27 research outputs found

    Bioactive Compounds from Brazilian Lichens and Their Biotechnological Applications

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    Lichens are the symbiotic organisms formed by one species of fungus associated to one or more species of green algae and/or cyanobacteria. The relationship between these organisms results in a metabolism that culminates in a production of exclusive compounds, named lichen substances, also known as lichen compounds or lichen acids. These products are known to exhibit several biological properties, and can be effective against several diseases. Several species of lichens found in Brazil have been identified and characterized for their bioactives during the last few decades. Studies have shown that these species possess antimicrobial, antineoplastic, anti-inflammatory, anti-leishmanial, and many more such bioactivities. In most cases, the articles mention different mechanisms of action. In complement, biotechnological studies have been carried out to achieve a continuous production of bioactive compounds, for example, the use of small amounts of thallus, collected directly from the environment, bioconservation processes, nanotechnological assays, nano and microencapsulations for a controlled drug liberation, incorporation in polymer matrix for pharmacological uses, etc. The possibility of extensive use of lichen substances encourages for further studies in this field, including the Brazilian species

    Cd-98(48)50:The two-proton-hole spectrum in Sn-100(50)50

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    Excited states in Cd-98, two proton holes from Sn-100, were identified and studied for the first time, using in-beam spectroscopy with highly selective ancillary detectors. The structure of the (pi g(9/2))(-2) two-proton-hole spectrum below a T-1/2 = 0.48(16) mu s isomer is deduced and compared to shell-model predictions. A tentative I-pi = (8(+)) assignment, as suggested by systematics, yields a strongly reduced B(E2,8(+) --> 6(+)) = 0.44((+20)(-10)) W.u., corresponding to an effective proton charge of e(pi) = 0.85((+20)(-10))e, which is at variance with existing theoretical predictions
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