A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

Meeting abstrac

Global Regulatory Functions of the Staphylococcus aureus Endoribonuclease III in Gene Expression

RNA turnover plays an important role in both virulence and adaptation to stress in the Gram-positive human pathogen Staphylococcus aureus. However, the molecular players and mechanisms involved in these processes are poorly understood. Here, we explored the functions of S. aureus endoribonuclease III (RNase III), a member of the ubiquitous family of double-strand-specific endoribonucleases. To define genomic transcripts that are bound and processed by RNase III, we performed deep sequencing on cDNA libraries generated from RNAs that were co-immunoprecipitated with wild-type RNase III or two different cleavage-defective mutant variants in vivo. Several newly identified RNase III targets were validated by independent experimental methods. We identified various classes of structured RNAs as RNase III substrates and demonstrated that this enzyme is involved in the maturation of rRNAs and tRNAs, regulates the turnover of mRNAs and non-coding RNAs, and autoregulates its synthesis by cleaving within the coding region of its own mRNA. Moreover, we identified a positive effect of RNase III on protein synthesis based on novel mechanisms. RNase III–mediated cleavage in the 5′ untranslated region (5′UTR) enhanced the stability and translation of cspA mRNA, which encodes the major cold-shock protein. Furthermore, RNase III cleaved overlapping 5′UTRs of divergently transcribed genes to generate leaderless mRNAs, which constitutes a novel way to co-regulate neighboring genes. In agreement with recent findings, low abundance antisense RNAs covering 44% of the annotated genes were captured by co-immunoprecipitation with RNase III mutant proteins. Thus, in addition to gene regulation, RNase III is associated with RNA quality control of pervasive transcription. Overall, this study illustrates the complexity of post-transcriptional regulation mediated by RNase III

A Classification Approach to Efficient Global Optimization in Presence of Non-Computable Domains

Gaussian-Process based optimization methods have become very popular in recent years for the global optimization of complex systems with high computational costs. These methods rely on the sequential construction of a statistical surrogate model, using a training set of computed objective function values, which is refined according to a prescribed infilling strategy. However, this sequential optimization procedure can stop prematurely if the objective function cannot be computed at a proposed point. Such a situation can occur when the search space encompasses design points corresponding to an unphysical configuration, an ill-posed problem, or a non-computable problem due to the limitation of numerical solvers. To avoid such a premature stop in the optimization procedure, we propose to use a classification model to learn non-computable areas and to adapt the infilling strategy accordingly. Specifically, the proposed method splits the training set into two subsets composed of computable and non-computable points. A surrogate model for the objective function is built using the training set of computable points, only, whereas a probabilistic classification model is built using the union of the computable and non-computable training sets. The classifier is then incorporated in the surrogate-based optimization procedure to avoid proposing new points in the non-computable domain while improving the classification uncertainty if needed. The method has the advantage to automatically adapt both the surrogate of the objective function and the classifier during the iterative optimization process. Therefore, non-computable areas do not need to be a priori known. The proposed method is applied to several analytical problems presenting different types of difficulty, and to the optimization of a fully nonlinear fluid-structure interaction system. The latter problem concerns the drag minimization of a flexible hydrofoil with cavitation constraints. The efficiency of the proposed method compared favorably to a reference evolutionary algorithm, except for situations where the feasible domain is a small portion of the design space

Selective acquisition of AMPA receptors over postnatal development suggests a molecular basis for silent synapses

Early in postnatal development, glutamatergic synapses transmit primarily through NMDA receptors. As development progresses, synapses acquire AMPA receptor function. The molecular basis of these physiological observations is not known. Here we examined single excitatory synapses with immunogold electron-microscopic analysis of AMPA and NMDA receptors along with electrophysiological measurements. Early in postnatal development, a significant fraction of excitatory synapses had NMDA receptors and lacked AMPA receptors. As development progressed, synapses acquired AMPA receptors with little change in NMDA receptor number. Thus, synapses with NMDA receptors but no AMPA receptors can account for the electrophysiologically observed 'silent synapse'