International Journal of Laboratory Hematology最新文献

Pseudo-Chediak-Higashi granules are large cytoplasmic inclusions commonly encountered in myeloblasts or other myeloid precursors in acute myeloid leukemia and myelodysplastic syndromes. However, pseudo-Chediak-Higashi granules are rarely found in acute lymphoblastic leukemia (ALL). We present the case of an 8-year-old boy who was diagnosed with ALL with pseudo-Chediak-Higashi granules in the initial diagnosis and relapse, acting like a characteristic marker.

The hemoglobin (Hb) variants are qualitative abnormalities due to production of structurally abnormal globin proteins. They are categorized based on the type of mutation present in the α1, α2, β, Gγ, Aγ and δ globin genes. So far, more than 1550 Hb variants are reported in the database. They could lead to Hb polymerization, Hb instability, altered oxygen affinity and decreased oxygen-carrying capacity of Hb or have no clinical manifestations. In India, ethnic diversity, consanguinity, regional variations and migration result in the presence of different Hb variants. We have compiled all the variants of α, β and δ globin chains in heterozygous, homozygous and in compound heterozygous forms reported from India in the last 52 years. Of the 63 rare and novel hemoglobin variants reported from India, 22 were α-globin chain variants, 37 were β-globin chain variants and 4 were δ-globin chain variants. Twelve novel Hb variants (Hb J Rajappan, Hb Koya Dora, Hb Rampa, Hb Godavari, Hb Chandigarh, Hb D Agri, Hb Lucknow, Hb Vellore, Hb Midnapore, Hb Bijnor, Hb A₂Tianhe and Hb A₂Saurashtra) were identified among persons of Indian origin. Majority of them were picked up on HPLC. Some of the variants like Hb Titusville, Hb Shimonoseki, Hb Chandigarh, Hb D Agri, Hb Yaizu and Hb Vellore eluted in the HbS window whereas variants like HbD Iran, Hb St. Louis, Hb G Coushata, HbM Saskatoon, Hb Lucknow, Hb Grange-Blanche and Hb Tianshui showed falsely elevated HbA₂. Hence, careful and systematic investigations are required to identify them.

Bone marrow aspirate showed diffuse infiltration by a population of monomorphic cells with scant cytoplasm, markedly increased nuclear-to-cytoplasmic ratio, and numerous indistinct nucleoli. Bone marrow biopsy confirmed extensive marrow infiltration by a malignant neoplasm with strong and diffuse expression of synaptophysin by immunohistochemistry, consistent with metastases from Merkel Cell carcinoma.

Schistocytes are fragmented red blood cells produced as a result of mechanical damage to erythrocytes, usually due to microangiopathic thrombotic diseases or mechanical factors. The early laboratory detection of schistocytes has a critical impact on the timely diagnosis, effective treatment, and positive prognosis of diseases such as thrombocytopenic purpura and hemolytic uremic syndrome. Due to the rapid development of science and technology, laboratory hematology has also advanced. The accuracy and efficiency of tests performed by fully automated hematology analyzers and fully automated morphology analyzers have been considerably improved. In recent years, substantial improvements in computing power and machine learning (ML) algorithm development have dramatically extended the limits of the potential of autonomous machines. The rapid development of machine learning and artificial intelligence (AI) has led to the iteration and upgrade of automated detection of schistocytes. However, along with significantly facilitated operation processes, AI has brought challenges. This review summarizes the progress in laboratory schistocyte detection, the relationship between schistocytes and clinical diseases, and the progress of AI in the detection of schistocytes. In addition, current challenges and possible solutions are discussed, as well as the great potential of AI techniques for schistocyte testing in peripheral blood.