Hard tissue formation adjacent to implants of various size and configuration immediately placed into extraction sockets: an experimental study in dogs

Objectives To evaluate the influence of implant size and configuration on osseointegration in implants immediately placed into extraction sockets. Material and methods Implants were installed immediately into extraction sockets in the mandibles of six Labrador dogs. In the control sites, cylindrical transmucosal implants (3.3 mm diameter) were installed, while in the test sites, larger and conical (root formed, 5 mm diameter) implants were installed. After 4 months of healing, the resorptive patterns of the alveolar crest were evaluated histomorphometrically. Results With one exception, all implants were integrated in mineralized bone, mainly composed of mature lamellar bone. The alveolar crest underwent resorption at the control as well as at the test implants. This resorption was more pronounced at the buccal aspects and significantly greater at the test (2.7 +/- 0.4 mm) than at the control implants (1.5 +/- 0.6 mm). However, the control implants were associated with residual defects that were deeper at the lingual than at the buccal aspects, while these defects were virtually absent at test implants. Conclusions The installment of root formed wide implants immediately into extraction sockets will not prevent the resorption of the alveolar crest. In contrast, this resorption is more marked both at the buccal and lingual aspects of root formed wide than at standard cylindrical implants. To cite this article:Caneva M, Salata LA, de Souza SS, Bressan E, Botticelli D, Lang NP. Hard tissue formation adjacent to implants of various size and configuration immediately placed into extraction sockets: an experimental study in dogs.Clin. Oral Impl. Res. 21, 2010; 885-895.doi: 10.1111/j.1600-0501.2010.01931.x.

Influence of implant positioning in extraction sockets on osseointegration: histomorphometric analyses in dogs

Aim To evaluate the influence of implant positioning into extraction sockets on osseointegration. Material and methods Implants were installed immediately into extraction sockets in the mandibles of six Labrador dogs. In the control sites, the implants were positioned in the center of the alveolus, while in the test sites, the implants were positioned 0.8 mm deeper and more lingually. After 4 months of healing, the resorptive patterns of the alveolar crest were evaluated histomorphometrically. Results All implants were integrated in mineralized bone, mainly composed of mature lamellar bone. The alveolar crest underwent resorption at the control as well as at the test sites. After 4 months of healing, at the buccal aspects of the control and test sites, the location of the implant rough/smooth limit to the alveolar crest was 2 +/- 0.9 mm and 0.6 +/- 0.9 mm, respectively (P < 0.05). At the lingual aspect, the bony crest was located 0.4 mm apically and 0.2 mm coronally to the implant rough/smooth limit at the control and test sites, respectively (NS). Conclusions From a clinical point of view, implants installed into extraction sockets should be positioned approximately 1 mm deeper than the level of the buccal alveolar crest and in a lingual position in relation to the center of the alveolus in order to reduce or eliminate the exposure above the alveolar crest of the endosseous (rough) portion of the implant. To cite this article:Caneva M, Salata LA, de Souza SS, Baffone G, Lang NP, Botticelli D. Influence of implant positioning in extraction sockets on osseointegration: histomorphometric analyses in dogs.Clin. Oral Impl. Res. 21, 2010; 43-49.

Ridge Preservation With Acellular Dermal Matrix and Anorganic Bone Matrix Cell-Binding Peptide P-15 After Tooth Extraction in Humans

Background: Preventing ridge collapse with the extraction of maxillary anterior teeth is vital to an esthetic restorative result. Several regenerative techniques are available and are used for socket preservation. The aim of this study is to analyze by clinical parameters the use of acellular dermal matrix (ADM) and anorganic bovine bone matrix (ABM) with synthetic cell-binding peptide P-15 to preserve alveolar bone after tooth extraction. Methods: Eighteen patients in need of extraction of maxillary anterior teeth were selected and randomly assigned to the test group (ADM plus ABM/P-15) or the control group (ADM only). Clinical measurements were recorded initially and at 6 months after ridge-preservation procedures. Results: In the clinical measurements (external vertical palatal measurement [EVPM], external vertical buccal measurement [EVBM], and alveolar horizontal measurement [AHM]) the statistical analysis showed no difference between test and control groups initially and at 6 months. The intragroup analysis, after 6 months, showed a statistically significant reduction in the measurements for both groups. In the comparison between the two groups, the differences in the test group were as follows: EVPM = 0.83 +/- 1.53 mm; EVBM = 1.20 +/- 2.02 mm; and AHM = 2.53 +/- 1.81 mm. The differences in the control group were as follows: EVPM = 0.87 +/- 1.13 mm; EVBM = 1.50 +/- 1.15 mm; and AHM = 3.40 +/- 1.39 mm. The differences in EVPM and EVBM were not statistically significant; however, in horizontal measurement (AHM), there was a statistically significant difference (P<0.05). Conclusion: The results of this study show that ADM used as membrane associated with ABM/P-15 can be used to reduce buccal-palatal dimensions compared to ADM alone for preservation of the alveolar ridge after extraction of anterior maxillary teeth. J Periodontol 2011;82:72-79.

Deterpenation of Bergamot Essential Oil Using Liquid-Liquid Extraction: Equilibrium Data of Model Systems at 298.2 K

The deterpenation of bergamot essential oil can be performed by liquid liquid extraction using hydrous ethanol as the solvent. A ternary mixture composed of 1-methyl-4-prop-1-en-2-yl-cydohexene (limonene), 3,7-dimethylocta-1,6-dien-3-yl-acetate (linalyl acetate), and 3,7-dimethylocta-1,6-dien-3-ol (linalool), three major compounds commonly found in bergamot oil, was used to simulate this essential oil. Liquid liquid equilibrium data were experimentally determined for systems containing essential oil compounds, ethanol, and water at 298.2 K and are reported in this paper. The experimental data were correlated using the NRTL and UNIQUAC models, and the mean deviations between calculated and experimental data were lower than 0.0062 in all systems, indicating the good descriptive quality of the molecular models. To verify the effect of the water mass fraction in the solvent and the linalool mass fraction in the terpene phase on the distribution coefficients of the essential oil compounds, nonlinear regression analyses were performed, obtaining mathematical models with correlation coefficient values higher than 0.99. The results show that as the water content in the solvent phase increased, the kappa value decreased, regardless of the type of compound studied. Conversely, as the linalool content increased, the distribution coefficients of hydrocarbon terpene and ester also increased. However, the linalool distribution coefficient values were negatively affected when the terpene alcohol content increased in the terpene phase.

Extracts from pitanga (Eugenia uniflora L.) leaves: Influence of extraction process on antioxidant properties and yield of phenolic compounds

Different extraction processes were employed to extract the polyphenolic compounds from pitanga (Eugenia uniflora L) leaves: a one-step process using water, ethanol or supercritical CO(2) as solvents, and a two-step process using supercritical CO(2) followed by either water or ethanol. The total polyphenolic compounds, total flavonoids and antioxidant activity were determined in all the extracts obtained. The process performance was evaluated with respect to three variables: global extraction yield, concentration and yield of both polyphenols and flavonoids in the extracts. For the one-step extraction, the results showed that the extraction yield increased with solvent polarity. For the two-step process, the results suggested that water was more efficient in extracting the phenolic compounds from E. uniflora when the matrix was previously extracted with scCO(2). With respect to the antioxidant activity, the ethanolic extracts obtained from both processes, using either the DPPH radical scavenging method or the beta-carotene bleaching method, presented high antioxidant activities. (C) 2010 Elsevier B.V. All rights reserved.

Vegetable Oils Deacidification by Solvent Extraction: Liquid-Liquid Equilibrium Data for Systems Containing Sunflower Seed Oil at 298.2 K

Liquid-liquid equilibrium experimental data for refined sunflower seed oil, artificially acidified with commercial oleic acid or commercial linoleic acid and a solvent (ethanol + water), were determined at 298.2 K. This set of experimental data and the experimental data from Cuevas et al.,(1) which were obtained from (283.2 to 333.2) K, for degummed sunflower seed oil-containing systems were correlated using NRTL and UNIQUAC models with temperature-dependent binary parameters. The deviation between experimental and calculated compositions presented average values of (1.13 and 1.41) % for NRTL and UNIQUAC equations, respectively, indicating that the models were able to correctly describe the behavior of compounds under different temperature and solvent hydration.

Response surface methodology applied to the analysis of rice bran oil extraction process with ethanol

P>Vegetable oils can be extracted using ethanol as solvent. The main goal of this work was to evaluate the ethanol performance on the extraction process of rice bran oil. The influence of process variables, solvent hydration and temperature was evaluated using the response surface methodology, aiming to maximise the soluble substances and gamma-oryzanol transfer and minimise the free fatty acids extraction and the liquid content in the underflow solid. It can be noted that oil solubility in ethanol was highly affected by the water content. The free fatty acids extraction is improved by increasing the moisture content in the solvent. Regarding the gamma-oryzanol, it can be observed that its extraction is affected by temperature when low level of water is added to ethanol. On the other hand, the influence of temperature is minimised with high levels of water in the ethanol.

Response surface analysis of extract yield and flavour intensity of Brazilian cherry (Eugenia uniflora L.) obtained by supercritical carbon dioxide extraction

This work evaluated the effect of pressure and temperature on yield and characteristic flavour intensity of Brazilian cherry (Eugenia uniflora L) extracts obtained by supercritical CO(2) using response surface analysis, which is a simple and efficient method for first inquiries. A complete central composite 2(2) factorial experimental design was applied using temperature (ranging from 40 to 60 degrees C) and pressure (from 150 to 250 bar) as independent variables. A second order model proved to be predictive (p <= 0.05) for the extract yield as affected by pressure and temperature, with better results being achieved at the central point (200 bar and 50 degrees C). For the flavour intensity, a first order model proved to be predictive (p <= 0.05) showing the influence of temperature. Greater characteristic flavour intensity in extracts was obtained for relatively high temperature (> 50 degrees C), Therefore, as far as Brazilian cherry is concerned, optimum conditions for achieving higher extract yield do not necessarily coincide to those for obtaining richer flavour intensity. Industrial relevance: Supercritical fluid extraction (SFE) is an emerging clean technology through which one may obtain extracts free from organic solvents. Extract yields from natural products for applications in food, pharmaceutical and cosmetic industries have been widely disseminated in the literature. Accordingly, two lines of research have industrial relevance, namely, (i) operational optimization studies for high SFE yields and (ii) investigation on important properties extracts are expected to present (so as to define their prospective industrial application). Specifically, this work studied the optimization of SFE process to obtain extracts from a tropical fruit showing high intensity of its characteristic flavour, aiming at promoting its application in natural aroma enrichment of processed foods. (C) 2008 Elsevier Ltd. All rights reserved.

Extraction of free fatty acids from peanut oil and avocado seed oil: Liquid-liquid equilibrium data at 298.2 K

The present paper reports phase equilibrium experimental data for two systems composed by peanut oil or avocado seed oil + commercial oleic acid + ethanol + water at 298.2 K and different water contents in the solvent. The addition of water to the solvent reduces the loss of neutral oil in the alcoholic phase and improves the solvent selectivity. The experimental data were correlated by the NRTL and UNIQUAC models. The global deviations between calculated and experimental values were 0.63 % and 1.08 %, respectively, for the systems containing avocado seed oil. In the case of systems containing peanut oil those deviations were 0.65 % and 0.98 %, respectively. Such results indicate that both models were able to reproduce correctly the experimental data, although the NRTL model presented a better performance.

Supercritical CO(2) extraction of carotenoids from pitanga fruits (Eugenia uniflora L.)

Supercritical carbon dioxide (SC-CO(2)) extraction was employed to extract carotenoids from the freeze-dried pulp of pitanga fruits (Eugenia uniflora L.), an exotic fruit, rich in carotenoids and still little explored commercially. The SC-CO(2) extraction was carried out at two temperatures, 40 and 60 degrees C, and seven pressures, 100, 150, 200, 250, 300, 350 and 400 bar. The carotenoids were determined by high-performance liquid chromatography connected to photodiode array and mass spectrometry detectors. Lycopene, rubixanthin and P-cryptoxanthin were the main carotenoids present in the freeze-dried pitanga pulp, whereas beta-cryptoxanthin concentration was negligible in the SC-CO(2) extracts, for all the investigated state conditions. The maximum recovery of carotenoids was obtained at 60 degrees C and 250 bar, extracting 55% of the total carotenoid content, 74% of the rubixanthin and 78% of the lycopene from the pulp. Under these state conditions, the total carotenoid concentration in the extract was 5474 mu g/g, represented by 66% lycopene and 32% rubixanthin. The experimental state conditions produced different SC-CO(2) extracts with respect to the extraction yield and concentration of different carotenoids, indicating that the supercritical carbon dioxide was selective in the extraction of the pitanga carotenoids as a function of temperature and pressure. (C) 2008 Elsevier B.V. All rights reserved.

Thermodynamic and statistical analysis of soybean oil extraction process using renewable solvent

The main goal of this work was to evaluate thermodynamic parameters of the soybean oil extraction process using ethanol as solvent. The experimental treatments were as follows: aqueous solvents with water contents varying from 0 to 13% (mass basis) and extraction temperature varying from 50 to 100 degrees C. The distribution coefficients of oil at equilibrium have been used to calculate enthalpy, entropy and free energy changes. The results indicate that oil extraction process with ethanol is feasible and spontaneous, mainly under higher temperature. Also, the influence of water level in the solvent and temperature were analysed using the response surface methodology (RSM). It can be noted that the extraction yield was highly affected by both independent variables. A joint analysis of thermodynamic and RSM indicates the optimal level of solvent hydration and temperature to perform the extraction process.

Alignment-based extraction of multiword expressions

Due to idiosyncrasies in their syntax, semantics or frequency, Multiword Expressions (MWEs) have received special attention from the NLP community, as the methods and techniques developed for the treatment of simplex words are not necessarily suitable for them. This is certainly the case for the automatic acquisition of MWEs from corpora. A lot of effort has been directed to the task of automatically identifying them, with considerable success. In this paper, we propose an approach for the identification of MWEs in a multilingual context, as a by-product of a word alignment process, that not only deals with the identification of possible MWE candidates, but also associates some multiword expressions with semantics. The results obtained indicate the feasibility and low costs in terms of tools and resources demanded by this approach, which could, for example, facilitate and speed up lexicographic work.

Towards improving cluster-based feature selection with a simplified silhouette filter

This paper proposes a filter-based algorithm for feature selection. The filter is based on the partitioning of the set of features into clusters. The number of clusters, and consequently the cardinality of the subset of selected features, is automatically estimated from data. The computational complexity of the proposed algorithm is also investigated. A variant of this filter that considers feature-class correlations is also proposed for classification problems. Empirical results involving ten datasets illustrate the performance of the developed algorithm, which in general has obtained competitive results in terms of classification accuracy when compared to state of the art algorithms that find clusters of features. We show that, if computational efficiency is an important issue, then the proposed filter May be preferred over their counterparts, thus becoming eligible to join a pool of feature selection algorithms to be used in practice. As an additional contribution of this work, a theoretical framework is used to formally analyze some properties of feature selection methods that rely on finding clusters of features. (C) 2011 Elsevier Inc. All rights reserved.

An investigation into feature construction to assist word sense disambiguation

Identifying the correct sense of a word in context is crucial for many tasks in natural language processing (machine translation is an example). State-of-the art methods for Word Sense Disambiguation (WSD) build models using hand-crafted features that usually capturing shallow linguistic information. Complex background knowledge, such as semantic relationships, are typically either not used, or used in specialised manner, due to the limitations of the feature-based modelling techniques used. On the other hand, empirical results from the use of Inductive Logic Programming (ILP) systems have repeatedly shown that they can use diverse sources of background knowledge when constructing models. In this paper, we investigate whether this ability of ILP systems could be used to improve the predictive accuracy of models for WSD. Specifically, we examine the use of a general-purpose ILP system as a method to construct a set of features using semantic, syntactic and lexical information. This feature-set is then used by a common modelling technique in the field (a support vector machine) to construct a classifier for predicting the sense of a word. In our investigation we examine one-shot and incremental approaches to feature-set construction applied to monolingual and bilingual WSD tasks. The monolingual tasks use 32 verbs and 85 verbs and nouns (in English) from the SENSEVAL-3 and SemEval-2007 benchmarks; while the bilingual WSD task consists of 7 highly ambiguous verbs in translating from English to Portuguese. The results are encouraging: the ILP-assisted models show substantial improvements over those that simply use shallow features. In addition, incremental feature-set construction appears to identify smaller and better sets of features. Taken together, the results suggest that the use of ILP with diverse sources of background knowledge provide a way for making substantial progress in the field of WSD.

Interactive Vector Field Feature Identification

We introduce a flexible technique for interactive exploration of vector field data through classification derived from user-specified feature templates. Our method is founded on the observation that, while similar features within the vector field may be spatially disparate, they share similar neighborhood characteristics. Users generate feature-based visualizations by interactively highlighting well-accepted and domain specific representative feature points. Feature exploration begins with the computation of attributes that describe the neighborhood of each sample within the input vector field. Compilation of these attributes forms a representation of the vector field samples in the attribute space. We project the attribute points onto the canonical 2D plane to enable interactive exploration of the vector field using a painting interface. The projection encodes the similarities between vector field points within the distances computed between their associated attribute points. The proposed method is performed at interactive rates for enhanced user experience and is completely flexible as showcased by the simultaneous identification of diverse feature types.