Presence of arsenic in different types of MTA and white and gray Portland cement

Objective. The presence of arsenic in various types of mineral trioxide aggregate (MTA) and Portland cements were evaluated to verify if they comply with the ISO-recommended limit for water-based cements of 2 mg arsenic/kg material. Study design. An amount of 5 mL of hydrochloric acid was added to 2 g each of MTA and Portland cement to be analyzed. After 15 minutes, the material was filtered and the volume of supernatant was diluted with reagent-grade water up to 40 mL. Atomic absorption spectrophotometry readings were performed in triplicate. Results. The following mean values were obtained: CPM (Egeo, Buenos Aires, Argentina) 11.06 mg/kg; CPM sealer (Egeo) 10.30 mg/kg; MTA- Obtura (Angelus, Londrina, PR, Brazil) 0.39 mg/kg; Experimental MTA: 10.30 mg/kg; White MTA- Angelus (Angelus) 1.03 mg/kg; Gray MTA- Angelus (Angelus) 5.91 mg/kg; ProRoot-MTA (Dentsply/Tulsa Dental Specialties, Tulsa, OK) 5.25 mg/kg; Gray Portland cement (Votorantim Cimentos, Cubatao, SP, Brazil): 34.27 mg/kg; and White Portland cement (Cimento Rio Branco, Rio de Janeiro, RJ, Brazil) 0.52 mg/kg. Conclusion. All tested materials presented arsenic in their composition. The form of arsenic was not analyzed nor the toxicity of the arsenic found. Only MTA- Obtura, White MTA- Angelus, and White Portland cement presented arsenic levels below the limit set in the ISO 9917-1 standard. (Oral Surg Oral Med Oral Pathol Oral Radiol Endod 2008; 106: 909-913)

IN VITRO FRACTURE RESISTANCE OF GLASS-FIBER AND CAST METAL POSTS WITH DIFFERENT LENGTHS

Statement of problem. Dental fractures can occur in endodontically treated teeth restored with posts. Purpose. The purpose of this study was to evaluate the in vitro fracture resistance of roots with glass-fiber and metal posts of different lengths. Material and methods. Sixty endodontically treated maxillary canines were embedded in acrylic resin, except for 4 mm of the cervical area, after removing the clinical crowns. The post spaces were opened with a cylindrical bur at low speed attached to a surveyor, resulting in preparations with lengths of 6 mm (group 6 mm), 8 mm (group 8 mm), or 10 mm (group 10 mm). Each group was divided into 2 subgroups according to the post material: cast post and core or glass-fiber post (n=30). The posts were luted with dual-polymerizing resin cement (Panavia F). Cast posts and cores of Co-Cr (Resilient Plus) crowns were made and cemented with zinc phosphate. Specimens were subjected to increasing compressive load (N) until fracture. Data were analyzed with 2-way ANOVA and the Tukey-Kramer test (alpha=.05). Results. The ANOVA analysis indicated significant differences (P<.05) among the groups, and the Tukey test revealed no significant difference among the metal posts of 6-mm length (26.5 N +/- 13.4), 8-mm length (25.2 N +/- 13.9), and 10-mm length (17.1 N +/- 5.2). Also, in the glass-fiber post group, there was no significant difference when posts of 8-mm length (13.4 N +/- 11.0) were compared with the 6-mm (6.9 N +/- 4.6) and 10-mm (31.7 N +/- 13.1) groups. The 10-mm-long post displayed superior fracture resistance, and the 6-mm-long post showed significantly lower mean values (P<.001). Conclusions. Within the limitations of this study, it was concluded that the glass-fiber post represents a viable alternative to the cast metal post, increasing the resistance to fracture of endodontically treated canines. (J Prosthet Dent 2009;101:183-188)

The Effect of Coating Patterns with Spinel-Based Investment on the Castability and Porosity of Titanium Cast into Three Phosphate-Bonded Investments

Purpose: This study evaluated the effect of pattern coating with spinel-based investment Rematitan Ultra (RU) on the castability and internal porosity of commercially pure (CP) titanium invested into phosphate-bonded investments. The apparent porosity of the investment was also measured. Materials and Methods: Square patterns (15 x 15 x 0.3 mm(3)) were either coated with RU, or not and invested into the phosphate-bonded investments: Rematitan Plus (RP), Rema Exakt (RE), Castorit Super C (CA), and RU (control group). The castings were made in an Ar-arc vacuum-pressure machine. The castability area (mm(2)) was measured by an image-analysis system (n = 10). For internal porosity, the casting (12 x 12 x 2 mm(3)) was studied by the X-ray method, and the projected porous area percentage was measured by an image-analysis system (n = 10). The apparent porosity of the investment (n = 10) was measured in accordance with the ASTM C373-88 standard. Results: Analysis of variance (One-way ANOVA) of castability was significant, and the Tukey test indicated that RU had the highest mean but the investing technique with coating increased the castability for all phosphate-bonded investments. The analysis of the internal porosity of the cast by the nonparametric test demonstrated that the RP, RE, and CA with coating and RP without coating did not differ from the control group (RU), while the CA and RE casts without coating were more porous. The one-way ANOVA of apparent porosity of the investment was significant, and the Tukey test showed that the means of RU (36.10%) and CA (37.22%) were higher than those of RP (25.91%) and RE (26.02%). Conclusion: Pattern coating with spinel-based material prior to phosphate-bonded investments can influence the castability and the internal porosity of CP Ti.

Comparison between Eysenck's and Gray's models of personality in the prediction of motivational work criteria

Impulsivity based on Gray's [Gray, J. A. (1982) The neuropsychology of anxiety: an enquiry into the function of the septo-hippocampal system. New York: Oxford University Press: (1991). The neurophysiology of temperament. In J. Strelau & A. Angleitner. Explorations in temperament: international perspectives on theory and measurement. London. Plenum Press]. physiological model of personality was hypothesised to be more predictive of goal oriented criteria within the workplace than scales derived From Eysenck's [Eysenck. H.J. (1967). The biological basis of personality. Springfield, IL: Charles C. Thompson.] physiological model of personality. Results confirmed the hypothesis and also showed that Gray's scale of Impulsivity was generally a better predictor than attributional style and interest in money. Results were interpreted as providing support for Gray's Behavioural Activation System which moderates response to reward. (C) 2001 Elsevier Science Ltd. All rights reserved.

The rights to a deceased's body and body parts : in the matter of Gray (2000) QSC 390 (12/10/2000).

Decision In the Matter of Gray highlights complications that advancing medical technology causes to the law - case concerns the issue of removal of semen from a deceased man - how the courts deal with matters concerning medical technology in the absence of specific legislation or established case law - legal and moral questions raised by the case.

Composition of the family Didelphidae Gray, 1821 (Didelphoidea:Marsupialia), with a review of the morphology and behavior of the included four-eyed pouched opossums of the genus Philander Tiedemann, 1808 /

n.s. no.86(1997)

Species of the scincid Genus Dasia Gray / Robert F. Inger and Walter C. Brown.

n.s. no.3(1980)

Darwiniana: essays and reviews pertaining to Darwinism. By Asa Gray ...

[1888 printing]

Central and Cortical Gray Mater Segmentation of Magnetic Resonance Images of the Fetal Brain

Motivation. The study of human brain development in itsearly stage is today possible thanks to in vivo fetalmagnetic resonance imaging (MRI) techniques. Aquantitative analysis of fetal cortical surfacerepresents a new approach which can be used as a markerof the cerebral maturation (as gyration) and also forstudying central nervous system pathologies [1]. However,this quantitative approach is a major challenge forseveral reasons. First, movement of the fetus inside theamniotic cavity requires very fast MRI sequences tominimize motion artifacts, resulting in a poor spatialresolution and/or lower SNR. Second, due to the ongoingmyelination and cortical maturation, the appearance ofthe developing brain differs very much from thehomogenous tissue types found in adults. Third, due tolow resolution, fetal MR images considerably suffer ofpartial volume (PV) effect, sometimes in large areas.Today extensive efforts are made to deal with thereconstruction of high resolution 3D fetal volumes[2,3,4] to cope with intra-volume motion and low SNR.However, few studies exist related to the automatedsegmentation of MR fetal imaging. [5] and [6] work on thesegmentation of specific areas of the fetal brain such asposterior fossa, brainstem or germinal matrix. Firstattempt for automated brain tissue segmentation has beenpresented in [7] and in our previous work [8]. Bothmethods apply the Expectation-Maximization Markov RandomField (EM-MRF) framework but contrary to [7] we do notneed from any anatomical atlas prior. Data set &Methods. Prenatal MR imaging was performed with a 1-Tsystem (GE Medical Systems, Milwaukee) using single shotfast spin echo (ssFSE) sequences (TR 7000 ms, TE 180 ms,FOV 40 x 40 cm, slice thickness 5.4mm, in plane spatialresolution 1.09mm). Each fetus has 6 axial volumes(around 15 slices per volume), each of them acquired inabout 1 min. Each volume is shifted by 1 mm with respectto the previous one. Gestational age (GA) ranges from 29to 32 weeks. Mother is under sedation. Each volume ismanually segmented to extract fetal brain fromsurrounding maternal tissues. Then, in-homogeneityintensity correction is performed using [9] and linearintensity normalization is performed to have intensityvalues that range from 0 to 255. Note that due tointra-tissue variability of developing brain someintensity variability still remains. For each fetus, ahigh spatial resolution image of isotropic voxel size of1.09 mm is created applying [2] and using B-splines forthe scattered data interpolation [10] (see Fig. 1). Then,basal ganglia (BS) segmentation is performed on thissuper reconstructed volume. Active contour framework witha Level Set (LS) implementation is used. Our LS follows aslightly different formulation from well-known Chan-Vese[11] formulation. In our case, the LS evolves forcing themean of the inside of the curve to be the mean intensityof basal ganglia. Moreover, we add local spatial priorthrough a probabilistic map created by fitting anellipsoid onto the basal ganglia region. Some userinteraction is needed to set the mean intensity of BG(green dots in Fig. 2) and the initial fitting points forthe probabilistic prior map (blue points in Fig. 2). Oncebasal ganglia are removed from the image, brain tissuesegmentation is performed as described in [8]. Results.The case study presented here has 29 weeks of GA. Thehigh resolution reconstructed volume is presented in Fig.1. The steps of BG segmentation are shown in Fig. 2.Overlap in comparison with manual segmentation isquantified by the Dice similarity index (DSI) equal to0.829 (values above 0.7 are considered a very goodagreement). Such BG segmentation has been applied on 3other subjects ranging for 29 to 32 GA and the DSI hasbeen of 0.856, 0.794 and 0.785. Our segmentation of theinner (red and blue contours) and outer cortical surface(green contour) is presented in Fig. 3. Finally, torefine the results we include our WM segmentation in theFreesurfer software [12] and some manual corrections toobtain Fig.4. Discussion. Precise cortical surfaceextraction of fetal brain is needed for quantitativestudies of early human brain development. Our workcombines the well known statistical classificationframework with the active contour segmentation forcentral gray mater extraction. A main advantage of thepresented procedure for fetal brain surface extraction isthat we do not include any spatial prior coming fromanatomical atlases. The results presented here arepreliminary but promising. Our efforts are now in testingsuch approach on a wider range of gestational ages thatwe will include in the final version of this work andstudying as well its generalization to different scannersand different type of MRI sequences. References. [1]Guibaud, Prenatal Diagnosis 29(4) (2009). [2] Rousseau,Acad. Rad. 13(9), 2006, [3] Jiang, IEEE TMI 2007. [4]Warfield IADB, MICCAI 2009. [5] Claude, IEEE Trans. Bio.Eng. 51(4) (2004). [6] Habas, MICCAI (Pt. 1) 2008. [7]Bertelsen, ISMRM 2009 [8] Bach Cuadra, IADB, MICCAI 2009.[9] Styner, IEEE TMI 19(39 (2000). [10] Lee, IEEE Trans.Visual. And Comp. Graph. 3(3), 1997, [11] Chan, IEEETrans. Img. Proc, 10(2), 2001 [12] Freesurfer,http://surfer.nmr.mgh.harvard.edu.