This paper proposes a model-based method to quantitatively measure baroreflex sensitivity in autonomic nervous regulation of cardiovascular system. The method measures the continuous blood pressure and heart rate in orthostatic scenario, models dynamics of the baroreflex firing rate, solves parameters by optimization of measured blood pressure and heart rate variations. With this model, we can get the baroreflx sensitivity (BRS) inner indicators to evaluate the status of the autonomic nervous regulation system. Experimental results have shown the validation of the quantitative measures and the effectiveness of the method.
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http://dx.doi.org/10.1109/EMBC.2016.7591284 | DOI Listing |
Comput Biol Med
January 2025
Department of Pharmacy and Yonsei Institute of Pharmaceutical Sciences, Yonsei University, Incheon, Republic of Korea; Department of Pharmaceutical Medicine and Regulatory Science, Yonsei University, Incheon, Republic of Korea; Graduate Program of Industrial Pharmaceutical Science, Yonsei University, Incheon, Republic of Korea; Department of Integrative Biotechnology, Yonsei University, Incheon, Republic of Korea. Electronic address:
Background: Erlotinib is a potent first-generation epidermal growth factor receptor tyrosine kinase inhibitor. Due to its proximity to the upper limit of tolerability, dose adjustments are often necessary to manage potential adverse reactions resulting from its pharmacokinetic (PK) variability.
Methods: Population PK studies of erlotinib were identified using PubMed databases.
Int J Neuropsychopharmacol
January 2025
Center for Drug Clinical Research, Shanghai University of Traditional Chinese Medicine, No.1200 Cailun Road, Shanghai 201203, China.
Objective: This study aims to quantitatively evaluate the efficacy and safety of various treatment regimens for treatment-resistant depression (TRD) across oral, intravenous, and intranasal routes to inform clinical guidelines.
Methods: A systematic review identified randomized controlled trials on TRD, with efficacy measured by changes in the Montgomery-Åsberg Depression Rating Scale (MADRS). We developed pharmacodynamic and covariate models for different administration routes, using Monte Carlo simulations to estimate efficacy distribution.
J Cardiothorac Surg
January 2025
Department of Cardiology, Fujian Medical University Union Hospital, Fujian Heart Medical Center, Fujian Institute of Coronary Heart Disease, Fujian Clinical Medical Research Center for Heart and Macrovascular Disease, Fuzhou, 350001, China.
Objective: The objective of this study is to assess the predictive utility of perioperative P-wave parameters in patients with paroxysmal atrial fibrillation (PAF) undergoing catheter ablation, and to develop a predictive model using these parameters.
Methods: A total of 213 patients with PAF undergoing catheter ablation were retrospectively analyzed. P-wave parameters were measured within 3 days preoperatively and on the day postoperatively to determine their predictive significance for postoperative PAF recurrence.
Sci Rep
January 2025
Division of Critical Care Medicine, Department of Emergency Medicine, Chung-Ang University Gwangmyeong Hospital, Gwangmyeong-si, Gyeonggi-do, Republic of Korea.
The optimal duration of on-scene cardiopulmonary resuscitation (CPR) for out-of-hospital cardiac arrest (OHCA) patients remains uncertain. Determining this critical time period requires outweighing the potential risks associated with intra-arrest transport while minimizing delays in accessing definitive hospital-based treatments. This study evaluated the association between on-scene CPR duration and 30-day neurologically favorable survival based on the transport time interval (TTI) in patients with OHCA.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Biomedical Engineering, School of Life Science and Technology, Changchun University of Science and Technology, Changchun, 130022, China.
The cervical cell classification technique can determine the degree of cellular abnormality and pathological condition, which can help doctors to detect the risk of cervical cancer at an early stage and improve the cure and survival rates of cervical cancer patients. Addressing the issue of low accuracy in cervical cell classification, a deep convolutional neural network A2SDNet121 is proposed. A2SDNet121 takes DenseNet121 as the backbone network.
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