Weaning practices in phenylketonuria vary between health professionals in Europe

Autor: A. Pinto, S. Adams, K. Ahring, H. Allen, M.F. Almeida, D. Garcia-Arenas, N. Arslan, M. Assoun, Y. Atik Altınok, D. Barrio-Carreras, A. Belanger Quintana, S.M. Bernabei, C. Bontemps, F. Boyle, G. Bruni, M. Bueno-Delgado, G. Caine, R. Carvalho, A. Chrobot, K. Chyż, B. Cochrane, C. Correia, K. Corthouts, A. Daly, S. De Leo, A. Desloovere, A. De Meyer, A. De Theux, B. Didycz, M.E. Dijsselhof, K. Dokoupil, J. Drabik, C. Dunlop, W. Eberle-Pelloth, K. Eftring, J. Ekengren, I. Errekalde, S. Evans, A. Foucart, L. Fokkema, L. François, M. French, E. Forssell, C. Gingell, C. Gonçalves, H. Gökmen Özel, A. Grimsley, G. Gugelmo, E. Gyüre, C. Heller, R. Hensler, I. Jardim, C. Joost, M. Jörg-Streller, C. Jouault, A. Jung, M. Kanthe, N. Koç, I.L. Kok, T. Kozanoğlu, B. Kumru, F. Lang, K. Lang, I. Liegeois, A. Liguori, R. Lilje, O. Ļubina, P. Manta-Vogli, D. Mayr, C. Meneses, C. Newby, U. Meyer, S. Mexia, C. Nicol, U. Och, S.M. Olivas, C. Pedrón-Giner, R. Pereira, K. Plutowska-Hoffmann, J. Purves, A. Re Dionigi, K. Reinson, M. Robert, L. Robertson, J.C. Rocha, C. Rohde, S. Rosenbaum-Fabian, A. Rossi, M. Ruiz, J. Saligova, A. Gutiérrez-Sánchez, A. Schlune, K. Schulpis, J. Serrano-Nieto, A. Skarpalezou, R. Skeath, A. Slabbert, K. Straczek, M. Giżewska, A. Terry, R. Thom, A. Tooke, J. Tuokkola, E. van Dam, T.A.M. van den Hurk, E.M.C. van der Ploeg, K. Vande Kerckhove, M. Van Driessche, A.M.J. van Wegberg, K. van Wyk, C. Vasconcelos, V. Velez García, J. Wildgoose, T. Winkler, J. Żółkowska, J. Zuvadelli, A. MacDonald

Publikováno v: Molecular Genetics and Metabolism Reports, Vol 18, Iss , Pp 39-44 (2019)

Background: In phenylketonuria (PKU), weaning is considered more challenging when compared to feeding healthy infants. The primary aim of weaning is to gradually replace natural protein from breast milk or standard infant formula with solids containi

Externí odkaz: https://doaj.org/article/357846d0650c409a859338dfc2ebb4fc

Dietary practices in propionic acidemia: A European survey

Autor: A. Daly, A. Pinto, S. Evans, M.F. Almeida, M. Assoun, A. Belanger-Quintana, S.M. Bernabei, S. Bollhalder, D. Cassiman, H. Champion, H. Chan, J. Dalmau, F. de Boer, C. de Laet, A. de Meyer, A. Desloovere, A. Dianin, M. Dixon, K. Dokoupil, S. Dubois, F. Eyskens, A. Faria, I. Fasan, E. Favre, F. Feillet, A. Fekete, G. Gallo, C. Gingell, J. Gribben, K. Kaalund Hansen, N.M. Ter Horst, C. Jankowski, R. Janssen-Regelink, I. Jones, C. Jouault, G.E. Kahrs, I.L. Kok, A. Kowalik, C. Laguerre, S. Le Verge, R. Lilje, C. Maddalon, D. Mayr, U. Meyer, A. Micciche, U. Och, M. Robert, J.C. Rocha, H. Rogozinski, C. Rohde, K. Ross, I. Saruggia, A. Schlune, K. Singleton, E. Sjoqvist, R. Skeath, L.H. Stolen, A. Terry, C. Timmer, L. Tomlinson, A. Tooke, K. Vande Kerckhove, E. van Dam, T. van den Hurk, L. van der Ploeg, M. van Driessche, M. van Rijn, A. van Wegberg, C. Vasconcelos, H. Vestergaard, I. Vitoria, D. Webster, F.J. White, L. White, H. Zweers, A. MacDonald

Publikováno v: Molecular Genetics and Metabolism Reports, Vol 13, Iss C, Pp 83-89 (2017)

Background: The definitive dietary management of propionic acidaemia (PA) is unknown although natural protein restriction with adequate energy provision is of key importance. Aim: To describe European dietary practices in the management of patients w

Externí odkaz: https://doaj.org/article/0cdc119d4cb043f7a29604303da07a36

Self-Supervised Clustering on Image-Subtracted Data with Deep-Embedded Self-Organizing Map

Autor: Mong, Y. -L., Ackley, K., Killestein, T. L., Galloway, D. K., Dyer, M., Cutter, R., Brown, M. J. I., Lyman, J., Ulaczyk, K., Steeghs, D., Dhillon, V., O'Brien, P., Ramsay, G., Noysena, K., Kotak, R., Breton, R., Nuttall, L., Palle, E., Pollacco, D., Thrane, E., Awiphan, S., Burhanudin, U., Chote, P., Chrimes, A., Daw, E., Duffy, C., Eyles-Ferris, R., Gompertz, B. P., Heikkila, T., Irawati, P., Kennedy, M., Levan, A., Littlefair, S., Makrygianni, L., Marsh, T., Sanchez, D. Mata, Mattila, S., Maund, J. R., McCormac, J., Mkrtichian, D., Mullaney, J., Rol, E., Sawangwit, U., Stanway, E., Starling, R., Strom, P., Tooke, S., Wiersema, K.

Developing an effective automatic classifier to separate genuine sources from artifacts is essential for transient follow-ups in wide-field optical surveys. The identification of transient detections from the subtraction artifacts after the image dif

Externí odkaz: http://arxiv.org/abs/2209.06375

Searching For Fermi GRB Optical Counterparts With The Prototype Gravitational-Wave Optical Transient Observer (GOTO)

Autor: Mong, Y. -L., Ackley, K., Galloway, D. K., Dyer, M., Cutter, R., Brown, M. J. I., Lyman, J., Ulaczyk, K., Steeghs, D., Dhillon, V., OBrien, P., Ramsay, G., Noysena, K., Kotak, R., Breton, R., Nuttall, L., Palle, E., Pollacco, D., Thrane, E., Awiphan, S., Burhanudin, U., Chote, P., Chrimes, A., Daw, E., Duffy, C., Eyles-Ferris, R., Gompertz, B., Heikkila, T., Irawati, P., Kennedy, M., Killestein, T., Levan, A., Littlefair, S., Makrygianni, L., Marsh, T., Mata-Sanchez, D., Mattila, S., Maund, J., McCormac, J., Mkrtichian, D., Mullaney, J., Rol, E., Sawangwit, U., Stanway, E., Starling, R., Strom, P., Tooke, S., Wiersema, K.

The typical detection rate of $\sim1$ gamma-ray burst (GRB) per day by the \emph{Fermi} Gamma-ray Burst Monitor (GBM) provides a valuable opportunity to further our understanding of GRB physics. However, the large uncertainty of the \emph{Fermi} loca

Externí odkaz: http://arxiv.org/abs/2108.11802

Light curve classification with recurrent neural networks for GOTO: dealing with imbalanced data

Autor: Burhanudin, U. F., Maund, J. R., Killestein, T., Ackley, K., Dyer, M. J., Lyman, J., Ulaczyk, K., Cutter, R., Mong, Y. -L., Steeghs, D., Galloway, D. K., Dhillon, V., O'Brien, P., Ramsay, G., Noysena, K., Kotak, R., Breton, R. P., Nuttall, L., Pallé, E., Pollacco, D., Thrane, E., Awiphan, S., Chote, P., Chrimes, A., Daw, E., Duffy, C., Eyles-Ferris, R., Gompertz, B., Heikkilä, T., Irawati, P., Kennedy, M. R., Levan, A., Littlefair, S., Makrygianni, L., Mata-Sánchez, D., Mattila, S., McCormac, J., Mkrtichian, D., Mullaney, J., Sawangwit, U., Stanway, E., Starling, R., Strøm, P., Tooke, S., Wiersema, K.

The advent of wide-field sky surveys has led to the growth of transient and variable source discoveries. The data deluge produced by these surveys has necessitated the use of machine learning (ML) and deep learning (DL) algorithms to sift through the

Externí odkaz: http://arxiv.org/abs/2105.11169