Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Anna Agakova"'
Autor:
John A. McKnight, Frano Vučković, Helen M. Colhoun, Alan W. Patrick, Gordan Lauc, Paul M. McKeigue, Sandeep Thekkepat, Sandra MacRury, Andrew Collier, Olga Gornik, Anna Agakova, Stuart J. McGurnaghan, Fiona Green, John R. Petrie, Mairead L. Bermingham, Irena Trbojević-Akmačić, Felix Agakov, Marco Colombo, Caroline Hayward, Luke A K Blackbourn, Maja Pučić Baković, Lucija Klaric, John Chalmers, Robert S. Lindsay, Colin N. A. Palmer
Publikováno v:
2018, ' N-glycan Profile and Kidney Disease in Type 1 Diabetes ', Diabetes Care . https://doi.org/10.2337/dc17-1042
OBJECTIVE Poorer glycemic control in type 1 diabetes may alter N-glycosylation patterns on circulating glycoproteins, and these alterations may be linked with diabetic kidney disease (DKD). We investigated associations between N-glycans and glycemic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::859950b438b86d04786cb7bc8c1d1b0e
https://www.pure.ed.ac.uk/ws/files/45342602/SDRNT1BIO_N_Glycan_Paper_Diabetes_Care_2017R1.docx
https://www.pure.ed.ac.uk/ws/files/45342602/SDRNT1BIO_N_Glycan_Paper_Diabetes_Care_2017R1.docx
Autor:
Anna Agakova, Christophe Sarran, Hilary Pinnock, Christopher R Burton, Felix Agakov, Peter Orchard, Brian McKinstry
Publikováno v:
Journal of Medical Internet Research
Orchard, P, Agakova, A, Pinnock, H, Burton, C D, Sarran, C, Agakov, F & McKinstry, B 2018, ' Improving Prediction of Risk of Hospital Admission in Chronic Obstructive Pulmonary Disease : Application of Machine Learning to Telemonitoring Data ', Journal of medical Internet research, vol. 20, no. 9, pp. e263 . https://doi.org/10.2196/jmir.9227
Orchard, P, Agakova, A, Pinnock, H, Burton, C D, Sarran, C, Agakov, F & McKinstry, B 2018, ' Improving Prediction of Risk of Hospital Admission in Chronic Obstructive Pulmonary Disease : Application of Machine Learning to Telemonitoring Data ', Journal of medical Internet research, vol. 20, no. 9, pp. e263 . https://doi.org/10.2196/jmir.9227
Background Telemonitoring of symptoms and physiological signs has been suggested as a means of early detection of chronic obstructive pulmonary disease (COPD) exacerbations, with a view to instituting timely treatment. However, algorithms to identify
Autor:
Peter Orchard, Anna Agakova, Hilary Pinnock, Christopher David Burton, Christophe Sarran, Felix Agakov, Brian McKinstry
BACKGROUND Telemonitoring of symptoms and physiological signs has been suggested as a means of early detection of exacerbations of chronic obstructive pulmonary disease (COPD) with a view to instituting timely treatment. However, current algorithms t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::35126cac9d067d58c9029e4aadb41e12
https://doi.org/10.2196/preprints.9227
https://doi.org/10.2196/preprints.9227
Publikováno v:
Methods in molecular biology (Clifton, N.J.). 1503
Ultra-performance liquid chromatography (UPLC) is the established technology for accurate analysis of IgG Fc N-glycosylation due to its superior sensitivity, resolution, speed, and its capability to provide branch-specific information of glycan speci
Autor:
Stuart Anderson, Felix Agakov, Anna Agakova, Brian McKinstry, Peter Orchard, Mary Paterson, Christopher R Burton, Lucy McCloughan, Hilary Pinnock
Publikováno v:
Pinnock, H, Agakov, F, Orchard, P, Agakova, A, Paterson, M, McCloughan, C, Burton, C, Anderson, S & McKinstry, B 2016, ' Learning to Care: using machine learning to improve prediction of COPD admissions ', 45th Annual Scientific Meeting of the SAPC, Wednesday 6th to Friday 8th July 2016, hosted by RCSI at Dublin Castle., Dublin, United Kingdom, 6/07/16-8/07/16 .
The problemTelehealth aims to predict exacerbations in order to facilitate prompt action to prevent admissions. However, recent randomised trials fail to demonstrate reductions in admissions when telehealth is applied. The systems under trial also ca
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::33bc5a0e38c0187f0a57a80d2066c8e8
https://www.pure.ed.ac.uk/ws/files/25516859/Abstract_LTC_SAPCfinal.docx
https://www.pure.ed.ac.uk/ws/files/25516859/Abstract_LTC_SAPCfinal.docx
Autor:
Felix Agakov, Jerko Štambuk, Evropi Theodoratou, Ewan Brown, Anna Agakova, Pauline M. Rudd, Maja Pučić-Baković, Kujtim Thaçi, Peter Orchard, Harry Campbell, Malcolm G. Dunlop, Frano Vučković, Farhat V N Din, Maria Timofeeva, Susan M. Farrington, Gordan Lauc
Publikováno v:
Scientific Reports
Theodoratou, E, Thaci, K, Agakov, F, Timofeeva, M, Stambuk, J, Pucic-Bakovic, M, Vuckovic, F, Orchard, P, Agakova, A, Din, F V N, Brown, E, Rudd, P M, Farrington, S M, Dunlop, M G, Campbell, H & Lauc, G 2016, ' Glycosylation of plasma IgG in colorectal cancer prognosis ', Scientific Reports . https://doi.org/10.1038/srep28098
Theodoratou, E, Thaci, K, Agakov, F, Timofeeva, M, Stambuk, J, Pucic-Bakovic, M, Vuckovic, F, Orchard, P, Agakova, A, Din, F V N, Brown, E, Rudd, P M, Farrington, S M, Dunlop, M G, Campbell, H & Lauc, G 2016, ' Glycosylation of plasma IgG in colorectal cancer prognosis ', Scientific Reports . https://doi.org/10.1038/srep28098
In this study we demonstrate the potential value of Immunoglobulin G (IgG) glycosylation as a novel prognostic biomarker of colorectal cancer (CRC). We analysed plasma IgG glycans in 1229 CRC patients and correlated with survival outcomes. We assesse