Mats Rudemo

Separation of human adipocytes by size: hypertrophic fat cells display distinct gene expression

Enlarged adipocytes are associated with insulin resistance and are an independent predictor of type 2 diabetes. To understand the molecular link between these diseases and adipocyte hypertrophy, we developed a technique to separate human adipocytes from an adipose tissue sample into populations of small cells (mean 57.6±3.54 pm) and large cells (mean 100.1±3.94 pm). Microarray analysis of the cell populations separated from adipose tissue from three subjects identified 14 genes, of which five immune‐related, with more than fourfold higher expression in large cells than small cells. Two of these genes were serum amyloid A (SAA) and transmembrane 4 L six family member 1 (TM4SF1). Real‐time RT‐PCR analysis of SAA and TM4SF1 expression in adipocytes from seven subjects revealed 19‐fold and 22‐fold higher expression in the large cells, respectively, and a correlation between adipocyte size and both SAA and TM4SF1 expression. The results were verified using immunohistochemistry. In comparison with 17 other human tissues and cell types by microarray, large adipocytes displayed by far the highest SAA and TM4SF1 expression. Thus, we have identified genes with markedly higher expression in large, compared with small, human adipocytes. These genes may link hypertrophic obesity to insulin resistance/type 2 diabetes.—Jernås, M., Palming, J., Sjöholm, K., Jennische, E., Svensson, P.‐A., Gabrielsson, B. G., Levin, M., Sjögren, A., Rudemo, M., Lystig, T. C., Carlsson, B., Carlsson, L. M. S., Lönn, M. Separation of human adipocytes by size: hypertrophic fat cells display distinct gene expression. FASEB J. 20, E832–E839 (2006)

Increased expression of aquaporin 3 in atopic eczema.

Background:  Dry skin in atopic eczema depends on increased water loss. The mechanisms behind this are poorly understood. The aim of this work was to identify genes that may contribute to water loss in eczema.

Optimizing templates for finding trees in aerial photographs

Abstract Positions of individual trees in high-resolution aerial photographs are estimated by use of templates derived from an optical tree crown model and the geometry at image acquisition. The template is bounded by an ellipse, for which we find the optimal size, eccentricity and translation along one axis. Tree top positions are estimated as local maxima of the correlation function for the successively transposed template over the whole image. Performance is evaluated using three images from a thinning experiment in spruce. The templates are compared with empirical shapes obtained by averaging over the individual trees in the image.

Identification of Adipocyte Genes Regulated by Caloric Intake

CONTEXT Changes in energy intake have marked and rapid effects on metabolic functions, and some of these effects may be due to changes in adipocyte gene expression that precede alterations in body weight. OBJECTIVE The aim of the study was to identify adipocyte genes regulated by changes in caloric intake independent of alterations in body weight. RESEARCH DESIGN AND METHODS Obese subjects given a very low-caloric diet followed by gradual reintroduction of ordinary food and healthy subjects subjected to overfeeding were investigated. Adipose tissue biopsies were taken at multiple time-points, and gene expression was measured by DNA microarray. Genes regulated in the obese subjects undergoing caloric restriction followed by refeeding were identified using two-way ANOVA corrected with Bonferroni. From these, genes regulated by caloric restriction and oppositely during the weight-stable refeeding phase were identified in the obese subjects. The genes that were also regulated, in the same direction as the refeeding phase, in the healthy subjects after overfeeding were defined as being regulated by caloric intake. Results were confirmed using real-time PCR or immunoassay. RESULTS Using a significance level of P < 0.05 for all comparisons, 52 genes were down-regulated, and 50 were up-regulated by caloric restriction and regulated in the opposite direction by refeeding and overfeeding. Among these were genes involved in lipogenesis (ACLY, ACACA, FASN, SCD), control of protein synthesis (4EBP1, 4EBP2), β-oxidation (CPT1B), and insulin resistance (PEDF, SPARC). CONCLUSIONS Metabolic genes involved in lipogenesis, protein synthesis, and insulin resistance are central in the transcriptional response of adipocytes to changes in caloric intake.

Hemocompatibility of siRNA loaded dextran nanogels

Although the behavior of nanoscopic delivery systems in blood is an important parameter when contemplating their intravenous injection, this aspect is often poorly investigated when advancing from in vitro to in vivo experiments. In this paper, the behavior of siRNA loaded dextran nanogels in human plasma and blood is examined using fluorescence fluctuation spectroscopy, platelet aggregometry, flow cytometry and single particle tracking. Our results show that, in contrast to their negatively charged counterparts, positively charged siRNA loaded dextran nanogels cause platelet aggregation and show increased binding to human blood cells. Although PEGylating the nanogels did not have a significant effect on their interaction with blood cells, single particle tracking revealed that it is necessary to prevent their aggregation in human plasma. We therefore conclude that PEGylated negatively charged dextran nanogels are the most suited for further in vivo studies as they do not aggregate in human plasma and exhibit minimal interactions with blood cells.

Spot shape modelling and data transformations for microarrays

MOTIVATION To study lowly expressed genes in microarray experiments, it is useful to increase the photometric gain in the scanning. However, a large gain may cause some pixels for highly expressed genes to become saturated. Spatial statistical models that model spot shapes on the pixel level may be used to infer information about the saturated pixel intensities. Other possible applications for spot shape models include data quality control and accurate determination of spot centres and spot diameters. RESULTS Spatial statistical models for spotted microarrays are studied including pixel level transformations and spot shape models. The models are applied to a dataset from 50mer oligonucleotide microarrays with 452 selected Arabidopsis genes. Logarithmic, Box-Cox and inverse hyperbolic sine transformations are compared in combination with four spot shape models: a cylindric plateau shape, an isotropic Gaussian distribution and a difference of two-scaled Gaussian distribution suggested in the literature, as well as a proposed new polynomial-hyperbolic spot shape model. A substantial improvement is obtained for the dataset studied by the polynomial-hyperbolic spot shape model in combination with the Box-Cox transformation. The spatial statistical models are used to correct spot measurements with saturation by extrapolating the censored data. AVAILABILITY Source code for R is available at http://www.matfys.kvl.dk/~ekstrom/spotshapes/

The gamma distribution model for pulsed-field gradient NMR studies of molecular-weight distributions of polymers

Self-diffusion in polymer solutions studied with pulsed-field gradient nuclear magnetic resonance (PFG NMR) is typically based either on a single self-diffusion coefficient, or a log-normal distribution of self-diffusion coefficients, or in some cases mixtures of these. Experimental data on polyethylene glycol (PEG) solutions and simulations were used to compare a model based on a gamma distribution of self-diffusion coefficients to more established models such as the single exponential, the stretched exponential, and the log-normal distribution model with regard to performance and consistency. Even though the gamma distribution is very similar to the log-normal distribution, its NMR signal attenuation can be written in a closed form and therefore opens up for increased computational speed. Estimates of the mean self-diffusion coefficient, the spread, and the polydispersity index that were obtained using the gamma model were in excellent agreement with estimates obtained using the log-normal model. Furthermore, we demonstrate that the gamma distribution is by far superior to the log-normal, and comparable to the two other models, in terms of computational speed. This effect is particularly striking for multi-component signal attenuation. Additionally, the gamma distribution as well as the log-normal distribution incorporates explicitly a physically plausible model for polydispersity and spread, in contrast to the single exponential and the stretched exponential. Therefore, the gamma distribution model should be preferred in many experimental situations.

Fluorescence recovery after photobleaching in material and life sciences: Putting theory into practice

Fluorescence recovery after photobleaching (FRAP) is a versatile tool for determining diffusion and interaction/binding properties in biological and material sciences. An understanding of the mechanisms controlling the diffusion requires a deep understanding of structure-interaction-diffusion relationships. In cell biology, for instance, this applies to the movement of proteins and lipids in the plasma membrane, cytoplasm and nucleus. In industrial applications related to pharmaceutics, foods, textiles, hygiene products and cosmetics, the diffusion of solutes and solvent molecules contributes strongly to the properties and functionality of the final product. All these systems are heterogeneous, and accurate quantification of the mass transport processes at the local level is therefore essential to the understanding of the properties of soft (bio)materials. FRAP is a commonly used fluorescence microscopy-based technique to determine local molecular transport at the micrometer scale. A brief high-intensity laser pulse is locally applied to the sample, causing substantial photobleaching of the fluorescent molecules within the illuminated area. This causes a local concentration gradient of fluorescent molecules, leading to diffusional influx of intact fluorophores from the local surroundings into the bleached area. Quantitative information on the molecular transport can be extracted from the time evolution of the fluorescence recovery in the bleached area using a suitable model. A multitude of FRAP models has been developed over the years, each based on specific assumptions. This makes it challenging for the non-specialist to decide which model is best suited for a particular application. Furthermore, there are many subtleties in performing accurate FRAP experiments. For these reasons, this review aims to provide an extensive tutorial covering the essential theoretical and practical aspects so as to enable accurate quantitative FRAP experiments for molecular transport measurements in soft (bio)materials.

Straightforward FRAP for quantitative diffusion measurements with a laser scanning microscope

Confocal or multi-photon laser scanning microscopes are convenient tools to perform FRAP diffusion measurements. Despite its popularity, accurate FRAP remains often challenging since current methods are either limited to relatively large bleach regions or can be complicated for non-specialists. In order to bring reliable quantitative FRAP measurements to the broad community of laser scanning microscopy users, here we have revised FRAP theory and present a new pixel based FRAP method relying on the photo bleaching of rectangular regions of any size and aspect ratio. The method allows for fast and straightforward quantitative diffusion measurements due to a closed-form expression for the recovery process utilizing all available spatial and temporal data. After a detailed validation, its versatility is demonstrated by diffusion studies in heterogeneous biopolymer mixtures.

Changes in adipose tissue gene expression and plasma levels of adipokines and acute-phase proteins in patients with critical illness.

Insulin resistance develops rapidly during critical illness. The release of adipokines from adipose tissue is thought to play a key role in the development of insulin resistance, as are elevated levels of acute-phase proteins. The aim of this study was to identify changes in adipose tissue gene expression and plasma levels of adipokines and acute-phase proteins during critical illness. From 8 patients with subarachnoidal hemorrhage, consecutive blood samples and adipose tissue biopsies were obtained at 3 time points, twice during intensive care (1-2 days [IC1] and 7-9 days after subarachnoidal hemorrhage) and once after 8 months (recovery). The patients received a continuous insulin infusion to maintain normal glucose levels reflecting insulin resistance. The DNA microarray analysis showed increased zink-alpha2 glycoprotein (ZAG) and phospholipase A2, group IIA messenger RNA levels during intensive care compared with recovery (P < .05). Real-time polymerase chain reaction confirmed the increased expression of ZAG and phospholipase A2, group IIA. Plasma levels of ZAG, serum amyloid A, and C-reactive protein were higher at 7 to 9 days after subarachnoidal hemorrhage compared with either IC1 or recovery (P = .0001); and plasma levels of retinol-binding protein 4 and adiponectin were lower at IC1 compared with recovery (P = .05). The described changes in adipose tissue gene expression and plasma levels of adipokines and acute-phase proteins may influence the development of insulin resistance during critical illness.