scholarly journals Model-Based Interspecies Scaling of Glucose Homeostasis

2017 ◽  
Vol 6 (11) ◽  
pp. 778-786 ◽  
Author(s):  
Oskar Alskär ◽  
Mats O. Karlsson ◽  
Maria C. Kjellsson
Keyword(s):  
Glucose Homeostasis ◽  
Interspecies Scaling ◽  
Model Based

Representation, abstraction, and simple-minded sophisticates

2020 ◽  
Vol 43 ◽  
Author(s):  
Peter Dayan
Keyword(s):  
Decision Theory ◽  
Predictive Coding ◽  
Bayesian Decision Theory ◽  
Bayesian Decision ◽  
Model Based ◽  
Model Free

Abstract Bayesian decision theory provides a simple formal elucidation of some of the ways that representation and representational abstraction are involved with, and exploit, both prediction and its rather distant cousin, predictive coding. Both model-free and model-based methods are involved.

Quantitative Model-Based Image Analysis of NuMa Distribution Links Nuclear Organization with Cell Phenotype

2001 ◽  
Vol 7 (S2) ◽  
pp. 578-579
Author(s):  
David W. Knowles ◽  
Sophie A. Lelièvre ◽  
Carlos Ortiz de Solόrzano ◽  
Stephen J. Lockett ◽  
Mina J. Bissell ◽  
...  
Keyword(s):  
Image Analysis ◽  
Mammary Epithelial Cells ◽  
Nuclear Organization ◽  
Critical Role ◽  
Quantitative Model ◽  
Mammary Epithelial ◽  
Cell Phenotype ◽  
Proliferating Cells ◽  
Mitotic Apparatus ◽  
Model Based

The extracellular matrix (ECM) plays a critical role in directing cell behaviour and morphogenesis by regulating gene expression and nuclear organization. Using non-malignant (S1) human mammary epithelial cells (HMECs), it was previously shown that ECM-induced morphogenesis is accompanied by the redistribution of nuclear mitotic apparatus (NuMA) protein from a diffuse pattern in proliferating cells, to a multi-focal pattern as HMECs growth arrested and completed morphogenesis . A process taking 10 to 14 days.To further investigate the link between NuMA distribution and the growth stage of HMECs, we have investigated the distribution of NuMA in non-malignant S1 cells and their malignant, T4, counter-part using a novel model-based image analysis technique. This technique, based on a multi-scale Gaussian blur analysis (Figure 1), quantifies the size of punctate features in an image. Cells were cultured in the presence and absence of a reconstituted basement membrane (rBM) and imaged in 3D using confocal microscopy, for fluorescently labeled monoclonal antibodies to NuMA (fαNuMA) and fluorescently labeled total DNA.

Model-Based Clustering and Classification for Data Science

2019 ◽  
Author(s):  
Charles Bouveyron ◽  
Gilles Celeux ◽  
T. Brendan Murphy ◽  
Adrian E. Raftery
Keyword(s):  
Data Science ◽  
Model Based Clustering ◽  
Model Based ◽  
Clustering And Classification

Model-Based Software Testing and Analysis with C#

2007 ◽  
Author(s):  
Jonathan Jacky ◽  
Margus Veanes ◽  
Colin Campbell ◽  
Wolfram Schulte
Keyword(s):  
Software Testing ◽  
Model Based

Supplementation with beta-hydroxy-beta-methylbutyrate impacts glucose homeostasis and increases liver size in trained mice

2020 ◽  
Vol 90 (1-2) ◽  
pp. 113-123
Author(s):  
Ines Schadock ◽  
Barbara G. Freitas ◽  
Irae L. Moreira ◽  
Joao A. Rincon ◽  
Marcio Nunes Correa ◽  
...  
Keyword(s):  
Strength Training ◽  
Muscle Mass ◽  
Glucose Homeostasis ◽  
Fasting Blood Glucose ◽  
Hepatic Metabolism ◽  
Mass Gain ◽  
Trained Group ◽  
Tissue Mass ◽  
Liver Size ◽  
Intensive Training

Abstract. β-hydroxy-β-methyl butyrate (HMB) is a bioactive metabolite derived from the amino acid leucine, usually applied for muscle mass increase during physical training, as well as for muscle mass maintenance in debilitating chronic diseases. The hypothesis of the present study is that HMB is a safe supplement for muscle mass gain by strength training. Based on this, the objective was to measure changes in body composition, glucose homeostasis and hepatic metabolism of HMB supplemented mice during strength training. Two of four groups of male mice (n = 6/group) underwent an 8-week training period session (climbing stairs) with or without HMB supplementation (190 mg/kgBW per day). We observed lower body mass gain (4.9 ± 0.43% versus 1.2 ± 0.43, p < 0.001) and increased liver mass (40.9 ± 0.9 mg/gBW versus 44.8 ± 1.3, p < 0.001) in the supplemented trained group compared with the non-supplemented groups. The supplemented trained group had an increase in relative adipose tissue mass (12.4 ± 0.63 mg/gBW versus 16.1 ± 0.88, P < 0.01) compared to the non-supplemented untrained group, and an increase in fasting blood glucose (111 ± 4.58 mg/dL versus 122 ± 3.70, P < 0.05) and insulin resistance (3.79 ± 0.19 % glucose decay/min versus 2.45 ± 0.28, P < 0.05) comparing with non-supplemented trained group. Adaptive heart hypertrophy was observed only in the non-supplemented trained group (4.82 ± 0.05 mg/gBW versus 5.12 ± 0.13, P < 0.05). There was a higher hepatic insulin-like growth factor-1 expression (P = 0.002) in supplemented untrained comparing with non-supplemented untrained group. Gene expression of gluconeogenesis regulatory factors was increased by training and reduced by HMB supplementation. These results confirm that HMB supplementation associated with intensive training protocol drives changes in glucose homeostasis and liver metabolism in mice.

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