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Purpose: The object of this literature review was to highlight the value of CBCT as a key resource for the oral surgeon, both in the diagnostic phase and in the therapeutic planning phase, in order to improve the quality and safety of clinical practice. Complementary aspects were also considered such as: basic operation of the machine, radiation dose and comparison with other diagnostic tools when needed. Materials & Methods: A literature research was carried out mainly using online sources, PubMed database, and paper sources (specialized books). 100 articles and 10 authoritative books published over the last 10 years have been firstly examined. Systematic reviews, narrative reviews, mini reviews and meta-analysis were primarily selected. If a subject matter appeared to have few or no such sources, articles based on case reports were also considered. Results: Finally, 62 sources considered eligible for the purpose of the review, 58 scientific articles and 4 specialized books (mainly comprising topics of advanced oral surgery, pathology and oral radiology) were selected. Conclusions: CBCT proves to be a fundamental tool for almost all procedures, whether or not routine, pertaining to the contemporary oral surgeon. It appears to be sufficiently accurate, safe and reliable for the therapeutic planning of all procedures related to impacted elements (extraction or exposure), implant planning (particularly for guided implant surgery) and most of the diagnostic questions (with the exception of some pathologies and/or neoformations that need to be investigated by other specific tools). [ABSTRACT FROM AUTHOR]

The assessment of bioaccumulation is an important step to describe the environmental behaviour and the potential risk due to exposure to potentially hazardous chemicals. In the last two decades, several in silico tools have been made available to predict bioconcentration, which is commonly used to assess bioaccumulation in risk assessment frameworks all over the world. However, only a few QSAR studies address the prediction of the biomagnification factor (BMF), which describes the accumulation of chemicals into organisms due to exposure through the diet. No classification models are currently available to this end. In this work, we developed classification QSARs to predict classes based on dietary biomagnification, using three different classifiers (i.e. LDA, ANN and RF). We started from a recently published dataset that includes more than 300 curated dietary BMF values measured in fish. The new models have high-quality performances (accuracy in fitting: from 94 to 96%; accuracy in prediction from 84 to 86%). The good performances of the here proposed QSARs confirm the quality of the original input data and highlight the importance of data curation and data sharing to support the development of new in silico approaches to assist risk assessment and chemicals screening. [ABSTRACT FROM AUTHOR]

Aedes aegypti vector control is of paramount importance owing to the damages induced by the various severe diseases that these insects may transmit, and the increasing risk of important outbreaks of these pathologies. Search for new chemicals efficient against Aedes aegypti, and devoid of side-effects, which have been associated to the currently most used active substance i. e. N,N-diethyl-mtoluamide (DEET), is therefore an important issue. In this context, we developed various Quantitative Structure Activity Relationship (QSAR) models to predict the repellent activity against Aedes aegypti of 43 carboxamides, by using Multiple Linear Regression (MLR) and various machine learning approaches. The easy computation of the four topological descriptors selected in this study, compared to the CODESSA descriptors used in the literature, and the predictive ability of the here proposed MLR and machine learning models developed using the software QSARINS and R, make the here proposed QSARs attractive. As demonstrated in this study, these models can be applied at the screening level, to guide the design of new alternatives to DEET. [ABSTRACT FROM AUTHOR]

QSAR models are proposed for predicting the toxicity of 33 piperidine derivatives againstAedes aegypti. From 2D topological descriptors, calculated with the PaDEL software, ordinary least squares multilinear regression (OLS-MLR) treatment from the QSARINS software and machine learning and related approaches including linear and radial support vector machine (SVM), projection pursuit regression (PPR), radial basis function neural network (RBFNN), general regression neural network (GRNN) andk-nearest neighbours (k-NN), led to four-variable models. Their robustness and predictive ability were evaluated through both internal and external validation. Determination coefficients (r2) greater than 0.85 on the training sets and 0.8 on the test sets were obtained with OLS-MLR and linear SVM. They slightly outperform PPR, radial SVM and RBFNN, whereas GRNN andk-NN showed lower performance. The easy availability of the involved structural descriptors and the simplicity of the MLR model make the corresponding model attractive at an exploratory level for proposing, from this limited dataset, guidelines in the design of new potentially active molecules. [ABSTRACT FROM PUBLISHER]

The synthesis of silica-fume based foams, with a multi-range macroporosity, was obtained by alkaline activation. Foams were obtained through an in situ foaming process exploiting the gaseous production of hydrogen caused by the oxidation, in alkaline medium, of metal silicon impurities contained in silica fume. Potassium or sodium alkaline solutions were selected and a temperature of 70 °C was sufficient to promote the development of hydrogen bubbles, the increase of the viscosity and the consolidation of the foams. The balance of these reactions allowed to entrap hydrogen bubbles inside the structures creating highly porous foams. The foams were characterized in term of macro- and microstructure, porosity distribution, infrared spectroscopy, thermal and acoustic properties achieved. The foams showed ultra-macroporous structures, with a total porosity of ≈80%. The average values of bulk density (0.5 g cm −3 ), thermal conductivity (0.16 W m −1 K −1 ), and the acoustic behaviors, highlighted a use of the foams as promising insulating materials. [ABSTRACT FROM AUTHOR]

The understanding of the mechanisms and interactions that occur when nanomaterials enter biological systems is important to improve their future use. The adsorption of proteins from biological fluids in a physiological environment to form a corona on the surface of nanoparticles represents a key step that influences nanoparticle behaviour. In this study, the quantitative description of the composition of the protein corona was used to study the effect on cell association induced by 84 surface-modified gold nanoparticles of different sizes. Quantitative relationships between the protein corona and the activity of the gold nanoparticles were modelled by using several machine learning-based linear and non-linear approaches. Models based on a selection of only six serum proteins had robust and predictive results. The Projection Pursuit Regression method had the best performances (r2= 0.91;Q2loo = 0.81;r2ext = 0.79). The present study confirmed the utility of protein corona composition to predict the bioactivity of gold nanoparticles and identified the main proteins that act as promoters or inhibitors of cell association. In addition, the comparison of several techniques showed which strategies offer the best results in prediction and could be used to support new toxicological studies on gold-based nanomaterials. [ABSTRACT FROM PUBLISHER]

Titanium oxide (TiO2) and zinc oxide (ZnO) nanoparticles are among the most widely used in different applications in daily life. In this study, local regression and classification models were developed for a set of ZnO and TiO2nanoparticles tested at different concentrations for their ability to disrupt the lipid membrane in cells. Different regression techniques were applied and compared by checking the robustness of the models and their external predictive ability. Additionally, a simple classification model was developed, which predicts the potential for disruption of the studied nanoparticles with good accuracy (overall accuracy, specificity, and sensitivity >80%) on the basis of two empirical descriptors. The present study demonstrates that empirical descriptors, such as experimentally determined size and tested concentrations, are relevant to modelling the activity of nanoparticles. This information may be useful to screen the potential for harmful effect of nanoparticles in different experimental conditions and to optimize the design of toxicological tests. Results from the present study are useful to support and refine the future application ofin silicotools to nanoparticles, for research and regulatory purposes. [ABSTRACT FROM PUBLISHER]

Pneumatization refers to the asymptomatic development of cavities containing air within them. There is great variability in the extent of temporal bone pneumatization. Nevertheless, in a few cases it extends to the zygomatic process. Images are presented in which the panoramic radiograph and hypocycloidal tomography reveal this variation from the norm, to which professionals must be alert, since the images may simulate the presence of pathology. In this case report we describe the presence of pneumatization of the petrous and zygomatic portions of the temporal bone, demonstrating the contribution of CT to reconstruction in volumetric 2D and 3D, with the aid of image rendering protocols. [ABSTRACT FROM AUTHOR]

Disposal of wool waste still encounters significant problems due to the need to satisfy environmental legislation and to the increasing cost of landfilling. Conversely, given the high content of useful nutrients it contains, sheep wool waste could still have a great potential for many applications, such as crop plant fertilizer and growth medium. The aim of this work was to highlight the possibility of reusing wool scraps as a constituent material for plant pots, producing innovative wool-geopolymer composite artifacts. Environmental-friendly pots for plant growing have been designed by impregnating chopped or hank wool scraps with a geopolymer resin. Composite pots were successfully realized. Preliminary comparative evaluations conduced on plant crops grown in peat or wool-geopolymer pots demonstrated that the presence of the organic material positively influenced the plant growth ratio. The composite pots were characterized both in term of macro- and micro-structure, before and after the plant growth testing. Wool fibers and geopolymer matrix acted together in providing a controlled release of nutrients to the plants and maintaining a higher and longer lasting level of soil moisture. [ABSTRACT FROM AUTHOR]

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The determination of the potential endocrine disruption (ED) activity of chemicals such as poly/perfluorinated compounds (PFCs) and brominated flame retardants (BFRs) is still hindered by a limited availability of experimental data. Quantitative structure–activity relationship (QSAR) strategies can be applied to fill this data gap, help in the characterization of the ED potential, and screen PFCs and BFRs with a hazardous toxicological profile. This paper proposes the modelling of T4-TTR (thyroxin-transthyretin) competing potency and relative binding potency toward T4 (logT4-REP) of PFCs and BFRs by regression and classification QSAR models. This study is a follow up of a former work, which analysed separately the interaction of BFRs and PFCs with the carrier TTR. The new results demonstrate the possibility of developing robust and predictive QSARs, which include both BFRs and PFCs in the training set, obtaining larger applicability domains than the existing models developed separately for BFRs and PFCs. The selection of modelling molecular descriptors confirms the importance of structural features, such as the aromatic OH or the molecular length, to increase the binding of the studied chemicals to TTR. Additionally, the need of experimental tests for some chemicals, and in particular for some of the BFRs, is highlighted. [ABSTRACT FROM AUTHOR]

Perfluorinated compounds (PFCs) are a class of emerging pollutants still widely used in different materials as non-adhesives, waterproof fabrics, fire-fighting foams, etc. Their toxic effects include potential for endocrine-disrupting activity, but the amount of experimental data available for these pollutants is limited. The use of predictive strategies such as quantitative structure–activity relationships (QSARs) is recommended under the REACH regulation, to fill data gaps and to screen and prioritize chemicals for further experimentation, with a consequent reduction of costs and number of tested animals. In this study, local classification models for PFCs were developed to predict their T4-TTR (thyroxin-transthyretin) competing potency. The best models were selected by maximizing the sensitivity and external predictive ability. These models, characterized by robustness, good predictive power and a defined applicability domain, were applied to predict the activity of 33 other PFCs of environmental concern. Finally, classification models recently published by our research group for T4-TTR binding of brominated flame retardants and for estrogenic and anti-androgenic activity were applied to the studied perfluorinated chemicals to compare results and to further evaluate the potential for these PFCs to cause endocrine disruption. [ABSTRACT FROM AUTHOR]

Fragrance materials are used as ingredients in many consumer and personal care products. The wide and daily use of these substances, as well as their mainly uncontrolled discharge through domestic sewage, make fragrance materials both potential indoor and outdoor air pollutants which are also connected to possible toxic effects on humans (asthma, allergies, headaches). Unfortunately, little is known about the environmental fate and toxicity of these substances. However, the use of alternative, predictive approaches, such as quantitative structure-activity relationships (QSARs), can help in filling the data gap and in the characterization of the environmental and toxicological profile of these substances. In the proposed study, ordinary least squares regression-based QSAR models were developed for three toxicological endpoints: mouse oral LD50, inhibition of NADH-oxidase (EC50 NADH-Ox) and the effect on mitochondrial membrane potential (EC50 ΔΨm). Theoretical molecular descriptors were calculated by using DRAGON software, and the best QSAR models were developed according to the principles defined by the Organization for Economic Co-operation and Development. [ABSTRACT FROM AUTHOR]

The troposphere is the principal recipient of volatile organic chemicals (VOCs) of both anthropogenic and biogenic origin. The persistence of these compounds in the troposphere is an important factor for the evaluation of their fate, and the possible negative effects to the environment and human health. In this study, the tropospheric lifetime of 166 VOCs, in terms of night-time degradation rates with nitrate radical (NO3), was modelled by the quantitative structure-property relationships (QSPR) approach. The multiple linear regression method was applied, in combination with the genetic algorithm-variable subset selection procedure, to a variety of theoretical molecular descriptors, calculated by the DRAGON software. The models were developed according to the OECD principles for regulatory acceptance of QSARs, with particular attention to external validation and applicability domain (AD). The external validation was performed on an unbiased external test set or by splitting the available data using self-organized maps or the random by response approach. The best QSPR models presented in this study showed good internal (range of [image omitted]: 89-92%) as well as external predictivity (range of Qext²: 75-89%). The AD of the models was analysed by the leverage approach, and was represented graphically in the Williams graph. [ABSTRACT FROM AUTHOR]

Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous pollutants of high environmental concern. The experimental data of a mutagenicity test on human B-lymphoblastoid cells (alternative to the Ames bacterial test) for a set of 70 oxo-, nitro- and unsubstituted PAHs, detected in particulate matter (PM), were modelled by Quantitative Structure-Activity Relationships (QSAR) classification methods (k-NN, k-Nearest Neighbour, and CART, Classification and Regression Tree) based on different theoretical molecular descriptors selected by Genetic Algorithms. The best models were validated for predictivity both externally and internally. For external validation, Self Organizing Maps (SOM) were applied to split the original data set. The best models, developed on the training set alone, show good predictive performance also on the prediction set chemicals (sensitivity 69.2-87.1%, specificity 62.5-87.5%). The classification of PAHs according to their mutagenicity, based only on a few theoretical molecular descriptors, allows a preliminary assessment of the human health risk, and the prioritisation of these compounds. [ABSTRACT FROM AUTHOR]

Nitrated Polycyclic Aromatic Hydrocarbons (nitro-PAHs), ubiquitous environmental pollutants, are recognized mutagens and carcinogens. A set of mutagenicity data (TA100) for 48 nitro-PAHs was modeled by the Quantitative Structure-Activity Relationships (QSAR) regression method, and OECD principles for QSAR model validation were applied. The proposed Multiple Linear Regression (MLR) models are based on two topological molecular descriptors. The models were validated for predictivity by both internal and external validation. For the external validation, three different splitting approaches, D-optimal Experimental Design, Self Organizing Maps (SOM) and Random Selection by activity sampling, were applied to the original data set in order to compare these methodologies and to select the best descriptors able to model each prediction set chemicals independently of the splitting method applied. The applicability domain was verified by the leverage approach. [ABSTRACT FROM AUTHOR]

In different cell types P-glycoproteins (P-gp) are involved in the transport of cyclosporin A (CyA). The aim of this study was to evaluate the effect of the pharmacological modulation of the hepatic P-gp on biliary secretion of CyA and on cholestasis induced by acute administration of CyA in the isolated perfused rat liver (IPRL). Verapamil was used as a P-gp specific inhibitor and acetylaminofluorene (AAF) as a P-gp inducer. CyA biliary excretion was determined by administering in the IPRL a tracer dose of [3H]CyA with or without verapamil or AAF. The effect on bile flow was evaluated by administering increasing doses of CyA (2.8, 8, and 20 mg/kg body wt) in the IPRL. Morphological evidence of damage was evaluated by optical and electron microscopy in the liver as well as in primary culture of rat hepatocytes exposed to CyA +/- verapamil. Verapamil significantly inhibited the biliary excretion of a tracer dose of [3H]CyA (0.15+/-0.04 vs 0.33+/-0.07%; P < 0.05). In contrast, pretreatment with AAF significantly increased the biliary excretion of [3H]CyA, (0.61+/-0.10 vs 0.33+/-0.07%; P < 0.05). CyA induced a dose-dependent inhibition of bile flow with a maximal effect at 20 mg/kg CyA (-49.3+/-4.5% decrease of basal bile flow). CyA cholestasis was significantly worsened by the P-gp inhibitor, verapamil (-75.5+/-7.5%; P < 0.05), but it was unaffected by induction of P-gp via AAF pretreatment (-44.9+/-1.7%). During CyA cholestasis, the cumulative biliary excretion of [3H]CyA was lower than in the absence of cholestasis (0.22+/-0.05 vs 0.33+/-0.07%; P < 0.05), was inhibited by verapamil (0.08+/-0.01%; P < 0.05), but was unaffected by AAF (0.23+/-0.05%). No morphological evidence of damage was observed in the liver, and no evidence of cytoskeleton derangement was seen in primary cultures of rat hepatocytes exposed to CyA +/- verapamil. We demonstrated that pharmacological modulation of P-gp may influence the biliary excretion of CyA. The acute cholestatic effect of CyA is worsened by P-gp inhibitors, while it is unaffected by P-gp inducers. This indicates CyA should not be given with other P-gp substrates or inhibitors. [ABSTRACT FROM AUTHOR]

Two unusual, heterogeneously-resistant, strains of Staphylococcus aureus appeared resistant to oxacillin, but susceptible to methicillin by disc diffusion methods. In agar dilution tests, both strains were oxacillin-resistant. One was susceptible to methicillin, and the other gave a paradoxical reaction, with growth only on plates containing low (0.5, 1 and 2 mg/l) and high (32 and 64 mg/l) concentrations of antibiotic. Induction of methicillin resistance was tested by inoculating each strain on to agar plates containing an inhibitory concentration of methicillin (8 mg/l), and then placing discs containing inducers (oxacillin, nafcillin, methicillin and CBAP [2-(2'-carboxyphenyl) benzoyl-6-aminopenicillanic acid]) on the agar surface. Colonies grew only around discs containing effective inducers. Oxacillin and CBAP were much more potent inducers of methicillin resistance and beta-lactamase than was nafcillin or methicillin. These data suggest that the mechanism that regulates induction of the low-affinity penicillin binding protein (PBP-2') may be altered in these strains. Similar mechanisms appear to induce both beta-lactamase and methicillin resistance. [ABSTRACT FROM AUTHOR]

We studied 192 recent clinical isolates, comprising six species of Gram-negative bacilli resistant either to cefotaxime or latamoxef (Moxalactam), from several hospitals. All isolates were resistant to several other third-generation cephalosporins or a monobactam. Two to five types of chromosomal β-lactamases, as defined by isoelectric focusing, were readily identified in each species. Isolates of Citrobacter, Enterobacter and Serratia produced higher levels of chromosomal β-lactamase than corresponding cefotaxime-susoeptible strains. In addition, 20 of 57 produced one or two plasmid-determined β-lactamases, TEM-1, OXA-2, or a novel enzyme, OHIO-1. The penem and carbapenem antibiotics, Sch 34343 and imipenem, were more active than cefotaxime, ceftazidime, ceftriaxone, latamoxef and aztreonam against isolates of Acinetobacter, Citrobacter, Ent. aerogenes, Ent. cloacae and Morganella, whereas imipenem, ceftazidime, and aztreonam were more active against Serratia isolates. The addition of plasmid-determined β-lactamase increased resistance to piperacillin, cefoperazone and cefamandole but not to cefotaxime, ceftazidime, ceftriaxone, latamoxef, aztreonam, Sch 34343, or imipenem. Of 24 strains susceptible to aminoglycosides, none produced a plasmid-determined β-lactamase, whereas 20 were found among the 33 strains resistant to aminoglycosides.Resistance of clinical isolates to newer β-lactams appears to be due primarily to a high level of chromosomal cepahalosporinase present without inducing agents. The plasmid-determined β-lactamases, TEM-1 and OHIO-1, contributed little to resistance to most of the newer β-lactams but were strongly associated with aminoglycoside resistance in these selected isolates. The greater in-vitro efficacy of the penem and carbapenem antibiotics, Sch 34343 and imipenem, against most of these isolates makes them promising candidates as first line agents against these pathogens. [ABSTRACT FROM PUBLISHER]