Always on my mind: Cross-brain associations of mental health symptoms during simultaneous parent-child scanning.

How parents manifest symptoms of anxiety or depression may affect how children learn to modulate their own distress, thereby influencing the children's risk for developing an anxiety or mood disorder. Conversely, children's mental health symptoms may impact parents' experiences of negative emotions. Therefore, mental health symptoms can have bidirectional effects in parent-child relationships, particularly during moments of distress or frustration (e.g., when a parent or child makes a costly mistake). The present study used simultaneous functional magnetic resonance imaging (fMRI) of parent-adolescent dyads to examine how brain activity when responding to each other's costly errors (i.e., dyadic error processing) may be associated with symptoms of anxiety and depression. While undergoing simultaneous fMRI scans, healthy dyads completed a task involving feigned errors that indicated their family member made a costly mistake. Inter-brain, random-effects multivariate modeling revealed that parents who exhibited decreased medial prefrontal cortex and posterior cingulate cortex activation when viewing their child's costly error response had children with more symptoms of depression and anxiety. Adolescents with increased anterior insula activation when viewing a costly error made by their parent had more anxious parents. These results reveal cross-brain associations between mental health symptomatology and brain activity during parent-child dyadic error processing

Measuring retention within the adolescent brain cognitive development (ABCD)SM study

The Adolescent Brain Cognitive Development (ABCD

OOI Biogeochemical Sensor Data: Best Practices and User Guide. Version 1.0.0.

The OOI Biogeochemical Sensor Data Best Practices and User Guide is intended to provide current and prospective users of data generated by biogeochemical sensors deployed on the Ocean Observatories Initiative (OOI) arrays with the information and guidance needed for them to ensure that the data is science-ready. This guide is aimed at researchers with an interest or some experience in ocean biogeochemical processes. We expect that users of this guide will have some background in oceanography, however we do not assume any prior experience working with biogeochemical sensors or their data. While initially envisioned as a “cookbook” for end users seeking to work with OOI biogeochemical (BGC) sensor data, our Working Group and Beta Testers realized that the processing required to meet the specific needs of all end users across a wide range of potential scientific applications and combinations of OOI BGC data from different sensors and platforms couldn’t be synthesized into a single “recipe”. We therefore provide here the background information and principles needed for the end user to successfully identify and understand all the available “ingredients” (data), the types of “cooking” (end user processing) that are recommended to prepare them, and a few sample “recipes” (worked examples) to support end users in developing their own “recipes” consistent with the best practices presented here. This is not intended to be an exhaustive guide to each of these sensors, but rather a synthesis of the key information to support OOI BGC sensor data users in preparing science-ready data products. In instances when more in-depth information might be helpful, references and links have been provided both within each chapter and in the Appendix

Lower export production during glacial periods in the equatorial Pacific derived from (231Pa/230Th)xs,0 measurements in deep-sea sediments

Author Posting. © American Geophysical Union, 2004. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Paleoceanography 19 (2004): PA4023, doi:10.1029/2003PA000994.The (231Pa/230Th)xs,0 records obtained from two cores from the western (MD97-2138; 1°25′S, 146°24′E, 1900 m) and eastern (Ocean Drilling Program Leg 138 Site 849, 0°11.59′N, 110°31.18′W, 3851 m) equatorial Pacific display similar variability over the last 85,000 years, i.e., from isotopic stages 1 to 5a, with systematically higher values during the Holocene, isotopic stage 3, and isotopic stage 5a, and lower values, approaching the production rate ratio of the two isotopes (0.093), during the colder periods corresponding to isotopic stages 2 and 4. We have also measured the 230Th-normalized biogenic preserved and terrigenous fluxes, as well as major and trace elements concentrations, in both cores. The (231Pa/230Th)xs,0 results combined with the changes in preserved carbonate and opal fluxes at the eastern site indicate lower productivity in the eastern equatorial Pacific during glacial periods. The (231Pa/230Th)xs,0 variations in the western equatorial Pacific also seem to be controlled by productivity (carbonate and/or opal). The generally high (231Pa/230Th)xs,0 ratios (>0.093) of the profile could be due to opal and/or MnO2 in the sinking particles. The profiles of (231Pa/230Th)xs,0 and 230Th-normalized fluxes indicate a decrease in exported carbonate, and possibly opal, during isotopic stages 2 and 4 in MD97-2138. Using 230Th-normalized flux, we also show that sediments from the two cores were strongly affected by sediment redistribution by bottom currents suggesting a control of mass accumulation rates by sediment focusing variability.SP funding for this research was provided by grants from the French Minister of Research and a EURODOC grant of the Re´gion Rhoˆne-Alpes (SAFIR-980065327). SP also gratefully acknowledges the financial support of the WHOI Geology and Geophysics Dept. This work was also supported by a CNRS-NSF grant (SP and KWWS). The contribution of JFM to this study was supported in part by the US NSF and by WHOI OCCI and Mellon awards

BioTIME: A database of biodiversity time series for the Anthropocene.

MotivationThe BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community-led open-source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene.Main types of variables includedThe database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record.Spatial location and grainBioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km2 (158 cm2) to 100 km2 (1,000,000,000,000 cm2).Time period and grainBioTIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year.Major taxa and level of measurementBioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates.Software format.csv and .SQL

Comment on "Do geochemical estimates of sediment focusing pass the sediment test in the equatorial Pacific?" by M. Lyle et al.

Accurately estimating the vertical flux of material reaching the seafloor from the overlying surface waters is essential for the paleoceanographic reconstruction of a wide variety of oceanic processes. Two approaches are currently being used. One consists of estimating mass accumulation rates (MAR) between dated horizons as the product of linear sedimentation rates, sediment dry bulk densities, and concentrations. One pitfall with this approach is that sediments can be redistributed on the seafloor by bottom currents, and their accumulation may not necessarily reflect the true vertical rain rate originating from the overlying water column. To address this problem, the method of ²³⁰Th normalization was developed [Bacon, 1984]. This method is based on the assumption that the rapid scavenging of ²³⁰Th produced in the water column by decay of dissolved uranium results in its flux to the seafloor always being close to its known rate of production. To the extent that this assumption is correct, scavenged ²³⁰Th can be used as a reference to estimate the settling flux of other sedimentary constituents and to correct for sediment redistribution on the seafloor [Henderson and Anderson, 2003; Francois et al., 2004]

Lambs with Scrapie Susceptible Genotypes Have Higher Postnatal Survival

BACKGROUND: Prion protein (PrP) alleles associated with scrapie susceptibility persist in many sheep populations even with high frequencies despite centuries of selection against them. This suggests that scrapie susceptibility alleles have a pleiotropic effect or are associated with fitness or other traits that have been subject to selection. METHODOLOGY/PRINCIPAL FINDINGS: We genotyped all lambs in two scrapie-free Scottish Blackface sheep flocks for polymorphisms at codons 136, 154 and 171 of the PrP gene. We tested potential associations of the PrP genotype with lamb viability at birth and postnatal survival using a complementary log-log link function and a Weibull proportional hazard model, respectively. Here we show there is an association between PrP genotype, as defined by polymorphisms at codons 154 ad 171, and postnatal lamb survival in the absence of scrapie. Sheep carrying the wild-type ARQ allele have higher postnatal survival rates than sheep carrying the more scrapie-resistant alleles (ARR or AHQ). CONCLUSION: The PrP genotypes associated with higher susceptibility to scrapie are associated with improved postnatal survival in the absence of the disease. This association helps to explain the existence, and in many instances the high frequency, of the ARQ allele in sheep populations

Persistent export of 231Pa from the deep central Arctic Ocean over the past 35,000 years

The Arctic Ocean has an important role in Earth’s climate, both through surface processes such as sea-ice formation and transport, and through the production and export of waters at depth that contribute to the global thermohaline circulation. Deciphering the deep Arctic Ocean’s palaeo-oceanographic history is a crucial part of understanding its role in climatic change. Here we show that sedimentary ratios of the radionuclides thorium-230 (230Th) and protactinium-231 (231Pa), which are produced in sea water and removed by particle scavenging on timescales of decades to centuries, respectively, record consistent evidence for the export of 231Pa from the deep Arctic and may indicate continuous deep-water exchange between the Arctic and Atlantic oceans throughout the past 35,000 years. Seven well-dated box-core records provide a comprehensive overview of 231Pa and 230Th burial in Arctic sediments during glacial, deglacial and interglacial conditions. Sedimentary 231Pa/230Th ratios decrease nearly linearly with increasing water depth above the core sites, indicating efficient particle scavenging in the upper water column and greater influence of removal by lateral transport at depth. Although the measured 230Th burial is in balance with its production in Arctic sea water, integrated depth profiles for all time intervals reveal a deficit in 231Pa burial that can be balanced only by lateral export in the water column. Because no enhanced sink for 231Pa has yet been found in the Arctic, our records suggest that deep-water exchange through the Fram strait may export 231Pa. Such export may have continued for the past 35,000 years, suggesting a century-scale replacement time for deep waters in the Arctic Ocean since the most recent glaciation and a persistent contribution of Arctic waters to the global ocean circulation

Communications Biophysics

Contains reports on four research projects.National Institutes of Health (Grant 5 P01 NS13126-02)National Institutes of Health (Grant 5 K04 NS00113-03)National Institutes of Health (Grant 2 ROI NS11153-02A1)National Science Foundation (Grant BNS77-16861)National Institutes of Health (Grant 5 RO1 NS10916-03)National Institutes of Health (Fellowship 1 F32 NS05327)National Institutes of Health (Grant 5 ROI NS12846-02)National Institutes of Health (Fellowship 1 F32 NS05266)Edith E. Sturgis FoundationNational Institutes of Health (Grant 1 R01 NS11680-01)National Institutes of Health (Grant 2 RO1 NS11080-04)National Institutes of Health (Grant 5 T32 GIM107301-03)National Institutes of Health (Grant 5 TOI GM01555-10