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- 저자 : Liuzzi, Michel (검색결과 5 건)
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Diatom Allantoin Synthase Provides Structural Insights into Natural Fusion Protein Therapeutics
Oh, Juntaek,Liuzzi, Anastasia,Ronda, Luca,Marchetti, Marialaura,Corsini, Romina,Folli, Claudia,Bettati, Stefano,Rhee, Sangkee,Percudani, Riccardo American Chemical Society 2018 ACS CHEMICAL BIOLOGY Vol.13 No.8
<P>Humans have lost the ability to convert urate into the more soluble allantoin with the evolutionary inactivation of three enzymes of the uricolytic pathway. Restoration of this function through enzyme replacement therapy can treat severe hyperuricemia and Lesch-Nyhan disease. Through a genomic exploration of natural gene fusions, we found that plants and diatoms independently evolved a fusion protein (allantoin synthase) complementing two human pseudogenes. The 1.85-Å-resolution crystal structure of allantoin synthase from the diatom <I>Phaeodactylum tricornutum</I> provides a rationale for the domain combinations observed in the metabolic pathway, suggesting that quaternary structure is key to the evolutionary success of protein domain fusions. Polyethylene glycol (PEG) conjugation experiments indicate that a PEG-modified form of the natural fusion protein provides advantages over separate enzymes in terms of activity maintenance and manufacturing of the bioconjugate. These results suggest that the combination of different activities in a single molecular unit can simplify the production and chemical modification of recombinant proteins for multifunctional enzyme therapy.</P> [FIG OMISSION]</BR>
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Big Data Analysis Using Modern Statistical and Machine Learning Methods in Medicine
유창원,Luis Ramirez,Juan Liuzzi 대한배뇨장애요실금학회 2014 International Neurourology Journal Vol.18 No.2
In this article we introduce modern statistical machine learning and bioinformatics approaches that have been used in learning statistical relationships from big data in medicine and behavioral science that typically include clinical, genomic (and proteomic) and environmental variables. Every year, data collected from biomedical and behavioral science is getting larger and more complicated. Thus, in medicine, we also need to be aware of this trend and understand the statistical tools that are available to analyze these datasets. Many statistical analyses that are aimed to analyze such big datasets have been introduced recently. However, given many different types of clinical, genomic, and environmental data, it is rather uncommon to see statistical methods that combine knowledge resulting from those different data types. To this extent, we will introduce big data in terms of clinical data, single nucleotide polymorphism and gene expression studies and their interactions with environment. In this article, we will introduce the concept of well-known regression analyses such as linear and logistic regressions that has been widely used in clinical data analyses and modern statistical models such as Bayesian networks that has been introduced to analyze more complicated data. Also we will discuss how to represent the interaction among clinical, genomic, and environmental data in using modern statistical models. We conclude this article with a promising modern statistical method called Bayesian networks that is suitable in analyzing big data sets that consists with different type of large data from clinical, genomic, and environmental data. Such statistical model form big data will provide us with more comprehensive understanding of human physiology and disease.
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( Nicola Di Fidio ),( Federico Liuzzi ),( Silvio Mastrolitti ),( Roberto Albergo ),( Isabella De Bari ) 한국미생물 · 생명공학회 2019 Journal of microbiology and biotechnology Vol.29 No.2
The use of low-cost substrates represents one key issue to make single cell oil production sustainable. Among low-input crops, Arundo donax L. is a perennial herbaceous rhizomatous grass containing both C5 and C6 carbohydrates. The scope of the present work was to investigate and optimize the production of lipids by the oleaginous yeast Cutaneotrichosporon curvatus from undetoxified lignocellulosic hydrolysates of steam-pretreated A. donax. The growth of C. curvatus was first optimized in synthetic media, similar in terms of sugar concentration to hydrolysates, by applying the response surface methodology (RSM) analysis. Then the bioconversion of undetoxified hydrolysates was investigated. A fed-batch process for the fermentation of A. donax hydrolysates was finally implemented in a 2-L bioreactor. Under optimized conditions, the total lipid content was 64% of the dry cell weight and the lipid yield was 63% of the theoretical. The fatty acid profile of C. curvatus triglycerides contained 27% palmitic acid, 33% oleic acid and 32% linoleic acid. These results proved the potential of lipid production from A. donax, which is particularly important for their consideration as substitutes for vegetable oils in many applications such as biodiesel or bioplastics.
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Lee, Sukjun,Lim, Donghyun,Lee, Eunyoung,Lee, Nakyung,Lee, Hong-gun,Cechetto, Jonathan,Liuzzi, Michel,Freitas-Junior, Lucio H.,Song, Jin Sook,Bae, Myung Ae,Oh, Sangmi,Ayong, Lawrence,Park, Seung Bum American Chemical Society 2014 Journal of medicinal chemistry Vol.57 No.17
<P>New antimalarial agents that exhibit multistage activities against drug-resistant strains of malaria parasites represent good starting points for developing next-generation antimalarial therapies. To facilitate the progression of such agents into the development phase, we developed an image-based parasitological screening method for defining drug effects on different asexual life cycle stages of <I>Plasmodium falciparum</I>. High-throughput screening of a newly assembled diversity-oriented synthetic library using this approach led to the identification of carbohybrid-based 2-aminopyrimidine compounds with fast-acting growth inhibitory activities against three laboratory strains of multidrug-resistant <I>P. falciparum</I>. Our structure–activity relationship study led to the identification of two derivatives (<B>8aA</B> and <B>11aA</B>) as the most promising antimalarial candidates (mean EC<SUB>50</SUB> of 0.130 and 0.096 μM against all three <I>P. falciparum</I> strains, selectivity indices >600, microsomal stabilities >80%, and mouse malaria ED<SUB>50</SUB> values of 0.32 and 0.12 mg/kg/day, respectively), targeting all major blood stages of multidrug-resistant <I>P. falciparum</I> parasites.</P><P><B>Graphic Abstract</B> <IMG SRC='http://pubs.acs.org/appl/literatum/publisher/achs/journals/content/jmcmar/2014/jmcmar.2014.57.issue-17/jm5009693/production/images/medium/jm-2014-009693_0007.gif'></P><P><A href='http://pubs.acs.org/doi/suppl/10.1021/jm5009693'>ACS Electronic Supporting Info</A></P>
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Oh, S.,Kwon, B.,Kong, S.,Yang, G.,Lee, N.,Han, D.,Goo, J.,Siqueira-Neto, J.,Freitas-Junior, L.,Liuzzi, M. TEH ROYAL SOCIETY OF CHEMISTRY 2014 MedChemComm Vol.5 No.2
A high-throughput (HTS) and high-content screening (HCS) campaign of a commercial library identified 2-acetamidothophen-3-carboxamide as a novel scaffold for developing new anti-leishmanial agents. A series of chemical modifications were performed to study the structure-activity relationship (SAR) and in vitro anti-leishmanial activities were evaluated using biological assays of not only extracellular promastigotes but also intracellular amastigotes. Compound 6a showed promising anti-amastigote activity (EC50 = 6.41 mu M) against L. donovani without any cytotoxicity (CC50 > 50 mu M) towards human macrophages.
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