Bioceramic Cements: Supporting in Remineralization of Osteolytic Lesions in Endodontic-periodontal Diseases: A Report of Two Cases

Bioceramic cements used for filling root canals in cases of endo-perio lesion of endodontic origin seem to be promising due to having the potential of promoting faster and more predictable healing of the periapical lesion as they stimulate osteogenesis. An effective treatment plan depends on the precise diagnosis of endo-perio lesions. The origin of an infection, being exclusive to the root canal, from the periodontium, or both, is extremely important for devising the treatment plan. In both cases, no clinical evidence of periodontal disease (bleeding, calculus, etc.) was found; however, primary endodontic lesions with the possibility of drainage through the gingival crevice were present. In addition to the disinfection strategies used during the root canal treatments, the bioceramics Bio C Sealer, Bio C Repair and Bio Root RCS were used to fill in the root canals. Both cases presented an impressive bone gain within 8 months for case 1 and 5 months for case 2. Regarding case 1, in the palatal root canal an apical plug with a bioceramic repair cement was used. Based on the literature studied, it can be concluded that after adequate disinfection of the root canals, using bioceramic cements in filling the root canals shows the potential of supporting capabilities in remineralization of osteolytic lesions in endo-perio diseases.

Influence of forensic examination on the accountability of sexual violence authors in teenagers

OBJETIVO: avaliar a influência do exame médico-legal na responsabilização criminal de acusados de violência sexual contra adolescentes do sexo feminino. MÉTODO: foram analisados retrospectivamente 137 processos judiciais de estupro contra adolescentes matriculadas no Centro de Referência da Criança e do Adolescente entre janeiro de 1995 e dezembro de 2004. Os laudos do Instituto Médico Legal foram classificados como negativos ou positivos para a materialidade do crime sexual e confrontados com a sentença judicial, condenatória ou não para o acusado. Os dados foram informatizados em Programa EpiInfo e submetidos ao teste de Qui-quadrado para Tabelas de contingência, fixando-se em p &lt; 0,05 o nível de rejeição da hipótese de nulidade. RESULTADOS: em 30 casos (21,9%) o laudo foi concordante com a queixa de estupro. Em 107 casos (78,1%) o exame médico-legal não encontrou evidência material do crime sexual. Entre os exames positivos, 25 acusados (83,3%) foram condenados, enquanto nas perícias negativas ocorreram 68 condenações (63,5%). CONCLUSÕES: o exame médico-legal positivo se associou com maior probabilidade de condenação do acusado da violência sexual. A ausência de elementos comprobatórios materiais não impediu a responsabilização de parte expressiva dos acusados, indicando que outros meios de convencimento são admitidos pela justiça.OBJECTIVE: to evaluate the influence of forensic examination on the accountability of sexual violence criminal charges in adolescent girls. METHOD: retrospective study, it was analyzed 137 lawsuits rape in teenagers enrolled in the Reference Center for Children and Adolescents between January 1995 and December 2004. The awards of the Forensic Institute were classified as negative or positive for the materiality of sexual crimes and confronted with the judicial sentence, condemnatory or not. Data was computerized in EpiInfo Program and subjected to chi-square test for contingency tables, considering p < 0.05 the level of rejection of the hypothesis of nullity. RESULTS: in 30 cases (21.9%) the award was consistent with the complaint of rape. In 107 cases (78.1%) the forensic examination found no physical evidence of sexual crime. Among the positive cases, 25 accused (83.3 %) were condemned, while in the negative skills it was observed 68 condemnations (63.5 %). CONCLUSIONS: the positive forensic examination was associated with the most part of probability of condemnation of the accused of the sexual violence. The absence of corroborative material elements did not obstruct the accountability of expressive part of the accused subjects, indicating that other means of persuasion are accepted by the courts

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

Predictive potential of urinary biomarkers for early diagnosis of acute kidney injury in major elective abdominal non-vascular surgeries

INTRODUÇÃO: A incidência de injúria renal aguda (IRA) tem aumentado significativamente nos últimos anos, fazendo com que seja considerada um problema de saúde pública mundial. IRA está associada com morbidade e mortalidade elevadas (precoce e tardia), aumento do tempo e dos custos de internação e desenvolvimento posterior de doença renal crônica. O diagnóstico precoce de IRA é extremamente importante para a instituição de medidas protetoras visando evitar a instalação ou minimizar a gravidade da IRA. Os pacientes submetidos a grandes cirurgias apresentam alta incidência de IRA, associada a eventos adversos em longo prazo. Há grande interesse em estudar a IRA pós-operatória desta população, pela possibilidade de estimativa do dano peri-operatório e potencial intervenção. Neste contexto, o uso de biomarcadores (BMs) para identificar pacientes de alto risco para IRA é relevante. A maioria dos estudos com BMs em pacientes cirúrgicos analisou cirurgias torácicas; existem poucos dados sobre o papel dos BMs urinários de lesão estrutural renal na predição da IRA em pacientes submetidos a grandes cirurgias abdominais eletivas não vasculares. Este estudo tem como objetivo analisar a acurácia de BMs urinários de lesão estrutural renal na predição de IRA após grandes cirurgias abdominais eletivas não vasculares. MÉTODOS: Um total de 298 pacientes submetidos a cirurgias abdominais eletivas não vasculares foram avaliados prospectivamente, no pré e peri-operatório, desde a admissão na UTI até sete dias ou alta da UTI. A creatinina sérica (CrS) foi avaliada antes da cirurgia e uma vez por dia até sete dias ou alta da UTI. A IRA foi diagnosticada e classificada usando o critério da CrS de acordo com as definições do Kidney Disease Improving Global Outcomes (KDIGO). Amostras de urina foram coletadas na internação hospitalar, na internação na UTI, 12 e 24h após a admissão na UTI. Os BMs urinários clusterina, calbindina, pi-glutationa transferase-S; interleucina 18 (IL-18), molécula de injúria renal 1 (KIM-1), proteína quimiotática de monócitos 1 (MCP-1); microalbumina, beta-2-microglobulina, cistatina C, lipocalina associada com gelatinase de neutrófilos humanos (NGAL), osteopontina (OPN), fator trifólio três, inibidor tecidual de metaloproteinase -2 (TIMP-2), e proteína ligadora-7 do fator de crescimento de insulina (IGFBP-7) foram avaliados pelo método Luminex x-MAP. Os dados foram testados para normalidade pelo teste de Kolmogorov-Smirnov e são apresentados como mediana (primeiro e terceiro quartis), média ± desvio padrão ou frequência, como adequado. A acurácia das curvas ROC foi obtida de pacientes sem IRA e IRA KDIGO I como controles e pacientes IRA KDIGO II e III como resultado positivo para IRA moderada ou grave. Os BM foram avaliados isoladamente e em combinações a fim de se encontrar a melhor acurácia diagnóstica. Considerada significância estatística para p < 0,05. RESULTADOS: A idade média dos pacientes foi de 56 ± 15 anos, 59% do sexo feminino; o tempo médio de internação foi de 17,7 ±16,2 dias, o tempo médio de internação na UTI foi de 3,1 ± 2,9 dias e mortalidade em 90 dias foi de 6,4%. Um total de 71 pacientes (24%) desenvolveu IRA. Os BMs MCP-1, IL-18, KIM-1, OPN, NGAL, TIMP-2 e IGFBP-7 foram significativamente mais elevados no grupo IRA em todos os períodos analisados. O produto da multiplicação dos BMs MCP-1 e KIM-1 na coleta pré-operatória demonstrou boa acurácia em predizer IRA moderada e grave (AUC de 0,79; intervalo de confiança 0,69-0,88). O melhor momento para predição de IRA foi após 12 horas da admissão da UTI, usando o produto da multiplicação dos BMs NGAL, KIM-1 e TIMP-2 (AUC de 0,86; intervalo de confiança 0,79-0,94). Estas duas combinações apresentaram melhor acurácia do que qualquer BM isoladamente ou em outras combinações para predizer IRA moderada ou grave e se associaram a tempo de internação mais longos e maior mortalidade 90 dias após cirurgia. CONCLUSÕES: A maioria dos pacientes que desenvolveu IRA moderada ou grave apresentou BMs elevados à internação (pré-operatório) e o produto dos BMs MCP-1 e KIM-1 demonstrou boa acurácia para prever IRA. O melhor desempenho para diagnosticar IRA moderada e grave foi o produto de KIM-1, NGAL e TIMP-2, 12h após admissão na UTI. As duas combinações de BMs descritas acima apresentaram acurácia maior do que qualquer BM isoladamenteBACKGROUND: Acute kidney injury (AKI) incidence has increased significantly in the last years, and AKI has emerged as a worldwide health public problem. AKI has been associated with higher morbidity and early and late mortality, higher hospital length of stay and development of chronic kidney disease. AKI early diagnosis is extremely important to institute protective measures in order to prevent and/or minimize AKI development. Major surgeries patients have a high incidence of AKI associated with long-term adverse events. There is great interest on the study of postoperative AKI in this population, due to the possibility of estimating perioperative damage and establishing potential interventions. In this context, the use of biomarkers (BMs) to identify AKI high risk patients is extremely relevant. Most of the studies with BMs in surgical patients had assessed thoracic surgeries; there are few data on the role of urinary BMs of kidney structural injury in predicting AKI from patients submitted to major elective non-vascular abdominal surgeries. The present study aimed to assess the accuracy of urinary BMs for AKI prediction after major elective non-vascular abdominal surgeries. METHODS: A total of 298 patients submitted to major elective abdominal non-vascular surgeries were prospectively assessed. They were evaluated pre, peri-operatively and from the ICU admission up to seven days. Serum creatinine (sCr) was evaluated before surgery and once a day up to seven days or until ICU discharge. AKI was diagnosed and staged using sCr according to Kidney Disease Improving Global Outcomes (KDIGO) definitions. Urine samples were collected at hospital admission (before surgery), at ICU admission, 12 and 24h after ICU admission. Urinary biomarkers clusterin, calbindin, pi-glutathione S-transferase; interleucin 18 (IL-18), kidney injury molecule 1 (KIM-1), monocyte chemoattractant protein 1 (MCP-1); microalbumin, beta-2-microglobulin, cistatin C, neutrophil gelatinase associated lipocalin (NGAL), osteopontin (OPN), trefoil factor 3, tissue inhibitor of metalloproteinase-2 (TIMP-2), and insulin-like growth factor-binding protein 7 (IGFBP-7) were assessed by Luminex x-MAP method. Data were tested for normality by Kolmogorov-Smirnov test, and are presented as median (first and third quartiles), mean ± standard deviation or frequency. The accuracy of ROC curves was assessed using non-AKI and AKI KDIGO I as control and AKI KDIGO II and III as positive result. We tested the biomarkers isolated and in different combinations to find the better accuracy. Statistical significance was p < 0.05. RESULTS: Patients\' median age was 56 ± 15 years, and 59% were female; hospital length of stay was 17.7 ± 16.2 days, ICU length of stay was 3.1 ± 2.9 days and 90 days mortality rate was 6.4%. A total of 71 patients (24%) developed AKI by KDIGO SCr criteria. The biomarkers MCP-1, IL-18, KIM-1, OPN, NGAL, TIMP-2 and IGFBP-7 were significantly higher for the AKI group on all time points analyzed. The product of MCP-1 and KIM-1 in the preoperative period achieved a good accuracy (AUC = 0.79; confidence interval 95% 0.69 - 0.88). The better time for AKI prediction was 12 hours after of ICU admission using the product of KIM-1, NGAL and TIMP-2 (AUC = 0.86; confidence interval 95% 0.79 - 0.94). These two biomarkers combinations presented higher accuracy than any of the biomarkers alone or in other combinations, and were associated to longer length of stay and 90 days mortality. CONCLUSIONS: Most of patients who developed moderate or severe AKI presented high levels of BM at hospitalization (before surgery) and the product of MCP-1 and KIM-1 showed good prediction accuracy for AKI. The best prediction accuracy for moderate or severe AKI was the product of KIM-1, NGAL and TIMP-2, 12 hours after ICU admission. Any of the two BMs combinations presented higher accuracy than the BM tested alon