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Temporal variations in and predictive values of ABG results prior to in-hospital cardiac arrest.
J Med Surg Public Health
December 2024
College of Nursing, Michigan State University, Michigan, Life Science, 1355 Bogue St Room A218, East Lansing, MI 48824, USA.
In-hospital cardiac arrest (IHCA) has been understudied relative to out-of-hospital cardiac arrest. Further, studies of IHCA have mainly focused on a limited number of pre-arrest patient characteristics (e.g.
View Article and Find Full Text PDFBackground: The American Heart Association (AHA), in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, nutrition, sleep, and obesity) and health factors (cholesterol, blood pressure, glucose control, and metabolic syndrome) that contribute to cardiovascular health. The AHA Heart Disease and Stroke Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, brain health, complications of pregnancy, kidney disease, congenital heart disease, rhythm disorders, sudden cardiac arrest, subclinical atherosclerosis, coronary heart disease, cardiomyopathy, heart failure, valvular disease, venous thromboembolism, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).
Methods: The AHA, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States and globally to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing.
Melatonin, modulation of hypothalamic activity, and reproduction.
Vitam Horm
January 2025
Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Ciudad Autónoma de Buenos Aires, Argentina; Centro de Estudios Biomédicos Básicos, Aplicados y Desarrollo (CEBBAD), Universidad Maimónides, Ciudad Autónoma de Buenos Aires, Argentina. Electronic address:
Light is the most reliable environmental cue allowing animals to breed successfully when conditions are optimal. In seasonal breeders, photoperiod (length of daylight) information is sensed by the eyes and transmitted to the suprachiasmatic nucleus, the master clock region located in the hypothalamus. This structure has a 24-h firing rhythm involving a cycle of clock protein synthesis and degradation, and provides the timing to synchronize the synthesis and release of melatonin, the chemical signal that transduces the photoperiod information.
View Article and Find Full Text PDFRESPIRATORY SURVEILLANCE AND INWARD RECTIFIER POTASSIUM CHANNEL EXPRESSION IN LUNG TISSUE WITHIN AN EXPERIMENTAL EPILEPSY MODEL.
Eur J Pharmacol
January 2025
Department of Histology and Embryology, Faculty of Medicine, Yozgat Bozok University, Yozgat, 66100, Turkey.
Epilepsy is characterized by neuronal discharges that occur as a result of disruption of the excitatory and inhibitory balance of the brain due to functional and structural changes. It has been shown in the literature that this neurological disorder may be related to the expression of ion channels. Any defect in the function or expression mechanism of these channels can lead to various neuronal disorders such as epilepsy.
View Article and Find Full Text PDFAge group classification based on optical measurement of brain pulsation using machine learning.
Sci Rep
January 2025
Research Unit of Health Sciences and Technology, University of Oulu, Oulu, Finland.
Optical techniques, such as functional near-infrared spectroscopy (fNIRS), contain high potential for the development of non-invasive wearable systems for evaluating cerebral vascular condition in aging, due to their portability and ability to monitor real-time changes in cerebral hemodynamics. In this study, thirty-six healthy adults were measured by single channel fNIRS to explore differences between two age groups using machine learning (ML). The subjects, measured during functional magnetic resonance imaging (fMRI) at Oulu University Hospital, were divided into young (age ≤ 32) and elderly (age ≥ 57) groups.
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