Periodontal regeneration : is it still a goal in clinical periodontology?

In the last decades, Periodontal Regeneration has been one of the most discussed topics in Periodontics, attracting the attention of researchers and clinicians. This can be justified by the evident and continuous progress observed in the field, characterized by a better understanding of the biological mechanisms involved, significant improvement of operative and technical principles, and the emergence of a wide range of biomaterials available for this purpose. Together, these aspects put the theme much in evidence in the search for functional and esthetic therapeutic solutions for periodontal tissue destruction. Despite the evident evolution, periodontal regeneration may be challenging and require the clinician to carefully evaluate each case before making a therapeutic decision. With a critical reassessment of the clinical and preclinical literature, the present study aimed to discuss the topic to answer whether Periodontal Regeneration is still a goal in clinical periodontology. The main aspects involved in the probability of success or failure of regenerative approaches were considered. A greater focus was given to intrabony and furcation defects, clinical conditions with greater therapeutic predictability. Aspects such as more appropriate materials/approaches, long-term benefits and their justification for a higher initial cost were discussed for each condition. In general, deep intrabony defects associated with residual pockets and buccal/lingual class II furcation lesions have predictable and clinically relevant results. Careful selection of the case (based on patient and defect characteristics) and excellent maintenance are essential conditions to ensure initial and long-term success

Wireless device with energy management for mlosed-loop deep brain stimulation (CLDBS)

Deep brain stimulation (DBS) is an effective and safe medical treatment that improves the lives of patients with a wide range of neurological and psychiatric diseases, and has been consolidated as a first-line tool in the last two decades. Closed-loop deep brain stimulation (CLDBS) pushes this tool further by automatically adjusting the stimulation parameters to the brain response in real time. The main contribution of this paper is a low-size/power-controlled, compact and complete CLDBS system with two simultaneous acquisition channels, two simultaneous neurostimulation channels and wireless communication. Each channel has a low-noise amplifier (LNA) buffer in differential configuration to eliminate the DC signal component of the input. Energy management is efficiently done by the control and communication unit. The battery supports almost 9 h with both the acquisition and stimulation circuits active. If only the stimulation circuit is used as an Open Loop DBS, the battery can hold sufficient voltage for 24 h of operation. The whole system is low-cost and portable and therefore it could be used as a wearable device.This work was partially supported by the FAPESP agency (Fundação de Amparo à Pesquisa do Estado de São Paulo) through the project with the reference 2019/05248-7. Professor João Paulo Carmo was supported by a PQ scholarship with the reference CNPq 304312/2020-7

Conhecimento sobre a doença renal crônica do paciente em hemodiálise

Objetivo: Verificar o grau de conhecimento e a fonte de informações sobre a doença renal de pacientes com Insuficiência Renal Crônica em tratamento em uma clínica de hemodiálise.Materiais e Métodos: O conhecimento desses pacientes foi avaliado em um estudo exploratório e descritivo realizado por meio de um questionário aplicado a 58 pacientes, de ambos os sexos, em uma clínica renal no Noroeste do Rio Grande do Sul.Resultados: Demonstramos que a maioria dos pacientes busca informações sobre Insuficiência Renal Crônica na internet e que menos da metade busca estas informações com profissionais da saúde. Quando a busca é realizada com profissionais da saúde, predomina o enfermeiro. Os pacientes demonstraram pouco conhecimento relativo as medicações que usam, mas a maioria soube relatar os alimentos que deve evitar e a quantidade de água que pode beber.Conclusão: Evidenciamos que a maioria dos pacientes possui conhecimento de sua condição e tratamento, mas, mesmo assim, alguns ainda desobedecem as regras alimentares. Os profissionais da saúde não são a principal doente de informações para os pacientes, demonstrando fragilidades na relação profissional-paciente

Modelagem do processo de troca iônica pela Lei da Ação das Massas e redes neurais artificiais

The Mass Action Law is usually employed in modeling of ion exchange processes equilibrium. This methodology is based on the definition of the chemical equilibrium constant and considers the non ideality of solid and aqueous phases. Another alternative to chemical and phase equilibrium modeling is the use of Artificial Neural Networks. This work makes a comparison between both methodologies used on modeling of the equilibrium on ion exchange processes of the binary systems Pb2+-Na+,  Cu2+-Na+ e Na+-Pb2+, and the ternary system Cu2+-Na+- Pb2+ in the conditions of concentration corresponding to 0,005 eq/L and temperature of 303K, using the natural zeolyte clinoptilotita as an ion exchanger. The obtained data by the Mass Action Law from the binary systems were used as an input signal on the Artificial Neural Network training. The used networks had three layers (input, hidden and output layer), and as input signals there were used the concentration and the composition of the ions in solution and as output variable the composition of the ions on the ion exchanger were used. Results have shown that both methodologies were efficient on the binaries systems modeling. Both methodologies were also applied on prediction of the ternary systems behavior from binary systems data. There were made tests with Artificial Neural Networks including the ternary system data on the learning step. The obtained results from non predictive networks on the ternary system equilibrium description were better than those obtained from the Mass Action Law and from predictive networks. Key words: Mass Action Law, artificial neural network, ion exchange.A Lei da Ação das Massas é geralmente empregada na modelagem dos dados experimentais de equilíbrio de processos de troca iônica. Esta metodologia é baseada na definição da constante termodinâmica de equilíbrio químico e considera as não idealidades na fase sólida e na fase aquosa. Outra alternativa para a modelagem de equilíbrio químico e de fases são as Redes Neurais Artificiais. Este trabalho compara ambas as metodologias na modelagem do equilíbrio da troca iônica dos sistemas binário Pb2+-Na+, Cu2+- Na+ e Na+-Pb2+ e do sistema ternário Cu2+-Na+-Pb2+. Na concentração de 0,005 eq/L e temperatura de 303K empregando como trocado iônico a zeólita natural clinoptilotita. Os dados obtidos pela Lei da Ação das Massas nos sistemas binários foram usados como variável de entrada no treinamento da Rede Neural Artificial. As redes utilizadas possuíam três camadas (entrada, oculta e saída), como variáveis de entrada foi utilizadas a concentração e a composição dos íons em solução e como variável resposta a composição dos íons no trocador iônico. Os resultados mostraram que ambas as metodologias foram eficiente na modelagem de sistemas binários. Também foram aplicadas ambas as metodologias na predição do comportamento ternário a partir das informações dos sistemas binários. Ambas as metodologias se mostraram ineficientes na predição dos sistemas ternários. Foram realizados testes com as Redes Neurais com a inclusão de dados experimentais de sistemas ternários na etapa de treinamento. Os resultados obtidos com as redes não preditivas na descrição do equilíbrio do sistema ternário foram superiores aos obtidos com a Lei da Ação das massas e com a rede preditiva. Palavras-chave: lei da ação das massas, rede neural artificial, troca iônica

An engineering perspective of ceramics applied in dental reconstructions

The demands for dental materials continue to grow, driven by the desire to reach a better performance than currently achieved by the available materials. In the dental restorative ceramic field, the structures evolved from the metal-ceramic systems to highly translucent multilayered zirconia, aiming not only for tailored mechanical properties but also for the aesthetics to mimic natural teeth. Ceramics are widely used in prosthetic dentistry due to their attractive clinical properties, including high strength, biocompatibility, chemical stability, and a good combination of optical properties. Metal-ceramics type has always been the golden standard of dental reconstruction. However, this system lacks aesthetic aspects. For this reason, efforts are made to develop materials that met both the mechanical features necessary for the safe performance of the restoration as well as the aesthetic aspects, aiming for a beautiful smile. In this field, glass and high-strength core ceramics have been highly investigated for applications in dental restoration due to their excellent combination of mechanical properties and translucency. However, since these are recent materials when compared with the metal-ceramic system, many studies are still required to guarantee the quality and longevity of these systems. Therefore, a background on available dental materials properties is a starting point to provoke a discussion on the development of potential alternatives to rehabilitate lost hard and soft tissue structures with ceramic-based tooth and implant-supported reconstructions. This review aims to bring the most recent materials research of the two major categories of ceramic restorations: ceramic-metal system and all-ceramic restorations. The practical aspects are herein presented regarding the evolution and development of materials, technologies applications, strength, color, and aesthetics. A trend was observed to use high-strength core ceramics type due to their ability to be manufactured by CAD/CAM technology. In addition, the impacts of COVID-19 on the market of dental restorative ceramics are presented

IMPACTO DE DETERMINANTES SOCIAIS NA SAÚDE MENTAL: UMA ANÁLISE DE SAÚDE COLETIVA

Introduction: It seeks to highlight the importance of social determinants of health in relation to the treatment and care of patients with mental disorders. Furthermore, it reports on the changes and how the determinants reflect positively and negatively on this topic, in addition to the evolution that has emerged since past years. Objective: Understand the impacts and the relationship of determinants with the issue of mental health. Methodology: A systematic literature review was carried out covering the years from January 2003 to December 2023 The study was based and guided by the question mentioned throughout the article. Results: The evident role of determinants in the subject of mental health stands out, in addition to showing that the evolution of these determinants can improve and facilitate the development of efficient and appropriate care strategies for patients suffering from some mental illness. Advanced cases can be mitigated gradually. Conclusion: With emphasis on social and economic issues, it is noted that these factors directly affect adherence to treatment and diagnosis for those in need and that even with all the efforts aimed at this topic to this day, an inequality is still seen in the way in which The health system is offered to the population.Introdução: Procura evidenciar a importância das determinantes sociais de saúde em relação ao tratamento e assistência de pacientes com transtornos mentais. Além disso, relata as mudanças e como as determinantes refletem positivamente e negativamente nessa temática, além da evolução que foi surgindo desde anos passados. Objetivo: Compreender os impactos e a relação das determinantes com a temática da saúde mental. Metodologia: Foi realizada uma revisão sistemática de literatura abrangendo os anos de janeiro de 2003 a dezembro de 2023. O estudo teve como base e norteamento a pergunta citada no decorrer do artigo. Resultados: Destaca-se o papel evidente das determinantes no assunto de saúde mental, além de evidenciar que a evolução dessas determinantes podem melhorar e facilitar o desenvolvimento de estratégias de cuidados eficientes e adequadas para pacientes que sofrem de com alguma doença mental Assim, o número avançado de casos podem ser mitigado de forma gradativa. Conclusão: Dando ênfase a questões sociais e econômicas, nota-se que esses fatores afetam diretamente a adesão ao tratamento e diagnóstico aos necessitados e que mesmo com todos os esforços voltados a essa temática até os dias atuais ainda é visto uma desigualdade na forma em como é ofertado o  sistema de saúde a população

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

Transtorno bipolar em crianças: análise de relato de caso 2018-2023

O transtorno bipolar em crianças é uma realidade clínica que demanda atenção especializada. A compreensão dos sintomas, fatores de risco, prevalência e desafios diagnósticos é fundamental para proporcionar intervenções precoces e adequadas, visando melhorar a qualidade de vida desses jovens e reduzir o impacto a longo prazo dessa condição psiquiátrica. Trata-se de um estudo cujo objetivo foi objetivo revisar relatos de caso publicados entre 2018 e 2023 sobre transtorno bipolar em crianças, identificando o estado da arte desses estudos. Para isso, se realizou uma revisão sistemática de literatura utilizando as bases de dados Medical Literature Analysis and Retrieval System Online (MEDLINE), Literatura Latino-Americana e do Caribe em Ciências da Saúde (LILACS) e Scientific Electronic Library Online (SCIELO). Com a análise e interpretação qualitativa dos resultados, a principal conclusão deste estudo é que o transtorno bipolar na infância é uma condição complexa, manifestando-se com comportamentos consistentes com o Transtorno de Conduta e sendo influenciado por fatores ambientais, familiares e genéticos. O tratamento eficaz requer uma abordagem multidisciplinar, integrando intervenções farmacológicas e não farmacológicas, personalizadas conforme as necessidades individuais. A supervisão familiar é crucial para a adesão ao tratamento, mas reconhece-se a necessidade contínua de pesquisa para aprimorar as estratégias terapêuticas diante da diversidade de casos