Structure Identification and Functional Mechanism of Natural Active Components

The natural active components derived from plants have attracted widespread attention due to their abundant species and source advantages. With the continuous deepening of research, studies have shown that many natural active components have broad-spectrum biological activities, such as antioxidant, antihypertensive, hypoglycemic, anti-inflammatory, antibacterial, anticancer, and enzyme-inhibiting activity properties, which are valuable sources of research and development in functional food factors and novel drugs. Systematical studies on the structure of components, physiological activities, the structure–activity relationship, and mechanisms of action for active components using modern scientific methods and experimental means are hot research topics. In addition, the exploration of the combined effect and mechanism of various natural bioactive substances will provide a theoretical basis for the further processing and comprehensive development of resources at multiple levels and from various points of view. This Special Issue of Foods, entitled “Structure Identification and Functional Mechanism of Natural Active Components”, provides a forum for researchers to communicate some of their latest findings in this field

Division of Research and Economic Development Annual Report for FY2005

Annual report for the Division of Research and Economic Development of the University of Rhode Island for the year 2004-2005. Includes statistics of project proposals, expenditures, URI Foundation Awards, previous annual report summaries and awards received by individual academic and administrative departments

Inhibiitorid ja fotoluminestsents-sondid proteiinkinaaside PKA ja PIM in vitro uuringuteks

Väitekirja elektrooniline versioon ei sisalda publikatsiooneProteiinkinaasid (PK-d) katalüüsivad valkude fosforüülimist. PK-de ebanormaalne aktiivsus rakkudes on korrelatsioonis keeruliste haigustega. Seetõttu teeb farmaatsiatööstus märkimisväärseid jõupingutusi, et reguleerida PK-de aktiivsust inhibiitoritega ja jälgida nende aktiivsust luminestsents-sondidega. Käesolevas töös kasutatud ARC-inhibiitorid on keemiliselt struktuurilt adenosiini matkivate heteroaromaatsete fragmentide ja peptiidide analoogide konjugaadid, neid ühendeid on pikemalt uuritud Tartu Ülikooli keemia instituudis. Käesolevas uuringus näidati, et PK PKA katalüütilise alaühiku α-isovormi (PKAcα) monoklonaalse antikeha (kloon D38C6) seondumine sihtvalguga on konkurentne ARC-Lum(Fluo) sondiga ja see antikeha inhibeerib substraadi fosforüülimist. Proovi järjestikust töötlemist nende konkureerivate PKAcα ligandidega kasutati tundliku AbARC immuunanalüüsi-meetodi väljatöötamiseks, mis võimaldas määrata väikseid koguseid (alates 93 pg) PKAcα rakulüsaatides. Hiljuti avastati Cushingi sündroomiga patsiendil S54L mutatsiooniga PRKACB geen. See mutatsioon viib PK glütsiinirikka aasa struktuuri muutumiseni. Käesolevas uuringus konstrueeriti muteerunud PK suhtes kuuekordse selektiivsusega inhibiitor. Lisaks töötati välja luminestsents-meetod PKAcβ-valgu kaubanduslike ja väljatöötatud inhibiitorite afiinsuse määramiseks. Koostöös Oxfordi ülikooliga viidi läbi ARC-inhibiitorite ja proteiinkinaasi PIM-1 komplekside röntgenstruktuuranalüüs. Saadud struktuurimudelitest lähtuvalt konstrueeriti lihtsustatud keemilise ehitusega ained. Uued inhibiitorid derivatiseeriti biotiiniga või fluorestsentsvärviga Cy5 ja neid aineid kasutati PIM-kinaasidetuvastamiseks biokeemilistes lahustes ja bioloogilistes proovides. Analüüsimeetod, milles kasutati ARC-sonde koos PIM-2-selektiivse antikehaga , võimaldas määrata sihtvalgu väikseid koguseid (alates 44 pg PIM-2). Konfokaalmikroskoopia abil tuvastati, et uued fluorestsents-sondid tungivad kiiresti U2OS-rakkudesse, kus nende paiknemine kattub PIM-1 ja fluorestsentsvalgu konjugaadi paiknemisega.Protein kinases (PKs) catalyze the phosphorylation of proteins. Abnormal activity of PKs in cells is correlated to complex diseases. Therefore, the pharma industry is making significant efforts to regulate the activity of PKs with inhibitors and to monitor the activity of PKs with luminescent probes. ARC inhibitors are conjugates of adenosine analogues and peptide mimetic moieties; they have been studied at length at the Institute of Chemistry of the University of Tartu. In the present study, it was shown that the binding of monoclonal antibody (clone D38C6) to α-isoform of the catalytic subunit of PKA (PKAcα) was competitive with binding of ARC-Lum(Fluo) probes. Sequential treatment of a sample with these competing PKAcα ligands was used to develop a sensitive AbARC immunoassay that allowed the determination of small amounts (from 93 pg) of PKAcα in cell lysates. Recently, PRKACB gene with the S54L mutation was discovered in a patient with the Cushing's syndrome. This mutation leads to a change in the structure of the glycine-rich loop of the PK. In the present study, an inhibitor with six-fold selectivity for the mutated PK was developed. In addition, a luminescence method was worked out for determination of affinity of both commercial and developed inhibitors of the PKAcβ protein. X-ray structure analysis of complexes of ARC inhibitors and PK PIM-1 was performed in collaboration with the University of Oxford. Based on the obtained structural models, compounds with simplified chemical structures were constructed. New inhibitors were derivatized with biotin or fluorescent dye Cy5 and applied for the detection of PIM PKs in biochemical solutions and complex biological samples. The sandwich assay utilizing a PIM-2-selective detection antibody featured a low limit of quantification (44 pg of PIM-2). A confocal microscopy study showed that the fluorescent probes were efficiently taken up by U2OS cells and the probes revealed high extent of co-localization with PIM-1-fused fluorescent proteins.https://www.ester.ee/record=b545989

Applications

Volume 3 describes how resource-aware machine learning methods and techniques are used to successfully solve real-world problems. The book provides numerous specific application examples: in health and medicine for risk modelling, diagnosis, and treatment selection for diseases in electronics, steel production and milling for quality control during manufacturing processes in traffic, logistics for smart cities and for mobile communications

Applications

Volume 3 describes how resource-aware machine learning methods and techniques are used to successfully solve real-world problems. The book provides numerous specific application examples: in health and medicine for risk modelling, diagnosis, and treatment selection for diseases in electronics, steel production and milling for quality control during manufacturing processes in traffic, logistics for smart cities and for mobile communications

The Interactive Question Protocol: Examining the Relationship Between Feedback, Cognitive Development and Student Achievement

Feedback is an essential component of effective learning. The advent of the internet as a delivery mode for distance education has expanded the access many people have to higher learning. Despite many advantages that online courses provide for distance learning students, they often lack real time feedback. A software intervention called the Interactive Question Protocol was designed for this study to provide automated, real time feedback. That treatment was then contrasted against changes in student achievement, satisfaction and participation. Learners can be categorized by Perry\u27s scheme of mental maturity according to how they understand and interpret the knowledge they acquire. Learners with low cognitive complexity levels are likely to appreciate basic automated feedback, while those with greater mental maturities are likely to be frustrated by a lack of true interaction. Therefore, Perry grouping was contrasted against changes in student achievement, satisfaction and participation for each subject. This study sought to discover if automated real time feedback had an effect on student achievement, participation and satisfaction. Similarly, it sought to discover if the same three variables were affected by cognitive complexity. Interactive effects between cognitive complexity and feedback treatment were also examined. No significant effects were found. The feedback treatment did not highlight group differences in achievement, satisfaction or participation. Group comparisons between the lower end of the cognitive complexity index scale also confirmed the null hypothesis. Sample sizes proved insufficient to compare subjects in Perry\u27s higher end groups 4 and 5. No interactive effects were found between independent variables. These findings do not refute the obvious value of feedback. Further studies may use a larger sample size to better compare Perry\u27s groups. More feedback complexity, along with the complexity of learning tasks may also be varied to investigate the impact of feedback on achievement, satisfaction and participation

D'ya like DAGs? A Survey on Structure Learning and Causal Discovery

Causal reasoning is a crucial part of science and human intelligence. In order to discover causal relationships from data, we need structure discovery methods. We provide a review of background theory and a survey of methods for structure discovery. We primarily focus on modern, continuous optimization methods, and provide reference to further resources such as benchmark datasets and software packages. Finally, we discuss the assumptive leap required to take us from structure to causality.Comment: 35 page

Protein function and inhibitor prediction by statistical learning approach

Ph.DDOCTOR OF PHILOSOPH