743914V1.Full.Pdf
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Molecular Profile of Tumor-Specific CD8+ T Cell Hypofunction in a Transplantable Murine Cancer Model
Downloaded from http://www.jimmunol.org/ by guest on September 25, 2021 T + is online at: average * The Journal of Immunology , 34 of which you can access for free at: 2016; 197:1477-1488; Prepublished online 1 July from submission to initial decision 4 weeks from acceptance to publication 2016; doi: 10.4049/jimmunol.1600589 http://www.jimmunol.org/content/197/4/1477 Molecular Profile of Tumor-Specific CD8 Cell Hypofunction in a Transplantable Murine Cancer Model Katherine A. Waugh, Sonia M. Leach, Brandon L. Moore, Tullia C. Bruno, Jonathan D. Buhrman and Jill E. Slansky J Immunol cites 95 articles Submit online. Every submission reviewed by practicing scientists ? is published twice each month by Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts http://jimmunol.org/subscription Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html http://www.jimmunol.org/content/suppl/2016/07/01/jimmunol.160058 9.DCSupplemental This article http://www.jimmunol.org/content/197/4/1477.full#ref-list-1 Information about subscribing to The JI No Triage! Fast Publication! Rapid Reviews! 30 days* Why • • • Material References Permissions Email Alerts Subscription Supplementary The Journal of Immunology The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2016 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. This information is current as of September 25, 2021. The Journal of Immunology Molecular Profile of Tumor-Specific CD8+ T Cell Hypofunction in a Transplantable Murine Cancer Model Katherine A. -
Supplementary Material for “Characterization of the Opossum Immune Genome Provides Insights Into the Evolution of the Mammalian Immune System”
Supplementary material for “Characterization of the opossum immune genome provides insights into the evolution of the mammalian immune system” Katherine Belov1*, Claire E. Sanderson1, Janine E. Deakin2, Emily S.W. Wong1, Daniel Assange3, Kaighin A. McColl3, Alex Gout3,4, Bernard de Bono5, Terence P. Speed3, John Trowsdale5, Anthony T. Papenfuss3 1. Faculty of Veterinary Science, University of Sydney, Sydney, Australia 2. ARC Centre for Kangaroo Genomics, Research School of Biological Sciences, The Australian National University, Canberra, Australia 3. Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Australia 4. Department of Medical Biology, The University of Melbourne, Parkville, Australia 5. Immunology Division, University of Cambridge, Cambridge, UK *Corresponding author: K. Belov, Faculty of Veterinary Science, University of Sydney, NSW 2006, Australia ph 61 2 9351 3454, fx 61 2 9351 3957, email [email protected] MHC paralogous regions Only 36 of the 114 genes in the opossum MHC have paralogs in one of the three paralogous regions (Supplementary Table 1). Genes represented in at least three of the four paralogous regions (13 genes) were used to compare gene order, revealing rearrangements between the four regions in opossum. Table 1: MHC genes with paralogs on opossum chromosomes 1, 2 and 3, corresponding to MHC paralogous regions on human chromosomes 9, 1 and 19 respectively. MHC Chromosome 1 Chromosome 2 Chromosome 3 (Human Chr 9) (Human Chr 1) (Human Chr 19) AGPAT1 AGPAT2 AIF1 C9orf58 ATP6V1G2 ATP6V1G1 ATP6V1G3 B3GALT4 B3GALT2 BAT1 DDX39 BAT2 KIAA0515 BAT2D1 BRD2 BRD3 BRDT BRD4 C4 C5 C3 SLC44A4 SLC44A5 SLC44A2 CLIC1 CLIC3 CLIC4 COL11A2 COL5A1 COL11A1 COL5A3 CREBL1 ATF6 DDAH2 DDAH1 DDR1 DDR2 EGFL8 EGFL7 EHMT2 EHMT1 GPX5 GPX4 MHC Class I CD1 HSPA1A HSPA5 MDC1 PRG4 NOTCH4 NOTCH1 NOTCH2 NOTCH3 PBX2 PBX3 PBX1 PBX4 PHF1 MTF2 PRSS16 DPP7 PSMB9 PSMB7 RGL2 RALGDS RGL1 RGL3 RING1 RNF2 RXRB RXRA RXRG SYNGAP1 RASAL2 TAP ABCA2 TNF/LTA/LTB TNFSF8/TNFSF15 TNFSF4 CD70/TNFSF9/ TNFSF14/ TNXB TNC TNR Table 2. -
Stx5-Mediated ER-Golgi Transport in Mammals and Yeast Linders, Peter Ta; Horst, Chiel Van Der; Beest, Martin Ter; Van Den Bogaart, Geert
University of Groningen Stx5-Mediated ER-Golgi Transport in Mammals and Yeast Linders, Peter Ta; Horst, Chiel van der; Beest, Martin Ter; van den Bogaart, Geert Published in: Cells DOI: 10.3390/cells8080780 IMPORTANT NOTE: You are advised to consult the publisher's version (publisher's PDF) if you wish to cite from it. Please check the document version below. Document Version Publisher's PDF, also known as Version of record Publication date: 2019 Link to publication in University of Groningen/UMCG research database Citation for published version (APA): Linders, P. T., Horst, C. V. D., Beest, M. T., & van den Bogaart, G. (2019). Stx5-Mediated ER-Golgi Transport in Mammals and Yeast. Cells, 8(8), [cells8080780]. https://doi.org/10.3390/cells8080780 Copyright Other than for strictly personal use, it is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license (like Creative Commons). The publication may also be distributed here under the terms of Article 25fa of the Dutch Copyright Act, indicated by the “Taverne” license. More information can be found on the University of Groningen website: https://www.rug.nl/library/open-access/self-archiving-pure/taverne- amendment. Take-down policy If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. Downloaded from the University of Groningen/UMCG research database (Pure): http://www.rug.nl/research/portal. -
A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus
Page 1 of 781 Diabetes A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes Mellitus Robert N. Bone1,6,7, Olufunmilola Oyebamiji2, Sayali Talware2, Sharmila Selvaraj2, Preethi Krishnan3,6, Farooq Syed1,6,7, Huanmei Wu2, Carmella Evans-Molina 1,3,4,5,6,7,8* Departments of 1Pediatrics, 3Medicine, 4Anatomy, Cell Biology & Physiology, 5Biochemistry & Molecular Biology, the 6Center for Diabetes & Metabolic Diseases, and the 7Herman B. Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN 46202; 2Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202; 8Roudebush VA Medical Center, Indianapolis, IN 46202. *Corresponding Author(s): Carmella Evans-Molina, MD, PhD ([email protected]) Indiana University School of Medicine, 635 Barnhill Drive, MS 2031A, Indianapolis, IN 46202, Telephone: (317) 274-4145, Fax (317) 274-4107 Running Title: Golgi Stress Response in Diabetes Word Count: 4358 Number of Figures: 6 Keywords: Golgi apparatus stress, Islets, β cell, Type 1 diabetes, Type 2 diabetes 1 Diabetes Publish Ahead of Print, published online August 20, 2020 Diabetes Page 2 of 781 ABSTRACT The Golgi apparatus (GA) is an important site of insulin processing and granule maturation, but whether GA organelle dysfunction and GA stress are present in the diabetic β-cell has not been tested. We utilized an informatics-based approach to develop a transcriptional signature of β-cell GA stress using existing RNA sequencing and microarray datasets generated using human islets from donors with diabetes and islets where type 1(T1D) and type 2 diabetes (T2D) had been modeled ex vivo. To narrow our results to GA-specific genes, we applied a filter set of 1,030 genes accepted as GA associated. -
Protein Identities in Evs Isolated from U87-MG GBM Cells As Determined by NG LC-MS/MS
Protein identities in EVs isolated from U87-MG GBM cells as determined by NG LC-MS/MS. No. Accession Description Σ Coverage Σ# Proteins Σ# Unique Peptides Σ# Peptides Σ# PSMs # AAs MW [kDa] calc. pI 1 A8MS94 Putative golgin subfamily A member 2-like protein 5 OS=Homo sapiens PE=5 SV=2 - [GG2L5_HUMAN] 100 1 1 7 88 110 12,03704523 5,681152344 2 P60660 Myosin light polypeptide 6 OS=Homo sapiens GN=MYL6 PE=1 SV=2 - [MYL6_HUMAN] 100 3 5 17 173 151 16,91913397 4,652832031 3 Q6ZYL4 General transcription factor IIH subunit 5 OS=Homo sapiens GN=GTF2H5 PE=1 SV=1 - [TF2H5_HUMAN] 98,59 1 1 4 13 71 8,048185945 4,652832031 4 P60709 Actin, cytoplasmic 1 OS=Homo sapiens GN=ACTB PE=1 SV=1 - [ACTB_HUMAN] 97,6 5 5 35 917 375 41,70973209 5,478027344 5 P13489 Ribonuclease inhibitor OS=Homo sapiens GN=RNH1 PE=1 SV=2 - [RINI_HUMAN] 96,75 1 12 37 173 461 49,94108966 4,817871094 6 P09382 Galectin-1 OS=Homo sapiens GN=LGALS1 PE=1 SV=2 - [LEG1_HUMAN] 96,3 1 7 14 283 135 14,70620005 5,503417969 7 P60174 Triosephosphate isomerase OS=Homo sapiens GN=TPI1 PE=1 SV=3 - [TPIS_HUMAN] 95,1 3 16 25 375 286 30,77169764 5,922363281 8 P04406 Glyceraldehyde-3-phosphate dehydrogenase OS=Homo sapiens GN=GAPDH PE=1 SV=3 - [G3P_HUMAN] 94,63 2 13 31 509 335 36,03039959 8,455566406 9 Q15185 Prostaglandin E synthase 3 OS=Homo sapiens GN=PTGES3 PE=1 SV=1 - [TEBP_HUMAN] 93,13 1 5 12 74 160 18,68541938 4,538574219 10 P09417 Dihydropteridine reductase OS=Homo sapiens GN=QDPR PE=1 SV=2 - [DHPR_HUMAN] 93,03 1 1 17 69 244 25,77302971 7,371582031 11 P01911 HLA class II histocompatibility antigen, -
Gateways to the FANTOM5 Promoter Level Mammalian Expression Atlas
Lizio et al. Genome Biology (2015) 16:22 DOI 10.1186/s13059-014-0560-6 SOFTWARE Open Access Gateways to the FANTOM5 promoter level mammalian expression atlas Marina Lizio1,2, Jayson Harshbarger1,2, Hisashi Shimoji1,2, Jessica Severin1,2, Takeya Kasukawa2, Serkan Sahin1,2, Imad Abugessaisa2, Shiro Fukuda1, Fumi Hori1,2, Sachi Ishikawa-Kato1,2, Christopher J Mungall5, Erik Arner1,2, J Kenneth Baillie7, Nicolas Bertin1,2,19, Hidemasa Bono10, Michiel de Hoon1,2, Alexander D Diehl13, Emmanuel Dimont12, Tom C Freeman7, Kaori Fujieda10, Winston Hide12,17, Rajaram Kaliyaperumal8, Toshiaki Katayama15, Timo Lassmann1,2,18, Terrence F Meehan6, Koro Nishikata16, Hiromasa Ono10, Michael Rehli9, Albin Sandelin11, Erik A Schultes8,14, Peter AC ‘t Hoen8, Zuotian Tatum8, Mark Thompson8, Tetsuro Toyoda16, Derek W Wright7, Carsten O Daub1, Masayoshi Itoh1,2,3, Piero Carninci1,2, Yoshihide Hayashizaki1,3, Alistair RR Forrest1,2*, Hideya Kawaji1,2,3,4* and the FANTOM consortium Abstract The FANTOM5 project investigates transcription initiation activities in more than 1,000 human and mouse primary cells, cell lines and tissues using CAGE. Based on manual curation of sample information and development of an ontology for sample classification, we assemble the resulting data into a centralized data resource (http://fantom. gsc.riken.jp/5/). This resource contains web-based tools and data-access points for the research community to search and extract data related to samples, genes, promoter activities, transcription factors and enhancers across the FANTOM5 atlas. Introduction ontologies [10]). However, the ability of these surveys to One of the most comprehensive ways to study the mo- quantify RNA abundance was limited mainly due to se- lecular basis of cellular function is to quantify the pres- quencing performance. -
Genome-Wide Analysis of Differential Transcriptional and Epigenetic
bioRxiv preprint doi: https://doi.org/10.1101/083246; this version posted October 26, 2016. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license. 1 Genome-wide Analysis of Differential Transcriptional and 2 Epigenetic Variability Across Human Immune Cell Types 3 Simone Ecker,1,2,* Lu Chen,3,4 Vera Pancaldi,1 Frederik O. Bagger,4,5,6 José María Fernández,1 Enrique Carrillo de 4 Santa Pau,1 David Juan,1 Alice L. Mann,3 Stephen Watt,3 Francesco Paolo Casale,6 Nikos Sidiropoulos,7,8,9 Nicolas 5 Rapin,7,8,9 Angelika Merkel,10 BLUEPRINT Consortium, Henk Stunnenberg,11 Oliver Stegle,6 Mattia Frontini,4,5,12 Kate 6 Downes,4,5 Tomi Pastinen,13 Taco W. Kuijpers,14,15 Daniel Rico,1,17 Alfonso Valencia,1,17 Stephan Beck,2,17 Nicole 7 Soranzo3,4,17,* and Dirk S. Paul2,16,17,* 8 9 1Structural Biology and Biocomputing Programme, Spanish National Cancer Research Center (CNIO), Melchor Fernández Almagro 3, 28029 Madrid, Spain 10 2UCL Cancer Institute, University College London, 72 Huntley Street, London, WC1E 6BT, UK 11 3Department of Human Genetics, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1HH, UK 12 4Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Long Road, Cambridge, CB2 0PT, UK 13 5National Health Service (NHS) Blood and Transplant, Cambridge Biomedical Campus, Long Road, Cambridge, CB2 -
Evaluation of Variability in Human Protein X-Ray Structures Risa Anzai
bioRxiv preprint doi: https://doi.org/10.1101/202028; this version posted October 12, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Evaluation of variability in human protein X-ray structures Risa Anzai, Yoshiki Asami, Waka Inoue, Hina Ueno, Koya Yamada, Tetsuji Okada Department of Life Science, Gakushuin University, 1-5-1 Mejiro, Toshima-ku, Tokyo 171-8588, Japan. Corresponding author: Tetsuji Okada, Department of Life Science, Gakushuin University, 1-5-1 Mejiro, Toshima-ku, Tokyo 171-8588, Japan. +81-3-3986-0221, [email protected] Abstract Systematic analysis of statistical and dynamical properties of proteins is critical to understanding cellular events. Extraction of biologically relevant information from a set of X-ray structures is important because it can provide mechanistic details behind the functional properties of protein families, enabling rational comparison between families. Most of the current structure comparisons are pairwise-based, which hampers the global analysis of increasing contents in the Protein Data Bank. Additionally, pairing of protein structures introduces uncertainty with respect to reproducibility because it frequently accompanies other settings such as alignment and/or superimposition. This study introduces intramolecular distance scoring, for the analysis of human proteins, for each of which at least several X-ray structures are available. We show that the results are comprehensively used to overview advances at the atomic level exploration of each protein and protein family. -
Supplementary Table S4. FGA Co-Expressed Gene List in LUAD
Supplementary Table S4. FGA co-expressed gene list in LUAD tumors Symbol R Locus Description FGG 0.919 4q28 fibrinogen gamma chain FGL1 0.635 8p22 fibrinogen-like 1 SLC7A2 0.536 8p22 solute carrier family 7 (cationic amino acid transporter, y+ system), member 2 DUSP4 0.521 8p12-p11 dual specificity phosphatase 4 HAL 0.51 12q22-q24.1histidine ammonia-lyase PDE4D 0.499 5q12 phosphodiesterase 4D, cAMP-specific FURIN 0.497 15q26.1 furin (paired basic amino acid cleaving enzyme) CPS1 0.49 2q35 carbamoyl-phosphate synthase 1, mitochondrial TESC 0.478 12q24.22 tescalcin INHA 0.465 2q35 inhibin, alpha S100P 0.461 4p16 S100 calcium binding protein P VPS37A 0.447 8p22 vacuolar protein sorting 37 homolog A (S. cerevisiae) SLC16A14 0.447 2q36.3 solute carrier family 16, member 14 PPARGC1A 0.443 4p15.1 peroxisome proliferator-activated receptor gamma, coactivator 1 alpha SIK1 0.435 21q22.3 salt-inducible kinase 1 IRS2 0.434 13q34 insulin receptor substrate 2 RND1 0.433 12q12 Rho family GTPase 1 HGD 0.433 3q13.33 homogentisate 1,2-dioxygenase PTP4A1 0.432 6q12 protein tyrosine phosphatase type IVA, member 1 C8orf4 0.428 8p11.2 chromosome 8 open reading frame 4 DDC 0.427 7p12.2 dopa decarboxylase (aromatic L-amino acid decarboxylase) TACC2 0.427 10q26 transforming, acidic coiled-coil containing protein 2 MUC13 0.422 3q21.2 mucin 13, cell surface associated C5 0.412 9q33-q34 complement component 5 NR4A2 0.412 2q22-q23 nuclear receptor subfamily 4, group A, member 2 EYS 0.411 6q12 eyes shut homolog (Drosophila) GPX2 0.406 14q24.1 glutathione peroxidase -
Multiplexed Engineering Glycosyltransferase Genes in CHO Cells Via Targeted Integration for Producing Antibodies with Diverse Complex‑Type N‑Glycans Ngan T
www.nature.com/scientificreports OPEN Multiplexed engineering glycosyltransferase genes in CHO cells via targeted integration for producing antibodies with diverse complex‑type N‑glycans Ngan T. B. Nguyen, Jianer Lin, Shi Jie Tay, Mariati, Jessna Yeo, Terry Nguyen‑Khuong & Yuansheng Yang* Therapeutic antibodies are decorated with complex‑type N‑glycans that signifcantly afect their biodistribution and bioactivity. The N‑glycan structures on antibodies are incompletely processed in wild‑type CHO cells due to their limited glycosylation capacity. To improve N‑glycan processing, glycosyltransferase genes have been traditionally overexpressed in CHO cells to engineer the cellular N‑glycosylation pathway by using random integration, which is often associated with large clonal variations in gene expression levels. In order to minimize the clonal variations, we used recombinase‑mediated‑cassette‑exchange (RMCE) technology to overexpress a panel of 42 human glycosyltransferase genes to screen their impact on antibody N‑linked glycosylation. The bottlenecks in the N‑glycosylation pathway were identifed and then released by overexpressing single or multiple critical genes. Overexpressing B4GalT1 gene alone in the CHO cells produced antibodies with more than 80% galactosylated bi‑antennary N‑glycans. Combinatorial overexpression of B4GalT1 and ST6Gal1 produced antibodies containing more than 70% sialylated bi‑antennary N‑glycans. In addition, antibodies with various tri‑antennary N‑glycans were obtained for the frst time by overexpressing MGAT5 alone or in combination with B4GalT1 and ST6Gal1. The various N‑glycan structures and the method for producing them in this work provide opportunities to study the glycan structure‑and‑function and develop novel recombinant antibodies for addressing diferent therapeutic applications. -
Stx5-Mediated ER-Golgi Transport in Mammals and Yeast
cells Review Stx5-Mediated ER-Golgi Transport in Mammals and Yeast Peter TA Linders 1 , Chiel van der Horst 1, Martin ter Beest 1 and Geert van den Bogaart 1,2,* 1 Tumor Immunology Lab, Radboud University Medical Center, Radboud Institute for Molecular Life Sciences, Geert Grooteplein 28, 6525 GA Nijmegen, The Netherlands 2 Department of Molecular Immunology, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Nijenborgh 7, 9747 AG Groningen, The Netherlands * Correspondence: [email protected]; Tel.: +31-50-36-35230 Received: 8 July 2019; Accepted: 25 July 2019; Published: 26 July 2019 Abstract: The soluble N-ethylmaleimide-sensitive factor attachment protein receptor (SNARE) syntaxin 5 (Stx5) in mammals and its ortholog Sed5p in Saccharomyces cerevisiae mediate anterograde and retrograde endoplasmic reticulum (ER)-Golgi trafficking. Stx5 and Sed5p are structurally highly conserved and are both regulated by interactions with other ER-Golgi SNARE proteins, the Sec1/Munc18-like protein Scfd1/Sly1p and the membrane tethering complexes COG, p115, and GM130. Despite these similarities, yeast Sed5p and mammalian Stx5 are differently recruited to COPII-coated vesicles, and Stx5 interacts with the microtubular cytoskeleton, whereas Sed5p does not. In this review, we argue that these different Stx5 interactions contribute to structural differences in ER-Golgi transport between mammalian and yeast cells. Insight into the function of Stx5 is important given its essential role in the secretory pathway of eukaryotic cells and its involvement in infections and neurodegenerative diseases. Keywords: syntaxin 5; Golgi apparatus; endoplasmic reticulum; membrane trafficking; secretory pathway 1. Introduction The secretory pathway is essential for secretion of cytokines, hormones, growth factors, and extracellular matrix proteins, as well as for the delivery of receptors and transporters to the cell membrane and lytic proteins to endo-lysosomal compartments. -
Cholesterol-Dependent Increases in Glucosylceramide
Neuropharmacology 110 (2016) 458e469 Contents lists available at ScienceDirect Neuropharmacology journal homepage: www.elsevier.com/locate/neuropharm Cholesterol-dependent increases in glucosylceramide synthase activity in Niemann-Pick disease type C model cells: Abnormal trafficking of endogenously formed ceramide metabolites by inhibition of the enzyme Naohiro Hashimoto 1, Ikiru Matsumoto 1, Hiromasa Takahashi, Hitomi Ashikawa, * Hiroyuki Nakamura , Toshihiko Murayama Laboratory of Chemical Pharmacology, Graduate School of Pharmaceutical Sciences, Chiba University, Chiba 260-8675, Japan article info abstract Article history: Sphingolipids such as sphingomyelin and glycosphingolipids (GSLs) derived from glucosylceramide Received 1 February 2016 (GlcCer), in addition to cholesterol, accumulate in cells/neurons in Niemann-Pick disease type C (NPC). Received in revised form The activities of acid sphingomyelinase and lysosomal glucocerebrosidase (GCase), which degrade 10 August 2016 sphingomyelin and GlcCer, respectively, are down-regulated in NPC cells, however, changes in GlcCer Accepted 12 August 2016 synthase activity have not yet been elucidated. We herein demonstrated for the first time that GlcCer Available online 15 August 2016 synthase activity for the fluorescent ceramide, 4-nitrobenzo-2-oxa-1,3-diazole-labeled C6-ceramide À À (NBD-ceramide) increased in intact NPC1( / ) cells and cell lysates without affecting the protein levels. Keywords: (À/À) fl Niemann-Pick disease type C In NBD-ceramide-labeled NPC1 cells, NBD- uorescence preferentially accumulated in the Golgi Cholesterol complex and vesicular specks in the cytoplasm 40 and 150 min, respectively, after labeling, while a Glucosylceramide synthase treatment for 48 h with the GlcCer synthase inhibitors, N-butyldeoxynojirimycin (NB-DNJ) and 1-phenyl- Sphingomyelin 2-palmitoylamino-3-morpholino-1-propanol, accelerated the appearance of vesicular specks emitting À À Vesicular trafficking NBD-fluorescence within 40 min.