The carbohydrate-binding specificity and molecular modelling of Canavalia maritima and Dioclea grandiflora lectins

The carbohydrate-binding specificity of lectins from the seeds of Canavalia maritima and Dioclea grandiflora was studied by hapten-inhibition of haemagglutination using various sugars and sugar derivatives as inhibitors, including N-acetylneuraminic acid and N-acetylmuramic acid. Despite some discrepancies, both lectins exhibited a very similar carbohydrate-binding specificity as previously reported for other lectins from Diocleinae (tribe Phaseoleae, sub-tribe Diocleinae). Accordingly, both lectins exhibited almost identical hydropathic profiles and their three-dimensional models built up from the atomic coordinates of ConA looked very similar. However, docking experiments of glucose and mannose in their monosaccharide-binding sites, by comparison with the ConA-mannose complex used as a model, revealed conformational changes in side chains of the amino acid residues involved in the binding of monosaccharides. These results fully agree with crystallographic data showing that binding of specific ligands to ConA requires conformational chances of its monosaccharide-binding site.

Modelling Interbank Relations during the International Financial Crisis

This paper examines the effects of the current financial crisis on the correlations of four international banking stocks. We find that in the beginning of the crisis banks generally show a transition to a higher correlation followed by a dramatic decline towards the end of 2008. These findings are consistent with both traditional contagion theory and the more recent network theory of contagion. JEL classifications: C51; G15 Keywords: Financial Crises; Contagion; Interbank Markets.

Update of the Gene Discovery Program in Schistosoma mansoni with the Expressed Sequence Tag Approach

Continuing the Schistosoma mansoni Genome Project 363 new templates were sequenced generating 205 more ESTs corresponding to 91 genes. Seventy four of these genes (81%) had not previously been described in S. mansoni. Among the newly discovered genes there are several of significant biological interest such as synaptophysin, NIFs-like and rho-GDP dissociation inhibitor

Clinical benefits of an adherence monitoring program in the management of secondary hyperparathyroidism with cinacalcet: results of a prospective randomized controlled study.

BACKGROUND/AIMS: One of the causes of uncontrolled secondary hyperparathyroidism (sHPT) is patient's poor drug adherence. We evaluated the clinical benefits of an integrated care approach on the control of sHPT by cinacalcet. METHODS: Prospective, randomized, controlled, multicenter, open-label study. Fifty hemodialysis patients on a stable dose of cinacalcet were randomized to an integrated care approach (IC) or usual care approach (UC). In the IC group, cinacalcet adherence was monitored using an electronic system. Results were discussed with the patients in motivational interviews, and drug prescription adapted accordingly. In the UC group, drug adherence was monitored, but results were not available. RESULTS: At six months, 84% of patients in the IC group achieved recommended iPTH targets versus 55% in the UC group (P = 0.04). The mean cinacalcet taking adherence improved by 10.8% in the IC group and declined by 5.3% in the UC group (P = 0.02). Concomitantly, the mean dose of cinacalcet was reduced by 7.2 mg/day in the IC group and increased by 6.4 mg/day in the UC group (P = 0.03). CONCLUSIONS: The use of a drug adherence monitoring program in the management of sHPT in hemodialysis patients receiving cinacalcet improves drug adherence and iPTH control and allows a reduction in the dose of cinacalcet.

Different approaches to modelling the cost-effectiveness of schistosomiasis control

This paper reviews three different approaches to modelling the cost-effectiveness of schistosomiasis control. Although these approaches vary in their assessment of costs, the major focus of the paper is on the evaluation of effectiveness. The first model presented is a static economic model which assesses effectiveness in terms of the proportion of cases cured. This model is important in highlighting that the optimal choice of chemotherapy regime depends critically on the level of budget constraint, the unit costs of screening and treatment, the rates of compliance with screening and chemotherapy and the prevalence of infection. The limitations of this approach is that it models the cost-effectiveness of only one cycle of treatment, and effectiveness reflects only the immediate impact of treatment. The second model presented is a prevalence-based dynamic model which links prevalence rates from one year to the next, and assesses effectiveness as the proportion of cases prevented. This model was important as it introduced the concept of measuring the long-term impact of control by using a transmission model which can assess reduction in infection through time, but is limited to assessing the impact only on the prevalence of infection. The third approach presented is a theoretical framework which describes the dynamic relationships between infection and morbidity, and which assesses effectiveness in terms of case-years prevented of infection and morbidity. The use of this model in assessing the cost-effectiveness of age-targeted treatment in controlling Schistosoma mansoni is explored in detail, with respect to varying frequencies of treatment and the interaction between drug price and drug efficacy.

Population pharmacokinetic modelling and evaluation of different dosage regimens for darunavir and ritonavir in HIV-infected individuals.

OBJECTIVES: Darunavir is a protease inhibitor that is administered with low-dose ritonavir to enhance its bioavailability. It is prescribed at standard dosage regimens of 600/100 mg twice daily in treatment-experienced patients and 800/100 mg once daily in naive patients. A population pharmacokinetic approach was used to characterize the pharmacokinetics of both drugs and their interaction in a cohort of unselected patients and to compare darunavir exposure expected under alternative dosage regimens. METHODS: The study population included 105 HIV-infected individuals who provided darunavir and ritonavir plasma concentrations. Firstly, a population pharmacokinetic analysis for darunavir and ritonavir was conducted, with inclusion of patients' demographic, clinical and genetic characteristics as potential covariates (NONMEM(®)). Then, the interaction between darunavir and ritonavir was studied while incorporating levels of both drugs into different inhibitory models. Finally, model-based simulations were performed to compare trough concentrations (Cmin) between the recommended dosage regimen and alternative combinations of darunavir and ritonavir. RESULTS: A one-compartment model with first-order absorption adequately characterized darunavir and ritonavir pharmacokinetics. The between-subject variability in both compounds was important [coefficient of variation (CV%) 34% and 47% for darunavir and ritonavir clearance, respectively]. Lopinavir and ritonavir exposure (AUC) affected darunavir clearance, while body weight and darunavir AUC influenced ritonavir elimination. None of the tested genetic variants showed any influence on darunavir or ritonavir pharmacokinetics. The simulations predicted darunavir Cmin much higher than the IC50 thresholds for wild-type and protease inhibitor-resistant HIV-1 strains (55 and 550 ng/mL, respectively) under standard dosing in >98% of experienced and naive patients. Alternative regimens of darunavir/ritonavir 1200/100 or 1200/200 mg once daily also had predicted adequate Cmin (>550 ng/mL) in 84% and 93% of patients, respectively. Reduction of darunavir/ritonavir dosage to 600/50 mg twice daily led to a 23% reduction in average Cmin, still with only 3.8% of patients having concentrations below the IC50 for resistant strains. CONCLUSIONS: The important variability in darunavir and ritonavir pharmacokinetics is poorly explained by clinical covariates and genetic influences. In experienced patients, treatment simplification strategies guided by drug level measurements and adherence monitoring could be proposed.

Phylogenetic conservatism in plant phenology

Phenological events - defined points in the life cycle of a plant or animal - have been regarded as highly plastic traits, reflecting flexible responses to various environmental cues. The ability of a species to track, via shifts in phenological events, the abiotic environment through time might dictate its vulnerability to future climate change. Understanding the predictors and drivers of phenological change is therefore critical. Here, we evaluated evidence for phylogenetic conservatism - the tendency for closely related species to share similar ecological and biological attributes - in phenological traits across flowering plants. We aggregated published and unpublished data on timing of first flower and first leaf, encompassing 4000 species at 23 sites across the Northern Hemisphere. We reconstructed the phylogeny for the set of included species, first, using the software program Phylomatic, and second, from DNA data. We then quantified phylogenetic conservatism in plant phenology within and across sites. We show that more closely related species tend to flower and leaf at similar times. By contrasting mean flowering times within and across sites, however, we illustrate that it is not the time of year that is conserved, but rather the phenological responses to a common set of abiotic cues. Our findings suggest that species cannot be treated as statistically independent when modelling phenological responses.Synthesis. Closely related species tend to resemble each other in the timing of their life-history events, a likely product of evolutionarily conserved responses to environmental cues. The search for the underlying drivers of phenology must therefore account for species' shared evolutionary histories.

Simulium spp. control program in Rio Grande do Sul, Brazil

Insects of the Simuliidae family have been the object of control in Rio Grande do Sul since the 70s. Their constant attacks became a social-economical problem as well as a problem of Public Health, with serious consequences to men and to the economy of the areas in which the insects develop. At first, the control was done with a chemical larvicide Themephos ABATE 500 E, but an imperfect measuring of outflow to determine the quantity of the product made Simulium spp. resistant to it. From 1983 on, following a study of a new method for the outflow measuring, we started to use a biological larvicide Bacillus thuringiensis serovar israelensis based. The biological control uses the new method in 36.4% of the state area, assisting about 3,500,000 inhabitants.

Re: Cost effectiveness of strategies to combat cardiovascular disease, diabetes, and tobacco use in sub-Saharan Africa and South East Asia: mathematical modelling study.

Rapid response to: Ortegón M, Lim S, Chisholm D, Mendis S. Cost effectiveness of strategies to combat cardiovascular disease, diabetes, and tobacco use in sub-Saharan Africa and South East Asia: mathematical modelling study. BMJ. 2012 Mar 2;344:e607. doi: 10.1136/bmj.e607. PMID: 22389337.

Extreme Precipitation Modelling Using Geostatistics and Machine Learning Algorithms

The paper presents an approach for mapping of precipitation data. The main goal is to perform spatial predictions and simulations of precipitation fields using geostatistical methods (ordinary kriging, kriging with external drift) as well as machine learning algorithms (neural networks). More practically, the objective is to reproduce simultaneously both the spatial patterns and the extreme values. This objective is best reached by models integrating geostatistics and machine learning algorithms. To demonstrate how such models work, two case studies have been considered: first, a 2-day accumulation of heavy precipitation and second, a 6-day accumulation of extreme orographic precipitation. The first example is used to compare the performance of two optimization algorithms (conjugate gradients and Levenberg-Marquardt) of a neural network for the reproduction of extreme values. Hybrid models, which combine geostatistical and machine learning algorithms, are also treated in this context. The second dataset is used to analyze the contribution of radar Doppler imagery when used as external drift or as input in the models (kriging with external drift and neural networks). Model assessment is carried out by comparing independent validation errors as well as analyzing data patterns.

A theoretical model of the tridimensional structure of Bacillus thuringiensis subsp. medellin Cry 11Bb toxin deduced by homology modelling

Cry11Bb is an insecticidal crystal protein produced by Bacillus thuringiensis subsp. medellin during its stationary phase; this ¶-endotoxin is active against dipteran insects and has great potential for mosquito borne disease control. Here, we report the first theoretical model of the tridimensional structure of a Cry11 toxin. The tridimensional structure of the Cry11Bb toxin was obtained by homology modelling on the structures of the Cry1Aa and Cry3Aa toxins. In this work we give a brief description of our model and hypothesize the residues of the Cry11Bb toxin that could be important in receptor recognition and pore formation. This model will serve as a starting point for the design of mutagenesis experiments aimed to the improvement of toxicity, and to provide a new tool for the elucidation of the mechanism of action of these mosquitocidal proteins.

Sound Texture Modelling

In the PhD thesis “Sound Texture Modeling” we deal with statistical modelling or textural sounds like water, wind, rain, etc. For synthesis and classification. Our initial model is based on a wavelet tree signal decomposition and the modeling of the resulting sequence by means of a parametric probabilistic model, that can be situated within the family of models trainable via expectation maximization (hidden Markov tree model ). Our model is able to capture key characteristics of the source textures (water, rain, fire, applause, crowd chatter ), and faithfully reproduces some of the sound classes. In terms of a more general taxonomy of natural events proposed by Graver, we worked on models for natural event classification and segmentation. While the event labels comprise physical interactions between materials that do not have textural propierties in their enterity, those segmentation models can help in identifying textural portions of an audio recording useful for analysis and resynthesis. Following our work on concatenative synthesis of musical instruments, we have developed a pattern-based synthesis system, that allows to sonically explore a database of units by means of their representation in a perceptual feature space. Concatenative syntyhesis with “molecules” built from sparse atomic representations also allows capture low-level correlations in perceptual audio features, while facilitating the manipulation of textural sounds based on their physical and perceptual properties. We have approached the problem of sound texture modelling for synthesis from different directions, namely a low-level signal-theoretic point of view through a wavelet transform, and a more high-level point of view driven by perceptual audio features in the concatenative synthesis setting. The developed framework provides unified approach to the high-quality resynthesis of natural texture sounds. Our research is embedded within the Metaverse 1 European project (2008-2011), where our models are contributting as low level building blocks within a semi-automated soundscape generation system.