CARACTERIZAÇÃO DO MODELO INFLAMATÓRIO DE CISTITE INDUZIDA POR CICLOFOSFAMIDA EM CAMUNDONGOS SWISS

A Cistite Hemorrágica é um problema de saúde importante no mundo causado pelo uso da oxazoforinas. Apesar dos tratamentos disponíveis, há uma incidência de 2 até 40% em pacientes tratados com Ciclofosfamida (CYP). O objetivo deste trabalho foi caracterizar um modelo experimental de cistite induzida por CYP em camundongos Swiss. Para isto, camundongos fêmeas foram distribuídos em 5 grupos com 7 animais, onde 4 grupos sofreram eutanásia após 0,5, 6, 12 e 24h da aplicação de 150mg/kg de CYP via intraperitoneal. O grupo controle recebeu salina tamponada pela mesma via. Foram avaliados o peso da bexiga e seu aspecto histopatológico, o hemograma, e a contagem celular de medula óssea e linfonodo ilíaco. Os resultados demonstraram que houve aumento significativo do peso da bexiga nos tempos de 6 e 12h. Houve aumento na infamação aguda nestes dois tempos. Após 24 horas houve diminuição da resposta inflamatória aguda e início da fibrose. O número de leucócitos foi menor em todos os tempos em relação ao controle. Da mesma forma, o número de células da medula óssea foi menor nos tempos de 6, 12 e 24h. Por outro lado, o número de células do linfonodo aumentou após 12 horas. Concluímos que houve aumento progressivo da inflamação até as 12h  e que após 24h já há um processo de resolução do quadro inflamatório. Sendo assim, sugerimos a utilização do tempo de 12h como padrão experimental por ser o de maior disponibilidade de parâmetros elevados para avaliação da inflamação.Descritores: Cistite. Ciclofosfamida. Camundongo. Modelo experimental.AbstractCharacterization of cyclophosphamide-induced cystitis inflammatory model in Swiss mice. The Hemorragic Cystitis (HC) is an important health problem over the world caused by oxazoforines. Despite the available treatments, still have an incidence of 2 to 40% of HC in patients following treatment with Cyclophosphamide (CYP). The aim of this work was characterize a model of CYP-induced cystitis  in Swiss mice. Female mice were divided  in 5 groups with 7 animals each, 4 groups were killed 0.5, 6, 12 and 24h after an injection of CYP (150mg/kg). The control group received phosphate buffered saline at the same way. In each time the bladders were collected, weighted and prepared to histopathology analyses. The complete blood count was evaluated. The cell number from lymph nodes and bone marrow was quantified. The results showed that bladder weight was increased at 6thand 12th hour pos cystitis induction. There was acute inflammation increased after 6 and 12h. After 24h there was an initial fibrosis. The leucocytes count was decreased in all times. The cells number was decreased at 6th,12th, and 24th hours in bone marrow and it was increased at 12th in lymph nodes. We concluded that there is an increase in inflammatory parameters until the 12th hour pos CYP injection which are decreased at 24th hour. We suggest using the time of 12h as the standard experimental time because of the biggest availability parameters for evaluating.Descriptors: Cyclophosphamide. Cystitis. Mice. Experimental model

POTENCIAL ANTI-INFLAMATÓRIO DAS FOLHAS DE Chenopodium ambrosioides L. NO MODELO DE CISTITE HEMORRÁGICA EM CAMUNDONGOS

A cistite hemorrágica (CH) possui etiologia infecciosa, medicamentosa ou radioterápica. Consiste na presença de hematúria macroscópica secundária a sangramento vesical e uma das suas possíveis causas é o uso de ciclofosfamida (CYP). Várias alternativas farmacológicas têm sido investigadas para o tratamento da CH. Dentre as possibilidades, o potencial terapêutico de espécies vegetais tem sido avaliado. A espécie Chenopodium ambrosioides L. (Amaranthaceae), tem sido utilizado popularmente como anti-infamatório, efeito que  tem  sido comprovado cientifcamente. Assim, o objetivo deste estudo  foi investigar os efeitos do extrato bruto hidroalcoólico (EBH) de folhas secas de C. ambrosioides na CH induzida em camundongos pela ciclofosfamida. Camundongos fêmeas da linhagem Swiss receberam 150 mg/kg de CYP por via intraperitoneal para indução de CH. Em seguida, os animais foram tratados em dose única de acordo com protocolo estabelecido para cada grupo: soro fsiológico a 0,9% (grupo Controle); diclofenaco potássico (grupo Diclofenaco); EBH com dose única de 5 (grupo EBH5) ou 50mg/kg (grupo EBH50). Após 12 horas da indução da CH, o sangue dos animais foi retirado para realização do hemograma.  Os animais foram então sacrifcados e as bexigas retiradas, avaliadas macroscopicamente (hemorragia) e pesadas. Foram removidos, ainda, os órgãos linfóides a fm de realizar contagem de células do baço, medula óssea e linfonodos. Os resultados demonstraram que houve diminuição do peso das bexigas e da hemorragia nos grupos Diclofenaco e EBH5 quando comparados ao grupo controle. Houve um aumento das células da medula óssea, baço e linfonodo mesentérico em todos os animais tratados em relação ao controle. Em relação ao hemograma houve apenas aumentos pontuais no grupo EBH50. Em conclusão, o extrato bruto hidroalcoólico de folhas de C. ambrosioides na dose de 5mg/Kg apresentou efeito anti-infamatório e imunoestimulante, pois diminuiu o peso e a hemorragia da bexiga, e aumentou a produção e proliferação de células linfóides. Diante dos resultados desse estudo, bem como da evidência de ausência de toxicidade de outros trabalhos, podemos sugerir o tratamento com este extrato como alternativa terapêutica nos modelos de CH induzida por CYP em camundongos.Descritores: Anti-infamatório. Chenopodium ambrosioides. Ciclofosfamida. Cistite.AbstractHemorrhagic cystitis (HC) has infectious, drug or radiotherapy etiology. Consists in the presence of macroscopic hematuria secondary to bladder bleeding, and one of its possible causes is the use of cyclophosphamide (CYP). Several pharmacological alternatives have been investigated for the treatment of HC. Among the possibilities, the therapeutic potential of plant species have been reported. The species Chenopodium ambrosioides L. (Amaranthaceae) has been popularly used as an anti-infammatory efect that has been proven scientifcally. The objective of this study was to investigate the efects of crude hydroalcoholic extract of dried leaves of C. ambrosioides in HC cyclophosphamide induced in mice. Female mice of the Swiss strain received 150 mg / kg of CYP intraperitoneally to induce HC. Then the animals were treated with a single dose according to protocol established for each group: normal saline 0.9% (control group); diclofenac (diclofenac group); hydroalcoholic extract with a single dose of 5 (EBH5 group) or 50 mg / kg (EBH50 group). After 12 hours from the induction of HC, the bleeding was performed in the animal for the complete blood count. The animals were then sacrifced and had their bladders removed, as assessed macroscopically (bleeding) and weighed. The lymphoid organs were also removed in order to perform spleen, bone marrow and lymph nodes cell count. The results demonstrated that there was a decrease in the weight of bladders and bleeding in the diclofenac group and EBH5 when compared to the control group. There was an increase of cells in the bone marrow, spleen and lymph node in all treated animals as compared to control. In blood count there were only occasional increases in EBH50 group. In conclusion, the hydroalcoholic crude extract of Chenopodium ambrosioides leaves at a dose of 5 mg / kg showed anti-infammatory and immunostimulatory efect as decreased body weight and bleeding of the bladder, and increased production and proliferation of lymphoid cells. Given the results of this study, as well as evidence of absence of toxicity in other studies, we suggest treatment with this extract as an alternative therapy in models of CH-induced CYP in mice.Descriptors: Anti-infammatory. Chenopodium ambrosioides. Cyclophosphamide. Cystitis

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space. While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes, vast areas of the tropics remain understudied. In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity, but it remains among the least known forests in America and is often underrepresented in biodiversity databases. To worsen this situation, human-induced modifications 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, 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

Correction: Pervasive gaps in Amazonian ecological research

In the original version of the article, the authors incorrectly stated the value of current and projected deforestation in the results: the values should be 23.50% and 27.29%, respectively. This error does not impact the results or conclusions presented in the paper. The error has now been corrected online. The authors apologize for the error and any confusion that may have resulted

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

Rationale, study design, and analysis plan of the Alveolar Recruitment for ARDS Trial (ART): Study protocol for a randomized controlled trial

Background: Acute respiratory distress syndrome (ARDS) is associated with high in-hospital mortality. Alveolar recruitment followed by ventilation at optimal titrated PEEP may reduce ventilator-induced lung injury and improve oxygenation in patients with ARDS, but the effects on mortality and other clinical outcomes remain unknown. This article reports the rationale, study design, and analysis plan of the Alveolar Recruitment for ARDS Trial (ART). Methods/Design: ART is a pragmatic, multicenter, randomized (concealed), controlled trial, which aims to determine if maximum stepwise alveolar recruitment associated with PEEP titration is able to increase 28-day survival in patients with ARDS compared to conventional treatment (ARDSNet strategy). We will enroll adult patients with ARDS of less than 72 h duration. The intervention group will receive an alveolar recruitment maneuver, with stepwise increases of PEEP achieving 45 cmH(2)O and peak pressure of 60 cmH2O, followed by ventilation with optimal PEEP titrated according to the static compliance of the respiratory system. In the control group, mechanical ventilation will follow a conventional protocol (ARDSNet). In both groups, we will use controlled volume mode with low tidal volumes (4 to 6 mL/kg of predicted body weight) and targeting plateau pressure <= 30 cmH2O. The primary outcome is 28-day survival, and the secondary outcomes are: length of ICU stay; length of hospital stay; pneumothorax requiring chest tube during first 7 days; barotrauma during first 7 days; mechanical ventilation-free days from days 1 to 28; ICU, in-hospital, and 6-month survival. ART is an event-guided trial planned to last until 520 events (deaths within 28 days) are observed. These events allow detection of a hazard ratio of 0.75, with 90% power and two-tailed type I error of 5%. All analysis will follow the intention-to-treat principle. Discussion: If the ART strategy with maximum recruitment and PEEP titration improves 28-day survival, this will represent a notable advance to the care of ARDS patients. Conversely, if the ART strategy is similar or inferior to the current evidence-based strategy (ARDSNet), this should also change current practice as many institutions routinely employ recruitment maneuvers and set PEEP levels according to some titration method.Hospital do Coracao (HCor) as part of the Program 'Hospitais de Excelencia a Servico do SUS (PROADI-SUS)'Brazilian Ministry of Healt

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