References of "de Beaufort, Carine"
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See detailLower plasma insulin levels during overnight closed loop in schoolchildren with type 1 diabetes: potential advantage?
Schierloh, Ulrike; Wilinska, M.; Pit-Ten Cate, Ineke UL et al

in PLoS ONE (2019), 14(3: e0212013), 1-11

Background Studies have shown that overnight closed-loop insulin delivery can improve glucose control and reduce the risk of hypoglycemia and hence may improve metabolic outcomes and reduce burden for ... [more ▼]

Background Studies have shown that overnight closed-loop insulin delivery can improve glucose control and reduce the risk of hypoglycemia and hence may improve metabolic outcomes and reduce burden for children with type 1 diabetes and their families. However, research so far has not reported insulin levels while comparing closed-loop to open-loop insulin delivery in children. Therefore, in this study we obtained glucose levels as well plasma insulin levels in children with type 1 diabetes to evaluate the efficacy of a model - based closed-loop algorithm compared to an open-loop administration. Methods Fifteen children with type 1 diabetes, 6-12 years, participated in this open-label single center study. We used a randomized cross over design in which we compared overnight closed-loop insulin delivery with sensor augmented pump therapy for two nights in both the hospital and at home (i.e., 1 night in-patient stay and at home per treatment condition). Only during the in-patient stay, hourly plasma insulin and blood glucose levels were assessed and are reported in this paper. Results Results of paired sample t-tests revealed that although plasma insulin levels were significantly lower during the closed-loop than in the open-loop (Mean difference 36.51 pmol/l; t(13)=2.13, p=.03, effect size d= 0.57), blood glucose levels did not vary between conditions (mean difference 0.76 mmol/l; t(13)=1.24, p=.12, d=0.37). The administered dose of insulin was significantly lower during the closed-loop compared with the open-loop (mean difference 0.10 UI; t(12)=2.45, p=.02, d=0.68). Conclusions Lower insulin doses were delivered in the closed-loop, resulting in lower plasma insulin levels , whereby glucose levels were not affected negatively. This suggests that the closed-loop administration is better targeted and hence could be more effective. [less ▲]

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See detailSmall RNA profiling of low biomass samples: identification and removal of contaminants
Heintz-Buschart, Anna; Yusuf, Dilmurat; Kaysen, Anne UL et al

in BMC Biology (2018), 16(52),

Background: Sequencing-based analyses of low-biomass samples are known to be prone to misinterpretation due to the potential presence of contaminating molecules derived from laboratory reagents and ... [more ▼]

Background: Sequencing-based analyses of low-biomass samples are known to be prone to misinterpretation due to the potential presence of contaminating molecules derived from laboratory reagents and environments. DNA contamination has been previously reported, however contamination with RNA is usually considered to be unlikely due to its inherent instability. Small RNAs (sRNAs) identified in tissues and bodily fluids such as blood plasma, have implications for physiology and pathology, and therefore the potential to act as disease biomarkers. Thus, the possibility for RNA contaminants demands a careful evaluation. Results: Here we report the presence of small RNA contaminants in widely used microRNA extraction kits and propose an approach for their depletion. We sequenced sRNAs extracted from human plasma samples and detected important levels of non-human (exogenous) sequences whose source could be traced to the microRNA extraction columns through a careful qPCR-based analysis of several laboratory reagents. Furthermore, we also detected the presence of artefactual sequences related to these contaminants in a range of published datasets, arguing for a re-evaluation of reports suggesting the presence of exogenous RNAs of microbial and dietary origins in blood plasma. To avoid artefacts in future experiments, we also devise several protocols of contaminant RNAs, define minimal amounts of starting material for artefact-free analyses, and confirm the reduction of contaminant levels for identification of bona fide sequences using ‘ultra-clean’ extraction kits. Conclusion: This is the first report of the presence of RNA molecules as contaminants in RNA extraction kits. The described protocols should be applied in the future to avoid confounding sRNA studies. [less ▲]

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See detailIsolation of nucleic acids from low biomass samples: detection and removal of sRNA contaminants
Heintz-Buschart, Anna; Yusuf, Dilmurat; Kaysen, Anne UL et al

E-print/Working paper (2017)

Sequencing-based analyses of low-biomass samples are known to be prone to misinterpretation due to the potential presence of contaminating molecules derived from laboratory reagents and environments. Due ... [more ▼]

Sequencing-based analyses of low-biomass samples are known to be prone to misinterpretation due to the potential presence of contaminating molecules derived from laboratory reagents and environments. Due to its inherent instability, contamination with RNA is usually considered to be unlikely. Here we report the presence of small RNA (sRNA) contaminants in widely used microRNA extraction kits and means for their depletion. Sequencing of sRNAs extracted from human plasma samples was performed and significant levels of non-human (exogenous) sequences were detected. The source of the most abundant of these sequences could be traced to the microRNA extraction columns by qPCR-based analysis of laboratory reagents. The presence of artefactual sequences originating from the confirmed contaminants were furthermore replicated in a range of published datasets. To avoid artefacts in future experiments, several protocols for the removal of the contaminants were elaborated, minimal amounts of starting material for artefact-free analyses were defined, and the reduction of contaminant levels for identification of bona fide sequences using 'ultra-clean' extraction kits was confirmed. In conclusion, this is the first report of the presence of RNA molecules as contaminants in laboratory reagents. The described protocols should be applied in the future to avoid confounding sRNA studies. [less ▲]

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See detailCan health indicators and psychosocial characteristics predict attrition in youth with overweight and obesity seeking ambulatory treatment? Data from a retrospective longitudinal study in a paediatric clinic in Luxembourg.
Pit-Ten Cate, Ineke UL; Samouda, Hanen; Schierloh, Ulrike et al

in BMJ Open (2017), 7(9),

ABSTRACT Objectives: The current study aimed to identify factors that could predict attrition in youth starting ambulatory treatment to control or lose weight. Design: retrospective longitudinal study ... [more ▼]

ABSTRACT Objectives: The current study aimed to identify factors that could predict attrition in youth starting ambulatory treatment to control or lose weight. Design: retrospective longitudinal study Setting: paediatric clinic: ambulatory treatment program Patients and measures: A youth sample (N=191; 89 boys; age 7-17 years) completed measures of demographic characteristics, health and psychosocial traits before starting an ambulatory weight management program. Anthropometric and biological markers related to obesity were also obtained. Test of mean differences and regression analyses were used to investigate the relationship between these variables and attrition after one year. Results: Chi-square and t-test results showed both psychosocial and health indicators differentiated between participants who continued attending the treatment program and those that dropped out. More specifically, youth that dropped out of treatment were significantly older, had higher BMI-Z scores, higher levels of insulin, triglycerides and HOMA-IR, reported poorer health and more conduct problems, and were more dissatisfied with themselves and their bodies before starting treatment. Results of regression analyses revealed that weight status (anthropometric and biological markers), age and body dissatisfaction predict attrition (overall prediction success 73%; prediction success for continued attendance 90/91%; prediction success for dropout 42/44%). Conclusion: Attrition, but especially the continued attendance in treatment, can be successfully predicted by age, weight status and body dissatisfaction. For patients who present with one or more risk factors, careful consideration is needed to decide which (combination of) in- or outpatient program may facilitate prolonged engagement of the patient and hence may be most effective in establishing weight loss. [less ▲]

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