scholarly journals SAT-116 A CELL LINE DERIVED FROM RENAL ERYTHROPOIETIN-PRODUCING CELLS PROVES THEIR MYOFIBROBLAST-TRANSFORMATION PROPERTY

2019 ◽  
Vol 4 (7) ◽  
pp. S54
Author(s):  
K. SATO ◽  
I. Hirano ◽  
H. Sekine ◽  
K. Miyauchi ◽  
T. Nakai ◽  
...  
Author(s):  
N. Savage ◽  
A. Hackett

A cell line, UC1-B, which was derived from Balb/3T3 cells, maintains the same morphological characteristics of the non-transformed parental culture, and shows no evidence of spontaneous virus production. Survey by electron microscopy shows that the cell line consists of spindle-shaped cells with no unusual features and no endogenous virus particles.UC1-B cells respond to Moloney leukemia virus (MLV) infection by a change in morphology and growth pattern which is typical of cells transformed by sarcoma virus. Electron microscopy shows that the cells are now variable in shape (rounded, rhomboid, and spindle), and each cell type has some microvilli. Virtually all (90%) of the cells show virus particles developing at the cell surface and within the cytoplasm. Maturing viruses, typical of the oncogenic viruses, are found along with atypical tubular forms in the same cell.


1983 ◽  
Vol 32 (2) ◽  
pp. 141-146 ◽  
Author(s):  
Tetsu Watanabe ◽  
Toshio Morizane ◽  
Kanji Tsuchimoto ◽  
Yasutaka Inagaki ◽  
Yoshio Munakata ◽  
...  

Blood ◽  
1985 ◽  
Vol 65 (1) ◽  
pp. 21-31 ◽  
Author(s):  
RC Stong ◽  
SJ Korsmeyer ◽  
JL Parkin ◽  
DC Arthur ◽  
JH Kersey

Abstract A cell line, designated RS4;11, was established from the bone marrow of a patient in relapse with an acute leukemia that was characterized by the t(4;11) chromosomal abnormality. The cell line and the patient's fresh leukemic cells both had the t(4;11)(q21;q23) and an isochromosome for the long arm of No. 7. Morphologically, all cells were lymphoid in appearance. Ultrastructurally and cytochemically, approximately 30% of the cells possessed myeloid features. The cells were strongly positive for terminal deoxynucleotidyl transferase. They were HLA-DR positive and expressed surface antigens characteristic for B lineage cells, including those detected by anti-B4, BA-1, BA-2, and PI153/3. Immunoglobulin gene analysis revealed rearrangements of the heavy chain and kappa chain genes. The cells lacked the common acute lymphoblastic leukemia antigen and antigenic markers characteristic of T lineage cells. The cells reacted with the myeloid antibody 1G10 but not with other myeloid monoclonal antibodies. Treatment with 12-O-tetradecanoyl- phorbol-13-acetate induced a monocyte-like phenotype demonstrated by cytochemical, functional, immunologic, and electron microscopic studies. The expression of markers of both early lymphoid and early myeloid cells represents an unusual phenotype and suggests that RS4;11 represents a cell with dual lineage capabilities. To our knowledge, RS4;11 is the first cell line established from t(4;11)-associated acute leukemia.


1993 ◽  
Vol &NA; (296) ◽  
pp. 229???241 ◽  
Author(s):  
RICHARD O. C. OREFFO ◽  
G. JUNE MARSHALL ◽  
MARY KIRCHEN ◽  
CARLOS GARCIA ◽  
WOLF E. GALLWITZ ◽  
...  

Science ◽  
1969 ◽  
Vol 163 (3866) ◽  
pp. 472-473 ◽  
Author(s):  
J. Leighton ◽  
Z. Brada ◽  
L. W. Estes ◽  
G. Justh
Keyword(s):  

1993 ◽  
Vol 11 (S1) ◽  
pp. S134-S136
Author(s):  
E. Motti ◽  
L. Ventrella ◽  
V. Pistotti ◽  
T. Dasdia ◽  
A. Ghiozzi ◽  
...  
Keyword(s):  

1996 ◽  
Vol 48 (1) ◽  
pp. A36-A37
Author(s):  
B VANKLINKEN ◽  
E OUSSOREN ◽  
J WEENINK ◽  
H BULLER ◽  
J DEKKER ◽  
...  

1972 ◽  
Vol 47 (6) ◽  
pp. 465-467
Author(s):  
TAKIJI ARATA ◽  
YOSHINORI TANAKA ◽  
TOHRU OKIGAKI

Author(s):  
Yang Lin ◽  
Xiaoyong Pan ◽  
Hong-Bin Shen

Abstract Motivation Long non-coding RNAs (lncRNAs) are generally expressed in a tissue-specific way, and subcellular localizations of lncRNAs depend on the tissues or cell lines that they are expressed. Previous computational methods for predicting subcellular localizations of lncRNAs do not take this characteristic into account, they train a unified machine learning model for pooled lncRNAs from all available cell lines. It is of importance to develop a cell-line-specific computational method to predict lncRNA locations in different cell lines. Results In this study, we present an updated cell-line-specific predictor lncLocator 2.0, which trains an end-to-end deep model per cell line, for predicting lncRNA subcellular localization from sequences.We first construct benchmark datasets of lncRNA subcellular localizations for 15 cell lines. Then we learn word embeddings using natural language models, and these learned embeddings are fed into convolutional neural network, long short-term memory and multilayer perceptron to classify subcellular localizations. lncLocator 2.0 achieves varying effectiveness for different cell lines and demonstrates the necessity of training cell-line-specific models. Furthermore, we adopt Integrated Gradients to explain the proposed model in lncLocator 2.0, and find some potential patterns that determine the subcellular localizations of lncRNAs, suggesting that the subcellular localization of lncRNAs is linked to some specific nucleotides. Availability The lncLocator 2.0 is available at www.csbio.sjtu.edu.cn/bioinf/lncLocator2 and the source code can be found at https://github.com/Yang-J-LIN/lncLocator2. Supplementary information Supplementary data are available at Bioinformatics online.


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