Geometric capture and escape of a microswimmer colliding with an obstacle.

Motivated by recent experiments, we consider the hydrodynamic capture of a microswimmer near a stationary spherical obstacle. Simulations of model equations show that a swimmer approaching a small spherical colloid is simply scattered. In contrast, when the colloid is larger than a critical size it acts as a passive trap: the swimmer is hydrodynamically captured along closed trajectories and endlessly orbits around the colloidal sphere. In order to gain physical insight into this hydrodynamic scattering problem, we address it analytically. We provide expressions for the critical trapping radius, the depth of the "basin of attraction," and the scattering angle, which show excellent agreement with our numerical findings. We also demonstrate and rationalize the strong impact of swimming-flow symmetries on the trapping efficiency. Finally, we give the swimmer an opportunity to escape the colloidal traps by considering the effects of Brownian, or active, diffusion. We show that in some cases the trapping time is governed by an Ornstein-Uhlenbeck process, which results in a trapping time distribution that is well-approximated as inverse-Gaussian. The predictions again compare very favorably with the numerical simulations. We envision applications of the theory to bioremediation, microorganism sorting techniques, and the study of bacterial populations in heterogeneous or porous environments.G.R. Moreno-Flores acknowledges funding by Fondecyt grant 1130280 and Inicitativa Cientifica Milenio NC130062; and E. Lauga acknowledges from the European Union through a Marie Curie CIG Grant.This is the accepted manuscipt. The final version is available at http://pubs.rsc.org/en/Content/ArticleLanding/2015/SM/C4SM02785J#!divAbstract

Ic‐P‐204: The Relationship Between Tau Pet And Other Ad Biomarkers In Autosomal Dominant Alzheimer Disease

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/152660/1/alzjjalz2018062271.pd

Fault kinematics in northern Central America and coupling along the subduction interface of the Cocos Plate, from GPS data in Chiapas (Mexico), Guatemala and El Salvador

International audienceNew GPS measurements in Chiapas (Mexico), Guatemala and El Salvador are used to constrain the fault kinematics in the North America (NA), Caribbean (CA) and Cocos (CO) plates triple junction area. The regional GPS velocity field is first analysed in terms of strain partitioning across the major volcano-tectonic structures, using elastic half-space modelling, then inverted through a block model. We show the dominant role of the Motagua Fault with respect to the Polochic Fault in the accommodation of the present-day deformation associated with the NA and CA relative motion. The NA/CA motion decreases from 18-22 mm yr−1 in eastern Guatemala to 14-20 mm yr−1 in central Guatemala (assuming a uniform locking depth of 14-28 km), down to a few millimetres per year in western Guatemala. As a consequence, the western tip of the CA Plate deforms internally, with ≃9 mm yr−1 of east-west extension (≃5 mm yr−1 across the Guatemala city graben alone). Up to 15 mm yr−1 of dextral motion can be accommodated across the volcanic arc in El Salvador and southeastern Guatemala. The arc seems to mark the northern boundary of an independent forearc sliver (AR), pinned to the NA plate. The inversion of the velocity field shows that a four-block (NA, CA, CO and AR) model, that combines relative block rotations with elastic deformation at the block boundaries, can account for most of the GPS observations and constrain the overall kinematics of the active structures. This regional modelling also evidences lateral variations of coupling at the CO subduction interface, with a fairly high-coupling (≃0.6) offshore Chiapas and low-coupling (≃0.25) offshore Guatemala and El Salvador

Comparison of Pittsburgh compound B and florbetapir in cross-sectional and longitudinal studies.

IntroductionQuantitative in vivo measurement of brain amyloid burden is important for both research and clinical purposes. However, the existence of multiple imaging tracers presents challenges to the interpretation of such measurements. This study presents a direct comparison of Pittsburgh compound B-based and florbetapir-based amyloid imaging in the same participants from two independent cohorts using a crossover design.MethodsPittsburgh compound B and florbetapir amyloid PET imaging data from three different cohorts were analyzed using previously established pipelines to obtain global amyloid burden measurements. These measurements were converted to the Centiloid scale to allow fair comparison between the two tracers. The mean and inter-individual variability of the two tracers were compared using multivariate linear models both cross-sectionally and longitudinally.ResultsGlobal amyloid burden measured using the two tracers were strongly correlated in both cohorts. However, higher variability was observed when florbetapir was used as the imaging tracer. The variability may be partially caused by white matter signal as partial volume correction reduces the variability and improves the correlations between the two tracers. Amyloid burden measured using both tracers was found to be in association with clinical and psychometric measurements. Longitudinal comparison of the two tracers was also performed in similar but separate cohorts whose baseline amyloid load was considered elevated (i.e., amyloid positive). No significant difference was detected in the average annualized rate of change measurements made with these two tracers.DiscussionAlthough the amyloid burden measurements were quite similar using these two tracers as expected, difference was observable even after conversion into the Centiloid scale. Further investigation is warranted to identify optimal strategies to harmonize amyloid imaging data acquired using different tracers

The Tara Pacific expedition—A pan-ecosystemic approach of the “-omics” complexity of coral reef holobionts across the Pacific Ocean

Coral reefs are the most diverse habitats in the marine realm. Their productivity, structural complexity, and biodiversity critically depend on ecosystem services provided by corals that are threatened because of climate change effects—in particular, ocean warming and acidification. The coral holobiont is composed of the coral animal host, endosymbiotic dinoflagellates, associated viruses, bacteria, and other microeukaryotes. In particular, the mandatory photosymbiosis with microalgae of the family Symbiodiniaceae and its consequences on the evolution, physiology, and stress resilience of the coral holobiont have yet to be fully elucidated. The functioning of the holobiont as a whole is largely unknown, although bacteria and viruses are presumed to play roles in metabolic interactions, immunity, and stress tolerance. In the context of climate change and anthropogenic threats on coral reef ecosystems, the Tara Pacific project aims to provide a baseline of the “-omics” complexity of the coral holobiont and its ecosystem across the Pacific Ocean and for various oceanographically distinct defined areas. Inspired by the previous Tara Oceans expeditions, the Tara Pacific expedition (2016–2018) has applied a pan-ecosystemic approach on coral reefs throughout the Pacific Ocean, drawing an east–west transect from Panama to Papua New Guinea and a south–north transect from Australia to Japan, sampling corals throughout 32 island systems with local replicates. Tara Pacific has developed and applied state-of-the-art technologies in very-high-throughput genetic sequencing and molecular analysis to reveal the entire microbial and chemical diversity as well as functional traits associated with coral holobionts, together with various measures on environmental forcing. This ambitious project aims at revealing a massive amount of novel biodiversity, shedding light on the complex links between genomes, transcriptomes, metabolomes, organisms, and ecosystem functions in coral reefs and providing a reference of the biological state of modern coral reefs in the Anthropocene

History of Galaxy Interactions and their Impact on Star Formation over the Last 7 Gyr from GEMS

We perform a comprehensive estimate of the frequency of galaxy mergers and their impact on star formation over z~0.24--0.80 (lookback time T_b~3--7 Gyr) using 3698 (M*>=1e9 Msun) galaxies with GEMS HST, COMBO-17, and Spitzer data. Our results are: (1) Among 790 high mass (M*>=2.5e10 Msun) galaxies, the visually-based merger fraction over z~0.24--0.80, ranges from 9%+-5% to 8%+-2%. Lower limits on the major and minor merger fractions over this interval range from 1.1% to 3.5%, and 3.6% to 7.5%, respectively. This is the first approximate empirical estimate of the frequency of minor mergers at z<1. For a visibility timescale of ~0.5 Gyr, it follows that over T_b~3--7 Gyr, ~68% of high mass systems have undergone a merger of mass ratio >1/10, with ~16%, 45%, and 7% of these corresponding respectively to major, minor, and ambiguous `major or minor' mergers. The mean merger rate is a few x 1e-4 Gyr-1 Mpc-3. (2) We compare the empirical merger fraction and rate for high mass galaxies to a suite of Lambda CDM-based models: halo occupation distribution models, semi-analytic models, and hydrodynamic SPH simulations. We find qualitative agreement between observations and models such that the (major+minor) merger fraction or rate from different models bracket the observations, and show a factor of five dispersion. Near-future improvements can now start to rule out certain merger scenarios. (3) Among ~3698 M*>=1e9 Msun galaxies, we find that the mean SFR of visibly merging systems is only modestly enhanced compared to non-interacting galaxies over z~0.24--0.80. Visibly merging systems only account for less than 30% of the cosmic SFR density over T_b~3--7 Gyr. This suggests that the behavior of the cosmic SFR density over the last 7 Gyr is predominantly shaped by non-interacting galaxies.Comment: Accepted for Publication in the Astrophysical Journal. 17 pages of text, 21 figures, 3 tables. Uses emulateapj5.st

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Comparing cortical signatures of atrophy between late-onset and autosomal dominant Alzheimer disease

Defining a signature of cortical regions of interest preferentially affected by Alzheimer disease (AD) pathology may offer improved sensitivity to early AD compared to hippocampal volume or mesial temporal lobe alone. Since late-onset Alzheimer disease (LOAD) participants tend to have age-related comorbidities, the younger-onset age in autosomal dominant AD (ADAD) may provide a more idealized model of cortical thinning in AD. To test this, the goals of this study were to compare the degree of overlap between the ADAD and LOAD cortical thinning maps and to evaluate the ability of the ADAD cortical signature regions to predict early pathological changes in cognitively normal individuals. We defined and analyzed the LOAD cortical maps of cortical thickness in 588 participants from the Knight Alzheimer Disease Research Center (Knight ADRC) and the ADAD cortical maps in 269 participants from the Dominantly Inherited Alzheimer Network (DIAN) observational study. Both cohorts were divided into three groups: cognitively normal controls (nADRC = 381; nDIAN = 145), preclinical (nADRC = 153; nDIAN = 76), and cognitively impaired (nADRC = 54; nDIAN = 48). Both cohorts underwent clinical assessments, 3T MRI, and amyloid PET imaging with either 11C-Pittsburgh compound B or 18F-florbetapir. To generate cortical signature maps of cortical thickness, we performed a vertex-wise analysis between the cognitively normal controls and impaired groups within each cohort using six increasingly conservative statistical thresholds to determine significance. The optimal cortical map among the six statistical thresholds was determined from a receiver operating characteristic analysis testing the performance of each map in discriminating between the cognitively normal controls and preclinical groups. We then performed within-cohort and cross-cohort (e.g. ADAD maps evaluated in the Knight ADRC cohort) analyses to examine the sensitivity of the optimal cortical signature maps to the amyloid levels using only the cognitively normal individuals (cognitively normal controls and preclinical groups) in comparison to hippocampal volume. We found the optimal cortical signature maps were sensitive to early increases in amyloid for the asymptomatic individuals within their respective cohorts and were significant beyond the inclusion of hippocampus volume, but the cortical signature maps performed poorly when analyzing across cohorts. These results suggest the cortical signature maps are a useful MRI biomarker of early AD-related neurodegeneration in preclinical individuals and the pattern of decline differs between LOAD and ADAD.Fil: Dincer, Aylin. Washington University in St. Louis; Estados UnidosFil: Gordon, Brian A.. Washington University in St. Louis; Estados UnidosFil: Hari-Raj, Amrita. Ohio State University; Estados UnidosFil: Keefe, Sarah J.. Washington University in St. Louis; Estados UnidosFil: Flores, Shaney. Washington University in St. Louis; Estados UnidosFil: McKay, Nicole S.. Washington University in St. Louis; Estados UnidosFil: Paulick, Angela M.. Washington University in St. Louis; Estados UnidosFil: Shady Lewis, Kristine E.. University of Kentucky; Estados UnidosFil: Feldman, Rebecca L.. Washington University in St. Louis; Estados UnidosFil: Hornbeck, Russ C.. Washington University in St. Louis; Estados UnidosFil: Allegri, Ricardo Francisco. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; ArgentinaFil: Ances, Beau M.. Washington University in St. Louis; Estados UnidosFil: Berman, Sarah B.. University of Pittsburgh; Estados UnidosFil: Brickman, Adam M.. Columbia University; Estados UnidosFil: Brooks, William S.. Neuroscience Research Australia; Australia. University of New South Wales; AustraliaFil: Cash, David M.. UCL Queen Square Institute of Neurology; Reino UnidoFil: Chhatwal, Jasmeer P.. Harvard Medical School; Estados UnidosFil: Farlow, Martin R.. Indiana University; Estados UnidosFil: Fougère, Christian la. German Center for Neurodegenerative Diseases; Alemania. University Hospital of Tübingen; AlemaniaFil: Fox, Nick C.. UCL Queen Square Institute of Neurology; Reino UnidoFil: Fulham, Michael J.. Royal Prince Alfred Hospital; Australia. University of Sydney; AustraliaFil: Jack, Clifford R.. Mayo Clinic; Estados UnidosFil: Joseph-Mathurin, Nelly. Washington University in St. Louis; Estados UnidosFil: Karch, Celeste M.. Washington University in St. Louis; Estados UnidosFil: Lee, Athene. University Brown; Estados UnidosFil: Levin, Johannes. German Center for Neurodegenerative Diseases; Alemania. Ludwig Maximilians Universitat; Alemania. Munich Cluster for Systems Neurology; AlemaniaFil: Masters, Colin L.. University of Melbourne; AustraliaFil: McDade, Eric M.. Washington University in St. Louis; Estados UnidosFil: Oh, Hwamee. University Brown; Estados UnidosFil: Perrin, Richard J.. Washington University in St. Louis; Estados Unido