60 research outputs found

    Classification of Pediatric Asthma: From Phenotype Discovery to Clinical Practice

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    Advances in big data analytics have created an opportunity for a step change in unraveling mechanisms underlying the development of complex diseases such as asthma, providing valuable insights that drive better diagnostic decision-making in clinical practice, and opening up paths to individualized treatment plans. However, translating findings from data-driven analyses into meaningful insights and actionable solutions requires approaches and tools which move beyond mining and patterning longitudinal data. The purpose of this review is to summarize recent advances in phenotyping of asthma, to discuss key hurdles currently hampering the translation of phenotypic variation into mechanistic insights and clinical setting, and to suggest potential solutions that may address these limitations and accelerate moving discoveries into practice. In order to advance the field of phenotypic discovery, greater focus should be placed on investigating the extent of within-phenotype variation. We advocate a more cautious modeling approach by “supervising” the findings to delineate more precisely the characteristics of the individual trajectories assigned to each phenotype. Furthermore, it is important to employ different methods within a study to compare the stability of derived phenotypes, and to assess the immutability of individual assignments to phenotypes. If we are to make a step change toward precision (stratified or personalized) medicine and capitalize on the available big data assets, we have to develop genuine cross-disciplinary collaborations, wherein data scientists who turn data into information using algorithms and machine learning, team up with medical professionals who provide deep insights on specific subjects from a clinical perspective

    Nano(Q)SAR: Challenges, pitfalls and perspectives

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    Regulation for nanomaterials is urgently needed, and the drive to adopt an intelligent testing strategy is evident. Such a strategy will not only provide economic benefits but will also reduce moral and ethical concerns arising from animal testing. For regulatory purposes, such an approach is promoted by REACH, particularly the use of quantitative structure–activity relationships [(Q)SAR] as a tool for the categorisation of compounds according to their physicochemical and toxicological properties. In addition to compounds, (Q)SAR has also been applied to nanomaterials in the form of nano(Q)SAR. Although (Q)SAR in chemicals is well established, nano(Q)SAR is still in early stages of development and its successful uptake is far from reality. This article aims to identify some of the pitfalls and challenges associated with nano-(Q)SARs in relation to the categorisation of nanomaterials. Our findings show clear gaps in the research framework that must be addressed if we are to have reliable predictions from such models. Three major barriers were identified: the need to improve quality of experimental data in which the models are developed from, the need to have practical guidelines for the development of the nano(Q)SAR models and the need to standardise and harmonise activities for the purpose of regulation. Of these three, the first, i.e. the need to improve data quality requires immediate attention, as it underpins activities associated with the latter two. It should be noted that the usefulness of data in the context of nano-(Q)SAR modelling is not only about the quantity of data but also about the quality, consistency and accessibility of those data

    Controlling the risks of nano-enabled products through the life cycle: The case of nano copper oxide paint for wood protection and nano-pigments used in the automotive industry

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    The widespread use of engineered nanomaterials (ENMs) in consumer products and the overwhelming uncertainties in their ecological and human health risks have raised concerns regarding their safety among industries and regulators. There has been an ongoing debate over the past few decades on ways to overcome the challenges in assessing and mitigating nano-related risks, which has reached a phase of general consensus that nanotechnology innovation should be accompanied by the application of the precautionary principle and best practice risk management, even if the risk assessment uncertainties are large. We propose a quantitative methodology for selecting the optimal risk control strategy based on information about human health and ecological risks, efficacy of risk mitigation measures, cost and other contextual factors. The risk control (RC) methodology was developed in the European FP7 research project SUN and successfully demonstrated in two case studies involving real industrial nano-enabled products (NEPs): nano-scale copper oxide (CuO) and basic copper carbonate (Cu₂(OH)₂CO₃) used as antimicrobial and antifungal coatings and impregnations for the preservation of treated wood, and two nanoscale pigments used for colouring plastic automotive parts (i.e. red organic pigment and carbon black). The application of RC for human health risks showed that although nano-related risks could easily be controlled in automotive plastics case study with modifications in production technology or specific type of engineering controls, nano-related risks due to sanding and sawing copper oxide painted wood were non-acceptable in the use lifecycle stage and would need the identification of a more effective risk control strategy

    Predictors of disease worsening defined by progression of organ damage in diffuse systemic sclerosis: a European Scleroderma Trials and Research (EUSTAR) analysis.

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    Objectives Mortality and worsening of organ function are desirable endpoints for clinical trials in systemic sclerosis (SSc). The aim of this study was to identify factors that allow enrichment of patients with these endpoints, in a population of patients from the European Scleroderma Trials and Research group database. Methods Inclusion criteria were diagnosis of diffuse SSc and follow-up over 12\ub13 months. Disease worsening/organ progression was fulfilled if any of the following events occurred: new renal crisis; decrease of lung or heart function; new echocardiography-suspected pulmonary hypertension or death. In total, 42 clinical parameters were chosen as predictors for the analysis by using (1) imputation of missing data on the basis of multivariate imputation and (2) least absolute shrinkage and selection operator regression. Results Of 1451 patients meeting the inclusion criteria, 706 had complete data on outcome parameters and were included in the analysis. Of the 42 outcome predictors, eight remained in the final regression model. There was substantial evidence for a strong association between disease progression and age, active digital ulcer (DU), lung fibrosis, muscle weakness and elevated C-reactive protein (CRP) level. Active DU, CRP elevation, lung fibrosis and muscle weakness were also associated with a significantly shorter time to disease progression. A bootstrap validation step with 10 000 repetitions successfully validated the model. Conclusions The use of the predictive factors presented here could enable cohort enrichment with patients at risk for overall disease worsening in SSc clinical trial

    Progressive skin fibrosis is associated with a decline in lung function and worse survival in patients with diffuse cutaneous systemic sclerosis in the European Scleroderma Trials and Research (EUSTAR) cohort.

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    Objectives To determine whether progressive skin fibrosis is associated with visceral organ progression and mortality during follow-up in patients with diffuse cutaneous systemic sclerosis (dcSSc). Methods We evaluated patients from the European Scleroderma Trials and Research database with dcSSc, baseline modified Rodnan skin score (mRSS) ≄7, valid mRSS at 12±3 months after baseline and ≄1 annual follow-up visit. Progressive skin fibrosis was defined as an increase in mRSS >5 and ≄25% from baseline to 12±3 months. Outcomes were pulmonary, cardiovascular and renal progression, and all-cause death. Associations between skin progression and outcomes were evaluated by Kaplan-Meier survival analysis and multivariable Cox regression. Results Of 1021 included patients, 78 (7.6%) had progressive skin fibrosis (skin progressors). Median follow-up was 3.4 years. Survival analyses indicated that skin progressors had a significantly higher probability of FVC decline ≄10% (53.6% vs 34.4%; p<0.001) and all-cause death (15.4% vs 7.3%; p=0.003) than non-progressors. These significant associations were also found in subgroup analyses of patients with either low baseline mRSS (≀22/51) or short disease duration (≀15 months). In multivariable analyses, skin progression within 1 year was independently associated with FVC decline ≄10% (HR 1.79, 95% CI 1.20 to 2.65) and all-cause death (HR 2.58, 95% CI 1.31 to 5.09). Conclusions Progressive skin fibrosis within 1 year is associated with decline in lung function and worse survival in dcSSc during follow-up. These results confirm mRSS as a surrogate marker in dcSSc, which will be helpful for cohort enrichment in future trials and risk stratification in clinical practice

    Phenotypes Determined by Cluster Analysis and Their Survival in the Prospective European Scleroderma Trials and Research Cohort of Patients With Systemic Sclerosis

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    Objective: Systemic sclerosis (SSc) is a heterogeneous connective tissue disease that is typically subdivided into limited cutaneous SSc (lcSSc) and diffuse cutaneous SSc (dcSSc) depending on the extent of skin involvement. This subclassification may not capture the entire variability of clinical phenotypes. The European Scleroderma Trials and Research (EUSTAR) database includes data on a prospective cohort of SSc patients from 122 European referral centers. This study was undertaken to perform a cluster analysis of EUSTAR data to distinguish and characterize homogeneous phenotypes without any a priori assumptions, and to examine survival among the clusters obtained. / Methods: A total of 11,318 patients were registered in the EUSTAR database, and 6,927 were included in the study. Twenty‐four clinical and serologic variables were used for clustering. / Results: Clustering analyses provided a first delineation of 2 clusters showing moderate stability. In an exploratory attempt, we further characterized 6 homogeneous groups that differed with regard to their clinical features, autoantibody profile, and mortality. Some groups resembled usual dcSSc or lcSSc prototypes, but others exhibited unique features, such as a majority of lcSSc patients with a high rate of visceral damage and antitopoisomerase antibodies. Prognosis varied among groups and the presence of organ damage markedly impacted survival regardless of cutaneous involvement. / Conclusion: Our findings suggest that restricting subsets of SSc patients to only those based on cutaneous involvement may not capture the complete heterogeneity of the disease. Organ damage and antibody profile should be taken into consideration when individuating homogeneous groups of patients with a distinct prognosis

    Development of allergic sensitization and its relevance to paediatric asthma

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    Purpose of review: The purpose of this review is to summarize the recent evidence on the distinct atopic phenotypes and their relationship with childhood asthma. We start by considering definitions and phenotypic classification of atopy and then review evidence on its association with asthma in children. Recent findings: It is now well recognised that both asthma and atopy are complex entities encompassing various different sub-groups that also differ in the way they interconnect. The lack of gold standards for diagnostic markers of atopy and asthma further adds to the existing complexity over diagnostic accuracy and definitions. Although recent statistical phenotyping studies contributed significantly to our understanding of these heterogeneous disorders, translating these findings into meaningful information and effective therapies requires further work on understanding underpinning biological mechanisms. Summary: The disaggregation of allergic sensitization may help predict how the allergic disease is likely to progress. One of the important questions is how best to incorporate tests for the assessment of allergic sensitisation into diagnostic algorithms for asthma, both in terms of confirming asthma diagnosis, and the assessment of future risk

    NanoSAR: Linking the structure of engineered nanomaterials with their toxicity

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    There is increasing recognition that some nanomaterials may pose risks to human health and the enviroiunent. As the use of engineered nanomaterials (ENMs) and the ethical pressure towards non-animal testing increase, we are approaching the point at which it is impossible to individually assess the toxicity of a vast mmiber of ENMs. Therefore, there is a need to use time- and cost-effective methods to predict the toxicity of ENMs. In silico methods, such as structure-activity relationship (SAR) models, are considered as an alternative source of hazard information and their apphcations to nanotoxicology have received growing attention in recent years as the use of ENMs expands. This paper presents a case study in the field of nanotoxicology and demonstrates how SAR approach can be applied to model the relationship between the toxicity and physicochemical characteristics of ENMs based on decision trees

    Zinc-deficient sprouting blight potatoes and their possible relation with neural tube defects

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    PubMed ID: 15376231Maternal nutritional zinc deficiency is blamed in the pathogenesis of neural tube defects. In animal and plant domains zinc is required for growth and development. The objective of the present study was to show that sprouting blighted potato tuber is zinc deficient. In five potato varieties, zinc was measured by atomic absorption spectrophotometry in wet-ashed paired slices of edible potato tuber and in its peel, in blighted potato tuber and in its sprout. Zinc contents were measured as the mean (± SEM) and the following values were found, 0.388 ± 0.036, 0.623 ± 0.059, 0.550 ± 0.030 and 1.089 ± 0.181 mg per 100 g wet weight, respectively. In conclusion, we believe that long-term consumption of zinc-depleted, blight potato tuber by pregnant woman could be potentially teratogenic with the consequent birth of a baby with neural tube defects. Copyright © 2004 John Wiley & Sons, Ltd
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