We illustrate the usefulness of this framework by identifying potential patient clusters based on integrated multi-'omics signatures in a publicly available ovarian cystadenocarcinoma dataset. The analysis generated a higher number of stable and clinically relevant clusters than previously reported, and enabled the generation of predictive models of patient outcomes. CONCLUSIONS: This framework will help health researchers plan and perform multi-'omics big data analyses to generate hypotheses and make sense of their rich, diverse and ever growing datasets, to enable implementation of translational P4 medicine

Continuously Tunable, Polarization Controlled, Colour Palette Produced from Nanoscale Plasmonic Pixels.

Colour filters based on nano-apertures in thin metallic films have been widely studied due to their extraordinary optical transmission and small size. These properties make them prime candidates for use in high-resolution colour displays and high accuracy bio-sensors. The inclusion of polarization sensitive plasmonic features in such devices allow additional control over the electromagnetic field distribution, critical for investigations of polarization induced phenomena. Here we demonstrate that cross-shaped nano-apertures can be used for polarization controlled color tuning in the visible range and apply fundamental theoretical models to interpret key features of the transmitted spectrum. Full color transmission was achieved by fine-tuning the periodicity of the apertures, whilst keeping the geometry of individual apertures constant. We demonstrate this effect for both transverse electric and magnetic fields. Furthermore we have been able to demonstrate the same polarization sensitivity even for nano-size, sub-wavelength sets of arrays, which is paramount for ultra-high resolution compact colour displays