Extracellular Matrix Aggregates from Differentiating Embryoid Bodies as a Scaffold to Support ESC Proliferation and Differentiation

Embryonic stem cells (ESCs) have emerged as potential cell sources for tissue engineering and regeneration owing to its virtually unlimited replicative capacity and the potential to differentiate into a variety of cell types. Current differentiation strategies primarily involve various growth factor/inducer/repressor concoctions with less emphasis on the substrate. Developing biomaterials to promote stem cell proliferation and differentiation could aid in the realization of this goal. Extracellular matrix (ECM) components are important physiological regulators, and can provide cues to direct ESC expansion and differentiation. ECM undergoes constant remodeling with surrounding cells to accommodate specific developmental event. In this study, using ESC derived aggregates called embryoid bodies (EB) as a model, we characterized the biological nature of ECM in EB after exposure to different treatments: spontaneously differentiated and retinoic acid treated (denoted as SPT and RA, respectively). Next, we extracted this treatment-specific ECM by detergent decellularization methods (Triton X-100, DOC and SDS are compared). The resulting EB ECM scaffolds were seeded with undifferentiated ESCs using a novel cell seeding strategy, and the behavior of ESCs was studied. Our results showed that the optimized protocol efficiently removes cells while retaining crucial ECM and biochemical components. Decellularized ECM from SPT EB gave rise to a more favorable microenvironment for promoting ESC attachment, proliferation, and early differentiation, compared to native EB and decellularized ECM from RA EB. These findings suggest that various treatment conditions allow the formulation of unique ESC-ECM derived scaffolds to enhance ESC bioactivities, including proliferation and differentiation for tissue regeneration applications. © 2013 Goh et al

Colouration and Colour Changes of the Fiddler Crab, Uca capricornis: A Descriptive Study

Colour changes in animals may be triggered by a variety of social and environmental factors and may occur over a matter of seconds or months. Crustaceans, like fiddler crabs (genus Uca), are particularly adept at changing their colour and have been the focus of numerous studies. However, few of these studies have attempted to quantitatively describe the individual variation in colour and pattern or their adaptive significance. This paper quantitatively describes the colour patterns of the fiddler crab Uca capricornis and their ability to change on a socially significant timescale. The most dramatic changes in colour pattern are associated with moulting. These ontogenetic changes result in a general reduction of the colour pattern with increasing size, although females are more colourful and variable than similarly-sized males. Uca capricornis are also capable of rapid colour changes in response to stress, but show no endogenous rhythms associated with the semilunar and tidal cycles commonly reported in other fiddler crabs. The extreme colour polymorphism and the relative stability of the colour patterns in Uca capricornis are consistent with their use in visually mediated mate recognition

Bioinformatics and molecular modeling in glycobiology

The field of glycobiology is concerned with the study of the structure, properties, and biological functions of the family of biomolecules called carbohydrates. Bioinformatics for glycobiology is a particularly challenging field, because carbohydrates exhibit a high structural diversity and their chains are often branched. Significant improvements in experimental analytical methods over recent years have led to a tremendous increase in the amount of carbohydrate structure data generated. Consequently, the availability of databases and tools to store, retrieve and analyze these data in an efficient way is of fundamental importance to progress in glycobiology. In this review, the various graphical representations and sequence formats of carbohydrates are introduced, and an overview of newly developed databases, the latest developments in sequence alignment and data mining, and tools to support experimental glycan analysis are presented. Finally, the field of structural glycoinformatics and molecular modeling of carbohydrates, glycoproteins, and protein–carbohydrate interaction are reviewed

Measurement of the transverse momentum distribution of [Z over γ*] bosons in proton-proton collisions at √s = 7 TeV with the ATLAS detector

A measurement of the [Z over γ*] transverse momentum (p[Z over T]) distribution in proton–proton collisions at √s = 7 TeV is presented using [Z over γ*] →e[superscript +]e[superscript −] and [Z over γ*] →μ[superscript +]μ[superscript −] decays collected with the ATLAS detector in data sets with integrated luminosities of 35 pb[superscript −1] and 40 pb[superscript −1], respectively. The normalized differential cross sections are measured separately for electron and muon decay channels as well as for their combination up to p[Z over T] of 350 GeV for invariant dilepton masses 66 GeV<m[subscript ℓℓ]<116 GeV. The measurement is compared to predictions of perturbative QCD and various event generators. The prediction of resummed QCD combined with fixed order perturbative QCD is found to be in good agreement with the data.United States. Dept. of EnergyNational Science Foundation (U.S.)Brookhaven National LaboratoryEuropean Organization for Nuclear Researc

Performance of the ATLAS Trigger System in 2010

Proton-proton collisions at sqrt{s} = 7 TeV and heavy ion collisions at sqrt{s_NN} = 2.76 TeV were produced by the LHC and recorded using the ATLAS experiment's trigger system in 2010. The LHC is designed with a maximum bunch crossing rate of 40 MHz and the ATLAS trigger system is designed to record approximately 200 of these per second. The trigger system selects events by rapidly identifying signatures of muon, electron, photon, tau lepton, jet, and B meson candidates, as well as using global event signatures, such as missing transverse energy. An overview of the ATLAS trigger system, the evolution of the system during 2010 and the performance of the trigger system components and selections based on the 2010 collision data are shown. A brief outline of plans for the trigger system in 2011 is presente

Economic Impact of a Medicaid Population Health Management Program

A population health management program was implemented to assess growth in health care expenditures for the disabled segment of Georgia's Medicaid population before and during the first year of a population health outcomes management program, and to compare those expenditures with projected costs based on various cost inflation trend assumptions. A retrospective, nonexperimental approach was used to analyze claims data from Georgia Medicaid claims files for all program-eligible persons for each relevant time period (intent-to-treat basis). These included all non-Medicare, noninstitutionalized Medicaid aged-blind-disabled adults older than 18 years of age. Comparisons of health care expenditures and utilization were made between base year (2003–2004) and performance year one (2006–2007), and of the difference between actual expenditures incurred in the performance year vs. projected expenditures based on various cost inflation assumptions. Demographic characteristics and clinical complexity of the population (as measured by the Chronic Illness and Disability Payment System risk score) actually increased from baseline to implementation. Actual expenditures were less than projected expenditures using any relevant medical inflation assumption. Actual expenditures were less than projected expenditures by $9.82 million when using a conservative US general medical inflation rate, by$43.6 million using national Medicaid cost trends, and by $106 million using Georgia Medicaid's own cost projections for the non-dually eligible disabled segment of Medicaid enrollees. Quadratic growth curve modeling also demonstrated a lower rate of increase in total expenditures. The rate of increase in expenditures was lower over the first year of program implementation compared with baseline. Weighted utilization rates were also lower in high-cost categories, such as inpatient days, despite increases in the risk profile of the population. Varying levels of cost avoidance could be inferred from differences between actual and projected expenditures using each of the health-related inflation assumptions. (Population Health Management 2011;14:215–222