Acute leukemias constitute some of the most common malignant disorders. Despite significant progress made in the treatment of these disorders, their etiology remains unknown. A large and diverse group of genetic and environmental variables have been proposed. The role of a variety of factors, including pre-existing and acquired genetic mutations, exposure to radiation and various chemicals during preconception, pregnancy and throughout life, have been explored. The effects of inherited genetic variations and disorders, pre-existing diseases, infectious agents, hobbies, occupations, prior treatments, and a host of other factors have been proposed, but none is universally applicable to all cases. Variation in the incidence and prognosis based on the age, sex, race, type of the disease, geographic area of residence and other factors are intriguing but remain unexplained. Advances in genomic profiling, including genome-wide gene expression, DNA copy number and single nucleotide polymorphism (SNP) genotype, may shed some light on the role of genetics in these disparities. Separate two-hit hypotheses for the development of acute myeloblastic and lymphoblastic leukemia have been proposed. The latter combines genetics and infection factors resulting in leukemogenesis. A number of pre- and post-natal environmental conditions and exposure to infections, including a mycovirus infected , have been suggested. The exact nature, timing, sequence of the events and mechanisms resulting in the occurrence of leukemia requires further investigations. This review summarizes some of the above factors in acute lymphoblastic and myeloblastic leukemias and the direction for future research on the etiology of these disorders.
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http://dx.doi.org/10.3390/cancers13092256 | DOI Listing |
ACS Chem Neurosci
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Department of Occupational Health, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi 030001, China.
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January 2025
Department of Medicine, Division of Occupational, Environmental and Climate Medicine, University of California, San Francisco; San Francisco, California, 94158United States.
Water scarcity is projected to affect half of the world's population, gradually exacerbated by climate change. This article elaborates from a panel discussion at the 2023 United Nations Water Conference on Addressing Water Scarcity to Achieve Climate Resilience and Human Health. Understanding and addressing water scarcity goes beyond hydrological water balances to also include societal and economic measures.
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January 2025
Department of Pharmacology, University of the Free State, Bloemfontein, 9300, South Africa.
Medicinal plants are products from natural sources that have found relevance in medicine for several decades. They are rich in bioactive compounds; thus, they are widely used to treat different ailments globally. Medicinal plants have provided hope for the health care industry as most are used to synthesize modern medicines currently used in the treatment of various diseases.
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Department of Big Data in Health Science, Zhejiang University School of Public Health and Department of Psychiatry, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Clonal haematopoiesis of indeterminate potential (CHIP) is associated with macrovascular diseases, including coronary artery disease and stroke. However, the effects of CHIP on microvascular complication have not been evaluated in individuals with type 2 diabetes (T2D). This study included 20,712 T2D participants without prevalent diabetic microvascular complication (DMCs) and hematologic malignancy at baseline.
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Department of Horticultural Science, Faculty of Agriculture, Jahrom University, Jahrom, Iran.
The approaches used to determine the medicinal properties of the plants are often destructive, labor-intensive, time-consuming, and expensive, making it impossible to analyze their quality analysis online. Performance of hyperspectral imaging (HSI) integrated with intelligent techniques to overcome these problems was investigated in this research. For this purpose, three classification methods-support vector machine, random forest (RF), and extreme gradient boosting-were studied for the classification of plants in three classes of medicinal, edible, and ornamental for the organs of leaf, stem, flower, and root.
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