Altered miRNA expression network in locus coeruleus of depressed suicide subjects

Norepinephrine (NE) is produced primarily by neurons in the locus coeruleus (LC). Retrograde and ultrastructural examinations reveal that the core of the LC and its surrounding region receives afferent projections from several brain areas which provide multiple neurochemical inputs to the LC with changes in LC neuronal firing, making it a highly coordinated event. Although NE and mediated signaling systems have been studied in relation to suicide and psychiatric disorders that increase the risk of suicide including depression, less is known about the corresponding changes in molecular network within LC. In this study, we examined miRNA networks in the LC of depressed suicide completers and healthy controls. Expression array revealed differential regulation of 13 miRNAs. Interaction between altered miRNAs and target genes showed dense interconnected molecular network. Functional clustering of predicated target genes yielded stress induced disorders that collectively showed the complex nature of suicidal behavior. In addition, 25 miRNAs were pairwise correlated specifically in the depressed suicide group, but not in the control group. Altogether, our study revealed for the first time the involvement of LC based dysregulated miRNA network in disrupting cellular pathways associated with suicidal behavior

Solidification Studies of Mg–Al Binary Alloys

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Bayesian learning of biodiversity models using repeated observations

Predictive biodiversity distribution models (BDM) are useful for understanding the structure and functioning of ecological communities and managing them in the face of anthropogenic disturbances. In cases where their predictive performance is good, such models can help fill knowledge gaps that could only otherwise be addressed using direct observation, an often logistically and financially onerous prospect. The cornerstones of such models are environmental and spatial predictors. Typically, however, these predictors vary on different spatial and temporal scales than the biodiversity they are used to predict and are interpolated over space and time. We explore the consequences of these scale mismatches between predictors and predictions by comparing the results of BDMs built to predict fish species richness on Australia’s Great Barrier Reef. Specifically, we compared a series of annual models with uninformed priors with models built using the same predictors and observations, but which accumulated information through time via the inclusion of informed priors calculated from previous observation years. Advantages of using informed priors in these models included (1) down-weighting the importance of a large disturbance, (2) more certain species richness predictions, (3) more consistent predictions of species richness and (4) increased certainty in parameter coefficients. Despite such advantages, further research will be required to find additional ways to improve model performance.Ana M. M. Sequeira, M. Julian Caley, Camille Mellin, and Kerrie L. Mengerse