| 1. |
- Ashrafian, Hutan, et al.
(författare)
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Metabolomics : The Stethoscope for the Twenty-First Century
- 2021
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Ingår i: Medical principles and practice. - : S. Karger. - 1011-7571 .- 1423-0151. ; 30:4, s. 301-310
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Tidskriftsartikel (refereegranskat)abstract
- Metabolomics encompasses the systematic identification and quantification of all metabolic products in the human body. This field could provide clinicians with novel sets of diagnostic biomarkers for disease states in addition to quantifying treatment response to medications at an individualized level. This literature review aims to highlight the technology underpinning metabolic profiling, identify potential applications of metabolomics in clinical practice, and discuss the translational challenges that the field faces. We searched PubMed, MEDLINE, and EMBASE for primary and secondary research articles regarding clinical applications of metabolomics. Metabolic profiling can be performed using mass spectrometry and nuclear magnetic resonance-based techniques using a variety of biological samples. This is carried out in vivo or in vitro following careful sample collection, preparation, and analysis. The potential clinical applications constitute disruptive innovations in their respective specialities, particularly oncology and metabolic medicine. Outstanding issues currently preventing widespread clinical use are scalability of data interpretation, standardization of sample handling practice, and e-infrastructure. Routine utilization of metabolomics at a patient and population level will constitute an integral part of future healthcare provision.
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| 2. |
- Berner-Rodoreda, Astrid, et al.
(författare)
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Where is the 'global' in the European Union's Health Research and Innovation Agenda?
- 2019
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Ingår i: BMJ Global Health. - : BMJ. - 2059-7908. ; 4:5
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Tidskriftsartikel (refereegranskat)abstract
- Global Health has not featured as prominently in the European Union (EU) research agenda in recent years as it did in the first decade of the new millennium, and participation of low-income and middle-income countries (LMICs) in EU health research has declined substantially. The Horizon Europe Research and Innovation Framework adopted by the European Parliament in April 2019 for the period 2021-2027 will serve as an important funding instrument for health research, yet the proposed health research budget to be finalised towards the end of 2019 was reduced from 10% in the current framework, Horizon 2020, to 8% in Horizon Europe. Our analysis takes the evolvement of Horizon Europe from the initial framework of June 2018 to the framework agreed on in April 2019 into account. It shows that despite some improvements in terms of Global Health and reference to the Sustainable Development Goals, European industrial competitiveness continues to play a paramount role, with Global Health research needs and relevant health research for LMICs being only partially addressed. We argue that the globally interconnected nature of health and the transdisciplinary nature of health research need to be fully taken into account and acted on in the new European Research and Innovation Framework. A facilitated global research collaboration through Horizon Europe could ensure that Global Health innovations and solutions benefit all parts of the world including EU countries.
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| 3. |
- Bueter, Marco, et al.
(författare)
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Vagal sparing surgical technique but not stoma size affects body weight loss in rodent model of gastric bypass.
- 2010
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Ingår i: Obesity surgery. - : Springer Science and Business Media LLC. - 1708-0428 .- 0960-8923. ; 20:5, s. 616-22
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: The aim of this study was to evaluate whether gastric bypass with or without vagal preservation resulted in a different outcome. METHODS: Body weight, food intake and postprandial peptide YY (PYY) and glucagon-like peptide (GLP-1) levels were compared between gastric bypass (n = 55) and sham-operated rats (n = 27) in three groups. In group 1 (n = 17), the vagal nerve was not preserved, while in group 2 the vagal nerve was preserved during gastric bypass (n = 10). In group 3, gastric bypass rats (n = 28) were randomised for either one of the two techniques. RESULTS: Rats in which the vagal nerve was preserved during gastric bypass showed a lower body weight (p < 0.001) and reduced food intake (p < 0.001) compared to rats in which the vagal nerve was not preserved during the gastric bypass operation. Levels of PYY and GLP-1 were significantly increased after gastric bypass compared to sham-operated controls (p < 0.05), but there was no difference between gastric bypass rats with and without vagal preservation. Differences in food intake and body weight were not related to the size of the gastro-jejunostomy in gastric bypass rats. There were no signs of malabsorption or inflammation after gastric bypass. CONCLUSION: We propose that the vagal nerve should be preserved during the gastric bypass operation as this might play an important role for the mechanisms that induce weight loss and reduce food intake in rats. In contrast, the gastro-jejunal stoma size was found to be of minor relevance.
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| 4. |
- Lidströmer, Niklas, et al.
(författare)
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Basic Concepts of Artificial Intelligence : Primed for Clinicians
- 2022
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Ingår i: Artificial Intelligence in Medicine. - Cham : Springer Nature. ; , s. 3-20
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- With the urgent need for automatized algorithm applications to an ever-increasing amount of data and a further decrease of the chances of human errors on crucial tasks, artificial intelligence algorithms were introduced. An expansive demand of AI applications in varying fields led to the development of specifically designed ad hoc algorithms with the role of better estimating (by learning) solutions to the problems. The boost of AI in healthcare right now is a consequence of two things - the availability of big data and better processors, able to train and execute algorithmic tasks, i.e., implementations of these algorithms with neural networks. It will soon be vital for medical students to grasp the principles of AI. The purpose of this major reference textbook on AI in medicine, of which this chapter is the base level introduction, is to become the greatest standard reference work. No area of medicine, preclinical or clinical, will escape the profound effects of AI: the whole healthcare domain will be reshaped thoroughly.
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| 5. |
- Lim, Eric, et al.
(författare)
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Longitudinal study of the profile and predictors of left ventricular mass regression after stentless aortic valve replacement
- 2008
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Ingår i: Annals of Thoracic Surgery. - : Elsevier BV. - 0003-4975 .- 1552-6259. ; 85:6, s. 2026-2029
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: The aim of this study was to evaluate the long-term profile and determine the factors that would influence the effect and rate of ventricular mass regression with time after aortic valve replacement with a stentless or a homograft valve.METHODS: We studied 300 patients during a 10-year period with at least a year of follow-up with a total of 1,273 serial echocardiographic measurements. Left ventricular mass was calculated from M-mode recordings and indexed to body surface area. Longitudinal data analysis was performed using a linear mixed effects model.RESULTS: The mean age (+/- standard deviation) was 65 (+/-14) years, consisting of 216 (72%) males. A stentless valve was implanted in 156 (52%), and a homograft in 144 (48%). The median time (interquartile range) to follow-up was 4.7 (2.8 to 6.6) years. The greatest rate of left ventricular mass regression occurred in the first year after surgery. On multivariable modeling, independent predictors of left ventricular mass were valve size (p = 0.011), left ventricular function (moderate impairment, p = 0.418; severe impairment, p = 0.011), and baseline left ventricular mass (middle tercile, p < 0.001; highest tercile, p < 0.001). Only baseline ventricular mass influenced the rate of subsequent left ventricular mass regression; the greatest rate of regression occurred in patients with the highest baseline values of ventricular mass (p < 0.001).CONCLUSIONS: The greatest rate of left ventricular mass regression occurs in the first year with baseline left ventricular mass as the strongest predictor and the only identified variable that influenced the rate of left ventricular mass regression.
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