17 research outputs found
Grau de perda Ăłssea periodontal em pacientes parcialmente dentados, reabilitados com implantes osseointegrados
Objetivo: Avaliar, retrospectivamente, radiografias panorâmicas de implantes osseointegrados a fim de discriminar o grau de perda Ăłssea periodontal de pacientes atendidos no Centro de Implantes Sobreimplantes e no curso de Especialização em Implantodontia do curso de Odontologia do Centro de SaĂşde Veiga de Almeida, ambos localizados na cidade Rio de Janeiro. Metodologia: As radiografias panorâmicas de 109 indivĂduos (38 homens e 71 mulheres, mĂ©dia de idade 56 ± 12 anos) foram analisadas por duas examinadoras calibradas. Foram avaliados o nĂşmero de dentes presentes, quantidade de sĂtios com perda Ăłssea periodontal e a quantidade de implantes instalados. A perda Ăłssea foi determinada em atĂ© 25%, entre 25% e 50% e maior do que 50% do tamanho da raiz. As análises foram executadas de duas formas: baseada no indivĂduo e nos sĂtios. Tendo como base o indivĂduo, foram avaliadas (1) a extensĂŁo da perda Ăłssea radiográfica (generalizada ou localizada) e (2) a severidade da perda Ăłssea radiográfica (mĂ©dia de severidade dos sĂtios). Em relação aos sĂtios, foi analisada a presença ou ausĂŞncia de perda Ăłssea e a severidade desta. Resultados: Cinquenta e seis por cento das radiografias avaliadas apresentavam perda Ăłssea periodontal generalizada; já 36%, perda Ăłssea periodontal localizada; e 8% nĂŁo apresentavam perda Ăłssea. Em relação aos sĂtios, foram avaliados 3.924 sĂtios, entre os quais 42% (n=1647) apresentavam perda Ăłssea, sendo que 22% (n=863) dos sĂtios revelavam perda Ăłssea periodontal em atĂ© 25% da raiz; 16% (n=627), entre 25% e 50% da raiz; e 4% (n=156), maior do que 50% do tamanho da raiz. A mĂ©dia de implantes instalados por paciente foi 4± 2. Os pacientes que tinham 100% dos sĂtios com perda Ăłssea apresentavam em mĂ©dia 7± 2 implantes osseointegrados. ConclusĂŁo: Nesta avaliação retrospectiva, observou-se que a maioria das radiografias (61,5%) revelava um histĂłrico de perda Ăłssea leve generalizada. Vinte por cento dos sĂtios com perda Ăłssea apresentavam perda moderada a severa. As radiografias panorâmicas podem ser utilizadas como um instrumento auxiliar na determinação de risco de peri-implantite de pacientes reabilitados com implantes osseointegrados.
Evaluation of the physical and antifungal effects of chlorhexidine diacetate incorporated into polymethyl methacrylate
This study aimed to evaluate the physical properties and antifungal activities of polymethyl methacrylate (PMMA) acrylic resins after the incorporation of chlorhexidine diacetate salt (CDA). Methodology: First, acrylic resin specimens were fabricated with Vipi Cor® and DuraLay® resins with and without the incorporation of 0.5%, 1.0% or 2.0% CDA. The residual monomer and CDA release were measured at intervals ranging from 2 hours to 28 days using ultraviolet spectrometry combined with high-performance liquid chromatography. The antifungal activity against C. albicans was evaluated with the agar diffusion method. Fourier transform infrared spectroscopy was used to analyze the degree of resin conversion. Finally, the water sorption values of the resins were also measured. Results: The incorporated CDA concentration significantly changed the rate of CDA release (p<0.0001); however, the brand of the material appeared to have no significant influence on drug release. Subsequently, the inhibition zones were compared between the tested groups and within the same brand, and only the comparisons between the CDA 2% and CDA 1% groups and between the CDA 1% and CDA 0.5% groups failed to yield significant differences. Regarding the degrees of conversion, the differences were not significant and were lower only in the CDA 2% groups. Water sorption was significantly increased at the 1.0% and 2.0% concentrations. Conclusions: We concluded that the incorporation of CDA into PMMA-based resins enabled the inhibition of C. albicans growth rate, did not alter the degrees of conversion of the tested resins and did not change the release of residual monomers
Peri-Implant Surgical Treatment Downregulates the Expression of sTREM-1 and MMP-8 in Patients with Peri-Implantitis: A Prospective Study
sTREM-1 and its ligand PGLYRP1 play an essential role in the inflammatory process around teeth and implants. In this study, we aimed to evaluate the impact of peri-implant treatment on the salivary levels of the sTREM-1/PGLYRP-1/MMP-8 axis after 3 months. A total of 42 participants (with a mean age of 61 years old ± 7.3) were enrolled in this longitudinal study, 24 having peri-implant mucositis (MU) and 18 having peri-implantitis (PI). Clinical peri-implant parameters, such as probing pocket depth (PPD), % of plaque, and bleeding on probing (BOP), and the whole unstimulated saliva samples were evaluated at baseline and 3 months after treatment. The MU group received nonsurgical peri-implant treatment, while the PI group received open-flap procedures. The levels of sTREM-1, PGLYRP-1, MMP-8, and TIMP-1 were analyzed using enzyme-linked immunosorbent assays. BOP, plaque levels, and PPD significantly reduced after treatment in both groups. A significant decrease in the salivary levels of sTREM-1, MMP-8, and TIMP-1 in the PI group and PGLYRP1 and TIMP-1 in the MU group were observed. Salivary levels of sTREM-1 were significantly reduced in patients with PI but not with MU. Additionally, peri-implant treatment had a significantly higher impact on MMP-8 reduction in patients with PI than in those with MU
Pervasive gaps in Amazonian ecological research
Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4
While the increasing availability of global databases on ecological communities has advanced our knowledge
of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In
the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of
Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus
crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced
environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian
Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by
2050. This means that unless we take immediate action, we will not be able to establish their current status,
much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio
Pervasive gaps in Amazonian ecological research
Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost
Pervasive gaps in Amazonian ecological research
Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost
Risk factors for implant failure: a retrospective study in an educational institution using GEE analyses
<div><p>Abstract This study aimed to evaluate dental implant outcomes and to identify risk factors associated with implant failure over 12 years via dental records of patients attending an educational institution. Dental records of 202 patients receiving 774 dental implants from 2002 to 2014 were analyzed by adopting a more reliable statistical method to evaluate risk factors with patients as the unit [generalized estimating equation (GEE)]. Information regarding patient age at implantation, sex, use of tobacco, and history of systemic diseases was collected. Information about implant location in the arch region and implant length, diameter, and placement in a grafted area was evaluated after 2 years under load. Systemic and local risk factors for early and late implant failure were studied. A total of 18 patients experienced 25 implant failures, resulting in an overall survival rate of 96.8% (2.84% and 0.38% early and late implant failures, respectively). The patient-based survival rate was 91.8%. GEE univariate and multivariate analyses revealed that a significant risk factor for implant failure was the maxillary implant (p = 0.006 and p = 0.014, respectively). Bone grafting appeared to be a risk factor for implant failure (p = 0.054). According to GEE analyses, maxillary implants had significantly worse outcomes in this population and were considered to be a risk factor for implant failure. Our results suggested that implants placed in a bone augmentation area had a tendency to fail.</p></div