Making sense of big data in health research: Towards an EU action plan.

Medicine and healthcare are undergoing profound changes. Whole-genome sequencing and high-resolution imaging technologies are key drivers of this rapid and crucial transformation. Technological innovation combined with automation and miniaturization has triggered an explosion in data production that will soon reach exabyte proportions. How are we going to deal with this exponential increase in data production? The potential of "big data" for improving health is enormous but, at the same time, we face a wide range of challenges to overcome urgently. Europe is very proud of its cultural diversity; however, exploitation of the data made available through advances in genomic medicine, imaging, and a wide range of mobile health applications or connected devices is hampered by numerous historical, technical, legal, and political barriers. European health systems and databases are diverse and fragmented. There is a lack of harmonization of data formats, processing, analysis, and data transfer, which leads to incompatibilities and lost opportunities. Legal frameworks for data sharing are evolving. Clinicians, researchers, and citizens need improved methods, tools, and training to generate, analyze, and query data effectively. Addressing these barriers will contribute to creating the European Single Market for health, which will improve health and healthcare for all Europeans.

Baseline CD4(+) T-cell counts and weighted background susceptibility scores strongly predict response to maraviroc regimens in treatment-experienced patients.

BACKGROUND: Maraviroc-containing regimens are known to achieve virological suppression in many treatment-experienced patients. This study aimed to evaluate a more rigorous methodological approach to resistance-response analysis in large clinical studies and to better establish which subpopulations of patients were most likely to benefit from maraviroc by refining and extending previous subgroup analyses from the MOTIVATE studies. METHODS: Individual weighted optimized background therapy (OBT) susceptibility scores were calculated by combining genotypic or phenotypic resistance testing with prior drug use information. Virological response (HIV-1 RNA<50 copies/ml at week 48) using each of these methods was compared with a commonly used method of counting active drugs. Baseline predictors of virological response, including weighted or unweighted scoring, maraviroc use, baseline CD4(+) T-cell count, HIV-1 plasma viral load and tropism, were assessed by logistic regression modelling. RESULTS: Genotypic or phenotypic weighted methods were similarly predictive of virological response and better than counting active drugs. Weighted scoring and baseline CD4(+) T-cell count were the strongest predictors of virological response (P<0.0001): ≈70% of maraviroc patients with a weighted score ≥2 had a virological response, rising to ≈80% when the baseline CD4(+) T-cell count was ≥50 cells/mm(3). CONCLUSIONS: Approximately 80% of patients with a CD4(+) T-cell count ≥50 cells/mm(3) receiving maraviroc with the equivalent of at least two fully active agents achieved HIV-1 RNA<50 copies/ml at week 48 in the MOTIVATE studies. Genotypic and phenotypic weighted scores were similarly predictive of virological response.

Characterization of the calcification of cardiac valve bioprostheses by environmental scanning electron microscopy and vibrational spectroscopy.

Bioprosthetic heart valve tissue and associated calcification were studied in their natural state, using environmental scanning electron microscopy (ESEM). Energy dispersive X-ray micro-analysis, X-ray diffraction, Fourier-transform infrared and Raman spectroscopy were used to characterize the various calcific deposits observed with ESEM. The major elements present in calcified valves were also analyzed by inductively coupled plasma-optical emission spectroscopy. To better understand the precursor formation of the calcific deposits, results from the elemental analyses were statistically correlated. ESEM revealed the presence of four broad types of calcium phosphate crystal morphology. In addition, two main patterns of organization of calcific deposits were observed associated with the collagen fibres. Energy dispersive X-ray micro-analysis identified the crystals observed by ESEM as salts containing mainly calcium and phosphate with ratios from 1.340 (possibly octacalcium phosphate, which has a Ca/P ratio of 1.336) to 2.045 (possibly hydroxyapatite with incorporation of carbonate and metal ion contaminants, such as silicon and magnesium, in the crystal lattice). Raman and fourier-transform infrared spectroscopy also identified the presence of carbonate and the analyses showed spectral features very similar to a crystalline hydroxyapatite spectrum, also refuting the presence of precursor phases such as beta-tricalcium phosphate, octacalcium phosphate and dicalcium phosphate dihydrate. The results of this study raised the possibility of the presence of precursor phases associated with the early stages of calcification.