Thrombocytes or platelets are anucleated cells derived from megakaryocytes by process of megakaryopoiesis, with maturation time of 4-5 days. They are small and discoid in shape with size ranging from 2 to 4 μm. The platelet concentration in blood varies between 150, 000 and 400, 000 cells/μl of blood. They are involved in both hemostasis and wound healing. Hence, any abnormalities in platelets can lead to various bleeding disorders. Platelet disorders include thrombocythemia and thrombocytosis, thrombocytopenia and platelet dysfunction. Thrombocythemia and thrombocytosis are associated with increased platelet count because of overproduction of platelets. Thrombocytopenia includes decreased platelet count because of failed platelet production, increased sequestration of platelets in spleen, dilution of platelets and combination of these mechanisms. Platelet dysfunction can be because of intrinsic platelet defect or an extrinsic factor that alters the normal platelet function and can be hereditary or acquired. The following review provides a comprehensive overview of the above platelet disorders.
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http://dx.doi.org/10.1097/01.mbc.0000469521.23628.2d | DOI Listing |
Front Neurosci
January 2025
Department of Neurosurgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China.
Intracerebral hemorrhage (ICH) is a major public health challenge worldwide, and is associated with elevated rates of mortality, disability, and morbidity, especially in low- and middle-income nations. However, our knowledge of the detailed molecular processes involved in ICH remains insufficient, particularly those involved in the secondary injury stage, resulting in a lack of effective treatments for ICH. Human platelet lysates (HPL) are abundant in bioactive factors, and numerous studies have demonstrated their beneficial effects on neurological diseases, including their anti-neuroinflammatory ability, anti-oxidant effects, maintenance of blood-brain barrier integrity, and promotion of neurogenesis.
View Article and Find Full Text PDFAtypical hemolytic uremic syndrome (aHUS) is an important differential diagnosis in thrombotic microangiopathy (TMA). The absence of definitive biomarkers usually allows for aHUS to be diagnosed only through a process of exclusion. Due to the unfavorable prognosis if adequate therapy is delayed or not provided, differential diagnostic considerations and initiation of treatment must occur promptly.
View Article and Find Full Text PDFJ Med Microbiol
January 2025
Midwifery Education Programme, Faculty of Health Sciences, Dr. Soebandi University, Jember, Indonesia.
Anaemia and thrombocytopenia are blood-related irregularities linked to an increased likelihood of disease progression, leading to death in people living with human immunodeficiency virus 1 (PLHIV). Severe clinical conditions associated with human immunodeficiency 1 (HIV-1) infection may be related to blood irregularities among PLHIV. The study aimed to examine the factors correlated with blood irregularities among PLHIV receiving antiretroviral treatment in West Papua.
View Article and Find Full Text PDFPain Ther
January 2025
Department of Trauma and Orthopaedic Surgery, Faculty of Medicine and Psychology, University La Sapienza, 00185, Rome, Italy.
Introduction: Elbow ailments are common, but conventional treatment modalities have shortcomings, offering only interim pain relief rather than targeting the underlying pathophysiology. The last two decades have seen a marked increase in the use of autologous peripheral blood-derived orthobiologics (APBOs), such as platelet-rich plasma (PRP), to manage elbow disorders. Platelet-rich plasma (PRP) is the most widely used APBO, but its efficacy remains debatable.
View Article and Find Full Text PDFBackground: High-grade serous ovarian cancer (HGSOC) remains one of the most challenging gynecological malignancies, with over 70% of ovarian cancer patients ultimately experiencing disease progression. The current prognostic tools for progression-free survival (PFS) in HGSOC patients have limitations. This study aims to develop an explainable machine learning (ML) model for predicting PFS in HGSOC patients.
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