Chronobiological factors for compassion satisfaction and fatigue among ambulatory oncology caregivers

Primary caregivers for victims of chronic illness and or trauma experience both positive and negative emotional consequences. These are broadly classified as compassion satisfaction (CS) and compassion fatigue (CF). Because one of the components of CF, burnout, varies with chronotype and sleep quality, we assessed the influence of chronobiological features on the broader constructs of CS and CF. Responses from primary ambulatory care oncology staff working dayshifts were assessed for potential relationships of chronotype and sleep quality with CS and CF using the professional quality of life scale. These were analyzed further in a multivariate model that included personality and job satisfaction as cofactors. We found that sleep quality was a key contributor to CS development and CF reduction. Morningness was positively linked to CS, but the univariate association was masked in the multivariate model. Job satisfaction (contingent rewards, nature of work and operating procedures) heavily influenced CS and CF development. Agreeableness and openness showed positive correlations with CS and negative with burnout, while emotional stability was linked to reduced CF. While job satisfaction and personality predictably played roles in the development of CS and CF, sleep quality and chronotype contributed significantly to benefits and negative consequences of providing care.     

A Spatial Framework for Understanding Population Structure and Admixture

Geographic patterns of genetic variation within modern populations, produced by complex histories of migration, can be difficult to infer and visually summarize. A general consequence of geographically limited dispersal is that samples from nearby locations tend to be more closely related than samples from distant locations, and so genetic covariance often recapitulates geographic proximity. We use genome-wide polymorphism data to build “geogenetic maps,” which, when applied to stationary populations, produces a map of the geographic positions of the populations, but with distances distorted to reflect historical rates of gene flow. In the underlying model, allele frequency covariance is a decreasing function of geogenetic distance, and nonlocal gene flow such as admixture can be identified as anomalously strong covariance over long distances. This admixture is explicitly co-estimated and depicted as arrows, from the source of admixture to the recipient, on the geogenetic map. We demonstrate the utility of this method on a circum-Tibetan sampling of the greenish warbler (Phylloscopus trochiloides), in which we find evidence for gene flow between the adjacent, terminal populations of the ring species. We also analyze a global sampling of human populations, for which we largely recover the geography of the sampling, with support for significant histories of admixture in many samples. This new tool for understanding and visualizing patterns of population structure is implemented in a Bayesian framework in the program SpaceMix.     

Cox model with interval‐censored covariate in cohort studies

In cohort studies the outcome is often time to a particular event, and subjects are followed at regular intervals. Periodic visits may also monitor a secondary irreversible event influencing the event of primary interest, and a significant proportion of subjects develop the secondary event over the period of follow‐up. The status of the secondary event serves as a time‐varying covariate, but is recorded only at the times of the scheduled visits, generating incomplete time‐varying covariates. While information on a typical time‐varying covariate is missing for entire follow‐up period except the visiting times, the status of the secondary event are unavailable only between visits where the status has changed, thus interval‐censored. One may view interval‐censored covariate of the secondary event status as missing time‐varying covariates, yet missingness is partial since partial information is provided throughout the follow‐up period. Current practice of using the latest observed status produces biased estimators, and the existing missing covariate techniques cannot accommodate the special feature of missingness due to interval censoring. To handle interval‐censored covariates in the Cox proportional hazards model, we propose an available‐data estimator, a doubly robust‐type estimator as well as the maximum likelihood estimator via EM algorithm and present their asymptotic properties. We also present practical approaches that are valid. We demonstrate the proposed methods using our motivating example from the Northern Manhattan Study.     

Mutual interplay between phytopathogenic powdery mildew fungi and other microorganisms

Powdery mildew is a common and widespread plant disease of considerable agronomic relevance. It is caused by obligate biotrophic fungal pathogens which, in most cases, epiphytically colonize aboveground plant tissues. The disease has been typically studied as a binary interaction of the fungal pathogen with its plant hosts, neglecting, for the most part, the mutual interplay with the wealth of other microorganisms residing in the phyllo- and/or rhizosphere and roots. However, the establishment of powdery mildew disease can be impacted by the presence/absence of host-associated microbiota (epi- and endophytes) and, conversely, plant colonization by powdery mildew fungi might disturb indigenous microbial community structures. In addition, other (foliar) phytopathogens could interact with powdery mildews, and mycoparasites may affect the outcome of plant–powdery mildew interactions. In this review, we discuss the current knowledge regarding the intricate and multifaceted interplay of powdery mildew fungi, host plants and other microorganisms, and outline current gaps in our knowledge, thereby setting the basis for potential future research directions.     

Outgassing Losses of Toluene and m-Xylene Evaluated by 14C-Based Mass Balances for Laboratory Bioventing Simulations

Mixtures of toluene, ethylbenzene, and the xylenes spiked with ¹⁴C-labeled toluene or m-xylene were added to bench-scale bioventing simulation columns filled with hydrocarbon-contaminated subsurface soils. After 2 to 4 weeks of incubation during which air was pumped through the column at rates of at least 2?ml·min^?1·kg^?1 between 54 and 84% of the radiolabel was recovered in traps as outgassed parent compound from four columns sterilized with gamma-irradiation. In contrast, seven nonsterilized but otherwise identically treated (except for inorganic nitrogen addition) columns lost less than 0.4% (and one column lost 0.7%) of the radiolabel through outgassing of the parent compound. Nonsterilized columns lost 40 to 61% of the radiolabel as ¹⁴CO₂, whereas gamma-irradiated columns usually lost only trace amounts of ¹⁴C in this form. Biologically active columns also retained much larger fractions than sterilized columns of the radiolabel in the subsoil in forms, possibly microbial biomass, from which it could be recovered by wet oxidation. Addition of 10 or 40?mg/kg of mineral nitrogen had no consistent effect on bioventing performance.     

Electronic properties of some inorganic solids

A simple bonding model previously used to calculate cohesive energies is used to calculate electronic properties of simple solids. The model assumes that AB compounds of CN6 or 8 are completely ionic and that CN4 compounds, and metals, are completely covalent. It is then possible to calculate the electronic chemical potential, the work function and the average energy gap between filled and empty bands in insulators, semiconductors and conductors.