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The main objective of GoodBerry is to provide the necessary knowledge and procedures to facilitate the development of highly productive and top quality berry fruits, even under multiple suboptimal growth conditions, at a competitive cost. The project is based on an integrative multi-actor approach, from cultivation techniques to molecular studies, aiming the development and validation of a range of tools to improve competitiveness of European berry production, and eventually the attraction and confidence of consumers. The selection of the model species can be considered as strategic since strawberry is the most important berry crop in Europe and the production of raspberry and blackcurrant are increasing strongly in recent years. The project will apply the most recent technical advances in: a) The identification of berry germplasm exhibiting advantageous balance of production vs nutritional quality throughout the EU, b) The search of innovative production systems to maintain high yield in a range of European-wide environments, c) The development of standardized and reliable analytical tools to evaluate berry production and fruit quality. As result, it is expected: a) the implementation of modern breeding strategies to accelerate the release of new berry cultivars; b) The adoption by EU-growers of high quality production systems to improve fruit quality. The proposal establishes as obligatory to disseminate and communicate the results to the scientific community, industry, the broad public and interested stakeholders user. The final impact will be to consolidate the emerging needs of high-quality berries, and to boost consumer and market confidence supported by an improved competitiveness of producers. It is a multidisciplinary, collaborative project based on complementary expertise and skills of internationally recognized berry research institutions, and highly involved key berry SMEs that will combine their effort to secure the robustness of the results.

Agency: Cordis | Branch: H2020 | Program: IA | Phase: ICT-28-2015 | Award Amount: 2.70M | Year: 2016

The overall aim of LIQBIOPSENS project is the further development and validation in real settings of a novel diagnostic platform for the early and fast detection of ctDNA and their KRAS and BRAF mutations associated to colorectal cancer through blood samples. The main features of LIQBIOPSENS are: reliability (detection rates vary from 95100 %), low-cost (40-50 per sample analysis), sensitivity (in the zM range), multiplexing capabilities (analysis of 27 KRAS and BRAF mutations simultaneously), short analysis time (30-60 min.), user-friendly interface and flexibility. Solution proposed by the LIQBIOPSENS project relies on the multidisciplinary integration of different Key Enabled Technologies: microelectronics, microfluidics, nanomaterials and genomics. In particular, LIQBIOPSENS platform is based on the integration of two novel complementary technologies. On the one hand, the revolutionary DGL technology property of DestiNA Genomics Ltd, capable of delivering faster, more error-free detection of nucleic acids and their mutations than current enzyme-based detection systems, making false positive results a thing of the past. On the other hand, a novel high resolution acoustic wave microsensor technology property of AWSensors, that allows an accurate, inexpensive, label-free, direct and real time transduction method to quantitatively evaluate the results of the application of the above mentioned DGL technique.

The forecasted increase in the number of older people for this century will be accompanied by an increase of those with disabilities. Disability is usually preceded by a condition named frailty that encompasses changes associated with ageing, life styles and chronic diseases. To detect and intervene on it is of outstanding importance to prevent disability, as recovery from disability is unlikely. Recent documents stress the necessity of testing the clinical utility (in terms of risk prediction, diagnosis validity and prognostic significance) of the existing definition of frailty by using combinations of clinical criteria (current definition) and lab Biomarkers (BMs). We will measure the levels of blood and urine omic-based BMs in old people selected from eight cohorts, which include up to 75,000 participants, using standardized and innovative technology (WP1). This figure will allow us to test the research questions with a high power and validity. Combining these lab BMs with clinical BMs, we will develop predictive, diagnostic and prognostic models (WP2), with its modulation by nutrition and physical activity, in general old population and in old people showing some characteristics that confer a high risk for developing frailty (selected cardiovascular risk factors and diseases) (WP4). After that, a selected set of BMs will be validated prospectively (WP3) and assessed to find the best-fitted models (WP4). These models will guide the development of the ready-to-use kits to be implemented in the clinical settings. These kits will be at the center of dissemination and exploitation activities (WP5, WP6). A well-balanced consortium distributed over the individual tasks in the respective work packages will carry it out, with a strong participation of SMEs. In summary, FRAILOMIC is original, relevant, pertinent, feasible, overcome the usual research bottlenecks on Biomarkers, and fits perfectly with the topics addressed by the HEALTH.2012.2.1.1-2 call in human subjects

Agency: Cordis | Branch: FP7 | Program: CP-TP | Phase: NMP-2007-3.1-2 | Award Amount: 5.45M | Year: 2008

Economical and health interests of skin problems are fast growing issues in Europe, following the remarkable extension in life expectancy in western countries, together with the increased awareness of UV radiation risks. Personalized health care approach has been discussed over the past few years and had been accompanied by developing innovative technologies capable of identifying specific biomarkers, supporting a personalized diagnosis and treatments, especially concerning bio-compatibility of drugs. Skin Treat intends to develop and validate nano-chemical and bio- technologies to achieve an accurate matching of drugs, and drug delivery vehicles, to skin diseases and sub pathogenic skin conditions in their individual context. The project will design novel generation of pharmaceutical products, as well as consumer personalized service, in order to fit customers tailored needs with a support of strategic consortium based on partnership among SMEs and research organizations. The development of personalized skin therapy protocols requires achieving an accurate diagnostics of skin condition and an extensive analysis of biological markers. Non invasive methods as well as minimal invasive skin sampling, will support the establishment of a range of biological profiles corresponding to skin diseases and skin sub pathologic conditions. Statistical processing of these data will allow defining biomarkers patterns specifically associated with given clinical conditions. A bio-informatics data mining protocol will be elaborated, together with multifunctional biomarker analysis software, to build a refined, personalized diagnosis method. Finally, the computer data analysis will yield a decision support system (DSS) to assist dermatologists, chemist and clients for prescription of personalized treatment. Skin Treat concept will be evaluated by a wet pilot study of the whole ervice chain on a few, selected skin disorders like psoriasis, contact dermatitis, and UV skin photo-aging damages.

Agency: Cordis | Branch: H2020 | Program: RIA | Phase: PHC-30-2015 | Award Amount: 3.34M | Year: 2016

Breast cancer is the most common type of cancer affecting woman in the EU. Multidisciplinary Breast Units (BUs) were introduced in order to deal efficiently with breast cancer cases, setting guideline-based quality procedures and a high standard of care. However, daily practice in the BUs is hampered by the complexity of the disease, the vast amount of patient and disease data available in the digital era, the difficulty in coordination, the pressure exerted by the system and the difficulty in deciding on cases that guidelines do not reflect. DESIREE aims to alleviate this situation by providing a web-based software ecosystem for the personalized, collaborative and multidisciplinary management of primary breast cancer (PBC) by specialized BUs. Decision support will be provided on the available therapy options by incorporating experience from previous cases and outcomes into an evolving knowledge model, going beyond the limitations of the few existing guideline-based decision support systems (DSS). Patient cases will be represented by a novel digital breast cancer patient (DBCP) data model, incorporating variables relevant for decision and novel sources of information and biomarkers of diagnostic and prognostic value, providing a holistic view of the patient presented to the BU through specialized visual exploratory interfaces. The influence of new variables and biomarkers in current and previous cases will be explored by a set of data mining and visual analytics tools, leveraging large amounts of retrospective data. Iintuitive web-based tools for multi-modality image analysis and fusion will be developed, providing advanced imaging biomarkers for breast and tumor characterization. Finally, a predictive tool for breast conservative therapy will be incorporated, based on a multi-scale physiological model, allowing to predict the aesthetic outcome of the intervention and the healing process, with important clinical and psychological implications for the patients.

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