Fitting Effective Diffusion Models to Data Associated with a "Glassy Potential": Estimation, Classical Inference Procedures and Some Heuristics

A variety of researchers have successfully obtained the parameters of low dimensional diffusion models using the data that comes out of atomistic simulations. This naturally raises a variety of questions about efficient estimation, goodness-of-fit tests, and confidence interval estimation. The first part of this article uses maximum likelihood estimation to obtain the parameters of a diffusion model from a scalar time series. I address numerical issues associated with attempting to realize asymptotic statistics results with moderate sample sizes in the presence of exact and approximated transition densities. Approximate transition densities are used because the analytic solution of a transition density associated with a parametric diffusion model is often unknown.I am primarily interested in how well the deterministic transition density expansions of Ait-Sahalia capture the curvature of the transition density in (idealized) situations that occur when one carries out simulations in the presence of a "glassy" interaction potential. Accurate approximation of the curvature of the transition density is desirable because it can be used to quantify the goodness-of-fit of the model and to calculate asymptotic confidence intervals of the estimated parameters. The second part of this paper contributes a heuristic estimation technique for approximating a nonlinear diffusion model. A "global" nonlinear model is obtained by taking a batch of time series and applying simple local models to portions of the data. I demonstrate the technique on a diffusion model with a known transition density and on data generated by the Stochastic Simulation Algorithm.Comment: 30 pages 10 figures Submitted to SIAM MMS (typos removed and slightly shortened

Interleukin-6 and Associated Cytokine Responses to An Acute Bout of High-intensity Interval Exercise: the Effect of Exercise Intensity and Volume

Acute increases in interleukin (IL)-6 following prolonged exercise are associated with the induction of a transient anti-inflammatory state (e.g., increases in IL-10) that is partly responsible for the health benefits of regular exercise. The purposes of this study were to investigate the IL-6–related inflammatory response to high-intensity interval exercise (HIIE) and to determine the impact of exercise intensity and volume on this response. Ten participants (5 males and 5 females) completed 3 exercise bouts of contrasting intensity and volume (LOW, MOD, and HIGH). The HIGH protocol was based upon standard HIIE protocols, while the MOD and LOW protocols were designed to enable a comparison of exercise intensity and volume with a fixed duration. Inflammatory cytokine concentrations were measured in plasma (IL-6, IL-10) and also determined the level of gene expression (IL-6, IL-10, and IL-4R) in peripheral blood. The plasma IL-6 response to exercise (reported as fold changes) was significantly greater in HIGH (2.70 ± 1.51) than LOW (1.40 ± 0.32) (P = 0.04) and was also positively correlated to the mean exercise oxygen uptake (r = 0.54, P < 0.01). However, there was no change in anti-inflammatory IL-10 or IL-4R responses in plasma or at the level of gene expression. HIIE caused a significant increase in IL-6 and was greater than that seen in low-intensity exercise of the same duration. The increases in IL-6 were relatively small in magnitude, and appear to have been insufficient to induce the acute systemic anti-inflammatory effects, which are evident following longer duration exercise

Spatiotemporal variation in drivers of parasitism in a wild wood mouse population

1. Host‐parasite interactions in nature are driven by a range of factors across several ecological scales, so observed relationships are often context‐dependent. Importantly, if these factors vary across space and time, practical sampling limitations can limit or bias inferences, and the relative importance of different drivers can be hard to discern.2. Here we ask to what degree environmental, host, and within‐host influences on parasitism are shaped by spatiotemporal variation. We use a replicated, longitudinal dataset of &gt;1500 individual wood mice (Apodemus sylvaticus) encompassing 6 years of sampling across 5 different woodland sites and investigate drivers of infection intensity with a highly prevalent gastrointestinal nematode, Heligmosomoides polygyrus.3. We used a Bayesian modelling approach to further quantify if and how each factor varied in space and time. Finally, we examined the extent to which a lack of spatially or temporally replication (i.e., within single years or single sites) would affect which drivers were found to predict H. polygyrus infection. 4. Season, host body condition, and sex were the three most important determinants of infection intensity; however, the strength and even direction of these effects varied in time, but not in space. Models fit to single year and site replicates in many cases showed sparse and variable detection of effects of factors investigated, highlighting the benefits of long‐term sampling for separating meaningful ecological variation from sampling variation.5. These results highlight the importance of accounting for spatiotemporal variation in determining what drives disease dynamics and the need to incorporate replication in both time and space when designing sampling regimes. Furthermore, we suggest that embracing, rather than simply controlling for, spatiotemporal variation can reveal meaningful variation for understanding the factors impacting parasitism (e.g. season and host factors) which can improve predictions of how wildlife health will respond to change

Green function techniques in the treatment of quantum transport at the molecular scale

The theoretical investigation of charge (and spin) transport at nanometer length scales requires the use of advanced and powerful techniques able to deal with the dynamical properties of the relevant physical systems, to explicitly include out-of-equilibrium situations typical for electrical/heat transport as well as to take into account interaction effects in a systematic way. Equilibrium Green function techniques and their extension to non-equilibrium situations via the Keldysh formalism build one of the pillars of current state-of-the-art approaches to quantum transport which have been implemented in both model Hamiltonian formulations and first-principle methodologies. We offer a tutorial overview of the applications of Green functions to deal with some fundamental aspects of charge transport at the nanoscale, mainly focusing on applications to model Hamiltonian formulations.Comment: Tutorial review, LaTeX, 129 pages, 41 figures, 300 references, submitted to Springer series "Lecture Notes in Physics

Physical activity attenuates the influence of FTO variants on obesity risk: A meta-analysis of 218,166 adults and 19,268 children

Background: The FTO gene harbors the strongest known susceptibility locus for obesity. While many individual studies have suggested that physical activity (PA) may attenuate the effect of FTO on obesity risk, other studies have not been able to confirm this interaction. To confirm or refute unambiguously whether PA attenuates the association of FTO with obesity risk, we meta-analyzed data from 45 studies of adults (n = 218,166) and nine studies of children and adolescents (n = 19,268). Methods and Findings: All studies identified to have data on the FTO rs9939609 variant (or any proxy [r2>0.8]) and PA were invited to participate, regardless of ethnicity or age of the participants. PA was standardized by categorizing it into a dichotomous variable (physically inactive versus active) in each study. Overall, 25% of adults and 13% of children were categorized as inactive. Interaction analyses were performed within each study by including the FTO×PA interaction term in an additive model, adjusting for age and sex. Subsequently, random effects meta-analysis was used to pool the interaction terms. In adults, the minor (A-) allele of rs9939609 increased the odds of obesity by 1.23-fold/allele (95% CI 1.20-1.26), but PA attenuated this effect (pinteraction= 0.001). More specifically, the minor allele of rs9939609 increased the odds of obesity less in the physically active group (odds ratio = 1.22/allele, 95% CI 1.19-1.25) than in the inactive group (odds ratio = 1.30/allele, 95% CI 1.24-1.36). No such interaction was found in children and adolescents. Concl

Influence of Powder Particle Size Distributions on Surface Topography of Polymer Laser Powder Bed Fusion Parts

The morphology and particle size distribution of commercial polymer powders for Laser based Powder Bed Fusion (PBF-LB) spans a wide range. This is a consequence of the traditional manufacturing methods of milling and grinding. In theory, a combination of large and fine powder particles provides dense powder packing which in turn allows for good processability and parts. This study focuses on correlating powder properties and part quality for parts manufactured with 3 different size distributions, i.e. commercial grade, narrower than commercial, and a mix of different size spans. Parts were made with polyamide-11 and the results indicate a more suitable particle size distribution for a specific material and a specific machine. Hence spending some additional resources on sieving powder prior to use can be beneficial. However, an optimization should be carried out for each powder and material to find the ideal powder size distribution corresponding to desired part quality.Mechanical Engineerin

Meta-analysis of Genome-Wide Association Studies for Extraversion: Findings from the Genetics of Personality Consortium

Extraversion is a relatively stable and heritable personality trait associated with numerous psychosocial, lifestyle and health outcomes. Despite its substantial heritability, no genetic variants have been detected in previous genome-wide association (GWA) studies, which may be due to relatively small sample sizes of those studies. Here, we report on a large meta-analysis of GWA studies for extraversion in 63,030 subjects in 29 cohorts. Extraversion item data from multiple personality inventories were harmonized across inventories and cohorts. No genome-wide significant associations were found at the single nucleotide polymorphism (SNP) level but there was one significant hit at the gene level for a long non-coding RNA site (LOC101928162). Genome-wide complex trait analysis in two large cohorts showed that the additive variance explained by common SNPs was not significantly different from zero, but polygenic risk scores, weighted using linkage information, significantly predicted extraversion scores in an independent cohort. These results show that extraversion is a highly polygenic personality trait, with an architecture possibly different from other complex human traits, including other personality traits. Future studies are required to further determine which genetic variants, by what modes of gene action, constitute the heritable nature of extraversion

Designing a broad-spectrum integrative approach for cancer prevention and treatment

Targeted therapies and the consequent adoption of "personalized" oncology have achieved notablesuccesses in some cancers; however, significant problems remain with this approach. Many targetedtherapies are highly toxic, costs are extremely high, and most patients experience relapse after a fewdisease-free months. Relapses arise from genetic heterogeneity in tumors, which harbor therapy-resistantimmortalized cells that have adopted alternate and compensatory pathways (i.e., pathways that are notreliant upon the same mechanisms as those which have been targeted). To address these limitations, aninternational task force of 180 scientists was assembled to explore the concept of a low-toxicity "broad-spectrum" therapeutic approach that could simultaneously target many key pathways and mechanisms. Using cancer hallmark phenotypes and the tumor microenvironment to account for the various aspectsof relevant cancer biology, interdisciplinary teams reviewed each hallmark area and nominated a widerange of high-priority targets (74 in total) that could be modified to improve patient outcomes. For thesetargets, corresponding low-toxicity therapeutic approaches were then suggested, many of which werephytochemicals. Proposed actions on each target and all of the approaches were further reviewed forknown effects on other hallmark areas and the tumor microenvironment. Potential contrary or procar-cinogenic effects were found for 3.9% of the relationships between targets and hallmarks, and mixedevidence of complementary and contrary relationships was found for 7.1%. Approximately 67% of therelationships revealed potentially complementary effects, and the remainder had no known relationship. Among the approaches, 1.1% had contrary, 2.8% had mixed and 62.1% had complementary relationships. These results suggest that a broad-spectrum approach should be feasible from a safety standpoint. Thisnovel approach has potential to be relatively inexpensive, it should help us address stages and types ofcancer that lack conventional treatment, and it may reduce relapse risks. A proposed agenda for futureresearch is offered

Genome-wide meta-analysis uncovers novel loci influencing circulating leptin levels.

Leptin is an adipocyte-secreted hormone, the circulating levels of which correlate closely with overall adiposity. Although rare mutations in the leptin (LEP) gene are well known to cause leptin deficiency and severe obesity, no common loci regulating circulating leptin levels have been uncovered. Therefore, we performed a genome-wide association study (GWAS) of circulating leptin levels from 32,161 individuals and followed up loci reaching P&lt;10(-6) in 19,979 additional individuals. We identify five loci robustly associated (P&lt;5 × 10(-8)) with leptin levels in/near LEP, SLC32A1, GCKR, CCNL1 and FTO. Although the association of the FTO obesity locus with leptin levels is abolished by adjustment for BMI, associations of the four other loci are independent of adiposity. The GCKR locus was found associated with multiple metabolic traits in previous GWAS and the CCNL1 locus with birth weight. Knockdown experiments in mouse adipose tissue explants show convincing evidence for adipogenin, a regulator of adipocyte differentiation, as the novel causal gene in the SLC32A1 locus influencing leptin levels. Our findings provide novel insights into the regulation of leptin production by adipose tissue and open new avenues for examining the influence of variation in leptin levels on adiposity and metabolic health