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Objective: The fabrication of furosemide (FSM) with enhanced oral bioavailability and encapsulation was achieved using a nanostructured lipid carriers (NLCs) drug delivery system.: The uniform drug distribution is a barrier due to its low dose. The lipid-based delivery system was selected based on its poor solubility and permeability, limiting its poor partitioning and solubility in water-based polymeric delivery systems.

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Background: While viruses remain the leading cause of infectious myocarditis, improved diagnostic methods have highlighted the role of bacteria as a possible cause. We report two cases of myocarditis as a complication of infection.

Case Summaries: Patient A, a 17-year-old Caucasian male with a history of asthma, presented to the emergency department (ED) after experiencing fever and nausea for four days, followed by 1 day of diarrhoea and chest discomfort.

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Background: Preeclampsia is a major hypertensive disorder of pregnancy, which may lead to severe complications, particularly in the first two weeks of the postpartum period. During the postpartum period, blood pressure levels remain high, often increasing to levels higher than those experienced during pregnancy. Furosemide, a fast-acting diuretic, reduces the intravascular volume overload and may represent an alternative to accelerate the normalization of blood pressure levels.

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This review explores the therapeutic potential of the stable gastric pentadecapeptide BPC 157 in addressing electrolyte imbalances, specifically hyperkalemia, hypokalemia, hypermagnesemia, and hyperlithemia. In hyperkalemia, BPC 157 demonstrated a comprehensive counteractive effect against KCl overdose (intraperitoneally, intragastrically, and in vitro), effectively mitigating symptoms such as muscular weakness, hypertension, sphincter dysfunction, arrhythmias, and lethality. It also counteracted the adverse effects of succinylcholine and magnesium overdose, including systemic muscle paralysis, arrhythmias, and hyperkalemia.

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: Earlier detection of severe immune-related hematological adverse events (irHAEs) in cancer patients treated with a PD-1 or PD-L1 inhibitor is critical to improving treatment outcomes. The study aimed to develop a simple machine learning (ML) model for predicting irHAEs associated with PD-1/PD-L1 inhibitors. : We utilized the Observational Medical Outcomes Partnership-Common Data Model based on electronic medical records from a tertiary (KHMC) and a secondary (KHNMC) hospital in South Korea.

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