The structure of an unconventional HD-GYP protein from Bdellovibrio reveals the roles of conserved residues in this class of cyclic-di-GMP phosphodiesterases

UNLABELLED: Cyclic-di-GMP is a near-ubiquitous bacterial second messenger that is important in localized signal transmission during the control of various processes, including virulence and switching between planktonic and biofilm-based lifestyles. Cyclic-di-GMP is synthesized by GGDEF diguanylate cyclases and hydrolyzed by EAL or HD-GYP phosphodiesterases, with each functional domain often appended to distinct sensory modules. HD-GYP domain proteins have resisted structural analysis, but here we present the first structural representative of this family (1.28 Å), obtained using the unusual Bd1817 HD-GYP protein from the predatory bacterium Bdellovibrio bacteriovorus. Bd1817 lacks the active-site tyrosine present in most HD-GYP family members yet remains an excellent model of their features, sharing 48% sequence similarity with the archetype RpfG. The protein structure is highly modular and thus provides a basis for delineating domain boundaries in other stimulus-dependent homologues. Conserved residues in the HD-GYP family cluster around a binuclear metal center, which is observed complexed to a molecule of phosphate, providing information on the mode of hydroxide ion attack on substrate. The fold and active site of the HD-GYP domain are different from those of EAL proteins, and restricted access to the active-site cleft is indicative of a different mode of activity regulation. The region encompassing the GYP motif has a novel conformation and is surface exposed and available for complexation with binding partners, including GGDEF proteins.

IMPORTANCE: It is becoming apparent that many bacteria use the signaling molecule cyclic-di-GMP to regulate a variety of processes, most notably, transitions between motility and sessility. Importantly, this regulation is central to several traits implicated in chronic disease (adhesion, biofilm formation, and virulence gene expression). The mechanisms of cyclic-di-GMP synthesis via GGDEF enzymes and hydrolysis via EAL enzymes have been suggested by the analysis of several crystal structures, but no information has been available to date for the unrelated HD-GYP class of hydrolases. Here we present the multidomain structure of an unusual member of the HD-GYP family from the predatory bacterium Bdellovibrio bacteriovorus and detail the features that distinguish it from the wider structural family of general HD fold hydrolases. The structure reveals how a binuclear iron center is formed from several conserved residues and provides a basis for understanding HD-GYP family sequence requirements for c-di-GMP hydrolysis.

On the halogenation of N(1),N(2)-di-t-Boc-5-hydroxy-piperazic acid esters and the conformational preferences of their 5-halo-piperazic acid products. The importance of A1,3 rotameric-strain in determining N(2)-acyl piperazic acid ring conformation

In this Letter, an unambiguous synthetic strategy is reported for the preparation of enantiomerically purecis-5-halo-piperazic acid derivatives in single diastereoisomer form. Contrary to the recent report by Shin and co-workers (Chem. Lett. 2001, 1172), in which it is claimed that the Ph₃P and N-chlorosuccinimide (NCS)-mediated chlorination of (3R,5S)-trans-N(1),N(2)-di-t-Boc-5-hydroxy-piperazic acid derivative 1proceeds with retention of configuration at C(5) to give 2, we now show that this and related Ph₃P-mediated halogenations all occur with S_N2 inversion at the alcohol center, as is customary for such reactions. Specifically, we demonstrate that the (3R,5S)-trans-5-Cl-piperazic acid derivative 2 claimed by Shin and co-workers (Chem. Lett. 2001, 1172) is in actual fact the chlorinated (3S,5R)-enantiomer 6, which must have been prepared from the cis-(3S,5S)-alcohol 3, a molecule whose synthesis is not formally described in the Shin paper. We further show here that the cis-(3R,5R)-5-Cl-Piz 13 claimed by Shin and co-workers inChem. Lett. 2001, 1172, is also (3S,5R)-trans-5-Cl-Piz 6. Authentic 13 has now been synthesized by us, for the very first time, here. Since Lindsley and Kennedy have recently utilized the now invalid Shin and co-workers’ retentive Ph₃P/NCS chlorination procedure on 1 in their synthetic approach to piperazimycin A (Tetrahedron Lett. 2010, 51, 2493), it follows that their claimed 5-Cl-Piz-containing dipeptide 25 probably has the alternate structure 26, where the 5-Cl-Piz residue has a 3,5-cis-configuration. The aforementioned stereochemical misassignments appear to have come from a mix-up of starting materials by Shin and co-workers (Chem. Lett. 2001, 1172), and an under-appreciation of the various steric and conformational effects that operate in N(2)-acylated piperazic acid systems, most especially rotameric A^1,3-strain. The latter has now been unambiguously delineated and defined here under the banner of the A^1,3-rotamer effect.

A Continuous Time Markov Chain Based Sequential Analytical Approach for Composite Power System Reliability Assessment

This paper proposes a continuous time Markov chain (CTMC) based sequential analytical approach for composite generation and transmission systems reliability assessment. The basic idea is to construct a CTMC model for the composite system. Based on this model, sequential analyses are performed. Various kinds of reliability indices can be obtained, including expectation, variance, frequency, duration and probability distribution. In order to reduce the dimension of the state space, traditional CTMC modeling approach is modified by merging all high order contingencies into a single state, which can be calculated by Monte Carlo simulation (MCS). Then a state mergence technique is developed to integrate all normal states to further reduce the dimension of the CTMC model. Moreover, a time discretization method is presented for the CTMC model calculation. Case studies are performed on the RBTS and a modified IEEE 300-bus test system. The results indicate that sequential reliability assessment can be performed by the proposed approach. Comparing with the traditional sequential Monte Carlo simulation method, the proposed method is more efficient, especially in small scale or very reliable power systems.

Using the hidden Markov model to capture quality of care in Lombardy geriatric wards

Quality of care is an important aspect of healthcare monitoring, which is used to ensure that the healthcare system is delivering care of the highest standard. With populations growing older there is an increased urgency in making sure that the healthcare delivered is of the highest standard. Healthcare providers are under increased pressure to ensure that this is the case with public and government demand expecting a healthcare system of the highest quality. Modelling quality of care is difficult to measure due to the many ways of defining it. This paper introduces a potential model which could be used to take quality of care into account when modelling length of stay. The Coxian phase-type distribution is used to model length of stay and the associated quality of care incorporated into the Coxian using a Hidden Markov model. Covariates are also introduced to determine their impact on the hidden level to find out what potentially can affect quality of care. This model is applied to geriatic patient data from the Lombardy region of Italy. The results obtained highlighted that bed numbers and the type of hospital (public or private) can have an effect on the quality of care delivered.

Confronto tra diverse localizzazioni di un impianto eolico contemperando produttività ed impatto visivo

This paper proposes a series of variations in designing the location of a wind farm on Monti della Tolfa. These project solutions aim at mitigating the visual impact caused by the wind aerogenerators. Besides the usual location of the wind aerogenerators on the skyline, these alternatives within the project design relate to the placement of wind turbines in the middle and at the bottom of the hillside. Other possible mitigation forms relate to the dimensions and the colour of the wind towers. This study proposes both a non-monetary and monetary analysis of the visual impact related to each project proposal. The final aim of the paper is to analyze economic and financial costs-benefits for each alternative to find out the economic optimal solution.

Hidden Markov Models With Set-Valued Parameters

Hidden Markov models (HMMs) are widely used probabilistic models of sequential data. As with other probabilistic models, they require the specification of local conditional probability distributions, whose assessment can be too difficult and error-prone, especially when data are scarce or costly to acquire. The imprecise HMM (iHMM) generalizes HMMs by allowing the quantification to be done by sets of, instead of single, probability distributions. iHMMs have the ability to suspend judgment when there is not enough statistical evidence, and can serve as a sensitivity analysis tool for standard non-stationary HMMs. In this paper, we consider iHMMs under the strong independence interpretation, for which we develop efficient inference algorithms to address standard HMM usage such as the computation of likelihoods and most probable explanations, as well as performing filtering and predictive inference. Experiments with real data show that iHMMs produce more reliable inferences without compromising the computational efficiency.

Using a Discrete Hidden Markov Model Kernel for lip-based biometric identification

In this paper, a novel and effective lip-based biometric identification approach with the Discrete Hidden Markov Model Kernel (DHMMK) is developed. Lips are described by shape features (both geometrical and sequential) on two different grid layouts: rectangular and polar. These features are then specifically modeled by a DHMMK, and learnt by a support vector machine classifier. Our experiments are carried out in a ten-fold cross validation fashion on three different datasets, GPDS-ULPGC Face Dataset, PIE Face Dataset and RaFD Face Dataset. Results show that our approach has achieved an average classification accuracy of 99.8%, 97.13%, and 98.10%, using only two training images per class, on these three datasets, respectively. Our comparative studies further show that the DHMMK achieved a 53% improvement against the baseline HMM approach. The comparative ROC curves also confirm the efficacy of the proposed lip contour based biometrics learned by DHMMK. We also show that the performance of linear and RBF SVM is comparable under the frame work of DHMMK.

Smartphone and GPS technology for freeroaming dog population surveillance -a methodological study (Studio metodologico sull’applicazione di smartphone e tecnologia GPS alla sorveglianza delle popolazioni di cani vaganti)

Free-roaming dogs (FRD) represent a potential threat to the quality of life in cities from an ecological, social and public health point of view. One of the most urgent concerns is the role of uncontrolled dogs as reservoirs of infectious diseases transmittable to humans and, above all, rabies. An estimate of the FRD population size and characteristics in a given area is the first step for any relevant intervention programme. Direct count methods are still prominent because of their non-invasive approach, information technologies can support such methods facilitating data collection and allowing for a more efficient data handling. This paper presents a new framework for data collection using a topological algorithm implemented as ArcScript in ESRI® ArcGIS software, which allows for a random selection of the sampling areas. It also supplies a mobile phone application for Android® operating system devices which integrates Global Positioning System (GPS) and Google Maps™. The potential of such a framework was tested in 2 Italian regions. Coupling technological and innovative solutions associated with common counting methods facilitate data collection and transcription. It also paves the way to future applications, which could support dog population management systems.

Christian Gottlob Neefe and the Early Reception of Le nozze di Figaro and Don Giovanni

A brief account of Christian Gottlob Neefe's engagement with Mozart's Le nozze di Figaro and Don Giovanni as exemplified in his correspondence.

Multilinear and Integer Programming for Markov Decision Processes with Imprecise Probabilities

Markov Decision Processes (MDPs) are extensively used to encode sequences of decisions with probabilistic effects. Markov Decision Processes with Imprecise Probabilities (MDPIPs) encode sequences of decisions whose effects are modeled using sets of probability distributions. In this paper we examine the computation of Γ-maximin policies for MDPIPs using multilinear and integer programming. We discuss the application of our algorithms to “factored” models and to a recent proposal, Markov Decision Processes with Set-valued Transitions (MDPSTs), that unifies the fields of probabilistic and “nondeterministic” planning in artificial intelligence research.