A PC-based multispectral scanner data evaluation workstation: Application to Daedalus scanners

In late 1989, a personal computer (PC)-based data evaluation workstation was developed to support post flight processing of Multispectral Atmospheric Mapping Sensor (MAMS) data. The MAMS Quick View System (QVS) is an image analysis and display system designed to provide the capability to evaluate Daedalus scanner data immediately after an aircraft flight. Even in its original form, the QVS offered the portability of a personal computer with the advanced analysis and display features of a mainframe image analysis system. It was recognized, however, that the original QVS had its limitations, both in speed and processing of MAMS data. Recent efforts are presented that focus on overcoming earlier limitations and adapting the system to a new data tape structure. In doing so, the enhanced Quick View System (QVS2) will accommodate data from any of the four spectrometers used with the Daedalus scanner on the NASA ER2 platform. The QVS2 is designed around the AST 486/33 MHz CPU personal computer and comes with 10 EISA expansion slots, keyboard, and 4.0 mbytes of memory. Specialized PC-McIDAS software provides the main image analysis and display capability for the system. Image analysis and display of the digital scanner data is accomplished with PC-McIDAS software

Marked expansion of exocrine and endocrine pancreas with incretin therapy in humans with increased exocrine pancreas dysplasia and the potential for glucagon-producing neuroendocrine tumors.

Controversy exists regarding the potential regenerative influences of incretin therapy on pancreatic β-cells versus possible adverse pancreatic proliferative effects. Examination of pancreata from age-matched organ donors with type 2 diabetes mellitus (DM) treated by incretin therapy (n = 8) or other therapy (n = 12) and nondiabetic control subjects (n = 14) reveals an ∼40% increased pancreatic mass in DM treated with incretin therapy, with both increased exocrine cell proliferation (P < 0.0001) and dysplasia (increased pancreatic intraepithelial neoplasia, P < 0.01). Pancreata in DM treated with incretin therapy were notable for α-cell hyperplasia and glucagon-expressing microadenomas (3 of 8) and a neuroendocrine tumor. β-Cell mass was reduced by ∼60% in those with DM, yet a sixfold increase was observed in incretin-treated subjects, although DM persisted. Endocrine cells costaining for insulin and glucagon were increased in DM compared with non-DM control subjects (P < 0.05) and markedly further increased by incretin therapy (P < 0.05). In conclusion, incretin therapy in humans resulted in a marked expansion of the exocrine and endocrine pancreatic compartments, the former being accompanied by increased proliferation and dysplasia and the latter by α-cell hyperplasia with the potential for evolution into neuroendocrine tumors

The impact of asking intention or self-prediction questions on subsequent behavior: a meta-analysis

The current meta-analysis estimated the magnitude of the impact of asking intention and self-prediction questions on rates of subsequent behavior, and examined mediators and moderators of this question–behavior effect (QBE). Random-effects meta-analysis on 116 published tests of the effect indicated that intention/prediction questions have a small positive effect on behavior (d+ = 0.24). Little support was observed for attitude accessibility, cognitive dissonance, behavioral simulation, or processing fluency explanations of the QBE. Multivariate analyses indicated significant effects of social desirability of behavior/behavior domain (larger effects for more desirable and less risky behaviors), difficulty of behavior (larger effects for easy-to-perform behaviors), and sample type (larger effects among student samples). Although this review controls for co-occurrence of moderators in multivariate analyses, future primary research should systematically vary moderators in fully factorial designs. Further primary research is also needed to unravel the mechanisms underlying different variants of the QBE

OH yields from the CH3CO+O-2 reaction using an internal standard

Laser flash photolysis of CH3C(O)OH at 248 nm was used to create equal zero time yields of CH3CO and OH. The absolute OH yield from the CH3CO + O2 (+M) reaction was determined by following the OH temporal profile using the zero time OH concentration as an internal standard. The OH yield from CH3CO + O2 (+M) was observed to decrease with increasing pressure with an extrapolated zero pressure yield close to unity (1.1 ± 0.2, quoted uncertainties correspond to 95% confidence limits). The results are in quantitative agreement with those obtained from 248 nm acetone photolysis in the presence of O2

Chapitre 21 - Au-delà des clôtures : faune sauvage, bétail et utilisation des terres en Afrique australe

Introduction Les pâturages et savanes du monde, autrefois ouverts, sont de plus en plus enclavés par des limites qui démarquent des parcelles de plus en plus petites. Les changements qui en résultent dans les échelles de gestion de ces paysages ont des répercussions à la fois sur les processus écologiques et sociaux et, en définitive, sur la santé du système ainsi que sur la santé et le bien-être de l’homme. Une approche One Hea..

The GLM-spectrum:A multilevel framework for spectrum analysis with covariate and confound modelling

The frequency spectrum is a central method for representing the dynamics within electrophysiological data. Some widely used spectrum estimators make use of averaging across time segments to reduce noise in the final spectrum. The core of this approach has not changed substantially since the 1960s, though many advances in the field of regression modelling and statistics have been made during this time. Here, we propose a new approach, the General Linear Model (GLM) Spectrum, which reframes time averaged spectral estimation as multiple regression. This brings several benefits, including the ability to do confound modelling, hierarchical modelling, and significance testing via non-parametric statistics. We apply the approach to a dataset of EEG recordings of participants who alternate between eyes-open and eyes-closed resting state. The GLM-Spectrum can model both conditions, quantify their differences, and perform denoising through confound regression in a single step. This application is scaled up from a single channel to a whole head recording and, finally, applied to quantify age differences across a large group-level dataset. We show that the GLM-Spectrum lends itself to rigorous modelling of within- and between-subject contrasts as well as their interactions, and that the use of model-projected spectra provides an intuitive visualisation. The GLM-Spectrum is a flexible framework for robust multilevel analysis of power spectra, with adaptive covariate and confound modelling

Influence of Fecal Sample Storage on Bacterial Community Diversity

Previous studies have identified a correlation, either positive or negative, between specific stool bacteria strains and certain autoimmune diseases. These conflicting data may relate to sample collection. The aim of this work was to evaluate the influence of the collection parameters of time and temperature on bacterial community composition. Samples were taken from healthy children and immediately divided in 5 sub-samples. One sample was frozen immediately at -80°C, while the other aliquots were frozen 12, 24, 48, and 72h later DNA extracted from each sample was used to amplify the 16S rRNA with barcoded primers. The amplified products were pooled and partial 16S rRNA sequences were obtained by pyrosequencing. Person-to-person variability in community diversity was high. A list of those taxa that comprise at least 1% of the community was made for each individual. None of these were present in high numbers in all individuals. The Bacteroides were present in the highest abundance in three of four subjects. A total of 23,701 16S rRNA sequences were obtained with an average of 1,185 reads per sample with an average length of 200 bases. Although pyrosequencing of amplified 16S rRNA identified changes in community composition over time (~10%), little diversity change was observed at 12 hours (3.06%) with gradual changes occurring after 24 (8.61%), 48 (9.72%), and 72 h (10.14%), post collection

Antithymocyte Globulin Plus G-CSF Combination Therapy Leads to Sustained Immunomodulatory and Metabolic Effects in a Subset of Responders With Established Type 1 Diabetes.

Low-dose antithymocyte globulin (ATG) plus pegylated granulocyte colony-stimulating factor (G-CSF) preserves β-cell function for at least 12 months in type 1 diabetes. Herein, we describe metabolic and immunological parameters 24 months following treatment. Patients with established type 1 diabetes (duration 4-24 months) were randomized to ATG and pegylated G-CSF (ATG+G-CSF) (N = 17) or placebo (N = 8). Primary outcomes included C-peptide area under the curve (AUC) following a mixed-meal tolerance test (MMTT) and flow cytometry. "Responders" (12-month C-peptide ≥ baseline), "super responders" (24-month C-peptide ≥ baseline), and "nonresponders" (12-month C-peptide < baseline) were evaluated for biomarkers of outcome. At 24 months, MMTT-stimulated AUC C-peptide was not significantly different in ATG+G-CSF (0.49 nmol/L/min) versus placebo (0.29 nmol/L/min). Subjects treated with ATG+G-CSF demonstrated reduced CD4+ T cells and CD4+/CD8+ T-cell ratio and increased CD16+CD56hi natural killer cells (NK), CD4+ effector memory T cells (Tem), CD4+PD-1+ central memory T cells (Tcm), Tcm PD-1 expression, and neutrophils. FOXP3+Helios+ regulatory T cells (Treg) were elevated in ATG+G-CSF subjects at 6, 12, and 18 but not 24 months. Immunophenotyping identified differential HLA-DR expression on monocytes and NK and altered CXCR3 and PD-1 expression on T-cell subsets. As such, a group of metabolic and immunological responders was identified. A phase II study of ATG+G-CSF in patients with new-onset type 1 diabetes is ongoing and may support ATG+G-CSF as a prevention strategy in high-risk subjects

Sulfatide Preserves Insulin Crystals Not by Being Integrated in the Lattice but by Stabilizing Their Surface

Background. Sulfatide is known to chaperone insulin crystallization within the pancreatic beta cell, but it is not known if this results from sulfatide being integrated inside the crystal structure or by binding the surface of the crystal. With this study, we aimed to characterize the molecular mechanisms underlying the integral role for sulfatide in stabilizing insulin crystals prior to exocytosis. Methods. We cocrystallized human insulin in the presence of sulfatide and solved the structure by molecular replacement. Results. The crystal structure of insulin crystallized in the presence of sulfatide does not reveal ordered occupancy representing sulfatide in the crystal lattice, suggesting that sulfatide does not permeate the crystal lattice but exerts its stabilizing effect by alternative interactions such as on the external surface of insulin crystals. Conclusions. Sulfatide is known to stabilize insulin crystals, and we demonstrate here that in beta cells sulfatide is likely coating insulin crystals. However, there is no evidence for sulfatide to be built into the crystal lattice

Environment and Co-occurring Native Mussel Species, but Not Host Genetics, Impact the Microbiome of a Freshwater Invasive Species (Corbicula fluminea)

The Asian clam Corbicula fluminea (Family: Cyneridae) has aggressively invaded freshwater habitats worldwide, resulting in dramatic ecological changes and declines of native bivalves such as freshwater mussels (Family: Unionidae), one of the most imperiled faunal groups. Despite increases in our knowledge of invasive C. fluminea biology, little is known of how intrinsic and extrinsic factors, including co-occurring native species, influence its microbiome. We investigated the gut bacterial microbiome across genetically differentiated populations of C. fluminea in the Tennessee and Mobile River Basins in the Southeastern United States and compared them to those of six co-occurring species of native freshwater mussels. The gut microbiome of C. fluminea was diverse, differed with environmental conditions and varied spatially among rivers, but was unrelated to host genetic variation. Microbial source tracking suggested that the gut microbiome of C. fluminea may be influenced by the presence of co-occurring native mussels. Inferred functions from 16S rRNA gene data using PICRUST2 predicted a high prevalence and diversity of degradation functions in the C. fluminea microbiome, especially the degradation of carbohydrates and aromatic compounds. Such modularity and functional diversity of the microbiome of C. fluminea may be an asset, allowing to acclimate to an extensive range of nutritional sources in invaded habitats, which could play a vital role in its invasive success