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- Morales, E, et al.
(författare)
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Combined impact of healthy lifestyle factors on risk of asthma, rhinoconjunctivitis and eczema in school children: ISAAC phase III
- 2019
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Ingår i: Thorax. - : BMJ. - 1468-3296 .- 0040-6376. ; 74:6, s. 531-538
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Tidskriftsartikel (refereegranskat)abstract
- Asthma is not the key focus of prevention strategies. A Healthy Lifestyle Index (HLI) was developed to examine the combined effect of modifiable lifestyle factors on asthma, rhinoconjunctivitis and eczema using data from the International Study of Asthma and Allergies in Childhood (ISAAC) phase III.MethodsInformation on symptoms of asthma, rhinoconjunctivitis, eczema and several lifestyle factors was obtained from children aged 6–7 years through written questionnaires. The HLI combined five lifestyle factors: no parental smoking, child’s adherence to Mediterranean diet, child’s healthy body mass index, high physical activity and non-sedentary behaviour. The association between the HLI and risk of asthma, rhinoconjunctivitis and eczema was evaluated using multilevel mixed-effects logistic regression models.FindingsData of 70 795 children from 37 centres in 19 countries were analysed. Each additional healthy lifestyle factor was associated with a reduced risk of current wheeze (OR 0.87, 95% CI 0.84 to 0.89), asthma ever (OR 0.89, 95% CI 0.87 to 0.92), current symptoms of rhinoconjunctivitis (OR 0.95, 95% CI 0.92 to 0.97) and current symptoms of eczema (OR 0.92, 95% CI 0.92 to 0.98). Theoretically, if associations were causal, a combination of four or five healthy lifestyle factors would result into a reduction up to 16% of asthma cases (ranging from 2.7% to 26.3 % according to region of the world).ConclusionsThese findings should be interpreted with caution given the limitations to infer causality from cross-sectional observational data. Efficacy of interventions to improve multiple modifiable lifestyle factors to reduce the burden asthma and allergy in childhood should be assessed.
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- Takahashi, H., et al.
(författare)
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A thermal-neutron detector with a phoswich system of LiCaAlF6 and BGO crystal scintillators onboard PoGOLite
- 2010
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Ingår i: 2010 IEEE Nuclear Science Symposium, Medical Imaging Conference, NSS/MIC 2010 and 17th International Workshop on Room-Temperature Semiconductor X-ray and Gamma-ray Detectors, RTSD 2010. ; , s. 32-37
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Konferensbidrag (refereegranskat)abstract
- To measure the flux of atmospheric neutrons and study the neutron contribution to the background of the main detector of the PoGOLite (Polarized Gamma-ray Observer) balloon-borne experiment, a thermal-neutron detector with a phoswich system of LiCaAlF6 (Eu) and BGO crystal scintillators is developed. The performance to separate thermal-neutron events from those of gamma-rays and charged particles is validated with 252Cf on ground. The detector is attached to the PoGOLite instrument and is launched in 2011 from the Esrange facility in the North of Sweden. Although the emission wavelength of the LiCaAlF6 (Ce) is 300 nm and overlaps with the absorption wavelength of the BGO, the phoswich capability of the LiCaAlF6 (Ce) with the BGO is also confirmed with installing a waveform shifter.
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- Franco, R, et al.
(författare)
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Partners for adenosine A1 receptors
- 2005
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Ingår i: Journal of molecular neuroscience : MN. - 0895-8696. ; 26:2-3, s. 221-231
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Tidskriftsartikel (refereegranskat)
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- Marti-Bonmati, Luis, et al.
(författare)
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Considerations for artificial intelligence clinical impact in oncologic imaging : an AI4HI position paper
- 2022
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Ingår i: Insights into Imaging. - : Springer. - 1869-4101. ; 13:1
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Tidskriftsartikel (refereegranskat)abstract
- To achieve clinical impact in daily oncological practice, emerging AI-based cancer imaging research needs to have clearly defined medical focus, AI methods, and outcomes to be estimated. AI-supported cancer imaging should predict major relevant clinical endpoints, aiming to extract associations and draw inferences in a fair, robust, and trustworthy way. AI-assisted solutions as medical devices, developed using multicenter heterogeneous datasets, should be targeted to have an impact on the clinical care pathway. When designing an AI-based research study in oncologic imaging, ensuring clinical impact in AI solutions requires careful consideration of key aspects, including target population selection, sample size definition, standards, and common data elements utilization, balanced dataset splitting, appropriate validation methodology, adequate ground truth, and careful selection of clinical endpoints. Endpoints may be pathology hallmarks, disease behavior, treatment response, or patient prognosis. Ensuring ethical, safety, and privacy considerations are also mandatory before clinical validation is performed. The Artificial Intelligence for Health Imaging (AI4HI) Clinical Working Group has discussed and present in this paper some indicative Machine Learning (ML) enabled decision-support solutions currently under research in the AI4HI projects, as well as the main considerations and requirements that AI solutions should have from a clinical perspective, which can be adopted into clinical practice. If effectively designed, implemented, and validated, cancer imaging AI-supported tools will have the potential to revolutionize the field of precision medicine in oncology.
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- Vasile, Massimiliano, et al.
(författare)
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The Suaineadh Project : a Stepping Stone Towards the Deployment of Large Flexible Structures in Space
- 2010
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Ingår i: Proceedings of the 61<sup>st</sup> International Astronautical Congress. - : the International Astronautical Federation. ; , s. IAC-10-C3.4-
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Konferensbidrag (refereegranskat)abstract
- The Suaineadh project aims at testing the controlled deployment and stabilization of space web. The deployment system is based on a simple yet ingenious control of the centrifugal force that will pull each of the four daughters sections apart. The four daughters are attached onto the four corners of a square web, and will be released from their initial stowed configuration attached to a central hub. Enclosed in the central hub is a specifically designed spinning reaction wheel that controls the rotational speed with a closed loop control fed by measurements from an onboard inertial measurement sensor. Five other such sensors located within the web and central hub provide information on the surface curvature of the web, and progression of the deployment. Suaineadh is currently at an advanced stage of development: all the components are manufactured with the subsystems integrated and are presently awaiting full integration and testing. This paper will present the current status of the Suaineadh project and the results of the most recent set of tests. In particular, the paper will cover the overall mechanical design of the system, the electrical and sensor assemblies, the communication and power systems and the spinning wheel with its control system.
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