Blood samples collected under venous oxygen pressure from patients with sickle cell disease contain a significant number of a new type of reversibly sickled cells: Constancy of the percentage of sickled cells in individual patients during steady state-Reference-Cited by-同舟云学术

Blood samples collected under venous oxygen pressure from patients with sickle cell disease contain a significant number of a new type of reversibly sickled cells: Constancy of the percentage of sickled cells in individual patients during steady state

Published:2005 Issue:4 Volume:80 Page:249-256
ISSN:0361-8609
Container-title:American Journal of Hematology
language:en
Short-container-title:Am. J. Hematol.

Author:

Asakura Toshio,Asakura Kenji,Obata Kazuo,Mattiello Julian,Ballas Samir K.

Publisher

Wiley

Subject

Hematology

Reference30 articles.

1. Hemoglobin: molecular, genetic and clinical aspects. Philadelphia: W.B. Saunders Company; 1986. p 541.

2. , Sickle cell disease. In: , , , editors. The molecular basis of blood disease. 1st edition. Philadelphia: WB Saunders; 1987. p 179-218.

3. Sickle Cell Hemoglobin Polymerization

4. , , (editors). Sickle cell disease: basic principles and clinical practice. Philadelphia: Lippincott-Raven; 1994. p 861-871.

5. Sickle cell disease. In: editor. Disorders of hemoglobin. Cambridge, England: Cambridge University Press; 2001. p 494-830.

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