Evaluation of Postpolymerization as a Function of the Storage Time of Triethylene Glycol Dimethacrylate/2,2-Bis[4-(2-Hydroxy-3-Methacryloxy-Prop-1-Oxy)-Phenyl]-propane Bisphenyl-alpha-Glycidyl Ether Dimethacrylate Copolymers Used in Dental Resins by Differential Scanning Calorimetry and Dynamic Mechanical Analysis

The aim of this work was to evaluate the effect of the storage time on the thermal properties of triethylene glycol dimethacrylate/2,2-bis[4-(2-hydroxy-3-methacryloxy-prop-1-oxy)-phenyl]propane bisphenyl-alpha-glycidyl ether dimethacrylate (TB) copolymers used in formulations of dental resins after photopolymerization. The TB copolymers were prepared by photopolymerization with an Ultrablue IS light-emitting diode, stored in the dark for 160 days at 37 degrees C, and characterized with differential scanning calorimetry (DSC), dynamic mechanical analysis (DMA), and Fourier transform infrared spectroscopy with attenuated total reflection. DSC curves indicated the presence of an exothermic peak, confirming that the reaction was not completed during the photopolymerization process. This exothermic peak became smaller as a function of the storage time and was shifted at higher temperatures. In DMA studies, a plot of the loss tangent versus the temperature initially showed the presence of two well-defined peaks. The presence of both peaks confirmed the presence of residual monomers that were not converted during the photopolymerization process. (C) 2009 Wiley Periodicals, Inc. J Appl Polym Sci 112: 679-684, 2009

Capacitación en gestión de los recursos hídricos en América Latina y el Caribe: diagnóstico y propuestas = Training in water resources management in Latin America and the Caribbean: analysis and proposals

Incluye Bibliografía

Evaluation report of the training workshop on the use of the module to analyse growth of international commerce (Magic Plus) and the competitive analysis of nations (TRADECAN 2009) software

The aim of the workshop was to provide a functional overview of the software package, to enable participants to use the software in order to inform more evidence-based trade strategies, and build capacity for researchers and trade negotiators to provide more rigorous, analytical policy research to inform future trade negotiations. Participants came from the ministries of trade of the following CDCC member countries: Dominica, Grenada, Jamaica, Saint Lucia, Saint Kitts and Nevis, Saint Vincent and the Grenadines, and Trinidad and Tobago. Representatives of the following regional institutions were represented: the Caribbean Community/Caribbean Regional Negotiating Mechanism (CARICOM/CRNM); the Organisation of Eastern Caribbean States (OECS); the University of Guyana, University of Suriname and the University of the West Indies (UWI). It was hoped the workshop would be a stepping stone towards more advanced trade analysis training. The list of participants appears as Annex I.

Role of Training and Detraining on Inflammatory and Metabolic Profile in Infarcted Rats: Influences of Cardiovascular Autonomic Nervous System

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Therapist’s directive and nondirective behavior: analysis of their effects in a parent training group

The study described the interaction between therapist and clients in a group intervention with two mothers and a grandmother. Five out of thirteen taped sessions were designated for analysis. Main results: a) therapist’s categories that stood out: approval, recommendation, interpretation, information and information request; b) clients’ categories that stood out: report, agreement, relation, and opposition, c) the probability for recommendation coupled with use of approval exceeded the probability of occurrence of other combinations. Possible explanations for the results were offered and new research questions were raised.

Fuzzy Connectedness Image Segmentation in Graph Cut Formulation: A Linear-Time Algorithm and a Comparative Analysis

A deep theoretical analysis of the graph cut image segmentation framework presented in this paper simultaneously translates into important contributions in several directions. The most important practical contribution of this work is a full theoretical description, and implementation, of a novel powerful segmentation algorithm, GC(max). The output of GC(max) coincides with a version of a segmentation algorithm known as Iterative Relative Fuzzy Connectedness, IRFC. However, GC(max) is considerably faster than the classic IRFC algorithm, which we prove theoretically and show experimentally. Specifically, we prove that, in the worst case scenario, the GC(max) algorithm runs in linear time with respect to the variable M=|C|+|Z|, where |C| is the image scene size and |Z| is the size of the allowable range, Z, of the associated weight/affinity function. For most implementations, Z is identical to the set of allowable image intensity values, and its size can be treated as small with respect to |C|, meaning that O(M)=O(|C|). In such a situation, GC(max) runs in linear time with respect to the image size |C|. We show that the output of GC(max) constitutes a solution of a graph cut energy minimization problem, in which the energy is defined as the a"" (a) norm ayenF (P) ayen(a) of the map F (P) that associates, with every element e from the boundary of an object P, its weight w(e). This formulation brings IRFC algorithms to the realm of the graph cut energy minimizers, with energy functions ayenF (P) ayen (q) for qa[1,a]. Of these, the best known minimization problem is for the energy ayenF (P) ayen(1), which is solved by the classic min-cut/max-flow algorithm, referred to often as the Graph Cut algorithm. We notice that a minimization problem for ayenF (P) ayen (q) , qa[1,a), is identical to that for ayenF (P) ayen(1), when the original weight function w is replaced by w (q) . Thus, any algorithm GC(sum) solving the ayenF (P) ayen(1) minimization problem, solves also one for ayenF (P) ayen (q) with qa[1,a), so just two algorithms, GC(sum) and GC(max), are enough to solve all ayenF (P) ayen (q) -minimization problems. We also show that, for any fixed weight assignment, the solutions of the ayenF (P) ayen (q) -minimization problems converge to a solution of the ayenF (P) ayen(a)-minimization problem (ayenF (P) ayen(a)=lim (q -> a)ayenF (P) ayen (q) is not enough to deduce that). An experimental comparison of the performance of GC(max) and GC(sum) algorithms is included. This concentrates on comparing the actual (as opposed to provable worst scenario) algorithms' running time, as well as the influence of the choice of the seeds on the output.

Computational methods for the analysis of protein structure and function

The vast majority of known proteins have not yet been experimentally characterized and little is known about their function. The design and implementation of computational tools can provide insight into the function of proteins based on their sequence, their structure, their evolutionary history and their association with other proteins. Knowledge of the three-dimensional (3D) structure of a protein can lead to a deep understanding of its mode of action and interaction, but currently the structures of <1% of sequences have been experimentally solved. For this reason, it became urgent to develop new methods that are able to computationally extract relevant information from protein sequence and structure. The starting point of my work has been the study of the properties of contacts between protein residues, since they constrain protein folding and characterize different protein structures. Prediction of residue contacts in proteins is an interesting problem whose solution may be useful in protein folding recognition and de novo design. The prediction of these contacts requires the study of the protein inter-residue distances related to the specific type of amino acid pair that are encoded in the so-called contact map. An interesting new way of analyzing those structures came out when network studies were introduced, with pivotal papers demonstrating that protein contact networks also exhibit small-world behavior. In order to highlight constraints for the prediction of protein contact maps and for applications in the field of protein structure prediction and/or reconstruction from experimentally determined contact maps, I studied to which extent the characteristic path length and clustering coefficient of the protein contacts network are values that reveal characteristic features of protein contact maps. Provided that residue contacts are known for a protein sequence, the major features of its 3D structure could be deduced by combining this knowledge with correctly predicted motifs of secondary structure. In the second part of my work I focused on a particular protein structural motif, the coiled-coil, known to mediate a variety of fundamental biological interactions. Coiled-coils are found in a variety of structural forms and in a wide range of proteins including, for example, small units such as leucine zippers that drive the dimerization of many transcription factors or more complex structures such as the family of viral proteins responsible for virus-host membrane fusion. The coiled-coil structural motif is estimated to account for 5-10% of the protein sequences in the various genomes. Given their biological importance, in my work I introduced a Hidden Markov Model (HMM) that exploits the evolutionary information derived from multiple sequence alignments, to predict coiled-coil regions and to discriminate coiled-coil sequences. The results indicate that the new HMM outperforms all the existing programs and can be adopted for the coiled-coil prediction and for large-scale genome annotation. Genome annotation is a key issue in modern computational biology, being the starting point towards the understanding of the complex processes involved in biological networks. The rapid growth in the number of protein sequences and structures available poses new fundamental problems that still deserve an interpretation. Nevertheless, these data are at the basis of the design of new strategies for tackling problems such as the prediction of protein structure and function. Experimental determination of the functions of all these proteins would be a hugely time-consuming and costly task and, in most instances, has not been carried out. As an example, currently, approximately only 20% of annotated proteins in the Homo sapiens genome have been experimentally characterized. A commonly adopted procedure for annotating protein sequences relies on the "inheritance through homology" based on the notion that similar sequences share similar functions and structures. This procedure consists in the assignment of sequences to a specific group of functionally related sequences which had been grouped through clustering techniques. The clustering procedure is based on suitable similarity rules, since predicting protein structure and function from sequence largely depends on the value of sequence identity. However, additional levels of complexity are due to multi-domain proteins, to proteins that share common domains but that do not necessarily share the same function, to the finding that different combinations of shared domains can lead to different biological roles. In the last part of this study I developed and validate a system that contributes to sequence annotation by taking advantage of a validated transfer through inheritance procedure of the molecular functions and of the structural templates. After a cross-genome comparison with the BLAST program, clusters were built on the basis of two stringent constraints on sequence identity and coverage of the alignment. The adopted measure explicity answers to the problem of multi-domain proteins annotation and allows a fine grain division of the whole set of proteomes used, that ensures cluster homogeneity in terms of sequence length. A high level of coverage of structure templates on the length of protein sequences within clusters ensures that multi-domain proteins when present can be templates for sequences of similar length. This annotation procedure includes the possibility of reliably transferring statistically validated functions and structures to sequences considering information available in the present data bases of molecular functions and structures.

Clinical and biochemical description of a novel CYP21A2 gene mutation 962_963insA using a new 3D model for the P450c21 protein

OBJECTIVE: A severely virilized 46, XX newborn girl was referred to our center for evaluation and treatment of congenital adrenal hyperplasia (CAH) because of highly elevated 17alpha-hydroxyprogesterone levels at newborn screening; biochemical tests confirmed the diagnosis of salt-wasting CAH. Genetic analysis revealed that the girl was compound heterozygote for a previously reported Q318X mutation in exon 8 and a novel insertion of an adenine between nucleotides 962 and 963 in exon 4 of the CYP21A2 gene. This 962_963insA mutation created a frameshift leading to a stop codon at amino acid 161 of the P450c21 protein. AIM AND METHODS: To better understand structure-function relationships of mutant P450c21 proteins, we performed multiple sequence alignments of P450c21 with three mammalian P450s (P450 2C8, 2C9 and 2B4) with known structures as well as with human P450c17. Comparative molecular modeling of human P450c21 was then performed by MODELLER using the X-ray crystal structure of rabbit P450 2B4 as a template. RESULTS: The new three dimensional model of human P450c21 and the sequence alignment were found to be helpful in predicting the role of various amino acids in P450c21, especially those involved in heme binding and interaction with P450 oxidoreductase, the obligate electron donor. CONCLUSION: Our model will help in analyzing the genotype-phenotype relationship of P450c21 mutations which have not been tested for their functional activity in an in vitro assay.

Analysis of endogenous retinoic acid receptor expression and function in murine melanoma cells

There have been numerous reports over the past several years on the ability of vitamin A analogs (retinoids) to modulate cell proliferation, malignant transformation, morphogenesis, and differentiation in a wide variety of cell types and organisms. Two families of nuclear retinoid-inducible, trans-acting, transcription-enhancing receptors that bear strong DNA sequence homology to thyroid and steroid hormone receptors have recently been discovered. The retinoic acid receptors (RARs) and retinoid X receptors (RXRs) each have at least three types designated $\alpha,$ $\beta,$ and $\gamma,$ which are encoded by separate genes and expressed in a tissue and cell type-specific manner. We have been interested in the mechanism by which retinoids inhibit tumor cell proliferation and induce differentiation. As a model system we have employed several murine melanoma cell lines (S91-C2, K1735P, and B16-F1), which are sensitive to the growth-inhibitory and differentiation-inducing effects of RA, as well as a RA-resistant subclone of one of the cell lines (S91-C154), in order to study the role of the nuclear RARs in these effects. The initial phase of this project consisted of the characterization of the expression pattern of the three known RAR and RXR types in the murine melanoma cell lines in order to determine whether any differences exist which may elucidate a role for any of the receptors in RA-induced growth inhibition and differentiation. The novel finding was made that the RAR-$\beta$ gene is rapidly induced from undetectable levels by RA treatment at the mRNA and protein level, and that the induction of RAR-$\beta$ by other biologically active retinoids correlated with their ability to inhibit the growth of the highly RA-sensitive S91-C2 cell line. This suggests a role for RAR-$\beta$ in the growth inhibiting effect of retinoids. The second phase of this project involves the stable expression of RAR-$\beta$ in the S91-C2 cells and the RAR-$\beta$ receptor-null cell line, K1735P. These studies have indicated an inverse correlation between RAR-$\beta$ expression and proliferation rate. ^

Early growth characteristics and the risk of reduced lung function and asthma: A meta-analysis of 25,000 children

BACKGROUND Children born preterm or with a small size for gestational age are at increased risk for childhood asthma. OBJECTIVE We sought to assess the hypothesis that these associations are explained by reduced airway patency. METHODS We used individual participant data of 24,938 children from 24 birth cohorts to examine and meta-analyze the associations of gestational age, size for gestational age, and infant weight gain with childhood lung function and asthma (age range, 3.9-19.1 years). Second, we explored whether these lung function outcomes mediated the associations of early growth characteristics with childhood asthma. RESULTS Children born with a younger gestational age had a lower FEV1, FEV1/forced vital capacity (FVC) ratio, and forced expiratory volume after exhaling 75% of vital capacity (FEF75), whereas those born with a smaller size for gestational age at birth had a lower FEV1 but higher FEV1/FVC ratio (P < .05). Greater infant weight gain was associated with higher FEV1 but lower FEV1/FVC ratio and FEF75 in childhood (P < .05). All associations were present across the full range and independent of other early-life growth characteristics. Preterm birth, low birth weight, and greater infant weight gain were associated with an increased risk of childhood asthma (pooled odds ratio, 1.34 [95% CI, 1.15-1.57], 1.32 [95% CI, 1.07-1.62], and 1.27 [95% CI, 1.21-1.34], respectively). Mediation analyses suggested that FEV1, FEV1/FVC ratio, and FEF75 might explain 7% (95% CI, 2% to 10%) to 45% (95% CI, 15% to 81%) of the associations between early growth characteristics and asthma. CONCLUSIONS Younger gestational age, smaller size for gestational age, and greater infant weight gain were across the full ranges associated with childhood lung function. These associations explain the risk of childhood asthma to a substantial extent.

Minimally invasive surgical video analysis: a powerful tool for surgical training and navigation

Analysis of minimally invasive surgical videos is a powerful tool to drive new solutions for achieving reproducible training programs, objective and transparent assessment systems and navigation tools to assist surgeons and improve patient safety. This paper presents how video analysis contributes to the development of new cognitive and motor training and assessment programs as well as new paradigms for image-guided surgery.

Minimally invasive surgical video analysis: a powerful tool for surgical training and navigation

Analysis of minimally invasive surgical videos is a powerful tool to drive new solutions for achieving reproducible training programs, objective and transparent assessment systems and navigation tools to assist surgeons and improve patient safety. This paper presents how video analysis contributes to the development of new cognitive and motor training and assessment programs as well as new paradigms for image-guided surgery.

Selection, training and validation process of a sensory panel for bread analysis: Influence of cultivar on the quality of breads made from common wheat and spelta wheat

A protocol of selection, training and validation of the members of the panel for bread sensory analysis is proposed to assess the influence of wheat cultivar on the sensory quality of bread. Three cultivars of bread wheat and two cultivars of spelt wheat organically-grown under the same edaphoclimatic conditions were milled and baked using the same milling and baking procedure. Through the use of triangle tests, differences were identified between the five breads. Significant differences were found between the spelt breads and those made with bread wheat for the attributes ?crumb cell homogeneity? and ?crumb elasticity?. Significant differences were also found for the odor and flavor attributes, with the bread made with ?Espelta Navarra? being the most complex, from a sensory point of view. Based on the results of this study, we propose that sensory properties should be considered as breeding criteria for future work on genetic improvement.