Search

Your search keyword '"Kozhevnikova, Mariya"' showing total 18 results
Start Over Author "Kozhevnikova, Mariya"
18 results on '"Kozhevnikova, Mariya"'

1. Blended Learning in Russian Higher Education: The Evolution of the Term in Science and Practice

Author

Strelchuk, Elena N., Kozhevnikova, Mariya N., and Borchenko, Victoria S.

Abstract

Background/purpose: The concept of "blended learning" was taken by Russian education from abroad. However, under the new conditions, the authors' original idea of combining different forms of learning has been transformed into a mixture of online and offline learning. This study aims to analyze the factors that led to the transformation of this concept in Russian research papers and the practice of teaching in universities. The observation method was necessary to describe how the term is applied and to draw conclusions about how it is understood by teachers. Materials/methods: The study is based on the comparative method, which includes a selection, description, and analysis of different interpretations of the studied concept in more than 90 Russian and foreign scientific publications. The results of the analysis are presented in diagrams, allowing consolidating a new point of view on the subject of research. Results: The study showed that Russian researchers understand "blended learning" as a combination of online and offline lessons, while the true meaning of the term is the combination of electronic learning tools with traditional face-to-face tools that can be used both synchronously and asynchronously. Conclusion: Prospects for the use of blended learning in Russian universities lie in the understanding that it is a special form of learning process, in which students interact either with a teacher or with an electronic learning resource, depending on what helps to achieve the learning objectives most effectively. This requires the development of new educational technology based on innovative software.

Published
2023

3. Generation of cell diversity in the developing brainstem and its modeling in vitro

Author

Kozhevnikova, Mariya and Kozhevnikova, Mariya

Abstract

The intersection of spatial and temporal patterning programs underlies the formation of neural cell type diversity in the developing central nervous system (CNS). Deciphering the molecular mechanisms regulating positional and temporal patterning provides a basic framework for how the developing brain can be functionally assembled, and the growing knowledge about these patterning mechanisms offer a powerful tool to effectively control the differentiation of pluripotent stem cells (PSCs) into different neuronal subtypes of clinical importance. The research described in this thesis is part of a continuing effort to define the molecular mechanisms that modulate the positional and temporal identity of immature neural stem cells (NSCs) and enables these to differentiate into specific subtypes of neurons at defined positions and over specific time-windows in the developing CNS. We have examined the sequential specification of motor neurons (MNs) and serotonergic neurons (5HTNs) by a Nkx2.2+ temporal lineage in the ventral hindbrain (HB) and outlined a three-node timer network that conceptually explains how time can be encoded by NSCs. Additionally, and unexpectedly, we show that timed exposure of retinoic acid (RA) can be applied to effectively pattern human PSC (hPSC)-derived neural progenitors into forebrain (FB), midbrain (MB), and HB regional identities. Based on this finding, we developed novel and robust differentiation protocols for production of mesencephalic dopaminergic (mDA) neurons and 5HTNs of the HB. We show that RA-specified human mDA neurons restore motor function after transplantation into a rat model of Parkinson’s disease (PD), and that mouse and human 5HTNs can be utilized as cellular platforms to screen small molecules for their capacity to modulate serotonin (5-HT) signaling in 5HTNs. In Paper I, we address how time is encoded by NSCs in temporal patterning processes in the CNS. We focused on a region in the ventral HB where NSCs, defined by expressio

Published
2022

7. EUNIS Habitat Classification: Expert system, characteristic species combinations and distribution maps of European habitats

Author

Chytrý, Milan, primary, Tichý, Lubomír, additional, Hennekens, Stephan M., additional, Knollová, Ilona, additional, Janssen, John A. M., additional, Rodwell, John S., additional, Peterka, Tomáš, additional, Marcenò, Corrado, additional, Landucci, Flavia, additional, Danihelka, Jiří, additional, Hájek, Michal, additional, Dengler, Jürgen, additional, Novák, Pavel, additional, Zukal, Dominik, additional, Jiménez‐Alfaro, Borja, additional, Mucina, Ladislav, additional, Abdulhak, Sylvain, additional, Aćić, Svetlana, additional, Agrillo, Emiliano, additional, Attorre, Fabio, additional, Bergmeier, Erwin, additional, Biurrun, Idoia, additional, Boch, Steffen, additional, Bölöni, János, additional, Bonari, Gianmaria, additional, Braslavskaya, Tatiana, additional, Bruelheide, Helge, additional, Campos, Juan Antonio, additional, Čarni, Andraž, additional, Casella, Laura, additional, Ćuk, Mirjana, additional, Ćušterevska, Renata, additional, De Bie, Els, additional, Delbosc, Pauline, additional, Demina, Olga, additional, Didukh, Yakiv, additional, Dítě, Daniel, additional, Dziuba, Tetiana, additional, Ewald, Jörg, additional, Gavilán, Rosario G., additional, Gégout, Jean‐Claude, additional, Giusso del Galdo, Gian Pietro, additional, Golub, Valentin, additional, Goncharova, Nadezhda, additional, Goral, Friedemann, additional, Graf, Ulrich, additional, Indreica, Adrian, additional, Isermann, Maike, additional, Jandt, Ute, additional, Jansen, Florian, additional, Jansen, Jan, additional, Jašková, Anni, additional, Jiroušek, Martin, additional, Kącki, Zygmunt, additional, Kalníková, Veronika, additional, Kavgacı, Ali, additional, Khanina, Larisa, additional, Yu. Korolyuk, Andrey, additional, Kozhevnikova, Mariya, additional, Kuzemko, Anna, additional, Küzmič, Filip, additional, Kuznetsov, Oleg L., additional, Laiviņš, Māris, additional, Lavrinenko, Igor, additional, Lavrinenko, Olga, additional, Lebedeva, Maria, additional, Lososová, Zdeňka, additional, Lysenko, Tatiana, additional, Maciejewski, Lise, additional, Mardari, Constantin, additional, Marinšek, Aleksander, additional, Napreenko, Maxim G., additional, Onyshchenko, Viktor, additional, Pérez‐Haase, Aaron, additional, Pielech, Remigiusz, additional, Prokhorov, Vadim, additional, Rašomavičius, Valerijus, additional, Rodríguez Rojo, Maria Pilar, additional, Rūsiņa, Solvita, additional, Schrautzer, Joachim, additional, Šibík, Jozef, additional, Šilc, Urban, additional, Škvorc, Željko, additional, Smagin, Viktor A., additional, Stančić, Zvjezdana, additional, Stanisci, Angela, additional, Tikhonova, Elena, additional, Tonteri, Tiina, additional, Uogintas, Domas, additional, Valachovič, Milan, additional, Vassilev, Kiril, additional, Vynokurov, Denys, additional, Willner, Wolfgang, additional, Yamalov, Sergey, additional, Evans, Douglas, additional, Palitzsch Lund, Mette, additional, Spyropoulou, Rania, additional, Tryfon, Eleni, additional, and Schaminée, Joop H. J., additional

Published
2020
Full Text
View/download PDF

8. EUNIS Habitat Classification: Expert system, characteristic species combinations and distribution maps of European habitats

Author

Schmidtlein, Sebastian, Chytry, Milan, Tichy, Lubomir, Hennekens, Stephan M., Knollová, Ilona, Janssen, John A. M., Rodwell, John S., Peterka, Tomáš, Marcenò, Corrado, Landucci, Flavia, Danihelka, Jiří, Hájek, Michal, Dengler, Jürgen, Novák, Pavel, Zukal, Dominik, Jiménez-Alfaro, Borja, Mucina, Ladislav, Abdulhak, Sylvain, Aćić, Svetlana, Agrillo, Emiliano, Attorre, Fabio, Bergmeier, Erwin, Biurrun, Idoia, Boch, Steffen, Bölöni, János, Bonari, Gianmaria, Braslavskaya, Tatiana, Bruelheide, Helge, Campos, Juan Antonio, Čarni, Andraž, Casella, Laura, Ćuk, Mirjana, Ćušterevska, Renata, de Bie, Els, Delbosc, Pauline, Demina, Olga, Didukh, Yakiv, Dítě, Daniel, Dziuba, Tetiana, Ewald, Jörg, Gavilán García, Rosario Gloria, Gégout, Jean-Claude, Giusso del Galdo, Gian Pietro, Golub, Valentin, Goncharova, Nadezhda, Goral, Friedemann, Graf, Ulrich, Indreica, Adrian, Isermann, Maike, Jandt, Ute, Jansen, Florian, Jansen, Jan, Jašková, Anni, Jiroušek, Martin, Kącki, Zygmunt, Kalníková, Veronika, Kavgacı, Ali, Khanina, Larisa, Yu. Korolyuk, Andrey, Kozhevnikova, Mariya, Kuzemko, Anna, Küzmič, Filip, Kuznetsov, Oleg L., Laiviņš, Māris, Lavrinenko, Igor, Lavrinenko, Olga, Lebedeva, Maria, Lososová, Zdeňka, Lysenko, Tatiana, Maciejewski, Lise, Mardari, Constantin, Marinšek, Aleksander, Napreenko, Maxim G., Onyshchenko, Viktor, Pérez-Haase, Aaron, Pielech, Remigiusz, Prokhorov, Vadim, Rašomavičius, Valerijus, Rodríguez Rojo, María Pilar, Rūsiņa, Solvita, Schrautzer, Joachim, Šibík, Jozef, Šilc, Urban, Škvorc, Željko, Smagin, Viktor A., Stančić, Zvjezdana, Stanisci, Angela, Tikhonova, Elena, Tonteri, Tiina, Uogintas, Domas, Valachovič, Milan, Vassilev, Kiril, Vynokurov, Denys, Willner, Wolfgang, Yamalov, Sergey, Evans, Douglas, Palitzsch Lund, Mette, Spyropoulou, Rania, Tryfon, Eleni, Schaminée, Joop H. J., Schmidtlein, Sebastian, Chytry, Milan, Tichy, Lubomir, Hennekens, Stephan M., Knollová, Ilona, Janssen, John A. M., Rodwell, John S., Peterka, Tomáš, Marcenò, Corrado, Landucci, Flavia, Danihelka, Jiří, Hájek, Michal, Dengler, Jürgen, Novák, Pavel, Zukal, Dominik, Jiménez-Alfaro, Borja, Mucina, Ladislav, Abdulhak, Sylvain, Aćić, Svetlana, Agrillo, Emiliano, Attorre, Fabio, Bergmeier, Erwin, Biurrun, Idoia, Boch, Steffen, Bölöni, János, Bonari, Gianmaria, Braslavskaya, Tatiana, Bruelheide, Helge, Campos, Juan Antonio, Čarni, Andraž, Casella, Laura, Ćuk, Mirjana, Ćušterevska, Renata, de Bie, Els, Delbosc, Pauline, Demina, Olga, Didukh, Yakiv, Dítě, Daniel, Dziuba, Tetiana, Ewald, Jörg, Gavilán García, Rosario Gloria, Gégout, Jean-Claude, Giusso del Galdo, Gian Pietro, Golub, Valentin, Goncharova, Nadezhda, Goral, Friedemann, Graf, Ulrich, Indreica, Adrian, Isermann, Maike, Jandt, Ute, Jansen, Florian, Jansen, Jan, Jašková, Anni, Jiroušek, Martin, Kącki, Zygmunt, Kalníková, Veronika, Kavgacı, Ali, Khanina, Larisa, Yu. Korolyuk, Andrey, Kozhevnikova, Mariya, Kuzemko, Anna, Küzmič, Filip, Kuznetsov, Oleg L., Laiviņš, Māris, Lavrinenko, Igor, Lavrinenko, Olga, Lebedeva, Maria, Lososová, Zdeňka, Lysenko, Tatiana, Maciejewski, Lise, Mardari, Constantin, Marinšek, Aleksander, Napreenko, Maxim G., Onyshchenko, Viktor, Pérez-Haase, Aaron, Pielech, Remigiusz, Prokhorov, Vadim, Rašomavičius, Valerijus, Rodríguez Rojo, María Pilar, Rūsiņa, Solvita, Schrautzer, Joachim, Šibík, Jozef, Šilc, Urban, Škvorc, Željko, Smagin, Viktor A., Stančić, Zvjezdana, Stanisci, Angela, Tikhonova, Elena, Tonteri, Tiina, Uogintas, Domas, Valachovič, Milan, Vassilev, Kiril, Vynokurov, Denys, Willner, Wolfgang, Yamalov, Sergey, Evans, Douglas, Palitzsch Lund, Mette, Spyropoulou, Rania, Tryfon, Eleni, and Schaminée, Joop H. J.

Abstract

Aim: The EUNIS Habitat Classification is a widely used reference framework for European habitat types (habitats), but it lacks formal definitions of individual habitats that would enable their unequivocal identification. Our goal was to develop a tool for assigning vegetation-plot records to the habitats of the EUNIS system, use it to classify a European vegetation-plot database, and compile statistically-derived characteristic species combinations and distribution maps for these habitats. Location: Europe. Methods: We developed the classification expert system EUNIS-ESy, which contains definitions of individual EUNIS habitats based on their species composition and geographic location. Each habitat was formally defined as a formula in a computer language combining algebraic and set-theoretic concepts with formal logical operators. We applied this expert system to classify 1,261,373 vegetation plots from the European Vegetation Archive (EVA) and other databases. Then we determined diagnostic, constant and dominant species for each habitat by calculating species-to-habitat fidelity and constancy (occurrence frequency) in the classified data set. Finally, we mapped the plot locations for each habitat. Results: Formal definitions were developed for 199 habitats at Level 3 of the EUNIS hierarchy, including 25 coastal, 18 wetland, 55 grassland, 43 shrubland, 46 forest and 12 man-made habitats. The expert system classified 1,125,121 vegetation plots to these habitat groups and 73,188 to other habitats, while 63,064 plots remained unclassified or were classified to more than one habitat. Data on each habitat were summarized in factsheets containing habitat description, distribution map, corresponding syntaxa and characteristic species combination. Conclusions: EUNIS habitats were characterized for the first time in terms of their species composition and distribution, based on a classification of a European database of vegetation plots using the newly developed electronic ex, Czech Science Foundation, Gobierno Vasco, Ministry of Science and Higher Education of the Russian Federation, European Environment Agency to Wageningen Environmental Research, Masaryk University, Depto. de Farmacología, Farmacognosia y Botánica, Fac. de Farmacia, TRUE, pub

Published
2020

9. EUNIS Habitat Classification: Expert system, characteristic species combinations and distribution maps of European habitats

Author

Chytrý, Milan, Tichý, Lubomír, Hennekens, Stephan M., Knollová, Ilona, Janssen, John A. M., Rodwell, John S., Peterka, Tomáš, Marcenò, Corrado, Landucci, Flavia, Danihelka, Jiří, Hájek, Michal, Dengler, Jürgen, Novák, Pavel, Zukal, Dominik, Jiménez-Alfaro, Borja, Mucina, Ladislav, Abdulhak, Sylvain, Aćić, Svetlana, Agrillo, Emiliano, Attorre, Fabio, Bergmeier, Erwin, Biurrun, Idoia, Boch, Steffen, Bölöni, János, Bonari, Gianmaria, Braslavskaya, Tatiana, Bruelheide, Helge, Campos, Juan Antonio, Čarni, Andraž, Casella, Laura, Cuk, Mirjana, Custerevska, Renata, De Bie, Els, Delbosc, Pauline, Demina, Olga, Didukh, Yakiv, Dítě, Daniel, Dziuba, Tetiana, Ewald, Jörg, Gavilán, Rosario G., Gégout, Jean-Claude, Giusso del Galdo, Gian Pietro, Golub, Valentin, Goncharova, Nadezhda, Goral, Friedemann, Graf, Ulrich, Indreica, Adrian, Isermann, Maike, Jandt, Ute, Jansen, Florian, Jansen, Jan, Jašková, Anni, Jiroušek, Martin, Kącki, Zygmunt, Kalníková, Veronika, Kavgacı, Ali, Khanina, Larisa, Yu. Korolyuk, Andrey, Kozhevnikova, Mariya, Kuzemko, Anna, Küzmič, Filip, Kuznetsov, Oleg L., Laiviņš, Māris, Lavrinenko, Igor, Lavrinenko, Olga, Lebedeva, Maria, Lososová, Zdeňka, Lysenko, Tatiana, Maciejewski, Lise, Mardari, Constantin, Marinšek, Aleksander, Napreenko, Maxim G., Onyshchenko, Viktor, Pérez-Haase, Aaron, Pielech, Remigiusz, Prokhorov, Vadim, Rašomavičius, Valerijus, Rodríguez Rojo, Maria Pilar, Rūsiņa, Solvita, Schrautzer, Joachim, Šibík, Jozef, Šilc, Urban, Škvorc, Željko, Smagin, Viktor A., Stančić, Zvjezdana, Stanisci, Angela, Tikhonova, Elena, Tonteri, Tiina, Uogintas, Domas, Valachovič, Milan, Vassilev, Kiril, Vynokurov, Denys, Willner, Wolfgang, Yamalov, Sergey, Evans, Douglas, Palitzsch Lund, Mette, Spyropoulou, Rania, Tryfon, Eleni, Schaminée, Joop, Chytrý, Milan, Tichý, Lubomír, Hennekens, Stephan M., Knollová, Ilona, Janssen, John A. M., Rodwell, John S., Peterka, Tomáš, Marcenò, Corrado, Landucci, Flavia, Danihelka, Jiří, Hájek, Michal, Dengler, Jürgen, Novák, Pavel, Zukal, Dominik, Jiménez-Alfaro, Borja, Mucina, Ladislav, Abdulhak, Sylvain, Aćić, Svetlana, Agrillo, Emiliano, Attorre, Fabio, Bergmeier, Erwin, Biurrun, Idoia, Boch, Steffen, Bölöni, János, Bonari, Gianmaria, Braslavskaya, Tatiana, Bruelheide, Helge, Campos, Juan Antonio, Čarni, Andraž, Casella, Laura, Cuk, Mirjana, Custerevska, Renata, De Bie, Els, Delbosc, Pauline, Demina, Olga, Didukh, Yakiv, Dítě, Daniel, Dziuba, Tetiana, Ewald, Jörg, Gavilán, Rosario G., Gégout, Jean-Claude, Giusso del Galdo, Gian Pietro, Golub, Valentin, Goncharova, Nadezhda, Goral, Friedemann, Graf, Ulrich, Indreica, Adrian, Isermann, Maike, Jandt, Ute, Jansen, Florian, Jansen, Jan, Jašková, Anni, Jiroušek, Martin, Kącki, Zygmunt, Kalníková, Veronika, Kavgacı, Ali, Khanina, Larisa, Yu. Korolyuk, Andrey, Kozhevnikova, Mariya, Kuzemko, Anna, Küzmič, Filip, Kuznetsov, Oleg L., Laiviņš, Māris, Lavrinenko, Igor, Lavrinenko, Olga, Lebedeva, Maria, Lososová, Zdeňka, Lysenko, Tatiana, Maciejewski, Lise, Mardari, Constantin, Marinšek, Aleksander, Napreenko, Maxim G., Onyshchenko, Viktor, Pérez-Haase, Aaron, Pielech, Remigiusz, Prokhorov, Vadim, Rašomavičius, Valerijus, Rodríguez Rojo, Maria Pilar, Rūsiņa, Solvita, Schrautzer, Joachim, Šibík, Jozef, Šilc, Urban, Škvorc, Željko, Smagin, Viktor A., Stančić, Zvjezdana, Stanisci, Angela, Tikhonova, Elena, Tonteri, Tiina, Uogintas, Domas, Valachovič, Milan, Vassilev, Kiril, Vynokurov, Denys, Willner, Wolfgang, Yamalov, Sergey, Evans, Douglas, Palitzsch Lund, Mette, Spyropoulou, Rania, Tryfon, Eleni, and Schaminée, Joop

Abstract

Contains fulltext : 222360.pdf (publisher's version ) (Open Access), Aim The EUNIS Habitat Classification is a widely used reference framework for European habitat types (habitats), but it lacks formal definitions of individual habitats that would enable their unequivocal identification. Our goal was to develop a tool for assigning vegetation-plot records to the habitats of the EUNIS system, use it to classify a European vegetation-plot database, and compile statistically-derived characteristic species combinations and distribution maps for these habitats. Location Europe. Methods We developed the classification expert system EUNIS-ESy, which contains definitions of individual EUNIS habitats based on their species composition and geographic location. Each habitat was formally defined as a formula in a computer language combining algebraic and set-theoretic concepts with formal logical operators. We applied this expert system to classify 1,261,373 vegetation plots from the European Vegetation Archive (EVA) and other databases. Then we determined diagnostic, constant and dominant species for each habitat by calculating species-to-habitat fidelity and constancy (occurrence frequency) in the classified data set. Finally, we mapped the plot locations for each habitat. Results Formal definitions were developed for 199 habitats at Level 3 of the EUNIS hierarchy, including 25 coastal, 18 wetland, 55 grassland, 43 shrubland, 46 forest and 12 man-made habitats. The expert system classified 1,125,121 vegetation plots to these habitat groups and 73,188 to other habitats, while 63,064 plots remained unclassified or were classified to more than one habitat. Data on each habitat were summarized in factsheets containing habitat description, distribution map, corresponding syntaxa and characteristic species combination. Conclusions EUNIS habitats were characterized for the first time in terms of their species composition and distribution, based on a classification of a European database of vegetation plots using the newly developed electroni

Published
2020

10. EUNIS Habitat Classification: Expert system, characteristic species combinations and distribution maps of European habitats

Author

Biología vegetal y ecología, Landaren biologia eta ekologia, Chytrý, Milan, Tichý, Lubomír, Hennekens, Stephan M., Knollová, Ilona, Janssen, John A. M., Rodwell, John S., Peterka, Tomáš, Marcenò, Corrado, Landucci, Flavia, Danihelka, Jiří, Hájek, Michal, Dengler, Jürgen, Novák, Pavel, Zukal, Dominik, Jiménez Alfaro, Borja, Mucina, Ladislav, Abdulhak, Sylvain, Aćić, Svetlana, Agrillo, Emiliano, Attorre, Fabio, Bergmeier, Erwin, Biurrun Galarraga, Miren Idoia, Boch, Steffen, Bölöni, János, Bonari, Gianmaria, Braslavskaya, Tatiana, Bruelheide, Helge, Campos Prieto, Juan Antonio, Čarni, Andraž, Casella, Laura, Ćuk, Mirjana, Ćušterevska, Renata, De Bie, Els, Delbosc, Pauline, Demina, Olga, Didukh, Yakiv, Dítě, Daniel, Dziuba, Tetiana, Ewald, Jörg, Gavilán, Rosario G., Gégout, Jean Claude, Giusso del Galdo, Gian Pietro, Golub, Valentin, Goncharova, Nadezhda, Goral, Friedemann, Graf, Ulrich, Indreica, Adrian, Isermann, Maike, Jandt, Ute, Jansen, Florian, Jansen, Jan, Jašková, Anni, Jiroušek, Martin, Kącki, Zygmunt, Kalníková, Veronika, Kavgacı, Ali, Khanina, Larisa, Korolyuk, Andrey Yu., Kozhevnikova, Mariya, Kuzemko, Anna, Küzmič, Filip, Kuznetsov, Oleg L., Laiviņš, Māris, Lavrinenko, Igor, Lavrinenko, Olga, Lebedeva, Maria, Lososová, Zdeňka, Lysenko, Tatiana, Maciejewski, Lise, Mardari, Constantin, Marinšek, Aleksander, Napreenko, Maxim G., Onyshchenko, Viktor, Pérez Haase, Aaron, Pielech, Remigiusz, Prokhorov, Vadim, Rašomavičius, Valerijus, Rodríguez Rojo, Maria Pilar, Rūsiņa, Solvita, Schrautzer, Joachim, Šibík, Jozef, Šilc, Urban, Škvorc, Željko, Smagin, Viktor A., Stančić, Zvjezdana, Stanisci, Angela, Tikhonova, Elena, Tonteri, Tiina, Uogintas, Domas, Valachovič, Milan, Vassilev, Kiril, Vynokurov, Denys, Willner, Wolfgang, Yamalov, Sergey, Evans, Douglas, Palitzsch Lund, Mette, Spyropoulou, Rania, Tryfon, Eleni, Schaminée, Joop H. J., Biología vegetal y ecología, Landaren biologia eta ekologia, Chytrý, Milan, Tichý, Lubomír, Hennekens, Stephan M., Knollová, Ilona, Janssen, John A. M., Rodwell, John S., Peterka, Tomáš, Marcenò, Corrado, Landucci, Flavia, Danihelka, Jiří, Hájek, Michal, Dengler, Jürgen, Novák, Pavel, Zukal, Dominik, Jiménez Alfaro, Borja, Mucina, Ladislav, Abdulhak, Sylvain, Aćić, Svetlana, Agrillo, Emiliano, Attorre, Fabio, Bergmeier, Erwin, Biurrun Galarraga, Miren Idoia, Boch, Steffen, Bölöni, János, Bonari, Gianmaria, Braslavskaya, Tatiana, Bruelheide, Helge, Campos Prieto, Juan Antonio, Čarni, Andraž, Casella, Laura, Ćuk, Mirjana, Ćušterevska, Renata, De Bie, Els, Delbosc, Pauline, Demina, Olga, Didukh, Yakiv, Dítě, Daniel, Dziuba, Tetiana, Ewald, Jörg, Gavilán, Rosario G., Gégout, Jean Claude, Giusso del Galdo, Gian Pietro, Golub, Valentin, Goncharova, Nadezhda, Goral, Friedemann, Graf, Ulrich, Indreica, Adrian, Isermann, Maike, Jandt, Ute, Jansen, Florian, Jansen, Jan, Jašková, Anni, Jiroušek, Martin, Kącki, Zygmunt, Kalníková, Veronika, Kavgacı, Ali, Khanina, Larisa, Korolyuk, Andrey Yu., Kozhevnikova, Mariya, Kuzemko, Anna, Küzmič, Filip, Kuznetsov, Oleg L., Laiviņš, Māris, Lavrinenko, Igor, Lavrinenko, Olga, Lebedeva, Maria, Lososová, Zdeňka, Lysenko, Tatiana, Maciejewski, Lise, Mardari, Constantin, Marinšek, Aleksander, Napreenko, Maxim G., Onyshchenko, Viktor, Pérez Haase, Aaron, Pielech, Remigiusz, Prokhorov, Vadim, Rašomavičius, Valerijus, Rodríguez Rojo, Maria Pilar, Rūsiņa, Solvita, Schrautzer, Joachim, Šibík, Jozef, Šilc, Urban, Škvorc, Željko, Smagin, Viktor A., Stančić, Zvjezdana, Stanisci, Angela, Tikhonova, Elena, Tonteri, Tiina, Uogintas, Domas, Valachovič, Milan, Vassilev, Kiril, Vynokurov, Denys, Willner, Wolfgang, Yamalov, Sergey, Evans, Douglas, Palitzsch Lund, Mette, Spyropoulou, Rania, Tryfon, Eleni, and Schaminée, Joop H. J.

Abstract

Aim The EUNIS Habitat Classification is a widely used reference framework for European habitat types (habitats), but it lacks formal definitions of individual habitats that would enable their unequivocal identification. Our goal was to develop a tool for assigning vegetation-plot records to the habitats of the EUNIS system, use it to classify a European vegetation-plot database, and compile statistically-derived characteristic species combinations and distribution maps for these habitats. Location Europe. Methods We developed the classification expert system EUNIS-ESy, which contains definitions of individual EUNIS habitats based on their species composition and geographic location. Each habitat was formally defined as a formula in a computer language combining algebraic and set-theoretic concepts with formal logical operators. We applied this expert system to classify 1,261,373 vegetation plots from the European Vegetation Archive (EVA) and other databases. Then we determined diagnostic, constant and dominant species for each habitat by calculating species-to-habitat fidelity and constancy (occurrence frequency) in the classified data set. Finally, we mapped the plot locations for each habitat. Results Formal definitions were developed for 199 habitats at Level 3 of the EUNIS hierarchy, including 25 coastal, 18 wetland, 55 grassland, 43 shrubland, 46 forest and 12 man-made habitats. The expert system classified 1,125,121 vegetation plots to these habitat groups and 73,188 to other habitats, while 63,064 plots remained unclassified or were classified to more than one habitat. Data on each habitat were summarized in factsheets containing habitat description, distribution map, corresponding syntaxa and characteristic species combination. Conclusions EUNIS habitats were characterized for the first time in terms of their species composition and distribution, based on a classification of a European database of vegetation plots using the newly developed electronic expert

Published
2020

11. EUNIS-ESy: Expert system for automatic classification of European vegetation plots to EUNIS habitats

Author

Chytrý, Milan, Tichý, Lubomír, Hennekens, Stephan M., Knollová, Ilona, Janssen, John A.M., Rodwell, John S., Peterka, Tomáš, Marcenò, Corrado, Landucci, Flavia, Danihelka, Jiří, Hájek, Michal, Dengler, Jürgen, Novák, Pavel, Zukal, Dominik, Jiménez-Alfaro, Borja, Mucina, Ladislav, Abdulhak, Sylvain, Aćić, Svetlana, Agrillo, Emiliano, Attorre, Fabio, Bergmeier, Erwin, Biurrun, Idoia, Boch, Steffen, Bölöni, János, Bonari, Gianmaria, Braslavskaya, Tatiana, Bruelheide, Helge, Campos, Juan Antonio, Čarni, Andraž, Casella, Laura, Ćuk, Mirjana, Ćušterevska, Renata, De Bie, Els, Delbosc, Pauline, Demina, Olga, Didukh, Yakiv, Dítě, Daniel, Dziuba, Tetiana, Ewald, Jörg, Gavilán, Rosario G., Gégout, Jean Claude, Giusso del Galdo, Gian Pietro, Golub, Valentin, Goncharova, Nadezhda, Goral, Friedemann, Graf, Ulrich, Indreica, Adrian, Isermann, Maike, Jandt, Ute, Jansen, Florian, Jansen, Jan, Jašková, Anni, Jiroušek, Martin, Kącki, Zygmunt, Kalníková, Veronika, Kavgacı, Ali, Khanina, Larisa, Yu. Korolyuk, Andrey, Kozhevnikova, Mariya, Kuzemko, Anna, Küzmič, Filip, Kuznetsov, Oleg L., Laiviņš, Māris, Lavrinenko, Igor, Lavrinenko, Olga, Lebedeva, Maria, Lososová, Zdeňka, Lysenko, Tatiana, Maciejewski, Lise, Mardari, Constantin, Marinšek, Aleksander, Napreenko, Maxim G., Onyshchenko, Viktor, Pérez-Haase, Aaron, Pielech, Remigiusz, Prokhorov, Vadim, Rašomavičius, Valerijus, Rodríguez Rojo, Maria Pilar, Rūsiņa, Solvita, Schrautzer, Joachim, Šibík, Jozef, Šilc, Urban, Škvorc, Željko, Smagin, Viktor A., Stančić, Zvjezdana, Stanisci, Angela, Tikhonova, Elena, Tonteri, Tiina, Uogintas, Domas, Valachovič, Milan, Vassilev, Kiril, Vynokurov, Denys, Willner, Wolfgang, Yamalov, Sergey, Evans, Douglas, Palitzsch Lund, Mette, Spyropoulou, Rania, Tryfon, Eleni, Schaminée, Joop H.J., Chytrý, Milan, Tichý, Lubomír, Hennekens, Stephan M., Knollová, Ilona, Janssen, John A.M., Rodwell, John S., Peterka, Tomáš, Marcenò, Corrado, Landucci, Flavia, Danihelka, Jiří, Hájek, Michal, Dengler, Jürgen, Novák, Pavel, Zukal, Dominik, Jiménez-Alfaro, Borja, Mucina, Ladislav, Abdulhak, Sylvain, Aćić, Svetlana, Agrillo, Emiliano, Attorre, Fabio, Bergmeier, Erwin, Biurrun, Idoia, Boch, Steffen, Bölöni, János, Bonari, Gianmaria, Braslavskaya, Tatiana, Bruelheide, Helge, Campos, Juan Antonio, Čarni, Andraž, Casella, Laura, Ćuk, Mirjana, Ćušterevska, Renata, De Bie, Els, Delbosc, Pauline, Demina, Olga, Didukh, Yakiv, Dítě, Daniel, Dziuba, Tetiana, Ewald, Jörg, Gavilán, Rosario G., Gégout, Jean Claude, Giusso del Galdo, Gian Pietro, Golub, Valentin, Goncharova, Nadezhda, Goral, Friedemann, Graf, Ulrich, Indreica, Adrian, Isermann, Maike, Jandt, Ute, Jansen, Florian, Jansen, Jan, Jašková, Anni, Jiroušek, Martin, Kącki, Zygmunt, Kalníková, Veronika, Kavgacı, Ali, Khanina, Larisa, Yu. Korolyuk, Andrey, Kozhevnikova, Mariya, Kuzemko, Anna, Küzmič, Filip, Kuznetsov, Oleg L., Laiviņš, Māris, Lavrinenko, Igor, Lavrinenko, Olga, Lebedeva, Maria, Lososová, Zdeňka, Lysenko, Tatiana, Maciejewski, Lise, Mardari, Constantin, Marinšek, Aleksander, Napreenko, Maxim G., Onyshchenko, Viktor, Pérez-Haase, Aaron, Pielech, Remigiusz, Prokhorov, Vadim, Rašomavičius, Valerijus, Rodríguez Rojo, Maria Pilar, Rūsiņa, Solvita, Schrautzer, Joachim, Šibík, Jozef, Šilc, Urban, Škvorc, Željko, Smagin, Viktor A., Stančić, Zvjezdana, Stanisci, Angela, Tikhonova, Elena, Tonteri, Tiina, Uogintas, Domas, Valachovič, Milan, Vassilev, Kiril, Vynokurov, Denys, Willner, Wolfgang, Yamalov, Sergey, Evans, Douglas, Palitzsch Lund, Mette, Spyropoulou, Rania, Tryfon, Eleni, and Schaminée, Joop H.J.

Abstract

EUNIS-ESy is an expert system for automatic classification of European vegetation plots to habitat types of the EUNIS Habitat Classification. The EUNIS classification and the principles of the expert system are described by Chytrý et al. (2020). The classification of a set of vegetation plots can be run using the JUICE program (Tichý 2002; https://www.sci.muni.cz/botany/juice/), TURBOVEG 3 program (Hennekens 2015) and an R script (Bruelheide et al. 2021). This dataset contains two parts: (1) the expert system and related files necessary for running it; (2) characterization of EUNIS habitats based on the results of the expert system classification., EUNIS-ESy is an expert system for automatic classification of European vegetation plots to habitat types of the EUNIS Habitat Classification. The EUNIS classification and the principles of the expert system are described by Chytrý et al. (2020). The classification of a set of vegetation plots can be run using the JUICE program (Tichý 2002; https://www.sci.muni.cz/botany/juice/), TURBOVEG 3 program (Hennekens 2015) and an R script (Bruelheide et al. 2021). This dataset contains two parts: (1) the expert system and related files necessary for running it; (2) characterization of EUNIS habitats based on the results of the expert system classification. 1. Expert system and related files necessary to run it 1.1. EUNIS-ESy-2021-06-01.txt – a file containing the script for the classification of vegetation plots by EUNIS-ESy. This version contains tested definitions for the revised classification vegetated Marine (coastal saltmarshes), Coastal, Wetland, Grassland, Shrubland, Forest, Inland sparsely vegetated and Man-made habitats, and preliminary non-tested definitions of the older classification of Marine, Aquatic and Inland sparsely vegetated habitats. 1.2. Nomenclature-translation-from-Turboveg-2-databases.zip – an archive containing the scripts for automatic translation of taxon concepts and names used in individual European Turboveg 2 databases (Hennekens & Schaminée 2001; https://www.synbiosys.alterra.nl/turboveg/) to the nomenclature that can be used as an input for EUNIS-ESy. 1.3. EUNIS-ESy-User-Guide.pdf – a brief user guide to the classification of vegetation plots by EUNIS-ESy using the JUICE program. Please read this guide carefully before running the expert system to avoid misclassifications. 2. Characterization of the EUNIS habitats based on the results of the EUNIS-ESy classification 2.1. EUNIS-habitats-2021-06-01.xlsx – the current list o

Published
2020

12. A Shh/Gli-driven three-node timer motif controls temporal identity and fate of neural stem cells

Author

Dias, José M., Alekseenko, Zhanna, Jeggari, Ashwini, Boareto do Amaral, Marcelo, Vollmer, Jannik, Kozhevnikova, Mariya, Wang, Hui, Matise, Michael P., Alexeyenko, Andrey, Iber, Dagmar, and Ericson, Johan

Abstract

How time is measured by neural stem cells during temporal neurogenesis has remained unresolved. By combining experiments and computational modelling, we here define a Shh/Gli-driven three-node timer underlying the sequential generation of motor neurons (MNs) and serotonergic neurons in the brainstem. The timer is founded on temporal decline of Gli-activator and Gli-repressor activities established through downregulation of Gli transcription. The circuitry conforms an incoherent feedforward loop, whereby Gli proteins promote expression of Phox2b and thereby MN-fate, but also account for a delayed activation of a self-promoting Tgfβ-node triggering a fate switch by repressing Phox2b. Hysteresis and spatial averaging by diffusion of Tgfβ counteracts noise and increases temporal accuracy at the population level. Our study defines how time is reliably encoded during the sequential specification of neurons., bioRxiv

Published
2019
Full Text
View/download PDF

14. In vitro generation of motor neuron precursors from mouse embryonic stem cells using mesoporous nanoparticles

Author

Garcia-Bennett, Alfonso, König, Niclas, Abrahamsson, Ninnie, Kozhevnikova, Mariya, Zhou, Chunfang, Trolle, Carl, Pankratova, Stanislava, Berezin, Vladimir, Kozlova, Elena, Garcia-Bennett, Alfonso, König, Niclas, Abrahamsson, Ninnie, Kozhevnikova, Mariya, Zhou, Chunfang, Trolle, Carl, Pankratova, Stanislava, Berezin, Vladimir, and Kozlova, Elena

Abstract

Aim: Stem cell-derived motor neurons (MNs) are utilized to develop replacement strategies for spinal cord disorders. Differentiation of embryonic stem cells into MN precursors involves factors and their repeated administration. We investigated if delivery of factors loaded into mesoporous nanoparticles could be effective for stem cell differentiation in vitro. Materials & methods: We used a mouse embryonic stem cell line expressing green fluorescent protein under the promoter for the MN-specific gene Hb9 to visualize the level of MN differentiation. The differentiation of stem cells was evaluated by expression of MN-specific transcription factors monitored by quantitative real-time PCR reactions and immunocytochemistry. Results: Mesoporous nanoparticles have strong affiliation to the embryoid bodies, penetrate inside the embryoid bodies and come in contact with differentiating cells. Conclusion: Repeated administration of soluble factors into a culture medium can be avoided due to a sustained release effect using mesoporous silica., De 2 förstaförfattarna delar förstaförfattarskapet

Published
2014
Full Text
View/download PDF

15. Delivery of Differentiation Factors by Mesoporous Silica Particles Assists Advanced Differentiation of Transplanted Murine Embryonic Stem Cells

Author

Garcia-Bennett, Alfonso E., Kozhevnikova, Mariya, König, Niclas, Zhou, Chunfang, Leao, Richardson, Knöpfel, Thomas, Pankratova, Stanislava, Trolle, Carl, Berezin, Vladimir, Bock, Elisabeth, Aldskogius, Håkan, Kozlova, Elena N., Garcia-Bennett, Alfonso E., Kozhevnikova, Mariya, König, Niclas, Zhou, Chunfang, Leao, Richardson, Knöpfel, Thomas, Pankratova, Stanislava, Trolle, Carl, Berezin, Vladimir, Bock, Elisabeth, Aldskogius, Håkan, and Kozlova, Elena N.

Abstract

Stem cell transplantation holds great hope for the replacement of damaged cells in the nervous system. However, poor long-term survival after transplantation and insufficiently robust differentiation of stem cells into specialized cell types in vivo remain major obstacles for clinical application. Here, we report the development of a novel technological approach for the local delivery of exogenous trophic factor mimetics to transplanted cells using specifically designed silica nanoporous particles. We demonstrated that delivering Cintrofin and Gliafin, established peptide mimetics of the ciliary neurotrophic factor and glial cell line-derived neurotrophic factor, respectively, with these particles enabled not only robust functional differentiation of motor neurons from transplanted embryonic stem cells but also their long-term survival in vivo. We propose that the delivery of growth factors by mesoporous nanoparticles is a potentially versatile and widely applicable strategy for efficient differentiation and functional integration of stem cell derivatives upon transplantation., De 3 första författarna delar förstaförfattarskapet

Published
2013
Full Text
View/download PDF

16. Delivery of differentiation factors by mesoporous silica particles assists advanced differentiation of transplanted murine embryonic stem cells

Author

Garcia-Bennett, Alfonso E, Kozhevnikova, Mariya, König, Niclas, Zhou, Chunfang, Leao, Richardson, Knöpfel, Thomas, Pankratova, Stanislava, Trolle, Carl, Berezin, Vladimir, Bock, Elisabeth, Aldskogius, Håkan, Kozlova, Elena N, Garcia-Bennett, Alfonso E, Kozhevnikova, Mariya, König, Niclas, Zhou, Chunfang, Leao, Richardson, Knöpfel, Thomas, Pankratova, Stanislava, Trolle, Carl, Berezin, Vladimir, Bock, Elisabeth, Aldskogius, Håkan, and Kozlova, Elena N

Abstract

Stem cell transplantation holds great hope for the replacement of damaged cells in the nervous system. However, poor long-term survival after transplantation and insufficiently robust differentiation of stem cells into specialized cell types in vivo remain major obstacles for clinical application. Here, we report the development of a novel technological approach for the local delivery of exogenous trophic factor mimetics to transplanted cells using specifically designed silica nanoporous particles. We demonstrated that delivering Cintrofin and Gliafin, established peptide mimetics of the ciliary neurotrophic factor and glial cell line-derived neurotrophic factor, respectively, with these particles enabled not only robust functional differentiation of motor neurons from transplanted embryonic stem cells but also their long-term survival in vivo. We propose that the delivery of growth factors by mesoporous nanoparticles is a potentially versatile and widely applicable strategy for efficient differentiation and functional integration of stem cell derivatives upon transplantation.

Published
2013

17. Delivery of Differentiation Factors by Mesoporous Silica Particles Assists Advanced Differentiation of Transplanted Murine Embryonic Stem Cells

Author

Garcia-Bennett, Alfonso E., primary, Kozhevnikova, Mariya, additional, König, Niclas, additional, Zhou, Chunfang, additional, Leao, Richardson, additional, Knöpfel, Thomas, additional, Pankratova, Stanislava, additional, Trolle, Carl, additional, Berezin, Vladimir, additional, Bock, Elisabeth, additional, Aldskogius, Håkan, additional, and Kozlova, Elena N., additional

Published
2013
Full Text
View/download PDF

18. EUNIS Habitat Classification : expert system, characteristic species combinations and distribution maps of European habitats

Author

Chytrý, Milan, Tichý, Lubomír, Hennekens, Stephan M., Knollová, Ilona, Janssen, John A. M., Rodwell, John S., Peterka, Tomáš, Marcenò, Corrado, Landucci, Flavia, Danihelka, Jiří, Hájek, Michal, Dengler, Jürgen, Novák, Pavel, Zukal, Dominik, Jiménez‐Alfaro, Borja, Mucina, Ladislav, Abdulhak, Sylvain, Aćić, Svetlana, Agrillo, Emiliano, Attorre, Fabio, Bergmeier, Erwin, Biurrun, Idoia, Boch, Steffen, Bölöni, János, Bonari, Gianmaria, Braslavskaya, Tatiana, Bruelheide, Helge, Campos, Juan Antonio, Čarni, Andraž, Casella, Laura, Ćuk, Mirjana, Ćušterevska, Renata, De Bie, Els, Delbosc, Pauline, Demina, Olga, Didukh, Yakiv, Dítě, Daniel, Dziuba, Tetiana, Ewald, Jörg, Gavilán, Rosario G., Gégout, Jean‐Claude, Giusso del Galdo, Gian Pietro, Golub, Valentin, Goncharova, Nadezhda, Goral, Friedemann, Graf, Ulrich, Indreica, Adrian, Isermann, Maike, Jandt, Ute, Jansen, Florian, Jansen, Jan, Jašková, Anni, Jiroušek, Martin, Kącki, Zygmunt, Kalníková, Veronika, Kavgacı, Ali, Khanina, Larisa, Yu. Korolyuk, Andrey, Kozhevnikova, Mariya, Kuzemko, Anna, Küzmič, Filip, Kuznetsov, Oleg L., Laiviņš, Māris, Lavrinenko, Igor, Lavrinenko, Olga, Lebedeva, Maria, Lososová, Zdeňka, Lysenko, Tatiana, Maciejewski, Lise, Mardari, Constantin, Marinšek, Aleksander, Napreenko, Maxim G., Onyshchenko, Viktor, Pérez‐Haase, Aaron, Pielech, Remigiusz, Prokhorov, Vadim, Rašomavičius, Valerijus, Rodríguez Rojo, Maria Pilar, Rūsiņa, Solvita, Schrautzer, Joachim, Šibík, Jozef, Šilc, Urban, Škvorc, Željko, Smagin, Viktor A., Stančić, Zvjezdana, Stanisci, Angela, Tikhonova, Elena, Tonteri, Tiina, Uogintas, Domas, Valachovič, Milan, Vassilev, Kiril, Vynokurov, Denys, Willner, Wolfgang, Yamalov, Sergey, Evans, Douglas, Palitzsch Lund, Mette, Spyropoulou, Rania, Tryfon, Eleni, and Schaminée, Joop H. J.

Subjects
Coastal habitat, Distribution map, 15. Life on land, Dune vegetation, Grassland, Habitat classification, Vegetation plot, Shrubland, Diagnostic species, Man‐made habitat, Vegetation database, Wetland, 14. Life underwater, Forest, 577: Ökologie, European Nature Information System (EUNIS), Expert system, European Vegetation Archive (EVA)
Abstract

Aim: The EUNIS Habitat Classification is a widely used reference framework for European habitat types (habitats), but it lacks formal definitions of individual habitats that would enable their unequivocal identification. Our goal was to develop a tool for assigning vegetation-plot records to the habitats of the EUNIS system, use it to classify a European vegetation-plot database, and compile statistically-derived characteristic species combinations and distribution maps for these habitats. Location: Europe. Methods: We developed the classification expert system EUNIS-ESy, which contains definitions of individual EUNIS habitats based on their species composition and geographic location. Each habitat was formally defined as a formula in a computer language combining algebraic and set-theoretic concepts with formal logical operators. We applied this expert system to classify 1,261,373 vegetation plots from the European Vegetation Archive (EVA) and other databases. Then we determined diagnostic, constant and dominant species for each habitat by calculating species-to-habitat fidelity and constancy (occurrence frequency) in the classified data set. Finally, we mapped the plot locations for each habitat. Results: Formal definitions were developed for 199 habitats at Level 3 of the EUNIS hierarchy, including 25 coastal, 18 wetland, 55 grassland, 43 shrubland, 46 forest and 12 man-made habitats. The expert system classified 1,125,121 vegetation plots to these habitat groups and 73,188 to other habitats, while 63,064 plots remained unclassified or were classified to more than one habitat. Data on each habitat were summarized in factsheets containing habitat description, distribution map, corresponding syntaxa and characteristic species combination. Conclusions: EUNIS habitats were characterized for the first time in terms of their species composition and distribution, based on a classification of a European database of vegetation plots using the newly developed electronic expert system EUNISESy. The data provided and the expert system have considerable potential for future use in European nature conservation planning, monitoring and assessment.

Catalog

Books, media, physical & digital resources
See catalog results