Publications

ObjectivesThis study evaluated different designs of the conical implant-abutment connection (IAC) and their resistance to microgap formation under oblique loads as specified by the ISO standard for testing dental implants. Also evaluated was the effect of deviations from the ISO specifications on the outcomes.MethodsFinite element analysis was conducted to compare the microgap formation and stress distribution among three conical IAC designs (A, B, and C) in two loading configurations: one compliant with ISO 14801 and one with a modified load adaptor (non-ISO). The different IAC designs varied in the taper, diameter, and cone height. The cone angle mismatch (Cam) between the implant and abutment was considered. A torque of 20 Ncm and oblique loads (up to 400 N) were simulated.ResultsThe stresses produced by the screw-tightening torque varied among the different IAC designs. The contact height was approximately 0.3 mm for Designs A and B, and less than 0.03 mm for Design C. Under oblique loads, Design A maintained IAC sealing without gap formation up to 400 N. With the ISO adaptor, gaps appeared in Design B at 300 N and in Design C at 90 N. The non-ISO adaptor resulted in gap formation at 160 N for Design B and at 50 N for Design C.ConclusionsThe IAC design and cone angle mismatch significantly influenced microgap formation, with some designs showing zero gaps even when the oblique load reached 400 N. The non-ISO adaptor increased gap formation in IACs B and C.

JTD Keywords: Bacterial leakage, Behavior, Dental implant, Dental implant-abutments design, Dimensional measurement accuracy, Finite element analysis, In-vitro, Interface, Mechanical, Peri-implantitis, Scre, Sealant agents, Stres, Taper

Several pathogenic Escherichia coli strains cause diarrhea. Enteroaggregative E. coli (EAEC) strains are one of the diarrheagenic pathotypes. EAEC cells form a "stacked-brick" arrangement over the intestinal epithelial cells. EAEC isolates express, among other virulence determinants, the AggR transcriptional activator and the aggregative adherence fimbriae (AAF). Overexpression of the aggR gene results in increased expression of virulence factors such as the aff genes, as well as several genes involved in specific metabolic pathways such as fatty acid degradation (fad) and arginine degradation (ast). To support the hypothesis that induction of the expression of some of these pathways may play a role in EAEC virulence, in this study we used a murine infection model to evaluate the impact of the expression of these pathways on infection parameters. Mice infected with a mutant derivative of the EAEC strain 042, characterized by overexpression of the aggR gene, showed increased disease symptoms compared to those exhibited by mice infected with the wild type (wt) strain 042. Several of these symptoms were not increased when the infecting mutant, which overexpressed aggR, lacked the fad and ast pathways. Therefore, our results support the hypothesis that different metabolic pathways contribute to EAEC virulence.

JTD Keywords: Adherence, Aggr, Burde, Chain fatty-acids, Children, Enteroaggregative e. coli, Escherichia-coli, Etiology, Infection, Mice, Microbiota, Persistent diarrhea, Protein, Scfa, Sex-differences

In this study we propose the correntropy function as a discriminative measure for detecting nonlinearities in the respiratory pattern of chronic heart failure (CHF) patients with periodic or nonperiodic breathing pattern (PB or nPB, respectively). The complexity seems to be reduced in CHF patients with higher risk level. Correntropy reflects information on both, statistical distribution and temporal structure of the underlying dataset. It is a suitable measure due to its capability to preserve nonlinear information. The null hypothesis considered is that the analyzed data is generated by a Gaussian linear stochastic process. Correntropy is used in a statistical test to reject the null hypothesis through surrogate data methods. Various parameters, derived from the correntropy and correntropy spectral density (CSD) to characterize the respiratory pattern, presented no significant differences when extracted from the iteratively refined amplitude adjusted Fourier transform (IAAFT) surrogate data. The ratio between the powers in the modulation and respiratory frequency bands R was significantly different in nPB patients, but not in PB patients, which reflects a higher presence of nonlinearities in nPB patients than in PB patients.

JTD Keywords: Practical, Theoretical or Mathematical, Experimental/cardiology diseases, Fourier transforms, Medical signal processing, Pattern classification, Pneumodynamics, Spectral analysis, Statistical analysis, Stochastic processes/ correntropy based nonlinearity test, Chronic heart failure, Correntropy function, Respiratory pattern nonlinearities, CHF patients, Nonperiodic breathing pattern, Dataset statistical distribution, Dataset temporal structure, Nonlinear information, Null hypothesis, Gaussian linear stochastic process, Statistical test, Correntropy spectral density, Iteratively refined amplitude adjusted Fourier transform, Surrogate data, Periodic breathing pattern