Inter-Pregnancy Weight Change and the Risk of Recurrent Pregnancy Complications

Funding: Funded by the Scottish Government’s Rural and Environment Science and Analytical Services Division (RESAS, Theme 7: Diet and Health). The funder had no role in study design, data collection and analysis, decision to publish, or preparation of this manuscript. Data Availability: All relevant data are owned by the Aberdeen Maternity and Neonatal Databank. Interested parties may request access to the data by following the instructions at http://www.abdn.ac.uk/iahs/research/obsgynae/amnd/access.php.

Effects of Dietary Fibre (Pectin) and/or Increased Protein (Casein or Pea) on Satiety, Body Weight, Adiposity and Caecal Fermentation in High Fat Diet-Induced Obese Rats

Funding: This work was funded by the Scottish Government Rural and Environment Science and Analytical Services Division. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Determinants and impact of suboptimal asthma control in Europe : The INTERNATIONAL CROSS-SECTIONAL AND LONGITUDINAL ASSESSMENT ON ASTHMA CONTROL (LIAISON) study

Acknowledgements We are grateful to THERAmetrics for the study management, data collection and analysis. The authors would like to thank the following investigators for their contribution (>30 patients enrolled): F. Fohler, A.G. Haider, J. Hesse-Tonsa, J. Messner, W. Pohl (Austria); G. Joos, J.L. Halloy, R. Peche, H. Simonis, P. Van den Brande (Belgium); B. Bugnas, J.M. Chavaillon, P. Debove, S. Dury, L. Mathieu, O. Lagrange, A. Prudhomme, S. Verdier (France); A. Benedix, O. Kestermann, A. Deimling, G. Eckhardt, M. Gernhold, V. Grimm-Sachs, M. Hoefer, G. Hoheisel, C. Stolpe, C. Schilder, M. John, J. Uerscheln, K.H. Zeisler (Germany); A. Chaniotou, P. Demertzis, V. Filaditaki-Loverdou, A. Gaga, E. Georgatou-Papageorgiou, S. Michailidis, G. Pavkalou, M. Toumpis (Greece); K. Csicsari, K. Hajdu, M. Póczi, M. Kukuly, T. Kecskes, C. Hangonyi, J. Schlezak, E. Takács, M. Szabo,G. Szabó, C. Szabo (Hungary); G.W. Canonica, W. Castellani, A. Cirillo, M.P. Foschino Barbaro, M. Gjomarkaj, G. Guerra, G. Idotta, D. Legnani, M. Lo Schiavo, R. Maselli, F. Mazza, S. Nutini, P. Paggiaro, A. Pietra, O. Resta, S. Salis, N.A. Scichilone, M.C. Zappa, A. Zedda (Italy); M. Goosens, R. Heller, K. Mansour, C. Meek, J. van den Berg (The Netherlands); A. Antczak, M. Faber, D. Madra-Rogacka, G. Mincewicz, M. Michnar, D. Olejniczak, G. Pulka, Z. Sankowski, K. Kowal, I. Krupa-Borek, B. Kubicka Kozik, K. Kuczynska, P. Kuna, A. Kwasniewski, M. Wozniak (Poland); F. Casas Maldonado, C. Cisneros, J. de Miguel Díez, L.M. Entrenas Costa, B. Garcìa-Cosio, M.V. Gonzales, L. Lores, M. Luengo, C. Martinez, C. Melero, I. Mir, X. Munoz, A. Pacheco, V. Plaza, J. Serra, J. Serrano, J.G. Soto Campos (Spain); T. Bekci, R. Demir, N. Dursunoglu, D. Ediger, A. Ekici, O. Goksel, H. Gunen, I.K. Oguzulgen, Z.F. Ozseker, (Turkey); L. Barnes, T. Hall, S. Montgomerie, J. Purohit, J. Ryan (United Kingdom). The authors would also like to thank P. Galletti (THERAMetrics S.p.A., Sesto San Giovanni, Italy) and K. Stockmeyer (THERAMetrics GmbH, Essen, Germany) for providing editorial assistance in the preparation of this manuscript. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Identification of the salmonid IL-17A/F1a/b, IL-17A/F2b, IL-17A/F3 and IL-17N genes and analysis of their expression following in vitro stimulation and infection

Date of Acceptance: 15/04/2015

Identification and analysis of the plant peroxisomal targeting signal 1 receptor NtPEX5

Protein translocation into peroxisomes takes place via recognition of a peroxisomal targeting signal present at either the extreme C termini (PTS1) or N termini (PTS2) of matrix proteins. In mammals and yeast, the peroxisomal targeting signal receptor, Pex5p, recognizes the PTS1 consisting of -SKL or variants thereof. Although many plant peroxisomal matrix proteins are transported through the PTS1 pathway, little is known about the PTS1 receptor or any other peroxisome assembly protein from plants. We cloned tobacco (Nicotiana tabacum) cDNAs encoding Pex5p (NtPEX5) based on the protein’s interaction with a PTS1-containing protein in the yeast two-hybrid system. Nucleotide sequence analysis revealed that the tobacco Pex5p contains seven tetratricopeptide repeats and that NtPEX5 shares greater sequence similarity with its homolog from humans than from yeast. Expression of NtPEX5 fusion proteins, consisting of the N-terminal part of yeast Pex5p and the C-terminal region of NtPEX5, in a Saccharomyces cerevisiae pex5 mutant restored protein translocation into peroxisomes. These experiments confirmed the identity of the tobacco protein as a PTS1 receptor and indicated that components of the peroxisomal translocation apparatus are conserved functionally. Two-hybrid assays showed that NtPEX5 interacts with a wide range of PTS1 variants that also interact with the human Pex5p. Interestingly, the C-terminal residues of some of these peptides deviated from the established plant PTS1 consensus sequence. We conclude that there are significant sequence and functional similarities between the plant and human Pex5ps.

Singular value decomposition for genome-wide expression data processing and modeling

We describe the use of singular value decomposition in transforming genome-wide expression data from genes × arrays space to reduced diagonalized “eigengenes” × “eigenarrays” space, where the eigengenes (or eigenarrays) are unique orthonormal superpositions of the genes (or arrays). Normalizing the data by filtering out the eigengenes (and eigenarrays) that are inferred to represent noise or experimental artifacts enables meaningful comparison of the expression of different genes across different arrays in different experiments. Sorting the data according to the eigengenes and eigenarrays gives a global picture of the dynamics of gene expression, in which individual genes and arrays appear to be classified into groups of similar regulation and function, or similar cellular state and biological phenotype, respectively. After normalization and sorting, the significant eigengenes and eigenarrays can be associated with observed genome-wide effects of regulators, or with measured samples, in which these regulators are overactive or underactive, respectively.