Annals of medicine
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There is an unmet clinical need for novel therapies addressing the residual risk in patients receiving guideline preventive therapy for coronary heart disease. Experimental studies have identified a pro-atherogenic role of the oxidized LDL receptor LOX-1. We investigated the association between circulating soluble LOX-1 (sLOX-1) and the risk for development of myocardial infarction. ⋯ In this prospective population study we found an association between elevated sLOX-1, the presence of carotid disease and the risk for first-time myocardial infarction. Taken together with previous experimental findings of a pro-atherogenic role of LOX-1, this observation supports LOX-1 inhibition as a possible target for prevention of myocardial infarction.
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Studies demonstrated that outpatient aerobic exercise programs (aEP) can significantly decrease aortic stiffness in people with metabolic syndrome (MetS). There is some limited data that remotely supervised home-based aEP can also improve arterial stiffness in this population. We aimed to evaluate the changes in the arterial wall parameters after the 2-month ambulatory supervised aEP followed by the 6-month home-based aEP with and without targeting of heart rate (HR) by electrocardiogram (ECG) in people with MetS. ⋯ The combination of 2-month ambulatory supervised aEP and successive 6-month home-based aEP targeted by HR monitoring using ECG improved arterial properties in MetS subjects more than the same combination without HR targeting, leading to the greater reduction of c-r PWV and cIMT.
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Artificial intelligence (AI) and machine learning (ML) are revolutionizing human activities in various fields, with medicine and infectious diseases being not exempt from their rapid and exponential growth. Furthermore, the field of explainable AI and ML has gained particular relevance and is attracting increasing interest. ⋯ For example, they have been employed or proposed to better understand complex models aimed at improving the diagnosis and management of coronavirus disease 2019, in the field of antimicrobial resistance prediction and in quantum vaccine algorithms. Although some issues concerning the dichotomy between explainability and interpretability still require careful attention, an in-depth understanding of how complex AI/ML models arrive at their predictions or recommendations is becoming increasingly essential to properly face the growing challenges of infectious diseases in the present century.
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The study aimed to develop a sensitive and high-throughput liquid chromatography coupled with tandem mass spectrometry method to quantify concentrations of tramadol and paracetamol simultaneously in human plasma. Sample preparation involved single-step protein precipitation using methanol and two deuterated internal standards, tramadol D6 and paracetamol D4. Agilent Poroshell 120 EC-C18 (100 × 2.1 mm, 2.1 µm) analytical column was employed to achieve chromatographic separation. ⋯ A small injection volume of 1 µL, low flow rate of 440 µL/min and short analysis time of 3.5 min reduced the solvent consumption, analysis cost and system contamination. The results of method validation parameters fulfilled the acceptance criteria of bioanalytical guidelines. The method was successfully applied to a bioequivalence study of fixed-dose combination products of tramadol and paracetamol in Malaysian healthy subjects.
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Neutrophil extracellular traps (NETs) could entrap tumour cells and promote their dissemination and metastasis. Further analysis of NETs-related molecules is expected to provide a new strategy for prognosis prediction and treatment of lung adenocarcinoma (LUAD) patients. ⋯ In conclusion, this model is a new and effective prognostic and efficacy predictive biomarker, FAM66C plays an oncogene role in the process of LUAD development. It may provide a new theoretical basis for the clinical diagnosis and treatment in LUAD patients in early stage.