scholarly journals Bayesian Metamodeling of pancreatic islet architecture and functional dynamics

2021 ◽  
Author(s):  
Roee Lieberman ◽  
Reshef Mintz ◽  
Barak Raveh
Keyword(s):  
Pancreatic Islet ◽  
Graphical Models ◽  
Monte Carlo Model ◽  
Feedforward Neural Networks ◽  
Physical World ◽  
Testable Hypothesis ◽  
Imaging Data ◽  
Theoretical Approaches ◽  
Functional Dynamics ◽  
And Function

The pancreatic islet (islet of Langerhans) is a mini-organ comprising several thousand endocrine cells, functioning jointly to maintain normoglycemia. Cellular networks within an islet were shown to influence its function in health and disease, but there are major gaps in our quantitative understanding of such architecture-function relations. Comprehensive modeling of an islet architecture and function requires the integration of vast amounts of information obtained through different experimental and theoretical approaches. To address this challenge, our lab has recently developed Bayesian metamodeling, a general approach for modeling complex systems by integrating heterogeneous input models. Here, we further developed metamodeling and applied it to construct a metamodel of a pancreatic islet. The metamodel relates islet architecture and function by combining a Monte-Carlo model of architecture trained on islet imaging data; and an ordinary differential equations (ODEs) mathematical model of function trained on calcium imaging, hormone imaging, and electrophysiological data. These input models are converted to a standardized statistical representation relying on Probabilistic Graphical Models; coupled by modeling their mutual relations with the physical world; and finally, harmonized through backpropagation. We validate the metamodel using existing data and use it to derive a testable hypothesis regarding the functional effect of varying intercellular connections. Since metamodeling currently requires substantial expert intervention, we also develop an automation tool for converting models to PGMs (step I) using feedforward neural networks. This automation is a first step towards automating the entire metamodeling process, working towards collaborative science through sharing of expertise, resources, data, and models.

The functional vascular anatomy of the swine for research

Vascular ◽  
2021 ◽  
pp. 170853812199650
Author(s):  
Joseph Edwards ◽  
Hossam Abdou ◽  
Neerav Patel ◽  
Marta J Madurska ◽  
Kelly Poe ◽  
...  
Keyword(s):  
Translational Research ◽  
Functional Anatomy ◽  
Three Dimensional ◽  
Vascular Anatomy ◽  
Review Article ◽  
Imaging Data ◽  
Preclinical Research ◽  
Iodinated Contrast ◽  
Translational Research Program ◽  
And Function

Objectives Swine ( Sus Scrofa) are utilized broadly in research settings, given similarities to human vessel size and function; however, there are some important differences for clinicians to understand in order to interpret and perform translational research. This review article uses angiograms acquired in the course of a translational research program to present a description of the functional anatomy of the swine. Methods Digital subtraction angiography and computed tomography angiography were obtained throughout the course of multiple studies utilizing power injection with iodinated contrast. Subtracted two-dimensional images and three-dimensional multiplanar reformations were utilized post image acquisition to create maximal intensity projections and three-dimensional renderings of using open-source software (OsiriX). These imaging data are presented along with vessel measurements for reference. Results An atlas highlighting swine vascular anatomy, with an emphasis on inter-species differences that may influence how studies are conducted and interpreted, was compiled. Conclusions Swine are utilized in broad-reaching fields for preclinical research. While many similarities between human and swine vasculature exist, there are important differences to consider when conducting and interpreting research. This review article highlights these differences and presents accompanying images to inform clinicians gaining experience in swine research.

REVASCULARIZATION AND FUNCTION OF PANCREATIC ISLET ISOGRAFTS IN DIABETIC RATS FOLLOWING TRANSPLANTATION.

2004 ◽  
Vol 78 ◽  
pp. 622-623
Author(s):  
H Furuya ◽  
T Kimura ◽  
M Morikawa ◽  
M Murakami ◽  
K Katayama ◽  
...  
Keyword(s):  
Pancreatic Islet ◽  
Diabetic Rats ◽  
And Function

scholarly journals Islet Biology and Metabolism

Metabolites ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. 786
Author(s):  
Belinda Yau ◽  
Melkam A. Kebede
Keyword(s):  
Pancreatic Islet ◽  
Special Issue ◽  
Form And Function ◽  
Metabolic Physiology ◽  
And Function

This Special Issue, Islet Biology and Metabolism, was intended as a collection of studies highlighting the importance of the pancreatic islet—in both form and function—to our growing understanding of metabolic physiology and disease [...]

scholarly journals Disentangling microbial associations from hidden environmental and technical factors via latent graphical models

2019 ◽  
Author(s):  
Zachary D. Kurtz ◽  
Richard Bonneau ◽  
Christian L. Müller
Keyword(s):  
Graphical Models ◽  
Graphical Model ◽  
R Package ◽  
Comprehensive Collection ◽  
Performance Guarantees ◽  
Ecological Association ◽  
Microbial Associations ◽  
Sparse Inverse Covariance Estimation ◽  
Statistical Relationships ◽  
And Function

AbstractDetecting community-wide statistical relationships from targeted amplicon-based and metagenomic profiling of microbes in their natural environment is an important step toward understanding the organization and function of these communities. We present a robust and computationally tractable latent graphical model inference scheme that allows simultaneous identification of parsimonious statistical relationships among microbial species and unobserved factors that influence the prevalence and variability of the abundance measurements. Our method comes with theoretical performance guarantees and is available within the SParse InversE Covariance estimation for Ecological ASsociation Inference (SPIEC-EASI) framework (‘SpiecEasi’ R-package). Using simulations, as well as a comprehensive collection of amplicon-based gut microbiome datasets, we illustrate the method’s ability to jointly identify compositional biases, latent factors that correlate with observed technical covariates, and robust statistical microbial associations that replicate across different gut microbial data sets.

scholarly journals Toll-like receptor 9 negatively regulates pancreatic islet beta cell growth and function in a mouse model of type 1 diabetes

Diabetologia ◽  
2018 ◽  
Vol 61 (11) ◽  
pp. 2333-2343 ◽  
Author(s):  
Mengju Liu ◽  
Jian Peng ◽  
Ningwen Tai ◽  
James A. Pearson ◽  
Changyun Hu ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Cell Growth ◽  
Mouse Model ◽  
Beta Cell ◽  
Pancreatic Islet ◽  
Toll Like Receptor ◽  
Beta Cell Growth ◽  
And Function ◽  
Pancreatic Islet Beta Cell

Preservation of morphology and function of guinea pig pancreatic islet cells in subculture

1983 ◽  
Vol 95 (3) ◽  
pp. 354-356
Author(s):  
M. E. Basmadzhyan ◽  
V. I. Gevorkyan ◽  
N. F. Gusakova ◽  
I. I. Martirosyan ◽  
G. A. Kazaryan ◽  
...  
Keyword(s):  
Guinea Pig ◽  
Pancreatic Islet ◽  
Islet Cells ◽  
Pancreatic Islet Cells ◽  
And Function

Systematics of Masses and Half-Lives of Nuclei with Neural Nets

2019 ◽  
Vol 7 ◽  
pp. 231
Author(s):  
E. Mavrommatis ◽  
S. Athanassopoulos ◽  
A. Dakos ◽  
K. A. Gernoth ◽  
J. W. Clark
Keyword(s):  
Back Propagation ◽  
Computer Experiments ◽  
Feedforward Neural Networks ◽  
Predictive Performance ◽  
Nuclear Data ◽  
Phenomenological Approach ◽  
Neural Nets ◽  
Coding Schemes ◽  
Theoretical Approaches ◽  
Test Sets

Ih the last few years a phenomenological approach to nuclear systematics based on multilayer feedforward neural networks has been under development[1,2,3]. Using suitable training sets,back- propagation and other related algorithms[4,5] are applied to teach such networks a given nuclear property. The networks are then asked to predict the property using test nuclei absent from the training set. Training and test sets are provided by the Brookhaven Nuclear Data facility. With proper architecture, coding schemes for input and output data,activation and error functions as well as pruning techniques,a number of networks can be produced that demonstrate high quality of performance in learning. Their predictive power can be competitive with that of traditional theoretical approaches. In this work,we study the nuclear masses and the half-lives of unstable β-decaying nuclear ground states using the following number of nuclides: 1882 and 1260 as learning sets and 627 and 423 as test sets respectively. Concerning masses, our work is a continuation of the work reported in refs [1,2]. It uses an enriched data basis and tries to achieve the highest possible performance with the smallest number of parameters. So far, our results for the root mean square error are comparable to those of ref. [2] and those derived by the mass fits of Mässon- Jänecket6! and Möller et al[7]. However, the number of the parameters used in the later fit is significantly smaller. Concerning half-lives,up to now there is no global model based on conventional nuclear theory. There are some models mainly for beta-decay. At present, most of our computer experiments have focused on the study of this decay channel.Our initial learning and test sets include 575 and 191 nuclei respectively. The performance of the models developed in learning is comparable to that of Klapdor et al[8]. The next step is to improve the predictive performance and to study and include the nuclides with other decay channels. The aim of this work is the production of global models of masses and half-lives of very good quality

Revascularization and Function of Pancreatic Islet Isografts in Diabetic Rats following Transplantation

2003 ◽  
Vol 12 (5) ◽  
pp. 537-544 ◽  
Author(s):  
Hajime Furuya ◽  
Toshihisa Kimura ◽  
Makoto Murakami ◽  
Kanji Katayama ◽  
Kazuo Hirose ◽  
...  
Keyword(s):  
Pancreatic Islet ◽  
Diabetic Rats ◽  
Isolated Islets ◽  
Diabetic Rat ◽  
Pancreatic Islet Transplantation ◽  
Intravenous Glucose ◽  
Lewis Rats ◽  
Group A ◽  
Group B ◽  
And Function

In pancreatic islet transplantation, revascularization is crucial for the graft's survival and function. In this study, the endothelium of isolated islets and revascularization and function of islet isografts in diabetic rat were investigated. Islets were isolated from Lewis rats by collagenase digestion method and were examined using immunohistochemistry (CD31 stain) on days 0, 1, 3, and 7 after isolation. The number of CD31-positive cells in these isolated islets was counted (mean ± SD%). Isografts (freshly isolated islets: group A, and islets cultured for 7 days: group B) transplanted in the renal subcapsule of streptozotocin-induced diabetic Lewis rats were examined using immunohistochemistry (CD31 stain) on days 3, 5, and 7 after transplantation. Intravenous glucose tolerance tests (IVGTT) were performed on days 3 and 7 after transplantation. The number of CD31-positive cells in the isolated islets on days 0, 1, 3, and 7 after isolation were: 17.3 ± 4.1%, 8.2 ± 0.7%, 2.1 ± 0.8%, and 0.8 ± 0.5%, respectively (p < 0.05). On day 5 after transplantation, CD31-positive cells were not detected in group A and B grafts, but were detected in both groups in periphery of the islets. On day 7, CD31-positive microvessels were present throughout the entire graft. IVGTT values in groups A and B on days 3 and 7 after transplantation did not show significant differences. In renal subcapsular isografts in diabetic rats, revascularization into islet grafts occurs from the surrounding host tissue 5 days after transplantation, but has no influence on the response to glucose during this period.

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