Anatomical and diffusion MRI of deep gray matter in pediatric spina bifida

AbstractIndividuals with spina bifida myelomeningocele (SBM) exhibit brain abnormalities in cortical thickness, white matter integrity, and cerebellar structure. Little is known about deep gray matter macro- and microstructure in this population. The current study utilized volumetric and diffusion-weighted MRI techniques to examine gray matter volume and microstructure in several subcortical structures: basal ganglia nuclei, thalamus, hippocampus, and amygdala. Sixty-six children and adolescents (ages 8–18; M = 12.0, SD = 2.73) with SBM and typically developing (TD) controls underwent T1- and diffusion-weighted neuroimaging. Microstructural results indicated that hippocampal volume was disproportionately reduced, whereas the putamen volume was enlarged in the group with SBM. Microstructural analyses indicated increased mean diffusivity (MD) and fractional anisotropy (FA) in the gray matter of most examined structures (i.e., thalamus, caudate, hippocampus), with the putamen exhibiting a unique pattern of decreased MD and increased FA. These results provide further support that SBM differentially disrupts brain regions whereby some structures are volumetrically normal whereas others are reduced or enlarged. In the hippocampus, volumetric reduction coupled with increased MD may imply reduced cellular density and aberrant organization. Alternatively, the enlarged volume and significantly reduced MD in the putamen suggest increased density

Assessment of the Carbonate Chemistry Seasonal Cycles in the Southern Ocean From Persistent Observational Platforms

Observations from Southern Ocean Carbon and Climate Observations and Modeling (SOCCOM) biogeochemical profiling Argo floats are used to characterize the climatological seasonal cycles and drivers of dissolved inorganic carbon, total alkalinity, pH, the partial pressure of carbon dioxide (CO2), and the saturation state of aragonite at the surface and at 200 m across five Southern Ocean frontal regimes, including under sea ice. The Southern Ocean ranges from a temperature-dominated system in the northernmost Subtropical Zone to a biologically dominated system in the most poleward Seasonal Sea Ice Zone. In all zones, the ingassing or outgassing of CO2 must be balanced by geostrophic and Ekman transport, mixing from below, and particle transport of carbon into or out of the euphotic zone. The climatological seasonal cycles spanning the period from 2014 to 2017 compare favorably with existing climatologies in spring and summer and less so during winter months, at higher latitudes, and in ice-covered regions due, in part, to limited wintertime observations before SOCCOM. We observe increases in the carbon and nutrient content of surface waters south of the Subantarctic Front between climatological data products and the SOCCOM float climatologies, even after adjusting for anthropogenic change, suggesting a large-scale increase in the amount of upwelled carbon- and nutrient-rich deep waters. This increased upwelling corresponds to a positive Southern Annular Mode Index over 2014-2017 and likely acts to decrease the magnitude of the Southern Ocean sink of total carbon by increasing outgassing of natural CO2, especially during winter months

Empirical algorithms to estimate water column pH in the Southern Ocean

Empirical algorithms are developed using high-quality GO-SHIP hydrographic measurements of commonly measured parameters (temperature, salinity, pressure, nitrate, and oxygen) that estimate pH in the Pacific sector of the Southern Ocean. The coefficients of determination, R² , are 0.98 for pH from nitrate (pH^N) and 0.97 for pH from oxygen (pH^Ox) with RMS errors of 0.010 and 0.008, respectively. These algorithms are applied to Southern Ocean Carbon and Climate Observations and Modeling (SOCCOM) biogeochemical profiling floats, which include novel sensors (pH, nitrate, oxygen, fluorescence, and backscatter). These algorithms are used to estimate pH on floats with no pH sensors and to validate and adjust pH sensor data from floats with pH sensors. The adjusted float data provide, for the first time, seasonal cycles in surface pH on weekly resolution that range from 0.05 to 0.08 on weekly resolution for the Pacific sector of the Southern Ocean.This is the publisher’s final pdf. The article is copyrighted by the American Geophysical Union and published by John Wiley & Sons, Inc. It can be found at: http://agupubs.onlinelibrary.wiley.com/agu/journal/10.1002/%28ISSN%291944-8007/ The measurement methods, calibration, and quality control for all discrete bottle data used in this study are available at http://cchdo.ucsd.edu, and all SOCCOM float data are available at http://soccom.princeton.edu/soccomviz.php

A novel method for determination of aragonite saturation state on the continental shelf of central Oregon using multi-parameter relationships with hydrographic data

We developed a multiple linear regression model to robustly determine aragonite saturation state (Ωarag) from observations of temperature and oxygen (R² = 0.987, RMS error 0.053), using data collected in the Pacific Northwest region in late May 2007. The seasonal evolution of Ωarag near central Oregon was evaluated by applying the regression model to a monthly (winter)/bi-weekly (summer) watercolumn hydrographic time-series collected over the shelf and slope in 2007. The Ωarag predicted by the regression model was less than 1, the thermodynamic calcification/dissolution threshold, over shelf/slope bottom waters throughout the entire 2007 upwelling season (May–November), with the Ωarag = 1 horizon shoaling to 30 m by late summer. The persistence of water with Ωarag < 1 on the continental shelf has not been previously noted and could have notable ecological consequences for benthic and pelagic calcifying organisms such as mussels, oysters, abalone, echinoderms, and pteropods.Keywords: aragonite saturation state, calcification, CaCO

The Pathway to Detangle a Scrambled Gene

Programmed DNA elimination and reorganization frequently occur during cellular differentiation. Development of the somatic macronucleus in some ciliates presents an extreme case, involving excision of internal eliminated sequences (IESs) that interrupt coding DNA segments (macronuclear destined sequences, MDSs), as well as removal of transposon-like elements and extensive genome fragmentation, leading to 98% genome reduction in Stylonychia lemnae. Approximately 20-30% of the genes are estimated to be scrambled in the germline micronucleus, with coding segment order permuted and present in either orientation on micronuclear chromosomes. Massive genome rearrangements are therefore critical for development.To understand the process of DNA deletion and reorganization during macronuclear development, we examined the population of DNA molecules during assembly of different scrambled genes in two related organisms in a developmental time-course by PCR. The data suggest that removal of conventional IESs usually occurs first, accompanied by a surprising level of error at this step. The complex events of inversion and translocation seem to occur after repair and excision of all conventional IESs and via multiple pathways.This study reveals a temporal order of DNA rearrangements during the processing of a scrambled gene, with simpler events usually preceding more complex ones. The surprising observation of a hidden layer of errors, absent from the mature macronucleus but present during development, also underscores the need for repair or screening of incorrectly-assembled DNA molecules

Single hadron response measurement and calorimeter jet energy scale uncertainty with the ATLAS detector at the LHC

The uncertainty on the calorimeter energy response to jets of particles is derived for the ATLAS experiment at the Large Hadron Collider (LHC). First, the calorimeter response to single isolated charged hadrons is measured and compared to the Monte Carlo simulation using proton-proton collisions at centre-of-mass energies of sqrt(s) = 900 GeV and 7 TeV collected during 2009 and 2010. Then, using the decay of K_s and Lambda particles, the calorimeter response to specific types of particles (positively and negatively charged pions, protons, and anti-protons) is measured and compared to the Monte Carlo predictions. Finally, the jet energy scale uncertainty is determined by propagating the response uncertainty for single charged and neutral particles to jets. The response uncertainty is 2-5% for central isolated hadrons and 1-3% for the final calorimeter jet energy scale.Comment: 24 pages plus author list (36 pages total), 23 figures, 1 table, submitted to European Physical Journal

Measurement of the flavour composition of dijet events in pp collisions at root s=7 TeV with the ATLAS detector

This paper describes a measurement of the flavour composition of dijet events produced in pp collisions at &#8730;s=7 TeV using the ATLAS detector. The measurement uses the full 2010 data sample, corresponding to an integrated luminosity of 39 pb−1. Six possible combinations of light, charm and bottom jets are identified in the dijet events, where the jet flavour is defined by the presence of bottom, charm or solely light flavour hadrons in the jet. Kinematic variables, based on the properties of displaced decay vertices and optimised for jet flavour identification, are used in a multidimensional template fit to measure the fractions of these dijet flavour states as functions of the leading jet transverse momentum in the range 40 GeV to 500 GeV and jet rapidity |y|&#60;2.1. The fit results agree with the predictions of leading- and next-to-leading-order calculations, with the exception of the dijet fraction composed of bottom and light flavour jets, which is underestimated by all models at large transverse jet momenta. The ability to identify jets containing two b-hadrons, originating from e.g. gluon splitting, is demonstrated. The difference between bottom jet production rates in leading and subleading jets is consistent with the next-to-leading-order predictions

Expected Performance of the ATLAS Experiment - Detector, Trigger and Physics

A detailed study is presented of the expected performance of the ATLAS detector. The reconstruction of tracks, leptons, photons, missing energy and jets is investigated, together with the performance of b-tagging and the trigger. The physics potential for a variety of interesting physics processes, within the Standard Model and beyond, is examined. The study comprises a series of notes based on simulations of the detector and physics processes, with particular emphasis given to the data expected from the first years of operation of the LHC at CERN

Standalone vertex finding in the ATLAS muon spectrometer

A dedicated reconstruction algorithm to find decay vertices in the ATLAS muon spectrometer is presented. The algorithm searches the region just upstream of or inside the muon spectrometer volume for multi-particle vertices that originate from the decay of particles with long decay paths. The performance of the algorithm is evaluated using both a sample of simulated Higgs boson events, in which the Higgs boson decays to long-lived neutral particles that in turn decay to bbar b final states, and pp collision data at √s = 7 TeV collected with the ATLAS detector at the LHC during 2011