Showing papers by "University of Notre Dame published in 2015"

The eleventh and twelfth data releases of the Sloan Digital Sky Survey: final data from SDSS-III

Abstract: The third generation of the Sloan Digital Sky Survey (SDSS-III) took data from 2008 to 2014 using the original SDSS wide-field imager, the original and an upgraded multi-object fiber-fed optical spectrograph, a new near-infrared high-resolution spectrograph, and a novel optical interferometer. All the data from SDSS-III are now made public. In particular, this paper describes Data Release 11 (DR11) including all data acquired through 2013 July, and Data Release 12 (DR12) adding data acquired through 2014 July (including all data included in previous data releases), marking the end of SDSS-III observing. Relative to our previous public release (DR10), DR12 adds one million new spectra of galaxies and quasars from the Baryon Oscillation Spectroscopic Survey (BOSS) over an additional 3000 sq. deg of sky, more than triples the number of H-band spectra of stars as part of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE), and includes repeated accurate radial velocity measurements of 5500 stars from the Multi-Object APO Radial Velocity Exoplanet Large-area Survey (MARVELS). The APOGEE outputs now include measured abundances of 15 different elements for each star. In total, SDSS-III added 2350 sq. deg of ugriz imaging; 155,520 spectra of 138,099 stars as part of the Sloan Exploration of Galactic Understanding and Evolution 2 (SEGUE-2) survey; 2,497,484 BOSS spectra of 1,372,737 galaxies, 294,512 quasars, and 247,216 stars over 9376 sq. deg; 618,080 APOGEE spectra of 156,593 stars; and 197,040 MARVELS spectra of 5,513 stars. Since its first light in 1998, SDSS has imaged over 1/3 of the Celestial sphere in five bands and obtained over five million astronomical spectra.

Advances in molecular quantum chemistry contained in the Q-Chem 4 program package

Abstract: A summary of the technical advances that are incorporated in the fourth major release of the Q-Chem quantum chemistry program is provided, covering approximately the last seven years. These include developments in density functional theory methods and algorithms, nuclear magnetic resonance (NMR) property evaluation, coupled cluster and perturbation theories, methods for electronically excited and open-shell species, tools for treating extended environments, algorithms for walking on potential surfaces, analysis tools, energy and electron transfer modelling, parallel computing capabilities, and graphical user interfaces. In addition, a selection of example case studies that illustrate these capabilities is given. These include extensive benchmarks of the comparative accuracy of modern density functionals for bonded and non-bonded interactions, tests of attenuated second order Moller–Plesset (MP2) methods for intermolecular interactions, a variety of parallel performance benchmarks, and tests of the accuracy of implicit solvation models. Some specific chemical examples include calculations on the strongly correlated Cr_2 dimer, exploring zeolite-catalysed ethane dehydrogenation, energy decomposition analysis of a charged ter-molecular complex arising from glycerol photoionisation, and natural transition orbitals for a Frenkel exciton state in a nine-unit model of a self-assembling nanotube.

Combined Measurement of the Higgs Boson Mass in pp Collisions at √s=7 and 8 TeV with the ATLAS and CMS Experiments

Abstract: A measurement of the Higgs boson mass is presented based on the combined data samples of the ATLAS and CMS experiments at the CERN LHC in the H→γγ and H→ZZ→4l decay channels. The results are obtained from a simultaneous fit to the reconstructed invariant mass peaks in the two channels and for the two experiments. The measured masses from the individual channels and the two experiments are found to be consistent among themselves. The combined measured mass of the Higgs boson is mH=125.09±0.21 (stat)±0.11 (syst) GeV.

Transformation of the Excited State and Photovoltaic Efficiency of CH3NH3PbI3 Perovskite upon Controlled Exposure to Humidified Air

Abstract: Humidity has been an important factor, in both negative and positive ways, in the development of perovskite solar cells and will prove critical in the push to commercialize this exciting new photovoltaic technology. The interaction between CH(3)NH(3)PbI(3) and H(2)O vapor is investigated by characterizing the ground-state and excited-state optical absorption properties and probing morphology and crystal structure. These undertakings reveal that H(2)O exposure does not simply cause CH(3)NH(3)PbI(3) to revert to PbI(2). It is shown that, in the dark, H(2)O is able to complex with the perovskite, forming a hydrate product similar to (CH(3)NH(3))(4)PbI(6)·2H(2)O. This causes a decrease in absorption across the visible region of the spectrum and a distinct change in the crystal structure of the material. Femtosecond transient absorption spectroscopic measurements show the effect that humidity has on the ultrafast excited state dynamics of CH(3)NH(3)PbI(3). More importantly, the deleterious effects of humidity on complete solar cells, specifically on photovoltaic efficiency and stability, are explored in the light of these spectroscopic understandings.

Microenvironment-induced PTEN loss by exosomal microRNA primes brain metastasis outgrowth

Abstract: The development of life-threatening cancer metastases at distant organs requires disseminated tumour cells' adaptation to, and co-evolution with, the drastically different microenvironments of metastatic sites. Cancer cells of common origin manifest distinct gene expression patterns after metastasizing to different organs. Clearly, the dynamic interaction between metastatic tumour cells and extrinsic signals at individual metastatic organ sites critically effects the subsequent metastatic outgrowth. Yet, it is unclear when and how disseminated tumour cells acquire the essential traits from the microenvironment of metastatic organs that prime their subsequent outgrowth. Here we show that both human and mouse tumour cells with normal expression of PTEN, an important tumour suppressor, lose PTEN expression after dissemination to the brain, but not to other organs. The PTEN level in PTEN-loss brain metastatic tumour cells is restored after leaving the brain microenvironment. This brain microenvironment-dependent, reversible PTEN messenger RNA and protein downregulation is epigenetically regulated by microRNAs from brain astrocytes. Mechanistically, astrocyte-derived exosomes mediate an intercellular transfer of PTEN-targeting microRNAs to metastatic tumour cells, while astrocyte-specific depletion of PTEN-targeting microRNAs or blockade of astrocyte exosome secretion rescues the PTEN loss and suppresses brain metastasis in vivo. Furthermore, this adaptive PTEN loss in brain metastatic tumour cells leads to an increased secretion of the chemokine CCL2, which recruits IBA1-expressing myeloid cells that reciprocally enhance the outgrowth of brain metastatic tumour cells via enhanced proliferation and reduced apoptosis. Our findings demonstrate a remarkable plasticity of PTEN expression in metastatic tumour cells in response to different organ microenvironments, underpinning an essential role of co-evolution between the metastatic cells and their microenvironment during the adaptive metastatic outgrowth. Our findings signify the dynamic and reciprocal cross-talk between tumour cells and the metastatic niche; importantly, they provide new opportunities for effective anti-metastasis therapies, especially of consequence for brain metastasis patients.

Consistent responses of soil microbial communities to elevated nutrient inputs in grasslands across the globe

Abstract: Soil microorganisms are critical to ecosystem functioning and the maintenance of soil fertility. However, despite global increases in the inputs of nitrogen (N) and phosphorus (P) to ecosystems due to human activities, we lack a predictive understanding of how microbial communities respond to elevated nutrient inputs across environmental gradients. Here we used high-throughput sequencing of marker genes to elucidate the responses of soil fungal, archaeal, and bacterial communities using an N and P addition experiment replicated at 25 globally distributed grassland sites. We also sequenced metagenomes from a subset of the sites to determine how the functional attributes of bacterial communities change in response to elevated nutrients. Despite strong compositional differences across sites, microbial communities shifted in a consistent manner with N or P additions, and the magnitude of these shifts was related to the magnitude of plant community responses to nutrient inputs. Mycorrhizal fungi and methanogenic archaea decreased in relative abundance with nutrient additions, as did the relative abundances of oligotrophic bacterial taxa. The metagenomic data provided additional evidence for this shift in bacterial life history strategies because nutrient additions decreased the average genome sizes of the bacterial community members and elicited changes in the relative abundances of representative functional genes. Our results suggest that elevated N and P inputs lead to predictable shifts in the taxonomic and functional traits of soil microbial communities, including increases in the relative abundances of faster-growing, copiotrophic bacterial taxa, with these shifts likely to impact belowground ecosystems worldwide.

Measuring the Macroeconomic Impact of Monetary Policy at the Zero Lower Bound

Abstract: This paper employs an approximation that makes a nonlinear term structure model extremely tractable for analysis of an economy operating near the zero lower bound for interest rates. We show that such a model offers an excellent description of the data compared to the benchmark model and can be used to summarize the macroeconomic effects of unconventional monetary policy. Our estimates imply that the efforts by the Federal Reserve to stimulate the economy since July 2009 succeeded in making the unemployment rate in December 2013 1% lower, which is 0.13% more compared to the historical behavior of the Fed.

Precise determination of the mass of the Higgs boson and tests of compatibility of its couplings with the standard model predictions using proton collisions at 7 and 8 TeV

Abstract: Properties of the Higgs boson with mass near 125 GeV are measured in proton-proton collisions with the CMS experiment at the LHC. Comprehensive sets of production and decay measurements are combined. The decay channels include gamma gamma, ZZ, WW, tau tau, bb, and mu mu pairs. The data samples were collected in 2011 and 2012 and correspond to integrated luminosities of up to 5.1 inverse femtobarns at 7 TeV and up to 19.7 inverse femtobarns at 8 TeV. From the high-resolution gamma gamma and ZZ channels, the mass of the Higgs boson is determined to be 125.02 +0.26 -0.27 (stat) +0.14 -0.15 (syst) GeV. For this mass value, the event yields obtained in the different analyses tagging specific decay channels and production mechanisms are consistent with those expected for the standard model Higgs boson. The combined best-fit signal relative to the standard model expectation is 1.00 +/- 0.09 (stat) +0.08 -0.07 (theo) +/- 0.07 (syst) at the measured mass. The couplings of the Higgs boson are probed for deviations in magnitude from the standard model predictions in multiple ways, including searches for invisible and undetected decays. No significant deviations are found.

Is psychology suffering from a replication crisis? What does "failure to replicate" really mean?

Abstract: Psychology has recently been viewed as facing a replication crisis because efforts to replicate past study findings frequently do not show the same result. Often, the first study showed a statistically significant result but the replication does not. Questions then arise about whether the first study results were false positives, and whether the replication study correctly indicates that there is truly no effect after all. This article suggests these so-called failures to replicate may not be failures at all, but rather are the result of low statistical power in single replication studies, and the result of failure to appreciate the need for multiple replications in order to have enough power to identify true effects. We provide examples of these power problems and suggest some solutions using Bayesian statistics and meta-analysis. Although the need for multiple replication studies may frustrate those who would prefer quick answers to psychology's alleged crisis, the large sample sizes typically needed to provide firm evidence will almost always require concerted efforts from multiple investigators. As a result, it remains to be seen how many of the recently claimed failures to replicate will be supported or instead may turn out to be artifacts of inadequate sample sizes and single study replications.

De novo identification of differentially methylated regions in the human genome

Abstract: The identification and characterisation of differentially methylated regions (DMRs) between phenotypes in the human genome is of prime interest in epigenetics. We present a novel method, DMRcate, that fits replicated methylation measurements from the Illumina HM450K BeadChip (or 450K array) spatially across the genome using a Gaussian kernel. DMRcate identifies and ranks the most differentially methylated regions across the genome based on tunable kernel smoothing of the differential methylation (DM) signal. The method is agnostic to both genomic annotation and local change in the direction of the DM signal, removes the bias incurred from irregularly spaced methylation sites, and assigns significance to each DMR called via comparison to a null model. We show that, for both simulated and real data, the predictive performance of DMRcate is superior to those of Bumphunter and Probe Lasso, and commensurate with that of comb-p. For the real data, we validate all array-derived DMRs from the candidate methods on a suite of DMRs derived from whole-genome bisulfite sequencing called from the same DNA samples, using two separate phenotype comparisons. The agglomeration of genomically localised individual methylation sites into discrete DMRs is currently best served by a combination of DM-signal smoothing and subsequent threshold specification. The findings also suggest the design of the 450K array shows preference for CpG sites that are more likely to be differentially methylated, but its overall coverage does not adequately reflect the depth and complexity of methylation signatures afforded by sequencing. For the convenience of the research community we have created a user-friendly R software package called DMRcate, downloadable from Bioconductor and compatible with existing preprocessing packages, which allows others to apply the same DMR-finding method on 450K array data.

Microbiomes in light of traits: A phylogenetic perspective.

Abstract: A focus on the phenotypic characteristics of microorganisms-their traits-offers a path for interpreting the growing amount of microbiome data. We review key aspects of microbial traits, as well as approaches used to assay their phylogenetic distribution. Recent studies reveal that microbial traits are differentially conserved across the tree of life and appear to be conserved in a hierarchical fashion, possibly linked to their biochemical complexity. These results suggest a predictive framework whereby the genetic (or taxonomic) resolution of microbiome variation among samples provides information about the traits under selection. The organizational parallels seen among human and free-living microbiomes seem to support this idea. Developments in this framework may offer predictions not only for how microbial composition responds to changing environmental conditions, but also for how these changes may alter the health or functioning in human, engineered, and environmental systems.

Extensive introgression in a malaria vector species complex revealed by phylogenomics

Abstract: Introgressive hybridization is now recognized as a widespread phenomenon, but its role in evolution remains contested. Here, we use newly available reference genome assemblies to investigate phylogenetic relationships and introgression in a medically important group of Afrotropical mosquito sibling species. We have identified the correct species branching order to resolve a contentious phylogeny and show that lineages leading to the principal vectors of human malaria were among the first to split. Pervasive autosomal introgression between these malaria vectors means that only a small fraction of the genome, mainly on the X chromosome, has not crossed species boundaries. Our results suggest that traits enhancing vectorial capacity may be gained through interspecific gene flow, including between nonsister species.

VectorBase: an updated bioinformatics resource for invertebrate vectors and other organisms related with human diseases

Abstract: VectorBase is a National Institute of Allergy and Infectious Diseases supported Bioinformatics Resource Center (BRC) for invertebrate vectors of human pathogens Now in its 11th year, VectorBase currently hosts the genomes of 35 organisms including a number of non-vectors for comparative analysis Hosted data range from genome assemblies with annotated gene features, transcript and protein expression data to population genetics including variation and insecticide-resistance phenotypes Here we describe improvements to our resource and the set of tools available for interrogating and accessing BRC data including the integration of Web Apollo to facilitate community annotation and providing Galaxy to support user-based workflows VectorBase also actively supports our community through hands-on workshops and online tutorials All information and data are freely available from our website at https://wwwvectorbaseorg/

A molecular mechanism of artemisinin resistance in Plasmodium falciparum malaria

Abstract: Artemisinins are the cornerstone of anti-malarial drugs. Emergence and spread of resistance to them raises risk of wiping out recent gains achieved in reducing worldwide malaria burden and threatens future malaria control and elimination on a global level. Genome-wide association studies (GWAS) have revealed parasite genetic loci associated with artemisinin resistance. However, there is no consensus on biochemical targets of artemisinin. Whether and how these targets interact with genes identified by GWAS, remains unknown. Here we provide biochemical and cellular evidence that artemisinins are potent inhibitors of Plasmodium falciparum phosphatidylinositol-3-kinase (PfPI3K), revealing an unexpected mechanism of action. In resistant clinical strains, increased PfPI3K was associated with the C580Y mutation in P. falciparum Kelch13 (PfKelch13), a primary marker of artemisinin resistance. Polyubiquitination of PfPI3K and its binding to PfKelch13 were reduced by the PfKelch13 mutation, which limited proteolysis of PfPI3K and thus increased levels of the kinase, as well as its lipid product phosphatidylinositol-3-phosphate (PI3P). We find PI3P levels to be predictive of artemisinin resistance in both clinical and engineered laboratory parasites as well as across non-isogenic strains. Elevated PI3P induced artemisinin resistance in absence of PfKelch13 mutations, but remained responsive to regulation by PfKelch13. Evidence is presented for PI3P-dependent signalling in which transgenic expression of an additional kinase confers resistance. Together these data present PI3P as the key mediator of artemisinin resistance and the sole PfPI3K as an important target for malaria elimination.

Exosomes and other extracellular vesicles in host–pathogen interactions

Abstract: An effective immune response requires the engagement of host receptors by pathogen-derived molecules and the stimulation of an appropriate cellular response. Therefore, a crucial factor in our ability to control an infection is the accessibility of our immune cells to the foreign material. Exosomes—which are extracellular vesicles that function in intercellular communication—may play a key role in the dissemination of pathogen- as well as host-derived molecules during infection. In this review, we highlight the composition and function of exosomes and other extracellular vesicles produced during viral, parasitic, fungal and bacterial infections and describe how these vesicles could function to either promote or inhibit host immunity.

Mechanical properties of gray and white matter brain tissue by indentation.

Abstract: The mammalian brain is composed of an outer layer of gray matter, consisting of cell bodies, dendrites, and unmyelinated axons, and an inner core of white matter, consisting primarily of myelinated axons Recent evidence suggests that microstructural differences between gray and white matter play an important role during neurodevelopment While brain tissue as a whole is rheologically well characterized, the individual features of gray and white matter remain poorly understood Here we quantify the mechanical properties of gray and white matter using a robust, reliable, and repeatable method, flat-punch indentation To systematically characterize gray and white matter moduli for varying indenter diameters, loading rates, holding times, post-mortem times, and locations we performed a series of n = 192 indentation tests We found that indenting thick, intact coronal slices eliminates the common challenges associated with small specimens: it naturally minimizes boundary effects, dehydration, swelling, and structural degradation When kept intact and hydrated, brain slices maintained their mechanical characteristics with standard deviations as low as 5% throughout the entire testing period of five days post mortem White matter, with an average modulus of 1895 kPa±0592 kPa, was on average 39% stiffer than gray matter, p 001 , with an average modulus of 1389 kPa±0289 kPa, and displayed larger regional variations It was also more viscous than gray matter and responded less rapidly to mechanical loading Understanding the rheological differences between gray and white matter may have direct implications on diagnosing and understanding the mechanical environment in neurodevelopment and neurological disorders

Abundances, Stellar Parameters, and Spectra From the SDSS-III/APOGEE Survey

Abstract: The SDSS-III/Apache Point Observatory Galactic Evolution Experiment (APOGEE) survey operated from 2011–2014 using the APOGEE spectrograph, which collects high-resolution (R ~ 22,500), near-IR (1.51–1.70 µm) spectra with a multiplexing (300 fiber-fed objects) capability. We describe the survey data products that are publicly available, which include catalogs with radial velocity, stellar parameters, and 15 elemental abundances for over 150,000 stars, as well as the more than 500,000 spectra from which these quantities are derived. Calibration relations for the stellar parameters (Teff , log g, [M/H], [a/M]) and abundances (C, N, O, Na, Mg, Al, Si, S, K, Ca, Ti, V, Mn, Fe, Ni) are presented and discussed. The internal scatter of the abundances within clusters indicates that abundance precision is generally between 0.05 and 0.09 dex across a broad temperature range; it is smaller for some elemental abundances within more limited ranges and at high signal-to-noise ratio. We assess the accuracy of the abundances using comparison of mean cluster metallicities with literature values, APOGEE observations of the solar spectrum and of Arcturus, comparison of individual star abundances with other measurements, and consideration of the locus of derived parameters and abundances of the entire sample, and find that it is challenging to determine the absolute abundance scale; external accuracy may be good to 0.1–0.2 dex. Uncertainties may be larger at cooler temperatures (Teff < 4000 K). Access to the public data release and data products is described, and some guidance for using the data products is provided.

Highly evolvable malaria vectors: The genomes of 16 Anopheles mosquitoes

Abstract: Variation in vectorial capacity for human malaria among Anopheles mosquito species is determined by many factors, including behavior, immunity, and life history To investigate the genomic basis of vectorial capacity and explore new avenues for vector control, we sequenced the genomes of 16 anopheline mosquito species from diverse locations spanning ~100 million years of evolution Comparative analyses show faster rates of gene gain and loss, elevated gene shuffling on the X chromosome, and more intron losses, relative to Drosophila Some determinants of vectorial capacity, such as chemosensory genes, do not show elevated turnover but instead diversify through protein-sequence changes This dynamism of anopheline genes and genomes may contribute to their flexible capacity to take advantage of new ecological niches, including adapting to humans as primary hosts

Observation of the rare B-s(0)->mu(+)mu(-) decay from the combined analysis of CMS and LHCb data

Abstract: The standard model of particle physics describes the fundamental particles and their interactions via the strong, electromagnetic and weak forces. It provides precise predictions for measurable quantities that can be tested experimentally. The probabilities, or branching fractions, of the strange B meson (B-s(0)) and the B-0 meson decaying into two oppositely charged muons (mu(+) and mu(-)) are especially interesting because of their sensitivity to theories that extend the standard model. The standard model predicts that the B-s(0)->mu(+)mu(-) and B-0 ->mu(+)mu(-) decays are very rare, with about four of the former occurring for every billion B-s(0) mesons produced, and one of the latter occurring for every ten billion B-0 mesons(1). A difference in the observed branching fractions with respect to the predictions of the standard model would provide a direction in which the standard model should be extended. Before the Large Hadron Collider (LHC) at CERN2 started operating, no evidence for either decay mode had been found. Upper limits on the branching fractions were an order of magnitude above the standard model predictions. The CMS (Compact Muon Solenoid) and LHCb(Large Hadron Collider beauty) collaborations have performed a joint analysis of the data from proton-proton collisions that they collected in 2011 at a centre-of-mass energy of seven teraelectronvolts and in 2012 at eight teraelectronvolts. Here we report the first observation of the B-s(0)->mu(+)mu(-) decay, with a statistical significance exceeding six standard deviations, and the best measurement so far of its branching fraction. Furthermore, we obtained evidence for the B-0 ->mu(+)mu(-) decay with a statistical significance of three standard deviations. Both measurements are statistically compatible with standard model predictions and allow stringent constraints to be placed on theories beyond the standard model. The LHC experiments will resume taking data in 2015, recording proton-proton collisions at a centre-of-mass energy of 13 teraelectronvolts, which will approximately double the production rates of B-s(0) and B-0 mesons and lead to further improvements in the precision of these crucial tests of the standard model.

Inferring social status and rich club effects in enterprise communication networks.

Abstract: Social status, defined as the relative rank or position that an individual holds in a social hierarchy, is known to be among the most important motivating forces in social behaviors. In this paper, we consider the notion of status from the perspective of a position or title held by a person in an enterprise. We study the intersection of social status and social networks in an enterprise. We study whether enterprise communication logs can help reveal how social interactions and individual status manifest themselves in social networks. To that end, we use two enterprise datasets with three communication channels — voice call, short message, and email — to demonstrate the social-behavioral differences among individuals with different status. We have several interesting findings and based on these findings we also develop a model to predict social status. On the individual level, high-status individuals are more likely to be spanned as structural holes by linking to people in parts of the enterprise networks that are otherwise not well connected to one another. On the community level, the principle of homophily, social balance and clique theory generally indicate a “rich club” maintained by high-status individuals, in the sense that this community is much more connected, balanced and dense. Our model can predict social status of individuals with 93% accuracy.

A Review and Meta-Analysis of Multimodal Affect Detection Systems

Abstract: Affect detection is an important pattern recognition problem that has inspired researchers from several areas The field is in need of a systematic review due to the recent influx of Multimodal (MM) affect detection systems that differ in several respects and sometimes yield incompatible results This article provides such a survey via a quantitative review and meta-analysis of 90 peer-reviewed MM systems The review indicated that the state of the art mainly consists of person-dependent models (622p of systems) that fuse audio and visual (556p) information to detect acted (522p) expressions of basic emotions and simple dimensions of arousal and valence (645p) with feature- (389p) and decision-level (356p) fusion techniques However, there were also person-independent systems that considered additional modalities to detect nonbasic emotions and complex dimensions using model-level fusion techniques The meta-analysis revealed that MM systems were consistently (85p of systems) more accurate than their best unimodal counterparts, with an average improvement of 983p (median of 660p) However, improvements were three times lower when systems were trained on natural (459p) versus acted data (127p) Importantly, MM accuracy could be accurately predicted (cross-validated R2 of 0803) from unimodal accuracies and two system-level factors Theoretical and applied implications and recommendations are discussed

Search for dark matter, extra dimensions, and unparticles in monojet events in proton–proton collisions at √s = 8 TeV

Abstract: Results are presented from a search for particle dark matter (DM), extra dimensions, and unparticles using events containing a jet and an imbalance in transverse momentum. The data were collected by the CMS detector in proton-proton collisions at the LHC and correspond to an integrated luminosity of 19.7 fb$^{-1}$ at a centre-of-mass energy of 8 TeV. The number of observed events is found to be consistent with the standard model prediction. Limits are placed on the DM-nucleon scattering cross section as a function of the DM particle mass for spin-dependent and spin-independent interactions. Limits are also placed on the scale parameter $M_\mathrm{D}$ in the ADD model of large extra dimensions, and on the unparticle model parameter $\Lambda_\mathrm{U}$. The constraints on ADD models and unparticles are the most stringent limits in this channel and those on the DM-nucleon scattering cross section are an improvement over previous collider results.

Social networks predict gut microbiome composition in wild baboons.

Abstract: The digestive system is home to a complex community of microbes—known as the gut microbiome—that contributes to our health and wellbeing by digesting food, producing essential vitamins, and preventing the growth of harmful bacteria. The recent development of rapid genome sequencing techniques has made it much easier to identify the species of microbes found in the gut microbiome, and how this microbiome's composition varies between individuals. Studies in humans and other primates suggest that direct contact during social interactions may alter the composition of the gut microbiome in an individual. This could explain why there is a strong association between social interactions and health in humans and other social animals. However, similarities in the gut microbiomes of individuals within a social group could also be due to a shared diet or a common environment. The information collected during long-term studies of wild primates offers an opportunity to analyze and assess the influence of diet, environment and social interaction on the gut microbiome. Here, Tung et al. studied the gut microbiomes of 48 wild baboons belonging to two different social groups in Amboseli, Kenya. Using a technique called shotgun metagenomic sequencing, they sequenced DNA extracted from samples of feces collected from individual baboons. The sequence data revealed that an individual's social group and social network can predict the species found in its gut microbiome. This remained the case even when other factors—such as diet, kinship, and shared environments—were taken into account. Tung et al.'s findings suggest that direct physical contact during social interactions may be important in transmitting gut microbiomes between members of the same social group. However, scientists still don't know whether this exchange is good or bad for the health of the baboons. Future work will try to understand whether baboons benefit from acquiring gut microbes from their group members, and if the gut microbes of some social groups are better than others.

Constraints on the spin-parity and anomalous HVV couplings of the Higgs boson in proton collisions at 7 and 8 TeV

Abstract: The study of the spin-parity and tensor structure of the interactions of the recently discovered Higgs boson is performed using the H to ZZ, Z gamma*, gamma* gamma* to 4 l, H to WW to l nu l nu, and H to gamma gamma decay modes. The full dataset recorded by the CMS experiment during the LHC Run 1 is used, corresponding to an integrated luminosity of up to 5.1 inverse femtobarns at a center-of-mass energy of 7 TeV and up to 19.7 inverse femtobarns at 8 TeV. A wide range of spin-two models is excluded at a 99% confidence level or higher, or at a 99.87% confidence level for the minimal gravity-like couplings, regardless of whether assumptions are made on the production mechanism. Any mixed-parity spin-one state is excluded in the ZZ and WW modes at a greater than 99.999% confidence level. Under the hypothesis that the resonance is a spin-zero boson, the tensor structure of the interactions of the Higgs boson with two vector bosons ZZ, Z gamma, gamma gamma, and WW is investigated and limits on eleven anomalous contributions are set. Tighter constraints on anomalous HVV interactions are obtained by combining the HZZ and HWW measurements. All observations are consistent with the expectations for the standard model Higgs boson with the quantum numbers J[PC]=0[++].

Independent Emergence of Artemisinin Resistance Mutations Among Plasmodium falciparum in Southeast Asia

Abstract: The emergence of artemisinin-resistant Plasmodium falciparum in Southeast Asia threatens malaria treatment efficacy. Mutations in a kelch protein encoded on P. falciparum chromosome 13 (K13) have been associated with resistance in vitro and in field samples from Cambodia.P. falciparum infections from artesunate efficacy trials in Bangladesh, Cambodia, Laos, Myanmar, and Vietnam were genotyped at 33 716 genome-wide single-nucleotide polymorphisms (SNPs). Linear mixed models were used to test associations between parasite genotypes and parasite clearance half-lives following artesunate treatment. K13 mutations were tested for association with artemisinin resistance, and extended haplotypes on chromosome 13 were examined to determine whether mutations arose focally and spread or whether they emerged independently.The presence of nonreference K13 alleles was associated with prolonged parasite clearance half-life (P = 1.97 × 10(-12)). Parasites with a mutation in any of the K13 kelch domains displayed longer parasite clearance half-lives than parasites with wild-type alleles. Haplotype analysis revealed both population-specific emergence of mutations and independent emergence of the same mutation in different geographic areas.K13 appears to be a major determinant of artemisinin resistance throughout Southeast Asia. While we found some evidence of spreading resistance, there was no evidence of resistance moving westward from Cambodia into Myanmar.

On disaggregating between-person and within-person effects with longitudinal data using multilevel models.

Abstract: This article extends current discussion of how to disaggregate between-person and within-person effects with longitudinal data using multilevel models. Our main focus is on the 2 issues of centering and detrending. Conceptual and analytical work demonstrates the similarities and differences among 3 centering approaches (no centering, grand-mean centering, and person-mean centering) and the relations and differences among various detrending approaches (no detrending, detrending X only, detrending Y only, and detrending both X and Y). Two real data analysis examples in psychology are provided to illustrate the differences in the results of using different centering and detrending methods for the disaggregation of between- and within-person effects. Simulation studies were conducted to further compare the various centering and detrending approaches under a wider span of conditions. Recommendations of how to perform centering, whether detrending is needed or not, and how to perform detrending if needed are made and discussed.

Ecosystem Consequences of Changing Inputs of Terrestrial Dissolved Organic Matter to Lakes: Current Knowledge and Future Challenges

Abstract: Lake ecosystems and the services that they provide to people are profoundly influenced by dissolved organic matter derived from terrestrial plant tissues. These terrestrial dissolved organic matter (tDOM) inputs to lakes have changed substantially in recent decades, and will likely continue to change. In this paper, we first briefly review the substantial literature describing tDOM effects on lakes and ongoing changes in tDOM inputs. We then identify and provide examples of four major challenges which limit predictions about the implications of tDOM change for lakes, as follows: First, it is currently difficult to forecast future tDOM inputs for particular lakes or lake regions. Second, tDOM influences ecosystems via complex, interacting, physical-chemical-biological effects and our holistic understanding of those effects is still rudimentary. Third, non-linearities and thresholds in relationships between tDOM inputs and ecosystem processes have not been well described. Fourth, much understanding of tDOM effects is built on comparative studies across space that may not capture likely responses through time. We conclude by identifying research approaches that may be important for overcoming those challenges in order to provide policy- and management-relevant predictions about the implications of changing tDOM inputs for lakes.

Improving the representation of hydrologic processes in Earth System Models

Abstract: Many of the scientific and societal challenges in understanding and preparing for global environmental change rest upon our ability to understand and predict the water cycle change at large river basin, continent, and global scales. However, current large-scale models, such as the land components of Earth System Models (ESMs), do not yet represent the terrestrial water cycle in a fully integrated manner or resolve the finer-scale processes that can dominate large-scale water budgets. This paper reviews the current representation of hydrologic processes in ESMs and identifies the key opportunities for improvement. This review suggests that (1) the development of ESMs has not kept pace with modeling advances in hydrology, both through neglecting key processes (e.g., groundwater) and neglecting key aspects of spatial variability and hydrologic connectivity; and (2) many modeling advances in hydrology can readily be incorporated into ESMs and substantially improve predictions of the water cycle. Accelerating modeling advances in ESMs requires comprehensive hydrologic benchmarking activities, in order to systematically evaluate competing modeling alternatives, understand model weaknesses, and prioritize model development needs. This demands stronger collaboration, both through greater engagement of hydrologists in ESM development and through more detailed evaluation of ESM processes in research watersheds. Advances in themore » representation of hydrologic process in ESMs can substantially improve energy, carbon and nutrient cycle prediction capabilities through the fundamental role the water cycle plays in regulating these cycles.« less