Arch Med Sci
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The increased risk of myocardial infarction (MI) in type 2 diabetes mellitus (T2DM) is well documented. Polymorphisms in APOA1 and APOB genes allow us to identify new genetic markers in the Mexican population with T2DM and MI. ⋯ The -75 G>A APOA1 polymorphism could be considered as a susceptibility factor for myocardial infarction in individuals with T2DM and 2488 C>T APOB polymorphism is associated with changes in HDL-C and LDL-C and triglycerides in the same group.
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Chemokines play a crucial role in tumor growth and progression according to proangiogenic and immunosuppressive action. The aim of this study was to investigate the serum levels of selected chemokines in patients with ovarian cancer or benign ovarian tumors to assess their role in tumorigenesis and their potential use in preoperative diagnosis of an adnexal mass. ⋯ CX3CL1 and CXCL1 are elevated in sera of EOC patients, which indicates their role in cancer development. Moreover, they might be useful in preoperative differential diagnosis of ovarian tumors, especially as they were not elevated in cases of endometriosis.
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There is a lot of evidence that suggests that microRNAs (miRs) play an imperative role in the pathogenesis of polycystic ovary syndrome (PCOS). This study was designed to decipher the role of miR-125b in PCOS pathogenesis. ⋯ Since miR-125b controls the proliferation rate of granulosa cells in polycystic ovaries, it might be addressed as a potential therapeutic target for PCOS patients.
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Blood cells are involved in systemic inflammation in chronic obstructive pulmonary disease (COPD). We aimed to assess differences in leukocyte subsets and their ratios between COPD patients and healthy individuals as well as their association with disease severity, smoking status and therapy in COPD. ⋯ Leukocyte subsets and their ratios could be implemented in COPD assessment, especially in evaluating disease severity and prediction.
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Identifying SARS-CoV-2 patients at higher risk of mortality is crucial in the management of a pandemic. Artificial intelligence techniques allow one to analyze large amounts of data to find hidden patterns. We aimed to develop and validate a mortality score at admission for COVID-19 based on high-level machine learning. ⋯ Machine learning techniques were applied in order to develop an accurate in-hospital mortality risk score for COVID-19 based on ten variables. The application of the proposed score has utility in clinical settings to guide the management and prognostication of COVID-19 patients.