301. DNA vakcine za zdravljenje rakaŠpela Kos, Gregor Serša, 2019, professional article Abstract: DNA vakcine predstavljajo obetaven pristop imunoterapije raka, predvsem zaradi njihove enostavnosti, stabilnosti in varnosti. DNA vakcine temeljijo na vnosu plazmidne DNA z zapisom za enega ali več tumorskih antigenov, udeleženih v nastanku, napredovanju ali zasevanju rakavih celic. Z vnosom DNA vakcine spodbudimo imunski odziv usmerjen proti tumorskemu antigenu, kar potencialno vodi do uničenja rakavih celic. Kljub številnim prednostim DNA vakcin pred klasičnimi vakcinami njihovo uporabo v humani kliniki omejuje prešibak antigen-specifični imunski odziv. Za izboljšanje imunogenosti DNA vakcin se razvoj osredotoča na optimizacijo sestave plazmidne DNA, raziskovanje novih tumorskih antigenov, razvoj novih dostavnih sistemov in sočasna uporaba adjuvantnih in imunomodulatornih molekul. Tovrstni pristopi so del številnih kliničnih raziskav na področju imunoterapije raka in predstavljajo korak bližje k izboljšanju imunogenosti DNA vakcin, učinkovitejšemu uničenju rakavih celic in lažjemu prenosu DNA vakcinacije v humano klinično prakso.
Keywords: DNK vakcine, dostavni sistemi, tumorski antigeni, imunogenost
Published in DiRROS: 26.06.2019; Views: 2556; Downloads: 686
 Full text (310,15 KB) |
302. Priporočila za obravnavo bolnikov z bazalnoceličnim karcinomomUroš Ahčan, Igor Bartenjev, Ana Benedičič, Tomi Bremec, Aleksandra Vučinič Dugonik, Aleš Grošelj, Nataša Grebenšek, Marko Hočevar, Boris Jančar, Boštjan Luzar, Liljana Mervic, Janja Ocvirk, Jože Pižem, Mirjam Rogl-Butina, Tanja Planinšek Ručigaj, Gregor Serša, Larisa Stojanovič, Neža Stopajnik, Primož Strojan, Vesna Tlaker Žunter, Borut Žgavec, 2019, professional article Keywords: bazalnocelični karcinom, bolniki, smernice zdravljenja, kožni rak
Published in DiRROS: 26.06.2019; Views: 2918; Downloads: 894
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304. Pomen kliničnih raziskav za bolnike z rakom : priročnik za bolnike z rakom2005, dictionary, encyclopaedia, lexicon, manual, atlas, map Abstract: Priročnik je namenjen onkološkim bolnikom, njihovim družinam in prijateljem. Pomagal jim bo razumeti , kaj klinične raziskave pravzaprav so, kako so zasnovane in kako potekajo.
Published in DiRROS: 25.03.2019; Views: 1955; Downloads: 487
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309. A comparison of models for forecasting the residential natural gas demand of an urban areaRok Hribar, Primož Potočnik, Jurij Šilc, Gregor Papa, 2019, original scientific article Abstract: Forecasting the residential natural gas demand for large groups of buildings is extremely important for efficient logistics in the energy sector. In this paper different forecast models for residential natural gas demand of an urban area were implemented and compared. The models forecast gas demand with hourly resolution up to 60 h into the future. The model forecasts are based on past temperatures, forecasted temperatures and time variables, which include markers for holidays and other occasional events. The models were trained and tested on gas-consumption data gathered in the city of Ljubljana, Slovenia. Machine-learning models were considered, such as linear regression, kernel machine and artificial neural network. Additionally, empirical models were developed based on data analysis. Two most accurate models were found to be recurrent neural network and linear regression model. In realistic setting such trained models can be used in conjunction with a weather-forecasting service to generate forecasts for future gas demand.
Keywords: demand forecasting, buildings, energy modeling, forecast accuracy, machine learning
Published in DiRROS: 15.03.2019; Views: 2324; Downloads: 1086
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