Development and validation of AMANDA, a new algorithm for selecting highly relevant regions in Molecular Interaction Fields

Descriptors based on Molecular Interaction Fields (MIF) are highly suitable for drug discovery, but their size (thousands of variables) often limits their application in practice. Here we describe a simple and fast computational method that extracts from a MIF a handful of highly informative points (hot spots) which summarize the most relevant information. The method was specifically developed for drug discovery, is fast, and does not require human supervision, being suitable for its application on very large series of compounds. The quality of the results has been tested by running the method on the ligand structure of a large number of ligand-receptor complexes and then comparing the position of the selected hot spots with actual atoms of the receptor. As an additional test, the hot spots obtained with the novel method were used to obtain GRIND-like molecular descriptors which were compared with the original GRIND. In both cases the results show that the novel method is highly suitable for describing ligand-receptor interactions and compares favorably with other state-of-the-art methods.

A systolic array for linear MIMO detection based on an all-swap lattice reduction algorithm

A systolic array to implement lattice-reduction-aided lineardetection is proposed for a MIMO receiver. The lattice reductionalgorithm and the ensuing linear detections are operated in the same array, which can be hardware-efficient. All-swap lattice reduction algorithm (ASLR) is considered for the systolic design.ASLR is a variant of the LLL algorithm, which processes all lattice basis vectors within one iteration. Lattice-reduction-aided linear detection based on ASLR and LLL algorithms have very similarbit-error-rate performance, while ASLR is more time efficient inthe systolic array, especially for systems with a large number ofantennas.

Alzheimer's disease: the amyloid hypothesis and the Inverse Warburg effect.

Epidemiological and biochemical studies show that the sporadic forms of Alzheimer's disease (AD) are characterized by the following hallmarks: (a) An exponential increase with age; (b) Selective neuronal vulnerability; (c) Inverse cancer comorbidity. The present article appeals to these hallmarks to evaluate and contrast two competing models of AD: the amyloid hypothesis (a neuron-centric mechanism) and the Inverse Warburg hypothesis (a neuron-astrocytic mechanism). We show that these three hallmarks of AD conflict with the amyloid hypothesis, but are consistent with the Inverse Warburg hypothesis, a bioenergetic model which postulates that AD is the result of a cascade of three events-mitochondrial dysregulation, metabolic reprogramming (the Inverse Warburg effect), and natural selection. We also provide an explanation for the failures of the clinical trials based on amyloid immunization, and we propose a new class of therapeutic strategies consistent with the neuroenergetic selection model.

Source wavelet estimation for waveform inversion of crosshole georadar data

AbstractFor a wide range of environmental, hydrological, and engineering applications there is a fast growing need for high-resolution imaging. In this context, waveform tomographic imaging of crosshole georadar data is a powerful method able to provide images of pertinent electrical properties in near-surface environments with unprecedented spatial resolution. In contrast, conventional ray-based tomographic methods, which consider only a very limited part of the recorded signal (first-arrival traveltimes and maximum first-cycle amplitudes), suffer from inherent limitations in resolution and may prove to be inadequate in complex environments. For a typical crosshole georadar survey the potential improvement in resolution when using waveform-based approaches instead of ray-based approaches is in the range of one order-of- magnitude. Moreover, the spatial resolution of waveform-based inversions is comparable to that of common logging methods. While in exploration seismology waveform tomographic imaging has become well established over the past two decades, it is comparably still underdeveloped in the georadar domain despite corresponding needs. Recently, different groups have presented finite-difference time-domain waveform inversion schemes for crosshole georadar data, which are adaptations and extensions of Tarantola's seminal nonlinear generalized least-squares approach developed for the seismic case. First applications of these new crosshole georadar waveform inversion schemes on synthetic and field data have shown promising results. However, there is little known about the limits and performance of such schemes in complex environments. To this end, the general motivation of my thesis is the evaluation of the robustness and limitations of waveform inversion algorithms for crosshole georadar data in order to apply such schemes to a wide range of real world problems.One crucial issue to making applicable and effective any waveform scheme to real-world crosshole georadar problems is the accurate estimation of the source wavelet, which is unknown in reality. Waveform inversion schemes for crosshole georadar data require forward simulations of the wavefield in order to iteratively solve the inverse problem. Therefore, accurate knowledge of the source wavelet is critically important for successful application of such schemes. Relatively small differences in the estimated source wavelet shape can lead to large differences in the resulting tomograms. In the first part of my thesis, I explore the viability and robustness of a relatively simple iterative deconvolution technique that incorporates the estimation of the source wavelet into the waveform inversion procedure rather than adding additional model parameters into the inversion problem. Extensive tests indicate that this source wavelet estimation technique is simple yet effective, and is able to provide remarkably accurate and robust estimates of the source wavelet in the presence of strong heterogeneity in both the dielectric permittivity and electrical conductivity as well as significant ambient noise in the recorded data. Furthermore, our tests also indicate that the approach is insensitive to the phase characteristics of the starting wavelet, which is not the case when directly incorporating the wavelet estimation into the inverse problem.Another critical issue with crosshole georadar waveform inversion schemes which clearly needs to be investigated is the consequence of the common assumption of frequency- independent electromagnetic constitutive parameters. This is crucial since in reality, these parameters are known to be frequency-dependent and complex and thus recorded georadar data may show significant dispersive behaviour. In particular, in the presence of water, there is a wide body of evidence showing that the dielectric permittivity can be significantly frequency dependent over the GPR frequency range, due to a variety of relaxation processes. The second part of my thesis is therefore dedicated to the evaluation of the reconstruction limits of a non-dispersive crosshole georadar waveform inversion scheme in the presence of varying degrees of dielectric dispersion. I show that the inversion algorithm, combined with the iterative deconvolution-based source wavelet estimation procedure that is partially able to account for the frequency-dependent effects through an "effective" wavelet, performs remarkably well in weakly to moderately dispersive environments and has the ability to provide adequate tomographic reconstructions.

ILS-ESP An efficient, simple, and parameter-free algorithm for solving the permutation flow-shop problem

From a managerial point of view, the more effcient, simple, and parameter-free (ESP) an algorithm is, the more likely it will be used in practice for solving real-life problems. Following this principle, an ESP algorithm for solving the Permutation Flowshop Sequencing Problem (PFSP) is proposed in this article. Using an Iterated Local Search (ILS) framework, the so-called ILS-ESP algorithm is able to compete in performance with other well-known ILS-based approaches, which are considered among the most effcient algorithms for the PFSP. However, while other similar approaches still employ several parameters that can affect their performance if not properly chosen, our algorithm does not require any particular fine-tuning process since it uses basic "common sense" rules for the local search, perturbation, and acceptance criterion stages of the ILS metaheuristic. Our approach defines a new operator for the ILS perturbation process, a new acceptance criterion based on extremely simple and transparent rules, and a biased randomization process of the initial solution to randomly generate different alternative initial solutions of similar quality -which is attained by applying a biased randomization to a classical PFSP heuristic. This diversification of the initial solution aims at avoiding poorly designed starting points and, thus, allows the methodology to take advantage of current trends in parallel and distributed computing. A set of extensive tests, based on literature benchmarks, has been carried out in order to validate our algorithm and compare it against other approaches. These tests show that our parameter-free algorithm is able to compete with state-of-the-art metaheuristics for the PFSP. Also, the experiments show that, when using parallel computing, it is possible to improve the top ILS-based metaheuristic by just incorporating to it our biased randomization process with a high-quality pseudo-random number generator.

Inverse association between circulating vitamin D and mortality-dependent on sex and cause of death?

BACKGROUND AND AIMS: In various populations, vitamin D deficiency is associated with chronic diseases and mortality. We examined the association between concentration of circulating 25-hydroxyvitamin D [25(OH)D], a marker of vitamin D status, and all-cause as well as cause-specific mortality. METHODS AND RESULTS: The study included 3404 participants of the general adult Swiss population, who were recruited between November 1988 and June 1989 and followed-up until the end of 2008. Circulating 25(OH)D was measured by protein-bound assay. Cox proportional hazards regression was used to examine the association between 25(OH)D concentration and all-cause and cause-specific mortality adjusting for sex, age, season, diet, nationality, blood pressure, and smoking status. Per 10 ng/mL increase in 25(OH)D concentration, all-cause mortality decreased by 20% (HR = 0.83; 95% CI 0.74-0.92). 25(OH)D concentration was inversely associated with cardiovascular mortality in women (HR = 0.68, 95% CI 0.46-1.00 per 10 ng/mL increase), but not in men (HR = 0.97; 95% CI 0.77-1.23). In contrast, 25(OH)D concentration was inversely associated with cancer mortality in men (HR = 0.72, 95% CI 0.57-0.91 per 10 ng/mL increase), but not in women (HR = 1.14, 95% CI 0.93-1.39). Multivariate adjustment only slightly modified the 25(OH)D-mortality association. CONCLUSION: 25(OH)D was similarly inversely related to all-cause mortality in men and women. However, we observed opposite effects in women and men with respect to cardiovascular and cancer mortality.

Up-regulation of the levels of expression and function of a constitutively active mutant of the hamster alpha1B-adrenoceptor by ligands that act as inverse agonists.

The alpha1-adrenergic agonist phenylephrine stimulated phospholipase D (PLD) activity in Rat 1 fibroblasts transfected to express either the wild-type hamster alpha1B-adrenoceptor or a constitutively active mutant (CAM) form of this receptor. The EC50 for agonist stimulation of PLD activity was substantially lower at the CAM receptor than at the wild-type receptor as previously noted for phenylephrine stimulation of phosphoinositidase C activity. Sustained treatment of cells expressing the CAM alpha1B-adrenoceptor with phentolamine resulted in a marked up-regulation in levels of this receptor with half-maximal effects produced within 24 h and with an EC50 of approx. 40 nM. Such an up-regulation could be produced with a range of other ligands generally viewed as alpha1-adrenoceptor antagonists but equivalent treatment of cells expressing the wild-type alpha1B-adrenoceptor was unable to mimic these effects. After sustained treatment of the CAM alpha1B-adrenoceptor expressing cells with phentolamine, basal PLD activity was increased and phenylephrine was now able to stimulate PLD activity to greater levels than in vehicle-treated CAM alpha1B-adrenoceptor-expressing cells. The EC50 for phenylephrine stimulation of PLD activity was not altered, however, by phentolamine pretreatment and the associated up-regulation of the receptor. After phentolamine-induced up-regulation of basal PLD activity, a range of alpha1-antagonists were shown to possess the characteristics of inverse agonists of the CAM alpha1B-adrenoceptor as they were able to substantially decrease the elevated basal PLD activity.

A polynomial algorithm for special case of the one-machine scheduling problem with time-lags

The standard one-machine scheduling problem consists in schedulinga set of jobs in one machine which can handle only one job at atime, minimizing the maximum lateness. Each job is available forprocessing at its release date, requires a known processing timeand after finishing the processing, it is delivery after a certaintime. There also can exists precedence constraints between pairsof jobs, requiring that the first jobs must be completed beforethe second job can start. An extension of this problem consistsin assigning a time interval between the processing of the jobsassociated with the precedence constrains, known by finish-starttime-lags. In presence of this constraints, the problem is NP-hardeven if preemption is allowed. In this work, we consider a specialcase of the one-machine preemption scheduling problem with time-lags, where the time-lags have a chain form, and propose apolynomial algorithm to solve it. The algorithm consist in apolynomial number of calls of the preemption version of the LongestTail Heuristic. One of the applicability of the method is to obtainlower bounds for NP-hard one-machine and job-shop schedulingproblems. We present some computational results of thisapplication, followed by some conclusions.

A quantitative analysis of antagonism and inverse agonism at wild-type and constitutively active hamster alpha1B-adrenoceptors.

In order to characterize inverse agonism at alpha1B-adrenoceptors, we have compared the concentration-response relationships of several quinazoline and non-quinazoline alpha1-adrenoceptor antagonists at cloned hamster wild-type (WT) alpha1B-adrenoceptors and a constitutively active mutant (CAM) thereof upon stable expression in Rat-1 fibroblasts. Receptor activation or inhibition thereof was assessed as [3H]inositol phosphate (IP) accumulation. Quinazoline (alfuzosin, doxazosin, prazosin, terazosin) and non-quinazoline alpha1-adrenoceptor antagonists (BE 2254, SB 216,469, tamsulosin) concentration-dependently inhibited phenylephrine-stimulated IP formation at both WT and CAM with Ki values similar to those previously found in radioligand binding studies. At CAM in the absence of phenylephrine, the quinazolines produced concentration-dependent inhibition of basal IP formation; the maximum inhibition was approximately 55%, and the corresponding EC50 values were slightly smaller than the Ki values. In contrast, BE 2254 produced much less inhibition of basal IP formation, SB 216,469 was close to being a neutral antagonist, and tamsulosin even weakly stimulated IP formation. The inhibitory effects of the quinazolines and BE 2254 as well as the stimulatory effect of tamsulosin were equally blocked by SB 216,469 at CAM. At WT in the absence of phenylephrine, tamsulosin did not cause significant stimulation and none of the other compounds caused significant inhibition of basal IP formation. We conclude that alpha1-adrenoceptor antagonsits with a quinazoline structure exhibit greater efficacy as inverse agonists than those without.

On the efficiency and sensitivity of a pyramidal classification algorithm

In this paper we propose a Pyramidal Classification Algorithm,which together with an appropriate aggregation index producesan indexed pseudo-hierarchy (in the strict sense) withoutinversions nor crossings. The computer implementation of thealgorithm makes it possible to carry out some simulation testsby Monte Carlo methods in order to study the efficiency andsensitivity of the pyramidal methods of the Maximum, Minimumand UPGMA. The results shown in this paper may help to choosebetween the three classification methods proposed, in order toobtain the classification that best fits the original structureof the population, provided we have an a priori informationconcerning this structure.

A simple randomized algorithm for consistent sequential prediction of ergodic time series

We present a simple randomized procedure for the prediction of a binary sequence. The algorithm uses ideas from recent developments of the theory of the prediction of individual sequences. We show that if thesequence is a realization of a stationary and ergodic random process then the average number of mistakes converges, almost surely, to that of the optimum, given by the Bayes predictor.

MSISpIC: A Probabilistic Scan Matching Algorithm Using a Mechanical Scanned Imaging Sonar

This paper compares two well known scan matching algorithms: the MbICP and the pIC. As a result of the study, it is proposed the MSISpIC, a probabilistic scan matching algorithm for the localization of an Autonomous Underwater Vehicle (AUV). The technique uses range scans gathered with a Mechanical Scanning Imaging Sonar (MSIS), and the robot displacement estimated through dead-reckoning with the help of a Doppler Velocity Log (DVL) and a Motion Reference Unit (MRU). The proposed method is an extension of the pIC algorithm. Its major contribution consists in: 1) using an EKF to estimate the local path traveled by the robot while grabbing the scan as well as its uncertainty and 2) proposing a method to group into a unique scan, with a convenient uncertainty model, all the data grabbed along the path described by the robot. The algorithm has been tested on an AUV guided along a 600m path within a marina environment with satisfactory results

An Efficient Nominal Unification Algorithm

Nominal Unification is an extension of first-order unification where terms can contain binders and unification is performed modulo α equivalence. Here we prove that the existence of nominal unifiers can be decided in quadratic time. First, we linearly-reduce nominal unification problems to a sequence of freshness and equalities between atoms, modulo a permutation, using ideas as Paterson and Wegman for first-order unification. Second, we prove that solvability of these reduced problems may be checked in quadràtic time. Finally, we point out how using ideas of Brown and Tarjan for unbalanced merging, we could solve these reduced problems more efficiently