Naphthoquinone Derivatives and Lignans from the Paraguayan Crude Drug “Tayï Pytá” (Tabebuia heptaphylla, Bignoniaceae)

The Paraguayan crude drug “tayï pytá” is used to treat cancer, wounds and inflammation. It consist of the bark and trunkwood of Tabebuia heptaphylla (Bignoniaceae). A phytochemical study of the crude drug gave, in addition to previously described naphthoquinones and the known lignans cycloolivil and secoisolariciresinol, three new lapachenol (lapachonone)-, two naphthofuran-, a chromone and a naphthalene derivative. The structures were elucidated by means of high field NMR spectroscopy. The biological activity of the main compound lapachol and the related α-lapachone as well as the lignans cycloolivil and secoisolariciresinol can explain, at least in part, the effect atributed to the crude drug in Paraguayan folk medicine

Naphthoquinone derivatives and lignans from the Paraguayan crude drug

Schmeda-Hirschmann,G. Laboratorio de Quımica de Productos Naturales,Instituto de Quımica de Recursos Naturales, Universidad de Talca, Casilla 747, Talca, Chile.The Paraguayan crude drug “tayı¨ pyta´” is used to treat cancer, wounds and inflammation. It consist of the bark and trunkwood of Tabebuia heptaphylla (Bignoniaceae). A phytochemical study of the crude drug gave, in addition to previously described naphthoquinones and the known lignans cycloolivil and secoisolariciresinol, three new lapachenol (lapachonone)-, two naphthofuran-, a chromone and a naphthalene derivative. The structures were elucidated by means of high field NMR spectroscopy. The biological activity of the main compound lapachol and the related α-lapachone as well as the lignans cycloolivil and secoisolariciresinol can explain, at least in part, the effect atributed to the crude drug in Paraguayan folk medicine

Application of chemometric methods for assessment and modelling of microbiological quality data concerning coastal bathing water in Greece

Background. Worldwide, the aim of managing water is to safeguard human health whilst maintaining sustainable aquatic and associated terrestrial, ecosystems. Because human enteric viruses are the most likely pathogens responsible for waterborne diseases from recreational water use, but detection methods are complex and costly for routine monitoring, it is of great interest to determine the quality of coastal bathing water with a minimum cost and maximum safety. Design and methods. This study handles the assessment and modelling of the microbiological quality data of 2149 seawater bathing areas in Greece over 10-year period (1997-2006) by chemometric methods. Results. Cluster analysis results indicated that the studied bathing beaches are classified in accordance with the seasonality in three groups. Factor analysis was applied to investigate possible determining factors in the groups resulted from the cluster analysis, and also two new parameters were created in each group; VF1 includes E. coli, faecal coliforms and total coliforms and VF2 includes faecal streptococci/enterococci. By applying the cluster analysis in each seasonal group, three new groups of coasts were generated, group A (ultraclean), group B (clean) and group C (contaminated). Conclusions. The above analysis is confirmed by the application of discriminant analysis, and proves that chemometric methods are useful tools for assessment and modeling microbiological quality data of coastal bathing water on a large scale, and thus could attribute to effective and economical monitoring of the quality of coastal bathing water in a country with a big number of bathing coasts, like Greece

A Qualitative Exploration of Practitioners' Understanding of and Response to Child-to-Parent Aggression.

There has been limited research and policy directed toward defining and understanding child-to-parent aggression (CPA), resulting in inconsistent definitions, understandings, and responses, which has a detrimental impact on families. In particular, there have been limited qualitative studies of those working on the frontline of CPA, hindering the development of effective policy. The present qualitative study therefore aimed to explore practitioner perspectives of CPA. Twenty-five practitioners from diverse fields (e.g., youth justice, police, charities) participated in four focus groups relating to their experiences of working with CPA in the United Kingdom. Thematic analysis of focus groups revealed three key themes: definitions of CPA, understanding of CPA risk factors, and responding to CPA. Practitioners understood CPA to be a broad use of aggression to intimidate and control parents and highlighted a range of individual (e.g., mental health, substance abuse) and social (e.g., parenting, gangs) risk factors for CPA. Further, practitioners felt that current methods of reporting CPA were ineffective and may have a detrimental impact on families. The findings of this study have implications for CPA policy and support the need for a multiagency and coordinated strategy for responding to CPA

Vulnerability prediction for secure healthcare supply chain service delivery

Healthcare organisations are constantly facing sophisticated cyberattacks due to the sensitivity and criticality of patient health care information and wide connectivity of medical devices. Such attacks can pose potential disruptions to critical services delivery. There are number of existing works that focus on using Machine Learning(ML) models for pre-dicting vulnerability and exploitation but most of these works focused on parameterized values to predict severity and exploitability. This paper proposes a novel method that uses ontology axioms to define essential concepts related to the overall healthcare ecosystem and to ensure semantic consistency checking among such concepts. The application of on-tology enables the formal specification and description of healthcare ecosystem and the key elements used in vulnerabil-ity assessment as a set of concepts. Such specification also strengthens the relationships that exist between healthcare-based and vulnerability assessment concepts, in addition to semantic definition and reasoning of the concepts. Our work also makes use of Machine Learning techniques to predict possible security vulnerabilities in health care supply chain services. The paper demonstrates the applicability of our work by using vulnerability datasets to predict the exploitation. The results show that the conceptualization of healthcare sector cybersecurity using an ontological approach provides mechanisms to better understand the correlation between the healthcare sector and the security domain, while the ML algorithms increase the accuracy of the vulnerability exploitability prediction. Our result shows that using Linear Regres-sion, Decision Tree and Random Forest provided a reasonable result for predicting vulnerability exploitability