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Articles by Vipul Periwal in JoVE

 JoVE General

بمساعدة الحاسوب على نطاق واسع التصور النوعي والكمي لقداس جزيرة البنكرياس والتوزيع الحجم والعمارة


JoVE 2471 3/04/2011

1Department of Medicine, University of Chicago, 2Laboratory of Biological Modeling, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, 3Department of Surgery, University of Chicago, 4Diabetes Division, University of Massachusetts

يتم وصف أساليب بمساعدة الحاسوب الرواية على نطاق واسع الشراء وتحليل العينات immunohistochemically البنكرياس الملون : (1) القبض على شريحة افتراضية للقسم كامل ، (2) التحليل الشامل للبيانات واسعة النطاق ، (3) إعادة بناء شرائح الظاهري 2D ، (4) رسم الخرائط 3D جزيرة ، و (5) التحليل الرياضي.

Other articles by Vipul Periwal on PubMed

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Patterns in Food Intake Correlate with Body Mass Index

Quantifying eating behavior may give clues to both the physiological and behavioral mechanisms behind weight regulation. We analyzed year-long dietary records of 29 stable-weight subjects. The records showed wide daily variations of food intake. We computed the temporal autocorrelation and skewness of food intake mass, energy, carbohydrate, fat, and protein. We also computed the cross-correlation coefficient between intake mass and intake energy. The mass of the food intake exhibited long-term trends that were positively skewed, with wide variability among individuals. The average duration of the trends (P = 0.003) and the skewness (P = 0.006) of the food intake mass were significantly correlated with mean body mass index (BMI). We also found that the lower the correlation coefficient between the energy content and the mass of food intake, the higher the BMI. Our results imply that humans in neutral energy balance eating ad libitum exhibit a long-term positive bias in the food intake that operates partially through the mass of food eaten to defend against eating too little more vigorously than eating too much.

Evaluation of Quantitative Models of the Effect of Insulin on Lipolysis and Glucose Disposal

The effects of insulin on the suppression of lipolysis are neither fully understood nor quantified. We examined a variety of mathematical models analogous to the minimal model of glucose disposal (MMG) to quantify the combined influence of insulin on lipolysis and glucose disposal during an insulin-modified frequently sampled intravenous glucose tolerance test. The tested models, which include two previously published ones, consisted of separate compartments for plasma free fatty acids (FFA), glucose, and insulin. They differed in the number of compartments and in the action of insulin to suppress lipolysis that decreased the plasma FFA level. In one category of models, a single insulin compartment acted on both glucose and FFA simultaneously. In a second category, there were two insulin compartments, each acting on FFA and glucose independently. For each of these two categories, we tested 11 variations of how insulin suppressed lipolysis. We also tested a model with an additional glucose compartment that acted on FFA. These 23 models were fit to the plasma FFA and glucose concentrations of 102 subjects individually. Using Bayesian model comparison methods, we selected the model that best balanced fit and minimized model complexity. In the best model, insulin suppressed lipolysis via a Hill function through a remote compartment that acted on both glucose and FFA simultaneously, and glucose dynamics obeyed the classic MMG.

Hypertrophy And/or Hyperplasia: Dynamics of Adipose Tissue Growth

Adipose tissue grows by two mechanisms: hyperplasia (cell number increase) and hypertrophy (cell size increase). Genetics and diet affect the relative contributions of these two mechanisms to the growth of adipose tissue in obesity. In this study, the size distributions of epididymal adipose cells from two mouse strains, obesity-resistant FVB/N and obesity-prone C57BL/6, were measured after 2, 4, and 12 weeks under regular and high-fat feeding conditions. The total cell number in the epididymal fat pad was estimated from the fat pad mass and the normalized cell-size distribution. The cell number and volume-weighted mean cell size increase as a function of fat pad mass. To address adipose tissue growth precisely, we developed a mathematical model describing the evolution of the adipose cell-size distributions as a function of the increasing fat pad mass, instead of the increasing chronological time. Our model describes the recruitment of new adipose cells and their subsequent development in different strains, and with different diet regimens, with common mechanisms, but with diet- and genetics-dependent model parameters. Compared to the FVB/N strain, the C57BL/6 strain has greater recruitment of small adipose cells. Hyperplasia is enhanced by high-fat diet in a strain-dependent way, suggesting a synergistic interaction between genetics and diet. Moreover, high-fat feeding increases the rate of adipose cell size growth, independent of strain, reflecting the increase in calories requiring storage. Additionally, high-fat diet leads to a dramatic spreading of the size distribution of adipose cells in both strains; this implies an increase in size fluctuations of adipose cells through lipid turnover.

A Model of Liver Regeneration

The network of interactions underlying liver regeneration is robust and precise with liver resections resulting in controlled hyperplasia (cell proliferation) that terminates when the liver regains its lost mass. The interplay of cytokines and growth factors responsible for the inception and termination of this hyperplasia is not well understood. A model is developed for this network of interactions based on the known data of liver resections. This model reproduces the relevant published data on liver regeneration and provides geometric insights into the experimental observations. The predictions of this model are used to suggest two novel strategies for speeding up liver mass recovery and a strategy for enabling liver mass recovery in cases where a resection leaves <20% of the liver that would otherwise result in complete loss of liver mass.

Islet Formation During the Neonatal Development in Mice

The islet of Langerhans is a unique micro-organ within the exocrine pancreas, which is composed of insulin-secreting beta-cells, glucagon-secreting alpha-cells, somatostatin-secreting delta-cells, pancreatic polypeptide-secreting PP cells and ghrelin-secreting epsilon-cells. Islets also contain non-endocrine cell types such as endothelial cells. However, the mechanism(s) of islet formation is poorly understood due to technical difficulties in capturing this dynamic event in situ. We have developed a method to monitor beta-cell proliferation and islet formation in the intact pancreas using transgenic mice in which the beta-cells are specifically tagged with a fluorescent protein. Endocrine cells proliferate contiguously, forming branched cord-like structures in both embryos and neonates. Our study has revealed long stretches of interconnected islets located along large blood vessels in the neonatal pancreas. Alpha-cells span the elongated islet-like structures, which we hypothesize represent sites of fission and facilitate the eventual formation of discrete islets. We propose that islet formation occurs by a process of fission following contiguous endocrine cell proliferation, rather than by local aggregation or fusion of isolated beta-cells and islets. Mathematical modeling of the fission process in the neonatal islet formation is also presented.

Differential Effects of Thiazolidinediones on Adipocyte Growth and Recruitment in Zucker Fatty Rats

Adipose tissue grows by two mechanisms: hyperplasia (cell number increase) and hypertrophy (cell size increase). Thiazolidinediones are insulin-sensitizing peroxisome proliferator-activated receptor gamma agonists that are known to affect the morphology of adipose tissue.

Cdk4 Regulates Recruitment of Quiescent Beta-cells and Ductal Epithelial Progenitors to Reconstitute Beta-cell Mass

Insulin-producing pancreatic islet beta cells (beta-cells) are destroyed, severely depleted or functionally impaired in diabetes. Therefore, replacing functional beta-cell mass would advance clinical diabetes management. We have previously demonstrated the importance of Cdk4 in regulating beta-cell mass. Cdk4-deficient mice display beta-cell hypoplasia and develop diabetes, whereas beta-cell hyperplasia is observed in mice expressing an active Cdk4R24C kinase. While beta-cell replication appears to be the primary mechanism responsible for beta-cell mass increase, considerable evidence also supports a contribution from the pancreatic ductal epithelium in generation of new beta-cells. Further, while it is believed that majority of beta-cells are in a state of 'dormancy', it is unclear if and to what extent the quiescent cells can be coaxed to participate in the beta-cell regenerative response. Here, we address these queries using a model of partial pancreatectomy (PX) in Cdk4 mutant mice. To investigate the kinetics of the regeneration process precisely, we performed DNA analog-based lineage-tracing studies followed by mathematical modeling. Within a week after PX, we observed considerable proliferation of islet beta-cells and ductal epithelial cells. Interestingly, the mathematical model showed that recruitment of quiescent cells into the active cell cycle promotes beta-cell mass reconstitution in the Cdk4R24C pancreas. Moreover, within 24-48 hours post-PX, ductal epithelial cells expressing the transcription factor Pdx-1 dramatically increased. We also detected insulin-positive cells in the ductal epithelium along with a significant increase of islet-like cell clusters in the Cdk4R24C pancreas. We conclude that Cdk4 not only promotes beta-cell replication, but also facilitates the activation of beta-cell progenitors in the ductal epithelium. In addition, we show that Cdk4 controls beta-cell mass by recruiting quiescent cells to enter the cell cycle. Comparing the contribution of cell proliferation and islet-like clusters to the total increase in insulin-positive cells suggests a hitherto uncharacterized large non-proliferative contribution.

Waves of Adipose Tissue Growth in the Genetically Obese Zucker Fatty Rat

In mammals, calories ingested in excess of those used are stored primarily as fat in adipose tissue; consistent ingestion of excess calories requires an enlargement of the adipose tissue mass. Thus, a dysfunction in adipose tissue growth may be a key factor in insulin resistance due to imbalanced fat storage and disrupted insulin action. Adipose tissue growth requires the recruitment and then the development of adipose precursor cells, but little is known about these processes in vivo.

Expression in Aneuploid Drosophila S2 Cells

Extensive departures from balanced gene dose in aneuploids are highly deleterious. However, we know very little about the relationship between gene copy number and expression in aneuploid cells. We determined copy number and transcript abundance (expression) genome-wide in Drosophila S2 cells by DNA-Seq and RNA-Seq. We found that S2 cells are aneuploid for >43 Mb of the genome, primarily in the range of one to five copies, and show a male genotype ( approximately two X chromosomes and four sets of autosomes, or 2X;4A). Both X chromosomes and autosomes showed expression dosage compensation. X chromosome expression was elevated in a fixed-fold manner regardless of actual gene dose. In engineering terms, the system "anticipates" the perturbation caused by X dose, rather than responding to an error caused by the perturbation. This feed-forward regulation resulted in precise dosage compensation only when X dose was half of the autosome dose. Insufficient compensation occurred at lower X chromosome dose and excessive expression occurred at higher doses. RNAi knockdown of the Male Specific Lethal complex abolished feed-forward regulation. Both autosome and X chromosome genes show Male Specific Lethal-independent compensation that fits a first order dose-response curve. Our data indicate that expression dosage compensation dampens the effect of altered DNA copy number genome-wide. For the X chromosome, compensation includes fixed and dose-dependent components.

Autoregulation of Free Radicals Via Uncoupling Protein Control in Pancreatic Beta-cell Mitochondria

Pancreatic beta-cells sense the ambient blood-glucose concentration and secrete insulin to signal other tissues to take up glucose. Mitochondria play a key role in this response as they metabolize nutrients to produce ATP and reactive oxygen species (ROS), both of which are involved in insulin secretion signaling. Based on data available in the literature and previously developed mathematical models, we present a model of glucose-stimulated mitochondrial respiration, ATP synthesis, and ROS production and control in beta-cells. The model is consistent with a number of experimental observations reported in the literature. Most notably, it captures the nonlinear rise in the proton leak rate at high membrane potential and the increase in this leak due to uncoupling protein (UCP) activation by ROS. The functional forms used to model ROS production and UCP regulation yield insight into these mechanisms, as many details have not yet been unraveled in the experimental literature. We examine short- and long-term effects of UCP activation inhibition and changes in the mitochondrial density on mitochondrial responses to glucose. Results suggest increasing mitochondrial density while decreasing UCP activity may be an effective way to increase glucose-stimulated insulin secretion while decreasing oxidative stress.

Hypertrophy-driven Adipocyte Death Overwhelms Recruitment Under Prolonged Weight Gain

Fat pads dynamically regulate energy storage capacity under energy excess and deficit. This remodeling process is not completely understood, with controversies regarding differences between fat depots and plasticity of adipose cell number. We examined changes of mouse adipose cell-size distributions in epididymal, inguinal, retroperitoneal, and mesenteric fat under both weight gain and loss. With mathematical modeling, we specifically analyzed the recruitment, growth/shrinkage, and loss of adipose cells, including the size dependence of these processes. We found a qualitatively universal adipose tissue remodeling process in all four fat depots: 1), There is continuous recruitment of new cells under weight gain; 2), the growth and shrinkage of larger cells (diameter >50 μm) is proportional to cell surface area; and 3), cell loss occurs under prolonged weight gain, with larger cells more susceptible. The mathematical model gives a predictive integrative picture of adipose tissue remodeling in obesity.

Higher Acute Insulin Response to Glucose May Determine Greater Free Fatty Acid Clearance in African-American Women

Obesity and diabetes are more common in African-Americans than whites. Because free fatty acids (FFA) participate in the development of these conditions, studying race differences in the regulation of FFA and glucose by insulin is essential.

Formation of Pancreatic Islets Involves Coordinated Expansion of Small Islets and Fission of Large Interconnected Islet-like Structures

The islets of Langerhans, micro-organs for maintaining glucose homeostasis, range in size from small clusters of <10 cells to large islets consisting of several thousand endocrine cells. Islet size distributions among various species are similar and independent of body size, suggesting an intrinsic limit to islet size. Little is known about the mechanisms regulating islet size. We have carried out a comprehensive analysis of changes of islet size distribution in the intact mouse pancreas from birth to eight months, including mathematical modeling to quantify this dynamic biological process. Islet growth was size-dependent during development, with preferential expansion of smaller islets and fission of large interconnected islet-like structures occurring most actively at approximately three weeks of age at the time of weaning. The process of islet formation was complete by four weeks with little or no new islet formation thereafter, and all the β-cells had low proliferation potential in the adult, regardless of islet size. Similarly, in insulinoma-bearing mice, the early postnatal developmental process including fission followed the same time course with no new islet formation in adults. However, tumor progression led to uncontrolled islet growth with accelerated expansion of larger islets. Thus, islet formation and growth is a tightly regulated process involving preferential expansion of small islets and fission of large interconnected islet-like structures.

Altered Islet Composition and Disproportionate Loss of Large Islets in Patients with Type 2 Diabetes

Human islets exhibit distinct islet architecture with intermingled alpha- and beta-cells particularly in large islets. In this study, we quantitatively examined pathological changes of the pancreas in patients with type 2 diabetes (T2D). Specifically, we tested a hypothesis that changes in endocrine cell mass and composition are islet-size dependent. A large-scale analysis of cadaveric pancreatic sections from T2D patients (n = 12) and non-diabetic subjects (n = 14) was carried out combined with semi-automated analysis to quantify changes in islet architecture. The method provided the representative islet distribution in the whole pancreas section that allowed us to examine details of endocrine cell composition in individual islets. We observed a preferential loss of large islets (>60 µm in diameter) in T2D patients compared to non-diabetic subjects. Analysis of islet cell composition revealed that the beta-cell fraction in large islets was decreased in T2D patients. This change was accompanied by a reciprocal increase in alpha-cell fraction, however total alpha-cell area was decreased along with beta-cells in T2D. Delta-cell fraction and area remained unchanged. The computer-assisted quantification of morphological changes in islet structure minimizes sampling bias. Significant beta-cell loss was observed in large islets in T2D, in which alpha-cell ratio reciprocally increased. However, there was no alpha-cell expansion and the total alpha-cell area was also decreased. Changes in islet architecture were marked in large islets. Our method is widely applicable to various specimens using standard immunohistochemical analysis that may be particularly useful to study large animals including humans where large organ size precludes manual quantitation of organ morphology.

Bayesian Functional Integral Method for Inferring Continuous Data from Discrete Measurements

Inference of the insulin secretion rate (ISR) from C-peptide measurements as a quantification of pancreatic β-cell function is clinically important in diseases related to reduced insulin sensitivity and insulin action. ISR derived from C-peptide concentration is an example of nonparametric Bayesian model selection where a proposed ISR time-course is considered to be a "model". An inferred value of inaccessible continuous variables from discrete observable data is often problematic in biology and medicine, because it is a priori unclear how robust the inference is to the deletion of data points, and a closely related question, how much smoothness or continuity the data actually support. Predictions weighted by the posterior distribution can be cast as functional integrals as used in statistical field theory. Functional integrals are generally difficult to evaluate, especially for nonanalytic constraints such as positivity of the estimated parameters. We propose a computationally tractable method that uses the exact solution of an associated likelihood function as a prior probability distribution for a Markov-chain Monte Carlo evaluation of the posterior for the full model. As a concrete application of our method, we calculate the ISR from actual clinical C-peptide measurements in human subjects with varying degrees of insulin sensitivity. Our method demonstrates the feasibility of functional integral Bayesian model selection as a practical method for such data-driven inference, allowing the data to determine the smoothing timescale and the width of the prior probability distribution on the space of models. In particular, our model comparison method determines the discrete time-step for interpolation of the unobservable continuous variable that is supported by the data. Attempts to go to finer discrete time-steps lead to less likely models.

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