Quantitative analysis of cell composition and purity of human pancreatic islet preparations

Author Manuscript 2011 May 1.Despite improvements in outcomes for human islet transplantation, characterization of islet preparations remains poorly defined. This study used both light microscopy (LM) and electron microscopy (EM) to characterize 33 islet preparations used for clinical transplants. EM allowed an accurate identification and quantification of cell types with measured cell number fractions (mean±s.e.m.) of 35.6±2.1% β-cells, 12.6±1.0% non-β-islet cells (48.3±2.6% total islet cells), 22.7±1.5% duct cells, and 25.3±1.8% acinar cells. Of the islet cells, 73.6±1.7% were β-cells. For comparison with the literature, estimates of cell number fraction, cell volume, and extracellular volume were combined to convert number fraction data to volume fractions applicable to cells, islets, and the entire preparation. The mathematical framework for this conversion was developed. By volume, β-cells were 86.5±1.1% of the total islet cell volume and 61.2±0.8% of intact islets (including the extracellular volume), which is similar to that of islets in the pancreas. Our estimates produced 1560±20 cells in an islet equivalent (volume of 150-μm diameter sphere), of which 1140±15 were β-cells. To test whether LM analysis of the same tissue samples could provide reasonable estimates of purity of the islet preparations, volume fraction of the islet tissue was measured on thin sections available from 27 of the clinical preparations by point counting morphometrics. Islet purity (islet volume fraction) of individual preparations determined by LM and EM analyses correlated linearly with excellent agreement (R[superscript 2]=0.95). However, islet purity by conventional dithizone staining was substantially higher with a 20–30% overestimation. Thus, both EM and LM provide accurate methods to determine the cell composition of human islet preparations and can help us understand many of the discrepancies of islet composition in the literature.National Institutes of Health (U.S.) (Grant RO1-DK063108)National Institutes of Health (U.S.) (Grant NCRR ICR U4Z RR 16606)Joslin Diabetes and Endocrinology Research Center (Grant DK36836)Diabetes Research & Wellness FoundationJuvenile Diabetes Research Foundation International (Islet Transplantation, Harvard Medical School

Detection of motor changes in huntington's disease using dynamic causal modeling

Deficits in motor functioning are one of the hallmarks of Huntington's disease (HD), a genetically caused neurodegenerative disorder. We applied functional magnetic resonance imaging (fMRI) and dynamic causal modeling (DCM) to assess changes that occur with disease progression in the neural circuitry of key areas associated with executive and cognitive aspects of motor control. Seventy-seven healthy controls, 62 pre-symptomatic HD gene carriers (preHD), and 16 patients with manifest HD symptoms (earlyHD) performed a motor finger-tapping fMRI task with systematically varying speed and complexity. DCM was used to assess the causal interactions among seven pre-defined regions of interest, comprising primary motor cortex, supplementary motor area (SMA), dorsal premotor cortex, and superior parietal cortex. To capture heterogeneity among HD gene carriers, DCM parameters were entered into a hierarchical cluster analysis using Ward's method and squared Euclidian distance as a measure of similarity. After applying Bonferroni correction for the number of tests, DCM analysis revealed a group difference that was not present in the conventional fMRI analysis. We found an inhibitory effect of complexity on the connection from parietal to premotor areas in preHD, which became excitatory in earlyHD and correlated with putamen atrophy. While speed of finger movements did not modulate the connection from caudal to pre-SMA in controls and preHD, this connection became strongly negative in earlyHD. This second effect did not survive correction for multiple comparisons. Hierarchical clustering separated the gene mutation carriers into three clusters that also differed significantly between these two connections and thereby confirmed their relevance. DCM proved useful in identifying group differences that would have remained undetected by standard analyses and may aid in the investigation of between-subject heterogeneity

Human subcortical brain asymmetries in 15,847 people worldwide reveal effects of age and sex

The two hemispheres of the human brain differ functionally and structurally. Despite over a century of research, the extent to which brain asymmetry is influenced by sex, handedness, age, and genetic factors is still controversial. Here we present the largest ever analysis of subcortical brain asymmetries, in a harmonized multi-site study using meta-analysis methods. Volumetric asymmetry of seven subcortical structures was assessed in 15,847 MRI scans from 52 datasets worldwide. There were sex differences in the asymmetry of the globus pallidus and putamen. Heritability estimates, derived from 1170 subjects belonging to 71 extended pedigrees, revealed that additive genetic factors influenced the asymmetry of these two structures and that of the hippocampus and thalamus. Handedness had no detectable effect on subcortical asymmetries, even in this unprecedented sample size, but the asymmetry of the putamen varied with age. Genetic drivers of asymmetry in the hippocampus, thalamus and basal ganglia may affect variability in human cognition, including susceptibility to psychiatric disorders

A comparison of oligonucleotide and cDNA-based microarray systems

Large-scale public data mining will become more common as public release of microarray data sets becomes a corequisite for publication. Therefore, there is an urgent need to clarify whether data from different microarray platforms are comparable. To assess the compatibility of microarray data, results were compared from the two main types of high-throughput microarray expression technologies, namely, an oligonucleotide-based and a cDNA-based platform, using RNA obtained from complex tissue (human colonic mucosa) of five individuals. From 715 sequence-verified genes represented on both platforms, 64% of the genes matched in "present" or "absent" calls made by both platforms. Calls were influenced by spurious signals caused by Alu repeats in cDNA clones, clone annotation errors, or matched probes that were designed to different regions of the gene; however, these factors could not completely account for the level of call discordance observed. Expression levels in sequence-verified, platform-overlapping genes were not related, as demonstrated by weakly positive rank order correlation. This study demonstrates that there is only moderate overlap in the results from the two array systems. This fact should be carefully considered when performing large-scale analyses on data originating from different microarray platforms

Multi-platform, multi-frequency SAR campaign with the F-SAR and Miranda35 Sensors

Multi-platform campaigns open up new opportunities and allow a comparison and analysis of SAR signatures of the same area at different frequency bands and incident angles. In this paper, we make use of two different sensor systems: DLR’s pulsed F-SAR operating at X-, C- and L-band, and FHR’s frequency-modulated continuous-wave (FMCW) MIRANDA35 operating at Ka-band. Main goals of the campaign include the comparison of high-resolution polarimetric signatures at different frequency bands, change detection, synchronized acquisition of ground moving targets and air-moving target indication (AMTI) experiments. We present the planning and implementation of the campaign and first results of the data processing