Imperial College London

DR Ceyda Oksel

Faculty of MedicineDepartment of Medicine

Research Associate in Statistical Machine Learning
 
 
 
//

Contact

 

+44 (0)20 7594 3633c.oksel

 
 
//

Location

 

Sir Alexander Fleming BuildingSouth Kensington Campus

//

Summary

 

Publications

Publication Type
Year
to

18 results found

Oksel C, Granell R, Haider S, Fontanella S, Simpson A, Turner S, Devereux G, Arshad SH, Murray CS, Roberts G, Holloway JW, Cullinan P, Henderson J, Custovic A, STELAR and Breathing Together investigatorset al., 2019, Distinguishing Wheezing Phenotypes from Infancy to Adolescence: A Pooled Analysis of Five Birth Cohorts., Ann Am Thorac Soc

RATIONALE: Pooling data from multiple cohorts and extending the time-frame across childhood should minimize study-specific effects, enabling better characterization of the childhood wheezing. OBJECTIVE: To analyze wheezing patterns from early childhood to adolescence using combined data from five birth cohorts. METHODS: We used latent class analysis to derive wheeze phenotypes among 7719 participants from five birth cohorts with complete report of wheeze at five time-periods. We tested the association of derived phenotypes with late asthma outcomes and lung function, and investigated the uncertainty in phenotype assignment. RESULTS: We identified five phenotypes: Never/Infrequent wheeze (52.1%), Early-onset pre-school remitting (23.9%), Early-onset mid-childhood remitting (9%), Persistent (7.9%) and Late-onset wheeze (7.1%). Compared to the Never/infrequent wheeze, all phenotypes had higher odds of asthma and lower FEV1 and FEV1/FVC in adolescence. The association with asthma was strongest for Persistent wheeze (adjusted odds ratio 56.54, 95%CI 43.75-73.06). We observed considerable within-class heterogeneity at individual level, with 913 (12%) children having low membership probability (<0.60) of any phenotype. Class membership certainty was highest in Persistent and Never/infrequent, and lowest in Late-onset wheeze (with 51% of participants having membership probabilities<0.80). Individual wheezing patterns were particularly heterogeneous in Late-onset wheeze, while many children assigned to Early-onset pre-school remitting class reported wheezing at later time points. CONCLUSIONS: All wheeze phenotypes had significantly diminished lung function in school-age, suggesting that the notion that early-life episodic wheeze has a benign prognosis may not be true for a proportion of transient wheezers. We observed considerable within-phenotype heterogeneity in individual wheezing patterns.

Journal article

Oksel C, Custovic A, Granell R, Mahmoud O, Henderson Jet al., 2018, Causes of variability in latent phenotypes of childhood wheeze, Journal of Allergy and Clinical Immunology, ISSN: 0091-6749

BackgroundLatent class analysis (LCA) has been used extensively to identify (latent) phenotypes of childhood wheezing. However, the number and trajectory of discovered phenotypes differed substantially between studies.ObjectiveWe sought to investigate sources of variability affecting the classification of phenotypes, identify key time points for data collection to understand wheeze heterogeneity, and ascertain the association of childhood wheeze phenotypes with asthma and lung function in adulthood.MethodsWe used LCA to derive wheeze phenotypes among 3167 participants in the ALSPAC cohort who had complete information on current wheeze recorded at 14 time points from birth to age 16½ years. We examined the effects of sample size and data collection age and intervals on the results and identified time points. We examined the associations of derived phenotypes with asthma and lung function at age 23 to 24 years.ResultsA relatively large sample size (>2000) underestimated the number of phenotypes under some conditions (eg, number of time points <11). Increasing the number of data points resulted in an increase in the optimal number of phenotypes, but an identical number of randomly selected follow-up points led to different solutions. A variable selection algorithm identified 8 informative time points (months 18, 42, 57, 81, 91, 140, 157, and 166). The proportion of asthmatic patients at age 23 to 24 years differed between phenotypes, whereas lung function was lower among persistent wheezers.ConclusionsSample size, frequency, and timing of data collection have a major influence on the number and type of wheeze phenotypes identified by using LCA in longitudinal data.

Journal article

Oksel C, Haider S, Fontanella S, Frainay C, Custovic Aet al., 2018, Classification of Pediatric Asthma: From Phenotype Discovery to Clinical Practice, FRONTIERS IN PEDIATRICS, Vol: 6, ISSN: 2296-2360

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.

Journal article

Nakamura T, Haider S, Colicino S, Fontanella S, Oksel C, Holloway J, Murray C, Simpson A, Cullinan P, Custovic Aet al., 2018, Defining childhood eczema: The variety of operational definition causes divergence in its prevalence estimate and model performance, Congress of the European-Academy-of-Allergy-and-Clinical-Immunology (EAACI), Publisher: WILEY, Pages: 108-109, ISSN: 0105-4538

Conference paper

Oksel C, Custovic A, 2018, Allergy for the respiratory pediatrician: which tests and interventions are useful?, 17th International Congress of Pediatric Pulmonology, Publisher: Wiley, Pages: S56-S57, ISSN: 1099-0496

Conference paper

Custovic A, Oksel C, 2018, Development of allergic sensitization and its relevance to paediatric asthma, Current Opinion in Allergy and Clinical Immunology, Vol: 18, Pages: 109-116, ISSN: 1473-6322

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.

Journal article

Oksel C, 2017, Accurate and interpretable nanoQSAR models from genetic programming-based decision tree construction approaches, 254th National Meeting and Exposition of the American-Chemical-Society (ACS) on Chemistry's Impact on the Global Economy, Publisher: AMER CHEMICAL SOC, ISSN: 0065-7727

Conference paper

Oksel C, Wang XZ, Wilkins T, Hunt Net al., 2017, RISK MANAGEMENT OF NANOMATERIALS, RISK MANAGEMENT OF NANOMATERIALSGuidelines for the Safe Manufacture and Use of Nanomaterials

Nanotechnology is an emerging field of science and engineering that has already been applied to a variety of industrial fields. Given the ever increasing use of engineered nanomaterials (ENMs) in industry, it is essential to properly assess all potential risks that may occur as a result of exposure to ENMs. It is generally agreed that the distinctive characteristicsof ENMs that have made them superior to bulk materials for particular applications might also have a substantial impact on the level of risk they pose. However, the complexity and large variety of ENMs presents a challenge for the existing general and product-specific regulation. Inorder to facilitate sustainable manufacturing of ENMs, it is desirable to develop transparent and comprehensive tools and best practice guidelines for risk assessment and management.While the risk management of ENMs receives significant attention, there is still a limited understanding of how to select optimal risk management measures (RMMs) for controlling and mitigating the risks associated with exposure to ENMs. Clearly, there exists the need to expand current risk management practices to ensure safe production, handling and use of ENMs. Moreover, the performance of the existing RMMs should be re-evaluated for ENMs since control options that are proven to be effective for preventing or limiting risks associated with traditional particles might give unsatisfactory results in the case of nano-scale particles.This guidance document brings together evidence on the suitability of traditional controls to minimize potential health and environmental risks resulting from exposure to ENMs. The aim is to advance our understanding of the risk management approaches relevant for ENMs, andultimately to support the selection of the most suitable RMMs when handling ENMs. To that end, evaluative evidence collected from the review of relevant literature, published guidelines, technical reports, and survey of nanotechnology institutions are sum

Report

Oksel C, Ma CY, Liu JJ, Wilkins T, Wang XZet al., 2017, Literature Review of (Q)SAR Modelling of Nanomaterial Toxicity., Adv Exp Med Biol, Vol: 947, Pages: 103-142, ISSN: 0065-2598

Despite the clear benefits that nanotechnology can bring to various sectors of industry, there are serious concerns about the potential health risks associated with engineered nanomaterials (ENMs), intensified by the limited understanding of what makes ENMs toxic and how to make them safe. As the use of ENMs for commercial purposes and the number of workers/end-users being exposed to these materials on a daily basis increases, the need for assessing the potential adverse effects of multifarious ENMs in a time- and cost-effective manner becomes more apparent. One strategy to alleviate the problem of testing a large number and variety of ENMs in terms of their toxicological properties is through the development of computational models that decode the relationships between the physicochemical features of ENMs and their toxicity. Such data-driven models can be used for hazard screening, early identification of potentially harmful ENMs and the toxicity-governing physicochemical properties, and accelerating the decision-making process by maximising the use of existing data. Moreover, these models can also support industrial, regulatory and public needs for designing inherently safer ENMs. This chapter is mainly concerned with the investigation of the applicability of (quantitative) structure-activity relationship ((Q)SAR) methods to modelling of ENMs' toxicity. It summarizes the key components required for successful application of data-driven toxicity prediction techniques to ENMs, the published studies in this field and the current limitations of this approach.

Journal article

Oksel C, Wang XZ, Wilkins T, Ma CY, Liu Jet al., 2017, Literature Review of (Q) SAR Modelling of Nanomaterial Toxicity, Modelling the Toxicity of Nanoparticles, Editors: Tran, Bañares, Rallo

Book chapter

Oksel C, Subramanian V, Semenzin E, Ma CY, Hristozov D, Wang XZ, Hunt N, Costa A, Fransman W, Marcomini A, Wilkins Tet al., 2016, Evaluation of existing control measures in reducing health and safety risks of engineered nanomaterials, Environmental Science: Nano, Vol: 3, Pages: 869-882, ISSN: 2051-8153

While the risk management of engineered nanomaterials (ENMs) receives significant attention, there is still a limited understanding of how to select optimal risk management measures (RMMs) for controlling and mitigating the risks associated with exposure to ENMs. Clearly, there exists a need to expand current risk management practices to ensure safe production, handling and use of ENMs. Moreover, the performance of the existing RMMs should be re-evaluated for ENMs since control options that are proven to be effective for preventing or limiting risks associated with traditional particles might give unsatisfactory results in the case of nano-scale particles. This paper has brought together the evidence on the adequacy of traditional controls to minimize potential health and environmental risks resulting from exposure to ENMs. The aim here is to advance our understanding of the risk management approaches relevant for ENMs, and ultimately to support the selection of the most suitable RMMs when handling ENMs. To that end, evaluative evidence collected from the review of relevant literature and survey of nanotechnology institutions are combined and summarised to understand the level of protection offered by each control measure, as well as the relative costs of their implementation. The findings suggest that most relevant risk control options are based on isolating people from hazard through engineering measures (e.g. ventilation and chemical fume hoods) or personal protective equipment (PPE), rather than eliminating hazard at source (e.g. substitution). Although control measures related to the modification of ENMs have high efficiency in the occupational risk control hierarchy, they are not widely employed since there is currently a high degree of uncertainty regarding the impact of manipulating nano-characteristics on the performance of final product. Lastly, despite its low cost, PPE is the least effective category in the occupational risk control hierarchy and should

Journal article

Oksel C, Winkler DA, Ma CY, Wilkins T, Wang XZet al., 2016, Accurate and interpretable nanoSAR models from genetic programming-based decision tree construction approaches, NANOTOXICOLOGY, Vol: 10, Pages: 1001-1012, ISSN: 1743-5390

Journal article

Liu JJ, Oksel C, Wang XZ, Ma CYet al., 2016, Visualization of Multidimensional Data for Nanomaterial Characterization, Nanomaterial Characterization: An Introduction, Editors: Tantra

Book chapter

Tantra R, Oksel C, Robinson KN, Sikora A, Wang XZ, Wilkins TAet al., 2015, A method for assessing nanomaterial dispersion quality based on principal component analysis of particle size distribution data, PARTICUOLOGY, Vol: 22, Pages: 30-38, ISSN: 1674-2001

Journal article

Oksel C, Ma CY, Liu JJ, Wilkins T, Wang XZet al., 2015, (Q)SAR modelling of nanomaterial toxicity: A critical review, PARTICUOLOGY, Vol: 21, Pages: 1-19, ISSN: 1674-2001

Journal article

Oksel C, Ma CY, Wang XZ, 2015, Current situation on the availability of nanostructure-biological activity data, SAR AND QSAR IN ENVIRONMENTAL RESEARCH, Vol: 26, Pages: 79-94, ISSN: 1062-936X

Journal article

Oksel C, Ma CY, Wang XZ, 2015, Structure-activity relationship models for hazard assessment and risk management of engineered nanomaterials, NEW PARADIGM OF PARTICLE SCIENCE AND TECHNOLOGY, PROCEEDINGS OF THE 7TH WORLD CONGRESS ON PARTICLE TECHNOLOGY, Vol: 102, Pages: 1500-1510, ISSN: 1877-7058

Journal article

Tantra R, Oksel C, Puzyn T, Wang J, Robinson KN, Wang XZ, Ma CY, Wilkins Tet al., 2015, Nano(Q)SAR: Challenges, pitfalls and perspectives, NANOTOXICOLOGY, Vol: 9, Pages: 636-642, ISSN: 1743-5390

Journal article

This data is extracted from the Web of Science and reproduced under a licence from Thomson Reuters. You may not copy or re-distribute this data in whole or in part without the written consent of the Science business of Thomson Reuters.

Request URL: http://wlsprd.imperial.ac.uk:80/respub/WEB-INF/jsp/search-html.jsp Request URI: /respub/WEB-INF/jsp/search-html.jsp Query String: respub-action=search.html&id=00944893&limit=30&person=true