A hybrid algorithm combining metaheuristic with Monte Carlo simulation for solving the Stochastic Flow Shop problem

In this paper, a hybrid simulation-based algorithm is proposed for the StochasticFlow Shop Problem. The main idea of the methodology is to transform the stochastic problem into a deterministic problem and then apply simulation to the latter. In order to achieve this goal, we rely on Monte Carlo Simulation and an adapted version of a deterministic heuristic. This approach aims to provide flexibility and simplicity due to the fact that it is not constrained by any previous assumption and relies in well-tested heuristics.

EADock : design of a new molecular docking algorithm and some of its applications

3 Summary 3. 1 English The pharmaceutical industry has been facing several challenges during the last years, and the optimization of their drug discovery pipeline is believed to be the only viable solution. High-throughput techniques do participate actively to this optimization, especially when complemented by computational approaches aiming at rationalizing the enormous amount of information that they can produce. In siiico techniques, such as virtual screening or rational drug design, are now routinely used to guide drug discovery. Both heavily rely on the prediction of the molecular interaction (docking) occurring between drug-like molecules and a therapeutically relevant target. Several softwares are available to this end, but despite the very promising picture drawn in most benchmarks, they still hold several hidden weaknesses. As pointed out in several recent reviews, the docking problem is far from being solved, and there is now a need for methods able to identify binding modes with a high accuracy, which is essential to reliably compute the binding free energy of the ligand. This quantity is directly linked to its affinity and can be related to its biological activity. Accurate docking algorithms are thus critical for both the discovery and the rational optimization of new drugs. In this thesis, a new docking software aiming at this goal is presented, EADock. It uses a hybrid evolutionary algorithm with two fitness functions, in combination with a sophisticated management of the diversity. EADock is interfaced with .the CHARMM package for energy calculations and coordinate handling. A validation was carried out on 37 crystallized protein-ligand complexes featuring 11 different proteins. The search space was defined as a sphere of 15 R around the center of mass of the ligand position in the crystal structure, and conversely to other benchmarks, our algorithms was fed with optimized ligand positions up to 10 A root mean square deviation 2MSD) from the crystal structure. This validation illustrates the efficiency of our sampling heuristic, as correct binding modes, defined by a RMSD to the crystal structure lower than 2 A, were identified and ranked first for 68% of the complexes. The success rate increases to 78% when considering the five best-ranked clusters, and 92% when all clusters present in the last generation are taken into account. Most failures in this benchmark could be explained by the presence of crystal contacts in the experimental structure. EADock has been used to understand molecular interactions involved in the regulation of the Na,K ATPase, and in the activation of the nuclear hormone peroxisome proliferatoractivated receptors a (PPARa). It also helped to understand the action of common pollutants (phthalates) on PPARy, and the impact of biotransformations of the anticancer drug Imatinib (Gleevec®) on its binding mode to the Bcr-Abl tyrosine kinase. Finally, a fragment-based rational drug design approach using EADock was developed, and led to the successful design of new peptidic ligands for the a5ß1 integrin, and for the human PPARa. In both cases, the designed peptides presented activities comparable to that of well-established ligands such as the anticancer drug Cilengitide and Wy14,643, respectively. 3.2 French Les récentes difficultés de l'industrie pharmaceutique ne semblent pouvoir se résoudre que par l'optimisation de leur processus de développement de médicaments. Cette dernière implique de plus en plus. de techniques dites "haut-débit", particulièrement efficaces lorsqu'elles sont couplées aux outils informatiques permettant de gérer la masse de données produite. Désormais, les approches in silico telles que le criblage virtuel ou la conception rationnelle de nouvelles molécules sont utilisées couramment. Toutes deux reposent sur la capacité à prédire les détails de l'interaction moléculaire entre une molécule ressemblant à un principe actif (PA) et une protéine cible ayant un intérêt thérapeutique. Les comparatifs de logiciels s'attaquant à cette prédiction sont flatteurs, mais plusieurs problèmes subsistent. La littérature récente tend à remettre en cause leur fiabilité, affirmant l'émergence .d'un besoin pour des approches plus précises du mode d'interaction. Cette précision est essentielle au calcul de l'énergie libre de liaison, qui est directement liée à l'affinité du PA potentiel pour la protéine cible, et indirectement liée à son activité biologique. Une prédiction précise est d'une importance toute particulière pour la découverte et l'optimisation de nouvelles molécules actives. Cette thèse présente un nouveau logiciel, EADock, mettant en avant une telle précision. Cet algorithme évolutionnaire hybride utilise deux pressions de sélections, combinées à une gestion de la diversité sophistiquée. EADock repose sur CHARMM pour les calculs d'énergie et la gestion des coordonnées atomiques. Sa validation a été effectuée sur 37 complexes protéine-ligand cristallisés, incluant 11 protéines différentes. L'espace de recherche a été étendu à une sphère de 151 de rayon autour du centre de masse du ligand cristallisé, et contrairement aux comparatifs habituels, l'algorithme est parti de solutions optimisées présentant un RMSD jusqu'à 10 R par rapport à la structure cristalline. Cette validation a permis de mettre en évidence l'efficacité de notre heuristique de recherche car des modes d'interactions présentant un RMSD inférieur à 2 R par rapport à la structure cristalline ont été classés premier pour 68% des complexes. Lorsque les cinq meilleures solutions sont prises en compte, le taux de succès grimpe à 78%, et 92% lorsque la totalité de la dernière génération est prise en compte. La plupart des erreurs de prédiction sont imputables à la présence de contacts cristallins. Depuis, EADock a été utilisé pour comprendre les mécanismes moléculaires impliqués dans la régulation de la Na,K ATPase et dans l'activation du peroxisome proliferatoractivated receptor a (PPARa). Il a également permis de décrire l'interaction de polluants couramment rencontrés sur PPARy, ainsi que l'influence de la métabolisation de l'Imatinib (PA anticancéreux) sur la fixation à la kinase Bcr-Abl. Une approche basée sur la prédiction des interactions de fragments moléculaires avec protéine cible est également proposée. Elle a permis la découverte de nouveaux ligands peptidiques de PPARa et de l'intégrine a5ß1. Dans les deux cas, l'activité de ces nouveaux peptides est comparable à celles de ligands bien établis, comme le Wy14,643 pour le premier, et le Cilengitide (PA anticancéreux) pour la seconde.

A hybrid algorithm combining metaheuristic with Monte Carlo simulation for solving the Stochastic Flow Shop problem

In this paper, a hybrid simulation-based algorithm is proposed for the StochasticFlow Shop Problem. The main idea of the methodology is to transform the stochastic problem into a deterministic problem and then apply simulation to the latter. In order to achieve this goal, we rely on Monte Carlo Simulation and an adapted version of a deterministic heuristic. This approach aims to provide flexibility and simplicity due to the fact that it is not constrained by any previous assumption and relies in well-tested heuristics.

Estimating soybean crop areas using spectral-temporal surfaces derived from MODIS images in Mato Grosso, Brazil

The objective of this work was to evaluate the application of the spectral-temporal response surface (STRS) classification method on Moderate Resolution Imaging Spectroradiometer (MODIS, 250 m) sensor images in order to estimate soybean areas in Mato Grosso state, Brazil. The classification was carried out using the maximum likelihood algorithm (MLA) adapted to the STRS method. Thirty segments of 30x30 km were chosen along the main agricultural regions of Mato Grosso state, using data from the summer season of 2005/2006 (from October to March), and were mapped based on fieldwork data, TM/Landsat-5 and CCD/CBERS-2 images. Five thematic classes were considered: Soybean, Forest, Cerrado, Pasture and Bare Soil. The classification by the STRS method was done over an area intersected with a subset of 30x30-km segments. In regions with soybean predominance, STRS classification overestimated in 21.31% of the reference values. In regions where soybean fields were less prevalent, the classifier overestimated 132.37% in the acreage of the reference. The overall classification accuracy was 80%. MODIS sensor images and the STRS algorithm showed to be promising for the classification of soybean areas in regions with the predominance of large farms. However, the results for fragmented areas and smaller farms were less efficient, overestimating soybean areas.

Oscillations, phase-of-firing coding, and spike timing-dependent plasticity: an efficient learning scheme

Recent experiments have established that information can be encoded in the spike times of neurons relative to the phase of a background oscillation in the local field potential—a phenomenon referred to as “phase-of-firing coding” (PoFC). These firing phase preferences could result from combining an oscillation in the input current with a stimulus-dependent static component that would produce the variations in preferred phase, but it remains unclear whether these phases are an epiphenomenon or really affect neuronal interactions—only then could they have a functional role. Here we show that PoFC has a major impact on downstream learning and decoding with the now well established spike timing-dependent plasticity (STDP). To be precise, we demonstrate with simulations how a single neuron equipped with STDP robustly detects a pattern of input currents automatically encoded in the phases of a subset of its afferents, and repeating at random intervals. Remarkably, learning is possible even when only a small fraction of the afferents (~10%) exhibits PoFC. The ability of STDP to detect repeating patterns had been noted before in continuous activity, but it turns out that oscillations greatly facilitate learning. A benchmark with more conventional rate-based codes demonstrates the superiority of oscillations and PoFC for both STDP-based learning and the speed of decoding: the oscillation partially formats the input spike times, so that they mainly depend on the current input currents, and can be efficiently learned by STDP and then recognized in just one oscillation cycle. This suggests a major functional role for oscillatory brain activity that has been widely reported experimentally.

Spatiotemporal adaptive multiscale multiphysics simulations of two-phase flow

We present a spatiotemporal adaptive multiscale algorithm, which is based on the Multiscale Finite Volume method. The algorithm offers a very efficient framework to deal with multiphysics problems and to couple regions with different spatial resolution. We employ the method to simulate two-phase flow through porous media. At the fine scale, we consider a pore-scale description of the flow based on the Volume Of Fluid method. In order to construct a global problem that describes the coarse-scale behavior, the equations are averaged numerically with respect to auxiliary control volumes, and a Darcy-like coarse-scale model is obtained. The space adaptivity is based on the idea that a fine-scale description is only required in the front region, whereas the resolution can be coarsened elsewhere. Temporal adaptivity relies on the fact that the fine-scale and the coarse-scale problems can be solved with different temporal resolution (longer time steps can be used at the coarse scale). By simulating drainage under unstable flow conditions, we show that the method is able to capture the coarse-scale behavior outside the front region and to reproduce complex fluid patterns in the front region.

Management of Pharyngeal Fistulas After Anterior Cervical Spine Surgery: A Treatment Algorithm for Severe Complications.

STUDY DESIGN:: Retrospective database- query to identify all anterior spinal approaches. OBJECTIVES:: To assess all patients with pharyngo-cutaneous fistulas after anterior cervical spine surgery. SUMMARY OF BACKGROUND DATA:: Patients treated in University of Heidelberg Spine Medical Center, Spinal Cord Injury Unit and Department of Otolaryngology (Germany), between 2005 and 2011 with the diagnosis of pharyngo-cutaneous fistulas. METHODS:: We conducted a retrospective study on 5 patients between 2005 and 2011 with PCF after ACSS, their therapy management and outcome according to radiologic data and patient charts. RESULTS:: Upon presentation 4 patients were paraplegic. 2 had PCF arising from one piriform sinus, two patients from the posterior pharyngeal wall and piriform sinus combined and one patient only from the posterior pharyngeal wall. 2 had previous unsuccessful surgical repair elsewhere and 1 had prior radiation therapy. In 3 patients speech and swallowing could be completely restored, 2 patients died. Both were paraplegic. The patients needed an average of 2-3 procedures for complete functional recovery consisting of primary closure with various vascularised regional flaps and refining laser procedures supplemented with negative pressure wound therapy where needed. CONCLUSION:: Based on our experience we are able to provide a treatment algorithm that indicates that chronic as opposed to acute fistulas require a primary surgical closure combined with a vascularised flap that should be accompanied by the immediate application of a negative pressure wound therapy. We also conclude that particularly in paraplegic patients suffering this complication the risk for a fatal outcome is substantial.

Exploring the space of histidine containing dipeptides in search of novel efficient RCS sequestering agents.

The study reports a set of forty proteinogenic histidine-containing dipeptides as potential carbonyl quenchers. The peptides were chosen to cover as exhaustively as possible the accessible chemical space, and their quenching activities toward 4-hydroxy-2-nonenal (HNE) and pyridoxal were evaluated by HPLC analyses. The peptides were capped at the C-terminus as methyl esters or amides to favor their resistance to proteolysis and diastereoisomeric pairs were considered to reveal the influence of configuration on quenching. On average, the examined dipeptides are less active than the parent compound carnosine (βAla + His) thus emphasizing the unfavorable effect of the shortening of the βAla residue as confirmed by the control dipeptide Gly-His. Nevertheless, some peptides show promising activities toward HNE combined with a remarkable selectivity. The results emphasize the beneficial role of aromatic and positively charged residues, while negatively charged and H-bonding side chains show a detrimental effect on quenching. As a trend, ester derivatives are slightly more active than amides while heterochiral peptides are more active than their homochiral diastereoisomer. Overall, the results reveal that quenching activity strongly depends on conformational effects and vicinal residues (as evidenced by the reported QSAR analysis), offering insightful clues for the design of improved carbonyl quenchers and to rationalize the specific reactivity of histidine residues within proteins.

Safety of a new algorithm for the management of childhood illness (Almanach) to improve quality of care and rational use of drugs

Introduction New evidence from randomized controlled and etiology of fever studies, the availability of reliable RDT for malaria, and novel technologies call for revision of the IMCI strategy. We developed a new algorithm based on (i) a systematic review of published studies assessing the safety and appropriateness of RDT and antibiotic prescription, (ii) results from a clinical and microbiological investigation of febrile children aged <5 years, (iii) international expert IMCI opinions. The aim of this study was to assess the safety of the new algorithm among patients in urban and rural areas of Tanzania.Materials and Methods The design was a controlled noninferiority study. Enrolled children aged 2-59 months with any illness were managed either by a study clinician using the new Almanach algorithm (two intervention health facilities), or clinicians using standard practice, including RDT (two control HF). At day 7 and day 14, all patients were reassessed. Patients who were ill in between or not cured at day 14 were followed until recovery or death. Primary outcome was rate of complications, secondary outcome rate of antibiotic prescriptions.Results 1062 children were recruited. Main diagnoses were URTI 26%, pneumonia 19% and gastroenteritis (9.4%). 98% (531/541) were cured at D14 in the Almanach arm and 99.6% (519/521) in controls. Rate of secondary hospitalization was 0.2% in each. One death occurred in controls. None of the complications was due to withdrawal of antibiotics or antimalarials at day 0. Rate of antibiotic use was 19% in the Almanach arm and 84% in controls.Conclusion Evidence suggests that the new algorithm, primarily aimed at the rational use of drugs, is as safe as standard practice and leads to a drastic reduction of antibiotic use. The Almanach is currently being tested for clinician adherence to proposed procedures when used on paper or a mobile phone

Spiral CT aortography: an efficient technique for the diagnosis of traumatic aortic injury.

The objective of this study was to assess the efficiency of spiral CT (SCT) aortography for diagnosing acute aortic lesions in blunt thoracic trauma patients. Between October 1992 and June 1997, 487 SCT scans of the chest were performed on blunt thoracic trauma patients. To assess aortic injury, the following SCT criteria were considered: hemomediastinum, peri-aortic hematoma, irregular aspect of the aortic wall, aortic pseudodiverticulum, intimal flap and traumatic dissection. Aortic injury was diagnosed on 14 SCT examinations (2.9 %), five of the patients having had an additional digital aortography that confirmed the aortic trauma. Twelve subjects underwent surgical repair of the thoracic aorta, which in all but one case confirmed the aortic injury. Two patients died before surgery from severe brain lesions. The aortic blunt lesions were confirmed at autopsy. According to the follow-up of the other 473 patients, we are aware of no false-negative SCT examination. Our limited series shows a sensitivity of 100 % and specificity of 99.8 % of SCT aortography in the diagnosis of aortic injury. It is concluded that SCT aortagraphy is an accurate diagnostic method for the assessment of aortic injury in blunt thoracic trauma patients.

Application of RNAi to silence tartrate-resistant acid phosphatase: unexpected effects on the monocyte-macrophage lineage

Tartraatti-resistentin happaman fosfataasin hiljentäminen RNAi menetelmällä: odottamaton vaikutus monosyytti-makrofagi linjan soluissa RNA interferenssi (RNAi) eli RNA:n hiljentyminen löydettiin ensimmäisenä kasveissa, ja 2000-luvulla RNAi menetelmä on otettu käyttöön myös nisäkässoluissa. RNAi on mekanismi, jossa lyhyet kaksi juosteiset RNA molekyylit eli siRNA:t sitoutuvat proteiinikompleksiin ja sitoutuvat komplementaarisesti proteiinia koodaavaan lähetti RNA:han katalysoiden lähetti RNA:n hajoamisen. Tällöin RNA:n koodaamaa proteiinia ei solussa tuoteta. Tässä työssä on RNA interferenssi menetelmän avuksi kehitetty uusi siRNA molekyylien suunnittelualgoritmi siRNA_profile, joka etsii lähetti RNA:sta geenin hiljentämiseen sopivia kohdealueita. Optimaalisesti suunnitellulla siRNA molekyylillä voi olla mahdollista saavuttaa pitkäaikainen geenin hiljeneminen ja spesifinen kohdeproteiinin määrän aleneminen solussa. Erilaiset kemialliset modifikaatiot, mm. 2´-Fluoro-modifikaatio, siRNA molekyylin riboosirenkaassa lisäsivät siRNA molekyylin stabiilisuutta veren plasmassa sekä siRNA molekyylin tehokkuutta. Nämä ovat tärkeitä siRNA molekyylien ominaisuuksia kun RNAi menetelmää sovelletaan lääketieteellisiin tarkoituksiin. Tartraatti-resistentti hapan fosfataasi (TRACP) on entsyymi, joka esiintyy luunsyöjäsoluissa eli osteoklasteissa, antigeenejä esittelevissä dendiriittisissä soluissa sekä eri kudosten makrofageissa, jotka ovat syöjäsoluja. TRACP entsyymin biologista tehtävää ei ole saatu selville, mutta oletetaan että TRACP entsyymin kyvyllä tuottaa reaktiivisia happiradikaaleja on tehtävä sekä luuta hajoittavissa osteoklasteissa sekä antigeenia esittelevissä dendriittisissä soluissa. Makrofageilla, jotka yliekpressoivat TRACP entsyymiä, on myös solunsisäinen reaktiivisten happiradikaalien tuotanto sekä bakteerin tappokyky lisääntynyt. TRACP-geenin hiljentämiseen tarkoitetut spesifiset DNA ja siRNA molekyylit aiheuttivat monosyytti-makrofagilinjan soluviljelymallissa TRACP entsyymin tuoton lisääntymistä odotusten vastaisesti. DNA ja RNA molekyylien vaikutusta TRACP entsyymin tuoton lisääntymiseen tutkittiin myös Tolllike reseptori 9 (TLR9) poistogeenisestä hiirestä eristetyissä monosyyttimakrofaagisoluissa. TRACP entsyymin tuoton lisääntyminen todettiin sekvenssistä ja TLR9:stä riippumattomaksi vasteeksi solun ulkopuolisia DNA ja RNA molekyylejä vastaan. Havainto TRACP entsyymin tuoton lisääntymisestä viittaa siihen, että TRACP entsyymillä on tehtävä solun immuunipuolustusjärjestelmässä.