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.     

Effects of experimental warming on survival,phenology, and morphology of an aquatic insect (Odonata)

1. Organisms can respond to changing climatic conditions in multiple ways including changes in phenology, body size or morphology, and range shifts. Understanding how developmental temperatures affect insect life‐history timing and morphology is crucial because body size and morphology affect multiple aspects of life history, including dispersal ability, whereas phenology can shape population performance and community interactions. 2. It was experimentally assessed how developmental temperatures experienced by aquatic larvae affected survival, phenology, and adult morphology of dragonflies [Pachydiplax longipennis (Burmeister)]. Larvae were reared under three environmental temperatures: ambient, +2.5, and +5 °C, corresponding to temperature projections for our study area 50 and 100 years in the future, respectively. Experimental temperature treatments tracked naturally‐occurring variation. 3. Clear effects of temperature were found in the rearing environment on survival and phenology: dragonflies reared at the highest temperatures had the lowest survival rates and emerged from the larval stage approximately 3 weeks earlier than animals reared at ambient temperatures. There was no effect of rearing temperature on overall body size. Although neither the relative wing nor thorax size was affected by warming, a non‐significant trend towards an interaction between sex and warming in relative thorax size suggests that males may be more sensitive to warming than females, a pattern that should be investigated further. 4. Warming strongly affected survival in the larval stage and the phenology of adult emergence. Understanding how warming in the developmental environment affects later life‐history stages is critical to interpreting the consequences of warming for organismal performance.     

A Dynamic Gene Regulatory Network Model That Recovers the Cyclic Behavior of Arabidopsis thaliana Cell Cycle

Cell cycle control is fundamental in eukaryotic development. Several modeling efforts have been used to integrate the complex network of interacting molecular components involved in cell cycle dynamics. In this paper, we aimed at recovering the regulatory logic upstream of previously known components of cell cycle control, with the aim of understanding the mechanisms underlying the emergence of the cyclic behavior of such components. We focus on Arabidopsis thaliana, but given that many components of cell cycle regulation are conserved among eukaryotes, when experimental data for this system was not available, we considered experimental results from yeast and animal systems. We are proposing a Boolean gene regulatory network (GRN) that converges into only one robust limit cycle attractor that closely resembles the cyclic behavior of the key cell-cycle molecular components and other regulators considered here. We validate the model by comparing our in silico configurations with data from loss- and gain-of-function mutants, where the endocyclic behavior also was recovered. Additionally, we approximate a continuous model and recovered the temporal periodic expression profiles of the cell-cycle molecular components involved, thus suggesting that the single limit cycle attractor recovered with the Boolean model is not an artifact of its discrete and synchronous nature, but rather an emergent consequence of the inherent characteristics of the regulatory logic proposed here. This dynamical model, hence provides a novel theoretical framework to address cell cycle regulation in plants, and it can also be used to propose novel predictions regarding cell cycle regulation in other eukaryotes.     

Advanced lymphoblastic clones detection in T-cell leukemia

T cell acute lymphoblastic leukemia (T-ALL) is an aggressive malignant neoplasm of the lymphocyte precursors that suffered malignant transformation arresting the lymphoid cell differentiation. Clinical studies revealed monoor, more rarely, oligoclonal nature of the disease. A precise identification of malignant clone markers is both the crucial stage of early diagnostics and the essential prognostic factor for therapeutic treatment. Here we present an improved system for unbiased detection of lymphoblastic clones in bone marrow aspirates of T-ALL patients. The system based on multiplex PCR of rearranged T-cell receptor locus (TRB) and straightforward sequencing of the resulted PCR fragments. Testing of the system on genomic DNA from Jurkat cell line and four clinical bone marrow aspirates revealed a set of unique TRB rearrangements that precisely characterize each of tested samples. Therefore, the outcome of the system produces highly informative molecular genetic markers for further monitoring of minimal residual disease in T-ALL patients.