| 1. |
- Avdic, H. B., et al.
(author)
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Reduced effects of social feedback on learning in Turner syndrome
- 2023
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In: Scientific Reports. - : Springer Nature. - 2045-2322. ; 13:1
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Journal article (peer-reviewed)abstract
- Turner syndrome is a genetic condition caused by a complete or partial loss of one of the X chromosomes. Previous studies indicate that Turner syndrome is associated with challenges in social skills, but the underlying mechanisms remain largely unexplored. A possible mechanism is a reduced social influence on learning. The current study examined the impact of social and non-social feedback on learning in women with Turner syndrome (n=35) and a sex- and age-matched control group (n=37). Participants were instructed to earn points by repeatedly choosing between two stimuli with unequal probabilities of resulting in a reward. Mastering the task therefore required participants to learn through feedback which of the two stimuli was more likely to be rewarded. Data were analyzed using computational modeling and analyses of choice behavior. Social feedback led to a more explorative choice behavior in the control group, resulting in reduced learning compared to non-social feedback. No effects of social feedback on learning were found in Turner syndrome. The current study thus indicates that women with Turner syndrome may be less sensitive to social influences on reinforcement learning, than the general population.
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| 2. |
- Arner, Erik, et al.
(author)
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Adipocyte Turnover : Relevance to Human Adipose Tissue Morphology
- 2010
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In: Diabetes. - : American Diabetes Association. - 0012-1797 .- 1939-327X. ; 59:1, s. 105-109
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Journal article (peer-reviewed)abstract
- OBJECTIVE-Adipose tissue may contain few large adipocytes (hypertrophy) or many small adipocytes (hyperplasia). We investigated factors of putative importance for adipose tissue morphology. RESEARCH DESIGN AND METHODS-Subcutaneous adipocyte size and total fat mass were compared in 764 subjects with BMI 18-60 kg/m(2). A morphology value was defined as tire difference between the measured adipocyte volume and the expected volume given by a curved-line fit for a given body fat mass and was related to insulin values. In 35 subjects, in vivo adipocyte turnover was measured by exploiting incorporation of atmospheric C-14 into DNA. RESULTS-Occurrence of hyperplasia (negative morphology value) or hypertrophy (positive morphology value) was independent of sex and body weight but con-elated with fasting plasma insulin levels and insulin sensitivity, independent of adipocyte volume (beta-coefficient = 0.3, P < 0.0001). Total adipocyte number and morphology were negatively related (r = -0.66); i.e., the total adipocyte number was greatest in pronounced hyperplasia and smallest in pronounced hypertrophy. The absolute number of new adipocytes generated each year was 70% lower (P < 0.001) in hypertrophy than in hyperplasia, and individual values for adipocyte generation and morphology were strongly related (r = 0.7, P < 0.001). The relative death rate (similar to 10% per year) or mean age of adipocytes (similar to 10 years) was not correlated with morphology. CONCLUSIONS-Adipose tissue morphology correlates with insulin measures and is linked to the total adipocyte number independently of sex and body fat level. Low generation rates of adipocytes associate with adipose tissue hypertrophy, whereas high generation rates associate with adipose hyperplasia. Diabetes 59:105-109, 2010
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| 3. |
- Spalding, KL, et al.
(author)
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Dynamics of fat cell turnover in humans
- 2008
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In: Nature. - : Springer Science and Business Media LLC. - 1476-4687 .- 0028-0836. ; 453:7196, s. 783-787
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Journal article (peer-reviewed)
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| 4. |
- Vickovic, Sanja, et al.
(author)
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Massive and parallel expression profiling using microarrayed single-cell sequencing
- 2016
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In: Nature Communications. - : Nature Publishing Group. - 2041-1723. ; 7
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Journal article (peer-reviewed)abstract
- Single-cell transcriptome analysis overcomes problems inherently associated with averaging gene expression measurements in bulk analysis. However, single-cell analysis is currently challenging in terms of cost, throughput and robustness. Here, we present a method enabling massive microarray-based barcoding of expression patterns in single cells, termed MASC-seq. This technology enables both imaging and high-throughput single-cell analysis, characterizing thousands of single-cell transcriptomes per day at a low cost (0.13 USD/cell), which is two orders of magnitude less than commercially available systems. Our novel approach provides data in a rapid and simple way. Therefore, MASC-seq has the potential to accelerate the study of subtle clonal dynamics and help provide critical insights into disease development and other biological processes.
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