336 research outputs found

    Validating atlas-based lesion disconnectomics in multiple sclerosis: A retrospective multi-centric study.

    Get PDF
    The translational potential of MR-based connectivity modelling is limited by the need for advanced diffusion imaging, which is not part of clinical protocols for many diseases. In addition, where diffusion data is available, brain connectivity analyses rely on tractography algorithms which imply two major limitations. First, tracking algorithms are known to be sensitive to the presence of white matter lesions and therefore leading to interpretation pitfalls and poor inter-subject comparability in clinical applications such as multiple sclerosis. Second, tractography quality is highly dependent on the acquisition parameters of diffusion sequences, leading to a trade-off between acquisition time and tractography precision. Here, we propose an atlas-based approach to study the interplay between structural disconnectivity and lesions without requiring individual diffusion imaging. In a multi-centric setting involving three distinct multiple sclerosis datasets (containing both 1.5 T and 3 T data), we compare our atlas-based structural disconnectome computation pipeline to disconnectomes extracted from individual tractography and explore its clinical utility for reducing the gap between radiological findings and clinical symptoms in multiple sclerosis. Results using topological graph properties showed that overall, our atlas-based disconnectomes were suitable approximations of individual disconnectomes from diffusion imaging. Small-worldness was found to decrease for larger total lesion volumes thereby suggesting a loss of efficiency in brain connectivity of MS patients. Finally, the global efficiency of the created brain graph, combined with total lesion volume, allowed to stratify patients into subgroups with different clinical scores in all three cohorts

    BIOCLAIMS standard diet (BIOsd): a reference diet for nutritional physiology

    Get PDF
    Experimental replication is fundamental for practicing science. To reduce variability, it is essential to control sources of variation as much as possible. Diet is an important factor that can influence many processes and functional outcomes in studies performed with rodent models. This is especially true for, but not limited to, nutritional studies. To compare functional effects of different nutrients, it is important to use standardized, semi-purified diets. Here, we propose and describe a standard reference diet, the BIOCLAIMS standard diet. The diet is AIN-93 based, but further defined with dietary and experimental requirements taken into account that allow for experiments with bioactive food components and natural (non-expensive) labeling. This diet will be implemented by two European research consortia, Mitofood and BIOCLAIMS, to ensure inter-laboratory comparability

    Empowering SMEs to make better decisions with Business Intelligence: A Case Study

    Get PDF
    With the advance of Business Information Systems (BIS), irrespective of the size, companies have adopted an approach to electronic data collection and management for two decades. The advancement in technology means they have in their possessions large volumes of historical data. Large organizations have cached on this and use a range of tools and techniques to leverage the usefulness of this information to make more informed business decisions. For most small and medium- sized enterprises (SMEs), however, such data typically sits in an archive without being utilized. While SMEs appreciate the need for utilizing historical data to make more informed business decisions, they often lack the technical knowhow and funding to embrace an effective BI solution. In this paper, drawing from our experience in implementing a BI solution for a UK SME we discuss some potential tools and strategies that could help SMEs overcome these challenges so as to reap the benefits of adopting an effective BI solution

    Big Data in Agriculture – From FOODIE towards data bio

    Get PDF
    What’s the role of Big Data in the farming ecosystem? Farmers need to measure and understand the impact of a huge amount and variety of data which drive overall quality and yield of their fields. Among those are local weather data, GPS data, ortophotos, satellite imagery, soil specifics, soil conductivity, seed, fertilizer and crop protectant specifications and many more. Being able to leverage this data for running long and short term simulations in response to “events” like changed weather, market need or other parameters is indispensable for farmers in terms of maximizing their profits. IoT (Internet of Technology) including field sensors and machinery monitoring. The experimentation in FarmTelemetry project demonstrates that one average Czech farm (i.e. around 1’000 hectares) could generate daily 20 MegaBytes of data. This could be only for Czech Republic something between 30 and 50 GB per one day. We may easily reach Terabytes of data a day from agricultural basic monitoring by sensors in Europe. Together with satellite data agriculture will need to manage extremely large amount of data. On one side there is growing whole ecosystem with a strong need to secure Big Data from different repositories and heterogeneous sources. In some cases, sharing of data could be common interest, but on other side, there are also different interests and data could help to one part of value chain to take bigger part of profit. From this reason Big data are sensitive topics and trusting of producers about data security is essential. The producers of seeds and chemicals want to maximize their business with farmers. Our team stated implementation of Big Data technologies in frame of European 7FP project FOODIE. This work currently the work continue as part of DataBio project

    ∆Np63/p40 correlates with the location and phenotype of basal/mesenchymal cancer stem-like cells in human ER+ and HER2+ breast cancers

    Get PDF
    ΔNp63, also known as p40, regulates stemness of normal mammary gland epithelium and provides stem cell characteristics in basal and HER2‐driven murine breast cancer models. Whilst ΔNp63/p40 is a characteristic feature of normal basal cells and basal‐type triple‐negative breast cancer, some receptor‐positive breast cancers express ΔNp63/p40 and its overexpression imparts cancer stem cell‐like properties in ER+ cell lines. However, the incidence of ER+ and HER2+ tumours that express ΔNp63/p40 is unclear and the phenotype of ΔNp63/p40+ cells in these tumours remains uncertain. Using immunohistochemistry with p63 isoform‐specific antibodies, we identified a ΔNp63/p40+ tumour cell subpopulation in 100 of 173 (58%) non‐triple negative breast cancers and the presence of this population associated with improved survival in patients with ER−/HER2+ tumours (p = 0.006). Furthermore, 41% of ER+/PR+ and/or HER2+ locally metastatic breast cancers expressed ΔNp63/p40, and these cells commonly accounted for <1% of the metastatic tumour cell population that localised to the tumour/stroma interface, exhibited an undifferentiated phenotype and were CD44+/ALDH−. In vitro studies revealed that MCF7 and T47D (ER+) and BT‐474 (HER2+) breast cancer cell lines similarly contained a small subpopulation of ΔNp63/p40+ cells that increased in mammospheres. In vivo, MCF7 xenografts contained ΔNp63/p40+ cells with a similar phenotype to primary ER+ cancers. Consistent with tumour samples, these cells also showed a distinct location at the tumour/stroma interface, suggesting a role for paracrine factors in the induction or maintenance of ΔNp63/p40. Thus, ΔNp63/p40 is commonly present in a small population of tumour cells with a distinct phenotype and location in ER+ and/or HER2+ human breast cancers.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/153532/1/cjp2149_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/153532/2/cjp2149.pd

    Tract-wise microstructural analysis informs on current and future disability in early multiple sclerosis.

    Get PDF
    Microstructural characterization of patients with multiple sclerosis (MS) has been shown to correlate better with disability compared to conventional radiological biomarkers. Quantitative MRI provides effective means to characterize microstructural brain tissue changes both in lesions and normal-appearing brain tissue. However, the impact of the location of microstructural alterations in terms of neuronal pathways has not been thoroughly explored so far. Here, we study the extent and the location of tissue changes probed using quantitative MRI along white matter (WM) tracts extracted from a connectivity atlas. We quantified voxel-wise T1 tissue alterations compared to normative values in a cohort of 99 MS patients. For each WM tract, we extracted metrics reflecting tissue alterations both in lesions and normal-appearing WM and correlated these with cross-sectional disability and disability evolution after 2 years. In early MS patients, T1 alterations in normal-appearing WM correlated better with disability evolution compared to cross-sectional disability. Further, the presence of lesions in supratentorial tracts was more strongly associated with cross-sectional disability, while microstructural alterations in infratentorial pathways yielded higher correlations with disability evolution. In progressive patients, all major WM pathways contributed similarly to explaining disability, and correlations with disability evolution were generally poor. We showed that microstructural changes evaluated in specific WM pathways contribute to explaining future disability in early MS, hence highlighting the potential of tract-wise analyses in monitoring disease progression. Further, the proposed technique allows to estimate WM tract-specific microstructural characteristics in clinically compatible acquisition times, without the need for advanced diffusion imaging

    Combined intervention with pioglitazone and n-3 fatty acids in metformin-treated type 2 diabetic patients: improvement of lipid metabolism

    No full text
    Background: The marine n-3 fatty acids, eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) exert numerous beneficial effects on health, but their potency to improve treatment of type 2 diabetic (T2D) patients remains poorly characterized. We aimed to evaluate the effect of a combination intervention using EPA?+?DHA and the insulin-sensitizing drug pioglitazone in overweight/obese T2D patients already treated with metformin.Methods: In a parallel-group, four-arm, randomized trial, 69 patients (66 % men) were assigned to 24-week-intervention using: (i) corn oil (5 g/day; Placebo), (ii) pioglitazone (15 mg/day; Pio), (iii) EPA?+?DHA concentrate (5 g/day, containing ~2.8 g EPA?+?DHA; Omega-3), or (iv) pioglitazone and EPA?+?DHA concentrate (Pio&amp; Omega-3). Data from 60 patients were used for the final evaluation. At baseline and after intervention, various metabolic markers, adiponectin and cytokines were evaluated in serum using standard procedures, EPA?+?DHA content in serum phospholipids was evaluated using shotgun lipidomics and mass spectrometry, and hyperinsulinemic-euglycemic clamp and meal test were also performed. Indirect calorimetry was conducted after the intervention. Primary endpoints were changes from baseline in insulin sensitivity evaluated using hyperinsulinemic-euglycemic clamp and in serum triacylglycerol concentrations in fasting state. Secondary endpoints included changes in fasting glycemia and glycated hemoglobin (HbA1c), changes in postprandial glucose, free fatty acid and triacylglycerol concentrations, metabolic flexibility assessed by indirect calorimetry, and inflammatory markers.Results: Omega-3 and Pio&amp; Omega-3 increased EPA?+?DHA content in serum phospholipids. Pio and Pio&amp; Omega-3 increased body weight and adiponectin levels. Both fasting glycemia and HbA1c were increased by Omega-3, but were unchanged by Pio&amp; Omega-3. Insulin sensitivity was not affected by Omega-3, while it was improved by Pio&amp; Omega-3. Fasting triacylglycerol concentrations and inflammatory markers were not significantly affected by any of the interventions. Lipid metabolism in the meal test and metabolic flexibility were additively improved by Pio&amp; Omega-3.Conclusion: Besides preventing a modest negative effect of n-3 fatty acids on glycemic control, the combination of pioglitazone and EPA?+?DHA can be used to improve lipid metabolism in T2D patients on stable metformin therapy.Trial registration: EudraCT number 2009-011106-42.<br/
    corecore