Detecting multivariate interactions in spatial point patterns with Gibbs models and variable selection

We propose a method for detecting significant interactions in very large multivariate spatial point patterns. This methodology develops high dimensional data understanding in the point process setting. The method is based on modelling the patterns using a flexible Gibbs point process model to directly characterise point-to-point interactions at different spatial scales. By using the Gibbs framework significant interactions can also be captured at small scales. Subsequently, the Gibbs point process is fitted using a pseudo-likelihood approximation, and we select significant interactions automatically using the group lasso penalty with this likelihood approximation. Thus we estimate the multivariate interactions stably even in this setting. We demonstrate the feasibility of the method with a simulation study and show its power by applying it to a large and complex rainforest plant population data set of 83 species

Estimating stellar oscillation-related parameters and their uncertainties with the moment method

The moment method is a well known mode identification technique in asteroseismology (where `mode' is to be understood in an astronomical rather than in a statistical sense), which uses a time series of the first 3 moments of a spectral line to estimate the discrete oscillation mode parameters l and m. The method, contrary to many other mode identification techniques, also provides estimates of other important continuous parameters such as the inclination angle alpha, and the rotational velocity v_e. We developed a statistical formalism for the moment method based on so-called generalized estimating equations (GEE). This formalism allows the estimation of the uncertainty of the continuous parameters taking into account that the different moments of a line profile are correlated and that the uncertainty of the observed moments also depends on the model parameters. Furthermore, we set up a procedure to take into account the mode uncertainty, i.e., the fact that often several modes (l,m) can adequately describe the data. We also introduce a new lack of fit function which works at least as well as a previous discriminant function, and which in addition allows us to identify the sign of the azimuthal order m. We applied our method to the star HD181558, using several numerical methods, from which we learned that numerically solving the estimating equations is an intensive task. We report on the numerical results, from which we gain insight in the statistical uncertainties of the physical parameters involved in the moment method.Comment: The electronic online version from the publisher can be found at http://www.blackwell-synergy.com/doi/abs/10.1111/j.1467-9876.2005.00487.

Combinatorial quorum sensing allows bacteria to resolve their social and physical environment

Quorum sensing (QS) is a cell–cell communication system that controls gene expression in many bacterial species, mediated by diffusible signal molecules. Although the intracellular regulatory mechanisms of QS are often well-understood, the functional roles of QS remain controversial. In particular, the use of multiple signals by many bacterial species poses a serious challenge to current functional theories. Here, we address this challenge by showing that bacteria can use multiple QS signals to infer both their social (density) and physical (mass-transfer) environment. Analytical and evolutionary simulation models show that the detection of, and response to, complex social/physical contrasts requires multiple signals with distinct half-lives and combinatorial (nonadditive) responses to signal concentrations. We test these predictions using the opportunistic pathogen Pseudomonas aeruginosa and demonstrate significant differences in signal decay betweeallyn its two primary signal molecules, as well as diverse combinatorial responses to dual-signal inputs. QS is associated with the control of secreted factors, and we show that secretome genes are preferentially controlled by synergistic “AND-gate” responses to multiple signal inputs, ensuring the effective expression of secreted factors in high-density and low mass-transfer environments. Our results support a new functional hypothesis for the use of multiple signals and, more generally, show that bacteria are capable of combinatorial communication

Deep three-dimensional solid-state qubit arrays with long-lived spin coherence

Nitrogen-vacancy centers (NVCs) in diamond show promise for quantum computing, communication, and sensing. However, the best current method for entangling two NVCs requires that each one is in a separate cryostat, which is not scalable. We show that single NVCs can be laser written 6–15-µm deep inside of a diamond with spin coherence times that are an order of magnitude longer than previous laser-written NVCs and at least as long as naturally occurring NVCs. This depth is suitable for integration with solid immersion lenses or optical cavities and we present depth-dependent T2 measurements. 200 000 of these NVCs would fit into one diamond

Careful prior specification avoids incautious inference for log-Gaussian Cox point processes

The BCI forest dynamics research project was founded by S.P. Hubbell and R.B. Foster and is now managed by R. Condit, S. Lao, and R. Perez under the Center for Tropical Forest Science and the Smithsonian Tropical Research in Panama. Numerous organizations have provided funding, principally the U.S. National Science Foundation, and hundreds of field workers have contributed. The data used can be requested and generally granted at http://ctfs.si.edudatarequest. Kriged estimates for concentration of the soil nutrients were downloaded from http://ctfs.si.edu/webatlas/datasets/bci/soilmaps/BCIsoil.html. We acknowledge the principal investigators that were responsible for collecting and analysing the soil maps (Jim Dallin, Robert John, Kyle Harms, Robert Stallard and Joe Yavitt), the funding sources (NSF DEB021104,021115, 0212284,0212818 and OISE 0314581, STRI Soils Initiative and CTFS) and field assistants (Paolo Segre and Juan Di Trani).Peer reviewedPostprin

Social evolution in micro-organisms and a Trojan horse approach to medical intervention strategies

Medical science is typically pitted against the evolutionary forces acting upon infective populations of bacteria. As an alternative strategy, we could exploit our growing understanding of population dynamics of social traits in bacteria to help treat bacterial disease. In particular, population dynamics of social traits could be exploited to introduce less virulent strains of bacteria, or medically beneficial alleles into infective populations. We discuss how bacterial strains adopting different social strategies can invade a population of cooperative wild-type, considering public good cheats, cheats carrying medically beneficial alleles (Trojan horses) and cheats carrying allelopathic traits (anti-competitor chemical bacteriocins or temperate bacteriophage viruses). We suggest that exploitation of the ability of cheats to invade cooperative, wild-type populations is a potential new strategy for treating bacterial disease

Approximate Bayesian Computation: a nonparametric perspective

Approximate Bayesian Computation is a family of likelihood-free inference techniques that are well-suited to models defined in terms of a stochastic generating mechanism. In a nutshell, Approximate Bayesian Computation proceeds by computing summary statistics s_obs from the data and simulating summary statistics for different values of the parameter theta. The posterior distribution is then approximated by an estimator of the conditional density g(theta|s_obs). In this paper, we derive the asymptotic bias and variance of the standard estimators of the posterior distribution which are based on rejection sampling and linear adjustment. Additionally, we introduce an original estimator of the posterior distribution based on quadratic adjustment and we show that its bias contains a fewer number of terms than the estimator with linear adjustment. Although we find that the estimators with adjustment are not universally superior to the estimator based on rejection sampling, we find that they can achieve better performance when there is a nearly homoscedastic relationship between the summary statistics and the parameter of interest. To make this relationship as homoscedastic as possible, we propose to use transformations of the summary statistics. In different examples borrowed from the population genetics and epidemiological literature, we show the potential of the methods with adjustment and of the transformations of the summary statistics. Supplemental materials containing the details of the proofs are available online

Vaccine uptake and SARS-CoV-2 antibody prevalence among 207,337 adults during May 2021 in England: REACT-2 study

Background The programme to vaccinate adults in England has been rapidly implemented since it began in December 2020. The community prevalence of SARS-CoV-2 anti-spike protein antibodies provides an estimate of total cumulative response to natural infection and vaccination. We describe the distribution of SARS-CoV-2 IgG antibodies in adults in England in May 2021 at a time when approximately 7 in 10 adults had received at least one dose of vaccine. Methods Sixth round of REACT-2 (REal-time Assessment of Community Transmission-2), a cross-sectional random community survey of adults in England, from 12 to 25 May 2021; 207,337 participants completed questionnaires and self-administered a lateral flow immunoassay test producing a positive or negative result. Results Vaccine coverage with one or more doses, weighted to the adult population in England, was 72.9% (95% confidence interval 72.7-73.0), varying by age from 25.1% (24.5- 25.6) of those aged 18 to 24 years, to 99.2% (99.1-99.3) of those 75 years and older. In adjusted models, odds of vaccination were lower in men (odds ratio [OR] 0.89 [0.85-0.94]) than women, and in people of Black (0.41 [0.34-0.49]) compared to white ethnicity. There was higher vaccine coverage in the least deprived and highest income households. People who reported a history of COVID-19 were less likely to be vaccinated (OR 0.61 [0.55-0.67]). There was high coverage among health workers (OR 9.84 [8.79-11.02] and care workers (OR 4.17 [3.20-5.43]) compared to non-key workers, but lower in hospitality and retail workers (OR 0.73 [0.64-0.82] and 0.77 [0.70-0.85] respectively) after adjusting for age and key covariates

Environmental modification via a quorum sensing molecule influences the social landscape of siderophore production

Bacteria produce a wide variety of exoproducts that favourably modify their environment and increase their fitness. These are often termed ‘public goods’ because they are costly for individuals to produce and can be exploited by non-producers (‘cheats’). The outcome of conflict over public goods is dependent upon the prevailing environment and the phenotype of the individuals in competition. Many bacterial species use quorum sensing (QS) signalling molecules to regulate the production of public goods. QS therefore determines the cooperative phenotype of individuals, and influences conflict over public goods. In addition to their regulatory functions, many QS molecules have additional properties that directly modify the prevailing environment. This leads to the possibility that QS molecules could influence conflict over public goods indirectly through non-signalling effects, and the impact of this on social competition has not previously been explored. The Pseudomonas aeruginosa QS signal molecule PQS is a powerful chelator of iron which can cause an iron starvation response. Here we show that PQS stimulates a concentration-dependent increase in the cooperative production of iron scavenging siderophores, resulting in an increase in the relative fitness of non-producing siderophore cheats. This is likely due to an increased cost of siderophore output by producing cells and a concurrent increase in the shared benefits, which accrue to both producers and cheats. Although PQS can be a beneficial signalling molecule for P. aeruginosa, our data suggests that it can also render a siderophore-producing population vulnerable to competition from cheating strains. More generally our results indicate that the production of one social trait can indirectly affect the costs and benefits of another social trait

The use of continuous electronic prescribing data to infer trends in antimicrobial consumption and estimate the impact of stewardship interventions in hospitalized children.

BACKGROUND: Understanding antimicrobial consumption is essential to mitigate the development of antimicrobial resistance, yet robust data in children are sparse and methodologically limited. Electronic prescribing systems provide an important opportunity to analyse and report antimicrobial consumption in detail. OBJECTIVES: We investigated the value of electronic prescribing data from a tertiary children's hospital to report temporal trends in antimicrobial consumption in hospitalized children and compare commonly used metrics of antimicrobial consumption. METHODS: Daily measures of antimicrobial consumption [days of therapy (DOT) and DDDs] were derived from the electronic prescribing system between 2010 and 2018. Autoregressive moving-average models were used to infer trends and the estimates were compared with simulated point prevalence surveys (PPSs). RESULTS: More than 1.3 million antimicrobial administrations were analysed. There was significant daily and seasonal variation in overall consumption, which reduced annually by 1.77% (95% CI 0.50% to 3.02%). Relative consumption of meropenem decreased by 6.6% annually (95% CI -3.5% to 15.8%) following the expansion of the hospital antimicrobial stewardship programme. DOT and DDDs exhibited similar trends for most antimicrobials, though inconsistencies were observed where changes to dosage guidelines altered consumption calculation by DDDs, but not DOT. PPS simulations resulted in estimates of change over time, which converged on the model estimates, but with much less precision. CONCLUSIONS: Electronic prescribing systems offer significant opportunities to better understand and report antimicrobial consumption in children. This approach to modelling administration data overcomes the limitations of using interval data and dispensary data. It provides substantially more detailed inferences on prescribing patterns and the potential impact of stewardship interventions