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  1. Artikel ; Online: Antiparasitic properties of 4-nerolidylcatechol from Pothomorphe umbellata (L.) Miq. (Piperaceae) in vitro and in mice models with either prepatent or patent Schistosoma mansoni infections.

    Costa, Danilo de Souza / Leal, Carla Monteiro / Cajas, Rayssa A / Gazolla, Matheus Coutinho / Silva, Lívia Mara / Carvalho, Lara Soares Aleixo de / Lemes, Bruna L / Moura, Renato Oliveira de / Almeida, Juliana de / de Moraes, Josué / da Silva Filho, Ademar A

    Journal of ethnopharmacology

    2023  Band 313, Seite(n) 116607

    Abstract: Ethnopharmacological relevance: Roots of Pothomorphe umbellata (L.) Miq. are used in traditional medicine of Africa and South America for the treatment of malaria and helminthiasis. However, neither P. umbellata nor its isolated compounds have been ... ...

    Abstract Ethnopharmacological relevance: Roots of Pothomorphe umbellata (L.) Miq. are used in traditional medicine of Africa and South America for the treatment of malaria and helminthiasis. However, neither P. umbellata nor its isolated compounds have been evaluated against Schistosoma species.
    Aims of this study: To investigate the antischistosomal effects of P. umbellata root extracts and the isolated compound 4-nerolidylcatechol (4-NC) against Schistosoma mansoni ex vivo and in murine models of schistosomiasis.
    Materials and methods: The crude hydroalcoholic (PuE) and hexane (PuH) extracts of P. umbellata roots were prepared and initially submitted to an ex vivo phenotypic screening against adult S. mansoni. PuH was analyzed by HPLC-DAD, characterized by UHPLC-HRMS/MS, and submitted to chromatographic fractionation, leading to the isolation of 4-NC. The anthelmintic properties of 4-NC were assayed ex vivo against adult schistosomes and in murine models of schistosomiasis for both patent and prepatent S. mansoni infections. Praziquantel (PZQ) was used as a reference compound.
    Results: PuE (EC
    Conclusions: This study demonstrates that P. umbellata roots possess antischistosomal activity, giving support for the medicinal use of this plant against parasites. 4-NC was identified from P. umbellata roots as one of the effective in vitro and in vivo antischistosomal compound and as a potential lead for the development of novel anthelmintics.
    Mesh-Begriff(e) Animals ; Mice ; Schistosomiasis mansoni/drug therapy ; Schistosomiasis mansoni/parasitology ; Piperaceae/chemistry ; Antiparasitic Agents/pharmacology ; Schistosoma mansoni ; Anthelmintics/pharmacology ; Anthelmintics/therapeutic use ; Praziquantel/pharmacology ; Schistosomiasis/drug therapy ; Plant Extracts/pharmacology ; Plant Extracts/therapeutic use ; Plant Extracts/chemistry ; Mammals
    Chemische Substanzen 4-nerolidylcatechol ; Antiparasitic Agents ; Anthelmintics ; Praziquantel (6490C9U457) ; Plant Extracts
    Sprache Englisch
    Erscheinungsdatum 2023-05-05
    Erscheinungsland Ireland
    Dokumenttyp Journal Article
    ZDB-ID 134511-4
    ISSN 1872-7573 ; 0378-8741
    ISSN (online) 1872-7573
    ISSN 0378-8741
    DOI 10.1016/j.jep.2023.116607
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  2. Artikel ; Online: Time series causal relationships discovery through feature importance and ensemble models.

    Castro, Manuel / Mendes Júnior, Pedro Ribeiro / Soriano-Vargas, Aurea / de Oliveira Werneck, Rafael / Moreira Gonçalves, Maiara / Lusquino Filho, Leopoldo / Moura, Renato / Zampieri, Marcelo / Linares, Oscar / Ferreira, Vitor / Ferreira, Alexandre / Davólio, Alessandra / Schiozer, Denis / Rocha, Anderson

    Scientific reports

    2023  Band 13, Heft 1, Seite(n) 11402

    Abstract: Inferring causal relationships from observational data is a key challenge in understanding the interpretability of Machine Learning models. Given the ever-increasing amount of observational data available in many areas, Machine Learning algorithms used ... ...

    Abstract Inferring causal relationships from observational data is a key challenge in understanding the interpretability of Machine Learning models. Given the ever-increasing amount of observational data available in many areas, Machine Learning algorithms used for forecasting have become more complex, leading to a less understandable path of how a decision is made by the model. To address this issue, we propose leveraging ensemble models, e.g., Random Forest, to assess which input features the trained model prioritizes when making a forecast and, in this way, establish causal relationships between the variables. The advantage of these algorithms lies in their ability to provide feature importance, which allows us to build the causal network. We present our methodology to estimate causality in time series from oil field production. As it is difficult to extract causal relations from a real field, we also included a synthetic oil production dataset and a weather dataset, which is also synthetic, to provide the ground truth. We aim to perform causal discovery, i.e., establish the existing connections between the variables in each dataset. Through an iterative process of improving the forecasting of a target's value, we evaluate whether the forecasting improves by adding information from a new potential driver; if so, we state that the driver causally affects the target. On the oil field-related datasets, our causal analysis results agree with the interwell connections already confirmed by tracer information; whenever the tracer data are available, we used it as our ground truth. This consistency between both estimated and confirmed connections provides us the confidence about the effectiveness of our proposed methodology. To our knowledge, this is the first time causal analysis using solely production data is employed to discover interwell connections in an oil field dataset.
    Mesh-Begriff(e) Time Factors ; Causality ; Algorithms ; Forecasting ; Random Forest
    Sprache Englisch
    Erscheinungsdatum 2023-07-14
    Erscheinungsland England
    Dokumenttyp Journal Article
    ZDB-ID 2615211-3
    ISSN 2045-2322 ; 2045-2322
    ISSN (online) 2045-2322
    ISSN 2045-2322
    DOI 10.1038/s41598-023-37929-w
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  3. Artikel: Progressive multifocal leukoencephalopathy in non-HIV patient.

    Vieira, Diego Rosseman / Zanella, Diogo / Avelino, Eurípedes Barsanulfo de Paula / Moura, Renato Batista Soares / Porto, Gislaine Cristina Lopes Machado / Yu, Liao Shin / Chojniak, Rubens

    Dementia & neuropsychologia

    2017  Band 10, Heft 2, Seite(n) 165–167

    Sprache Englisch
    Erscheinungsdatum 2017-08-22
    Erscheinungsland Brazil
    Dokumenttyp Case Reports
    ISSN 1980-5764
    ISSN 1980-5764
    DOI 10.1590/S1980-5764-2016DN1002015
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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