Energy Gradients Structure Microbial Communities Across Sediment Horizons in Deep Marine Sediments of the South China Sea

The deep marine subsurface is a heterogeneous environment in which the assembly of microbial communities is thought to be controlled by a combination of organic matter deposition, electron acceptor availability, and sedimentology. However, the relative importance of these factors in structuring microbial communities in marine sediments remains unclear. The South China Sea (SCS) experiences significant variability in sedimentation across the basin and features discrete changes in sedimentology as a result of episodic deposition of turbidites and volcanic ashes within lithogenic clays and siliceous or calcareous ooze deposits throughout the basin\u27s history. Deep subsurface microbial communities were recently sampled by the International Ocean Discovery Program (IODP) at three locations in the SCS with sedimentation rates of 5, 12, and 20 cm per thousand years. Here, we used Illumina sequencing of the 16S ribosomal RNA gene to characterize deep subsurface microbial communities from distinct sediment types at these sites. Communities across all sites were dominated by several poorly characterized taxa implicated in organic matter degradation, including Atribacteria, Dehalococcoidia, and Aerophobetes. Sulfate-reducing bacteria comprised only 4% of the community across sulfate-bearing sediments from multiple cores and did not change in abundance in sediments from the methanogenic zone at the site with the lowest sedimentation rate. Microbial communities were significantly structured by sediment age and the availability of sulfate as an electron acceptor in pore waters. However, microbial communities demonstrated no partitioning based on the sediment type they inhabited. These results indicate that microbial communities in the SCS are structured by the availability of electron donors and acceptors rather than sedimentological characteristics

17O NMR study of q=0 spin excitations in a nearly ideal S=1/2 1D Heisenberg antiferromagnet, Sr2CuO3, up to 800 K

We used 17O NMR to probe the uniform (wavevector q=0) electron spin excitations up to 800 K in Sr2CuO3 and separate the q=0 from the q=\pm\pi/a staggered components. Our results support the logarithmic decrease of the uniform spin susceptibility below T ~ 0.015J, where J=2200 K. From measurement of the dynamical spin susceptibility for q=0 by the spin-lattice relaxation rate 1/T_{1}, we demonstrate that the q=0 mode of spin transport is ballistic at the T=0 limit, but has a diffusion-like contribution at finite temperatures even for T << J.Comment: Submitted to Phys. Rev. Lett. 4 pages, 4 figure

Destruction of long-range antiferromagnetic order by hole doping

We study the renormalization of the staggered magnetization of a two-dimensional antiferromagnet as a function of hole doping, in the framework of the t-J model. It is shown that the motion of holes generates decay of spin waves into ''particle-hole'' pairs, which causes the destruction of the long-range magnetic order at a small hole concentration. This effect is mainly determined by the coherent motion of holes. The value obtained for the critical hole concentration, of a few percent, is consistent with experimental data for the doped copper oxide high-Tc superconductors.Comment: 12 pages, 2 figure

Nuclear spin relaxation rates in two-leg spin ladders

Using the transfer-matrix DMRG method, we study the nuclear spin relaxation rate 1/T_1 in the two-leg s=1/2 ladder as function of the inter-chain (J_{\perp}) and intra-chain (J_{|}) couplings. In particular, we separate the q_y=0 and \pi contributions and show that the later contribute significantly to the copper relaxation rate ^{63}(1/T_1) in the experimentally relevant coupling and temperature range. We compare our results to both theoretical predictions and experimental measures on ladder materials.Comment: Few modifications from the previous version 4 pages, 5 figures, accepted for publication in PR

Measuring Positive Childhood Experiences: Testing the structural and predictive validity of the Health Outcomes from Positive Experiences (HOPE) framework

OBJECTIVE: Positive childhood experiences (PCEs), that occur within secure and nurturing social environments, are fundamental to healthy physical, socio-emotional, and cognitive development. However, reliable measures of these experiences are not yet widely available. We used data from the Longitudinal Study of Australian Children (LSAC) to empirically represent and psychometrically evaluate three primary domains of PCEs defined within the Health Outcomes from Positive Experiences (HOPE) framework, specifically: (1) nurturing and supportive relationships; (2) safe and protective environments and; (3) constructive social engagement and connectedness. METHODS: LSAC is a nationally representative cohort that has followed young Australians from birth since 2004. LSAC data were used to represent the three primary HOPE-PCEs domains (0-11 years) across four interrelated PCEs constructs: (1) positive parenting, (2) trusting and supportive relationships, (3) supportive neighbourhood and home learning environments, and (4) social engagement and enjoyment. Confirmatory factor analysis was used to test the proposed four-factor structure. Predictive validity was examined through associations with mental health problems and academic difficulties at 14-15 years. RESULTS: The four-factor structure was supported by empirical data at each time point. Higher exposure to PCEs across each domain was associated with lower reporting of mental health problems (β=-0.20 to -2.05) and academic difficulties (β=-0.01 to -0.13) in adolescence. CONCLUSIONS: The four LSAC-based HOPE-PCEs have sufficient internal coherence and predictive validity to offer a potentially useful way of conceptualizing and measuring PCEs in future cohort studies and intervention trials aiming to enhance understanding of, and mitigate the negative impacts of, adverse childhood experiences

Retrospective Data Filter

In a target detection communication system, apparatus and method for determining the presence of probable targets based on contacts (which can indicate the presence of a target, noise, chatter, or objects not of interest) detected within a predefined position sector or sectors over a specified number of scans. The position of each detected contact, as a contact of interest, is compared with the positions of contacts detected at previous times or scans. Velocity profiles indicate which previous contacts support the likelihood that the contact of interest represents a target having a velocity within a defined band. The likelihood, which can be represented by a quality value, may be a function of number of contacts, timing of contacts, or both the number and timing of contacts in a given velocity profile. A preselected threshold value, which is related to false alarm rate, is compared to the most likely, or highest quality, velocity profile associated with a contact of interest. If the highest quality value exceeds the threshold value, an output is provided indicating that the contact of interest represents a probable target having a velocity within the band defined by the highest quality velocity profile

Coral-associated bacteria demonstrate phylosymbiosis and cophylogeny

Scleractinian corals' microbial symbionts influence host health, yet how coral microbiomes assembled over evolution is not well understood. We survey bacterial and archaeal communities in phylogenetically diverse Australian corals representing more than 425 million years of diversification. We show that coral microbiomes are anatomically compartmentalized in both modern microbial ecology and evolutionary assembly. Coral mucus, tissue, and skeleton microbiomes differ in microbial community composition, richness, and response to host vs. environmental drivers. We also find evidence of coral-microbe phylosymbiosis, in which coral microbiome composition and richness reflect coral phylogeny. Surprisingly, the coral skeleton represents the most biodiverse coral microbiome, and also shows the strongest evidence of phylosymbiosis. Interactions between bacterial and coral phylogeny significantly influence the abundance of four groups of bacteria-including Endozoicomonas-like bacteria, which divide into host-generalist and host-specific subclades. Together these results trace microbial symbiosis across anatomy during the evolution of a basal animal lineage

How linear features alter predator movement and the functional response

In areas of oil and gas exploration, seismic lines have been reported to alter the movement patterns of wolves (Canis lupus). We developed a mechanistic first passage time model, based on an anisotropic elliptic partial differential equation, and used this to explore how wolf movement responses to seismic lines influence the encounter rate of the wolves with their prey. The model was parametrized using 5 min GPS location data. These data showed that wolves travelled faster on seismic lines and had a higher probability of staying on a seismic line once they were on it. We simulated wolf movement on a range of seismic line densities and drew implications for the rate of predator–prey interactions as described by the functional response. The functional response exhibited a more than linear increase with respect to prey density (type III) as well as interactions with seismic line density. Encounter rates were significantly higher in landscapes with high seismic line density and were most pronounced at low prey densities. This suggests that prey at low population densities are at higher risk in environments with a high seismic line density unless they learn to avoid them

63Cu NQR evidence of dimensional crossover to anisotropic 2d regime in S= 1/2 three-leg ladder Sr2Cu3O5

We probed spin-spin correlations up to 725 K with 63Cu NQR in the S= 1/2 three-leg ladder Sr2Cu3O5. We present experimental evidence that below 300 K, weak inter-ladder coupling causes dimensional crossover of the spin-spin correlation length \xi from quasi-1d (\xi ~ 1/T) to anisotropic 2d regime (\xi \~ exp[2\pi\rho_{s}/T], where 2\pi\rho_{s} = 290 +/- 30 K is the effective spin stiffness). This is the first experimental verification of the renormalized classical behavior of the anisotropic non-linear sigma model in 2d, which has been recently proposed for the striped phase in high T_{c} cuprates.Comment: 4 pages, 3 figure

A Systems Approach for Tumor Pharmacokinetics

Recent advances in genome inspired target discovery, small molecule screens, development of biological and nanotechnology have led to the introduction of a myriad of new differently sized agents into the clinic. The differences in small and large molecule delivery are becoming increasingly important in combination therapies as well as the use of drugs that modify the physiology of tumors such as anti-angiogenic treatment. The complexity of targeting has led to the development of mathematical models to facilitate understanding, but unfortunately, these studies are often only applicable to a particular molecule, making pharmacokinetic comparisons difficult. Here we develop and describe a framework for categorizing primary pharmacokinetics of drugs in tumors. For modeling purposes, we define drugs not by their mechanism of action but rather their rate-limiting step of delivery. Our simulations account for variations in perfusion, vascularization, interstitial transport, and non-linear local binding and metabolism. Based on a comparison of the fundamental rates determining uptake, drugs were classified into four categories depending on whether uptake is limited by blood flow, extravasation, interstitial diffusion, or local binding and metabolism. Simulations comparing small molecule versus macromolecular drugs show a sharp difference in distribution, which has implications for multi-drug therapies. The tissue-level distribution differs widely in tumors for small molecules versus macromolecular biologic drugs, and this should be considered in the design of agents and treatments. An example using antibodies in mouse xenografts illustrates the different in vivo behavior. This type of transport analysis can be used to aid in model development, experimental data analysis, and imaging and therapeutic agent design.National Institutes of Health (U.S.) (grant T32 CA079443