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  • Skaaning Griffith posted an update 1 week, 2 days ago

    ggregates were projected onto the PLS factorial plane of the NIR spectra from the lab incubation. Selleck Indoximod The projection of the NIR spectral signals onto the PLSR models for C, N, [Formula see text] and [Formula see text] from casts produced and incubated in the lab allowed us to identify the species and the age of the field biogenic aggregates. Our hypothesis was to test whether field aggregates would match or be in the vicinity of the NIR signals that corresponded to a certain species and the age of the depositions produced in the lab. A NIRS biogenic background noise (BBN) is present in the soil as a result of earthworm activity. This study provides insights on how to analyse the role of these organisms in important ecological processes of soil macro-aggregation and associated organic matter dynamics by means of analyzing the BBN in the soil matrix.Dynamical networks are pervasive in a multitude of natural and human-made systems. Often, we seek to guarantee that their state is steered to the desired goal within a specified number of time steps. Different network topologies lead to implicit trade-offs between the minimum number of driven nodes and the time-to-control. In this study, we propose a generative model to create artificial dynamical networks with trade-offs similar to those of real networks. Remarkably, we show that several centrality and non-centrality measures are not necessary nor sufficient to explain the trade-offs, and as a consequence, commonly used generative models do not suffice to capture the dynamical properties under study. Therefore, we introduce the notion of time-to-control communities, that combine networks’ partitions and degree distributions, which is crucial for the proposed generative model. We believe that the proposed methodology is crucial when invoking generative models to investigate dynamical network properties across science and engineering applications. Lastly, we provide evidence that the proposed generative model can generate a variety of networks with statistically indiscernible trade-offs (i.e., the minimum number of driven nodes vs. the time-to-control) from those steaming from real networks (e.g., neural and social networks).Blended therapy is a new approach combining advantages of face-to-face psychotherapy and Internet- and mobile-based interventions. Acceptance is a fundamental precondition for its implementation. The aim of this study was to assess 1) the acceptance of psychotherapists towards blended therapy, 2) the effectiveness of an acceptance facilitating intervention (AFI) on psychotherapists’ acceptance towards blended therapy and 3) to identify potential effect moderators. Psychotherapists (N = 284) were randomly assigned to a control (CG) or an intervention group (IG). The IG received a short video showing an example of blended therapy, the CG an attention placebo video. Both groups received a reliable online questionnaire assessing acceptance, effort expectancy, performance expectancy, facilitating conditions, social influence and internet anxiety. Between group differences were examined using t-tests and Mann-Whitney tests. Exploratory analysis was conducted to identify moderators. Psychotherapists in CG showed mixed baseline acceptance towards blended therapy (low = 40%, moderate = 33%, high = 27%). IG showed significantly higher acceptance compared to CG (d = .27, pone-sided = .029; low = 24%, moderate = 47%, high = 30%). Bootstrapped confidence intervals were overlapping. Performance expectancy (d = .35), effort expectancy (d = .44) and facilitating conditions (d = .28) were significantly increased (p .05). Exploratory analysis indicated psychodynamic oriented psychotherapists profiting particularly from the AFI. Blended therapy is a promising approach to improve healthcare. Psychotherapists show mixed acceptance, which might be improvable by AFIs, particularly in subpopulations of initially rather skeptical psychotherapists. Forthcoming studies should extend the present study by shifting focus from attitudes to the impact of different forms of AFIs on uptake.

    Melanocytes play a central role in skin homeostasis. In this study, we focus on the function of melanocyte releasing exosomes as well as exosomal microRNAs (miRNAs) and investigate whether ultraviolet B (UVB) irradiation exerts an impact on it.

    Exosomes derived from human primary melanocytes were isolated through differential centrifugation and were identified in three ways, including transmission electron microscopy observation, nanoparticle tracking analysis, and Western blot analysis. Melanocytes were irradiated with UVB for the indicated time, and then melanin production and exosome secretion were measured. The exosomal miRNA expression profile of melanocytes were obtained by miRNA sequencing and confirmed by real-time PCR.

    Exosomes derived from human primary melanocytes were verified. UVB irradiation induced melanin production and increased the exosome release by the melanocytes. In total, 15 miRNAs showed higher levels in UVB-irradiated melanocyte-derived exosomes compared with non-irradiated ones, and the top three upregulated exosomal miRNAs were miR-4488, miR-320d, and miR-7704 (fold change > 4.0).

    It is verified for the first time that UVB irradiation enhanced the secretion of exosomes by melanocytes and changed their exosomal miRNA profile. This findings open a new direction for investigating the communication between melanocytes and other skin cells, and the connection between UVB and skin malignant initiation.

    It is verified for the first time that UVB irradiation enhanced the secretion of exosomes by melanocytes and changed their exosomal miRNA profile. This findings open a new direction for investigating the communication between melanocytes and other skin cells, and the connection between UVB and skin malignant initiation.Knowledge about population genetic structure and dispersal capabilities is important for the development of targeted management strategies for agricultural pest species. The apple fruit moth, Argyresthia conjugella (Lepidoptera, Yponomeutidae), is a pre-dispersal seed predator. Larvae feed on rowanberries (Sorbus aucuparia), and when rowanberry seed production is low (i.e., inter-masting), the moth switches from laying eggs in rowanberries to apples (Malus domestica), resulting in devastating losses in apple crops. Using genetic methods, we investigated if this small moth expresses any local genetic structure, or alternatively if gene flow may be high within the Scandinavian Peninsula (~850.000 km2, 55o – 69o N). Genetic diversity was found to be high (n = 669, mean He = 0.71). For three out of ten tetranucleotide STRs, we detected heterozygote deficiency caused by null alleles, but tests showed little impact on the overall results. Genetic differentiation between the 28 sampling locations was very low (average FST = 0.