Zobrazeno 1 - 10
of 26
pro vyhledávání: '"Mette Rose, Jørgensen"'
Autor:
Peter Østrup Jensen, Pernille Dukanovic Rikvold, Kristine Røn Larsen, Mette Rose Jørgensen, Camilla Kragelund
Publikováno v:
International Journal of Dentistry, Vol 2023 (2023)
Aim. There is need of an objective “standard procedure” that is reliable and clinically applicable for estimating oral neutrophil content in relation to oral diseases. Methods. Forty-one patients with suspected oral candidosis (OC) and nine healt
Externí odkaz:
https://doaj.org/article/9234a9e3d43f479aa0d2b0160fe715b7
Autor:
Mette Rose Jørgensen, Pernille Thestrup Rikvold, Mads Lichtenberg, Peter Østrup Jensen, Camilla Kragelund, Svante Twetman
Publikováno v:
Journal of Oral Microbiology, Vol 12, Iss 1 (2020)
Background: Intake of probiotic bacteria may prevent oral Candida infection. Objective: To screen the antifungal activity of 14 Lactobacillus candidate strains of human origin, against six opportunistic C. albicans and non-albicans species. A second
Externí odkaz:
https://doaj.org/article/10dd426d3acf4048b39e255ebca16096
Autor:
Svante Twetman, Mette Rose Jørgensen
Publikováno v:
Aktuel Nordisk Odontologi. 47:71-87
Autor:
Mette Rose Jørgensen, Camilla Kragelund, Peter Østrup Jensen, Mette Kirstine Keller, Svante Twetman
Publikováno v:
Journal of Oral Microbiology, Vol 9, Iss 1 (2017)
Background: An alternative approach for managing Candida infections in the oral cavity by modulating the oral microbiota with probiotic bacteria has been proposed. Objective: The aim was to investigate the antifungal potential of the probiotic bacter
Externí odkaz:
https://doaj.org/article/9b2328bb2532463f98376b05581358d1
Autor:
Mette Rose Jørgensen, Svante Twetman
Publikováno v:
Beneficial microbes. 12(3)
The aim of this study was to explore the preventive effect of probiotic supplements on the development of early childhood caries (ECC). We searched the PubMed, Google Scholar and Cochrane databases up to January 15, 2021. The authors screened the hit
Autor:
Mette Rose Jørgensen, Svante Twetman
Publikováno v:
Probiotic Research in Therapeutics ISBN: 9789813362352
The evolving understanding that the oral diseases are preventable by modulation of the oral biofilm has paved the way for the use of beneficial bacteria in dentistry. The main oral diseases, dental caries and periodontitis, result from an ecological
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cd04b5db943037c26f80352aa4683ed4
https://doi.org/10.1007/978-981-33-6236-9_11
https://doi.org/10.1007/978-981-33-6236-9_11
Autor:
Adam Baker, Mette Rose Jørgensen, Malue Wielje, Dennis Sandris Nielsen, Marianne Stage, Yun Chen, Albin Sandelin, Natalia Ivonne Vera-Jimenéz, Anita Wichmann
Publikováno v:
Appl Environ Microbiol
Lactobacillus rhamnosus GG is one of the most widely marketed and studied probiotic strains. In L. rhamnosus GG, the spaCBA-srtC1 gene cluster encodes pili, which are important for some of the probiotic properties of the strain. A previous study show
Autor:
Jakob Hjorth von Stemann, Christian Brieghel, Bruno Ledergerber, Christen Lykkegaard Andersen, Michael A. E. Andersen, Jasmin Bahlo, Cameron Ross MacPherson, Alexander T. Pearson, Jens D Lundgren, Magnus Fontes, Rudi Agius, Michael Hallek, Man-Hung Eric Tang, Carsten Utoft Niemann, Jan Larsen, Jacob Bergstedt, Mette Rose Jørgensen, Yoram Louzoun, Carmen D. Herling, Alessandro Cozzi-Lepri
Publikováno v:
Nature Communications
Nature Communications, Vol 11, Iss 1, Pp 1-17 (2020)
Agius, R, Brieghel, C, Andersen, M A, Pearson, A T, Ledergerber, B, Cozzi-Lepri, A, Louzoun, Y, Andersen, C L, Bergstedt, J, von Stemann, J H, Jørgensen, M, Tang, M H E, Fontes, M, Bahlo, J, Herling, C D, Hallek, M, Lundgren, J, MacPherson, C R, Larsen, J & Niemann, C U 2020, ' Machine learning can identify newly diagnosed patients with CLL at high risk of infection ', Nature Communications, vol. 11, no. 1, 363 . https://doi.org/10.1038/s41467-019-14225-8
Agius, R, Brieghel, C, Andersen, M A, Pearson, A T, Ledergerber, B, Cozzi-Lepri, A, Louzoun, Y, Andersen, C L, Bergstedt, J, von Stemann, J H, Jørgensen, M, Tang, M-H E, Fontes, M, Bahlo, J, Herling, C D, Hallek, M, Lundgren, J, MacPherson, C R, Larsen, J & Niemann, C U 2020, ' Machine learning can identify newly diagnosed patients with CLL at high risk of infection ', Nature Communications, vol. 11, no. 1, 363 . https://doi.org/10.1038/s41467-019-14225-8
Nature Communications, Vol 11, Iss 1, Pp 1-17 (2020)
Agius, R, Brieghel, C, Andersen, M A, Pearson, A T, Ledergerber, B, Cozzi-Lepri, A, Louzoun, Y, Andersen, C L, Bergstedt, J, von Stemann, J H, Jørgensen, M, Tang, M H E, Fontes, M, Bahlo, J, Herling, C D, Hallek, M, Lundgren, J, MacPherson, C R, Larsen, J & Niemann, C U 2020, ' Machine learning can identify newly diagnosed patients with CLL at high risk of infection ', Nature Communications, vol. 11, no. 1, 363 . https://doi.org/10.1038/s41467-019-14225-8
Agius, R, Brieghel, C, Andersen, M A, Pearson, A T, Ledergerber, B, Cozzi-Lepri, A, Louzoun, Y, Andersen, C L, Bergstedt, J, von Stemann, J H, Jørgensen, M, Tang, M-H E, Fontes, M, Bahlo, J, Herling, C D, Hallek, M, Lundgren, J, MacPherson, C R, Larsen, J & Niemann, C U 2020, ' Machine learning can identify newly diagnosed patients with CLL at high risk of infection ', Nature Communications, vol. 11, no. 1, 363 . https://doi.org/10.1038/s41467-019-14225-8
Infections have become the major cause of morbidity and mortality among patients with chronic lymphocytic leukemia (CLL) due to immune dysfunction and cytotoxic CLL treatment. Yet, predictive models for infection are missing. In this work, we develop
Publikováno v:
Aktuel Nordisk Odontologi. 43:144-167
Autor:
Mette Rose Jørgensen, Svante Twetman
Publikováno v:
European archives of paediatric dentistry : official journal of the European Academy of Paediatric Dentistry. 21(2)
To evaluate the accuracy of commonly advocated caries risk assessment (CRA) tools in preschool children and to search for evidence whether or not this process provides better oral care and less caries in the future. As an update of a previous systema