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- Duffy, J. M. N., et al.
(author)
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Top 10 priorities for future infertility research: an international consensus development study
- 2020
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In: Human Reproduction. - : Oxford University Press (OUP). - 0268-1161 .- 1460-2350. ; 35:12, s. 2715-2724
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Journal article (peer-reviewed)abstract
- STUDY QUESTION: Can the priorities for future research in infertility be identified? SUMMARY ANSWER: The top 10 research priorities for the four areas of male infertility, female and unexplained infertility, medically assisted reproduction and ethics, access and organization of care for people with fertility problems were identified. WHAT IS KNOWN ALREADY: Many fundamental questions regarding the prevention, management and consequences of infertility remain unanswered. This is a barrier to improving the care received by those people with fertility problems. STUDY DESIGN, SIZE, DURATION: Potential research questions were collated from an initial international survey, a systematic review of clinical practice guidelines and Cochrane systematic reviews. A rationalized list of confirmed research uncertainties was prioritized in an interim international survey. Prioritized research uncertainties were discussed during a consensus development meeting. Using a formal consensus development method, the modified nominal group technique, diverse stakeholders identified the top 10 research priorities for each of the categories male infertility, female and unexplained infertility, medically assisted reproduction and ethics, access and organization of care. PARTICIPANTS/MATERIALS, SETTING, METHODS: Healthcare professionals, people with fertility problems and others (healthcare funders, healthcare providers, healthcare regulators, research funding bodies and researchers) were brought together in an open and transparent process using formal consensus methods advocated by the James Lind Alliance. MAIN RESULTS AND THE ROLE OF CHANCE: The initial survey was completed by 388 participants from 40 countries, and 423 potential research questions were submitted. Fourteen clinical practice guidelines and 162 Cochrane systematic reviews identified a further 236 potential research questions. A rationalized list of 231 confirmed research uncertainties was entered into an interim prioritization survey completed by 317 respondents from 43 countries. The top 10 research priorities for each of the four categories male infertility, female and unexplained infertility (including age-related infertility, ovarian cysts, uterine cavity abnormalities and tubal factor infertility), medically assisted reproduction (including ovarian stimulation, IUI and IVF) and ethics, access and organization of care were identified during a consensus development meeting involving 41 participants from I I countries. These research priorities were diverse and seek answers to questions regarding prevention, treatment and the longer-term impact of infertility. They highlight the importance of pursuing research which has often been overlooked, including addressing the emotional and psychological impact of infertility, improving access to fertility treatment, particularly in lower resource settings and securing appropriate regulation. Addressing these priorities will require diverse research methodologies, including laboratory-based science, qualitative and quantitative research and population science. LIMITATIONS, REASONS FOR CAUTION: We used consensus development methods, which have inherent limitations, including the representativeness of the participant sample, methodological decisions informed by professional judgment and arbitrary consensus definitions. WIDER IMPLICATIONS OF THE FINDINGS: We anticipate that identified research priorities, developed to specifically highlight the most pressing clinical needs as perceived by healthcare professionals, people with fertility problems and others, will help research funding organizations and researchers to develop their future research agenda.
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- Barbé, Kurt, et al.
(author)
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Fractional-Order Time Series Models for Extracting the Haemodynamic Response From Functional Magnetic Resonance Imaging Data
- 2012
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In: IEEE Transactions on Biomedical Engineering. - 0018-9294 .- 1558-2531. ; 59:8, s. 2264-2272
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Journal article (peer-reviewed)abstract
- The postprocessing of functional magnetic resonance imaging (fMRI) data to study the brain functions deals mainly with two objectives: signal detection and extraction of the haemodynamic response. Signal detection consists of exploring and detecting those areas of the brain that are triggered due to an external stimulus. Extraction of the haemodynamic response deals with describing and measuring the physiological process of activated regions in the brain due to stimulus. The haemodynamic response represents the change in oxygen levels since the brain functions require more glucose and oxygen upon stimulus that implies a change in blood flow. In the literature, different approaches to estimate and model the haemodynamic response have been proposed. These approaches can be discriminated in model structures that either provide a proper representation of the obtained measurements but provide no or a limited amount of physiological information, or provide physiological insight but lacks a proper fit to the data. In this paper, a novel model structure is studied for describing the haemodynamics in fMRI measurements: fractional models. We show that these models are flexible enough to describe the gathered data with the additional merit of providing physiological information.
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- Beecham, Ashley H, et al.
(author)
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Analysis of immune-related loci identifies 48 new susceptibility variants for multiple sclerosis.
- 2013
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In: Nature genetics. - : Springer Science and Business Media LLC. - 1546-1718 .- 1061-4036. ; 45:11, s. 1353-60
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Journal article (peer-reviewed)abstract
- Using the ImmunoChip custom genotyping array, we analyzed 14,498 subjects with multiple sclerosis and 24,091 healthy controls for 161,311 autosomal variants and identified 135 potentially associated regions (P < 1.0 × 10(-4)). In a replication phase, we combined these data with previous genome-wide association study (GWAS) data from an independent 14,802 subjects with multiple sclerosis and 26,703 healthy controls. In these 80,094 individuals of European ancestry, we identified 48 new susceptibility variants (P < 5.0 × 10(-8)), 3 of which we found after conditioning on previously identified variants. Thus, there are now 110 established multiple sclerosis risk variants at 103 discrete loci outside of the major histocompatibility complex. With high-resolution Bayesian fine mapping, we identified five regions where one variant accounted for more than 50% of the posterior probability of association. This study enhances the catalog of multiple sclerosis risk variants and illustrates the value of fine mapping in the resolution of GWAS signals.
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