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Subject-specific mathematical models for prediction of physiological parameters such as blood volume, cardiac output, and blood pressure in response to hemorrhage have been developed. studies using these models may provide an effective tool to generate pre-clinical safety evidence for medical devices and help reduce the size and scope of animal studies that are performed prior to initiation of human trials. To achieve such a goal, the credibility of the mathematical model must be established for the purpose of pre-clinical testing. In this work, the credibility of a subject-specific mathematical model of blood volume kinetics intended to predict blood volume response to hemorrhage and fluid resuscitation during fluid therapy was evaluated. A workflow was used in which: (i) the foundational properties of the mathematical model such as structural identifiability were evaluated; (ii) practical identifiability was evaluated both pre- and post-calibration, with the pre-calibration results used to determine an optimal splitting of experimental data into calibration and validation datasets; (iii) uncertainty in model parameters and the experimental uncertainty were quantified for each subject; and (iv) the uncertainty was propagated through the blood volume kinetics model and its predictive capability was evaluated validation tests. The mathematical model was found to be structurally identifiable. Pre-calibration identifiability analysis led to splitting the 180 min of time series data per subject into 50 and 130 min calibration and validation windows, respectively. The average root mean squared error of the mathematical model was 12.6% using the calibration window of (0 min, 50 min). Practical identifiability was established post-calibration after fixing one of the parameters to a nominal value. In the validation tests, 82 and 75% of the subject-specific mathematical models were able to correctly predict blood volume response when predictive capability was evaluated at 180 min and at the time when amount of infused fluid equals fluid loss.
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http://dx.doi.org/10.3389/fphys.2021.705222 | DOI Listing |
Alzheimers Res Ther
September 2025
Department of Neurology, Saarland University, Kirrberger Straße, 66421, Homburg/Saar, Germany.
Background: Alzheimer's disease (AD) patients and animal models exhibit an altered gut microbiome that is associated with pathological changes in the brain. Intestinal miRNA enters bacteria and regulates bacterial metabolism and proliferation. This study aimed to investigate whether the manipulation of miRNA could alter the gut microbiome and AD pathologies.
View Article and Find Full Text PDFLipids Health Dis
September 2025
Department of Gastroenterology, Weifang People's Hospital, The First Affiliated Hospital of Shandong Second Medical University, 151 Guangwen Street, Weifang, Shandong, 261000, China.
Background: Current scoring systems for hypertriglyceridaemia-induced acute pancreatitis (HTG-AP) severity are few and lack reliability. The present work focused on screening predicting factors for HTG-SAP, then constructing and validating the visualization model of HTG-AP severity by combining relevant metabolic indexes.
Methods: Between January 2020 and December 2024, retrospective clinical information for HTG-AP inpatients from Weifang People's Hospital was examined.
Ren Fail
December 2025
Department of Nephrology, Kidney Disease Medical Center, Tianjin Medical University General Hospital, National Key Clinical Specialty, Tianjin Key Medical Discipline, Tianjin, China.
Purpose: This study aimed to investigate the association between body roundness index (BRI) and deaths from all causes and cardiovascular disease (CVD) in participants with chronic kidney disease (CKD).
Materials And Methods: The data was sourced from the National Health and Nutrition Examination Survey (NHANES) 1999-2018. Cox proportional hazards regression along with restricted cubic splines were applied to assess the associations of BRI with deaths from all causes and CVD in individuals with CKD.
Ren Fail
December 2025
Department of Rehabilitation Medicine, Shanghai University of Medicine and Health Sciences Affiliated Zhoupu Hospital, Shanghai, China.
Background: Depression is a common mental disorder in hemodialysis patients. The present study aimed to identify subgroups of patients receiving hemodialysis based on depression and explore the influencing factors in a multicenter hemodialysis population in China.
Methods: A total of 1,090 hemodialysis patients (682 men, mean aged 61.
Metabolomics
September 2025
Toxalim (Research Centre in Food Toxicology), Université de Toulouse, INRAE, ENVT, INP-Purpan, UPS, Toulouse, France.
Introduction: Initially developed for transcriptomics data, pathway analysis (PA) methods can introduce biases when applied to metabolomics data, especially if input parameters are not chosen with care. This is particularly true for exometabolomics data, where there can be many metabolic steps between the measured exported metabolites in the profile and internal disruptions in the organism. However, evaluating PA methods experimentally is practically impossible when the sample's "true" metabolic disruption is unknown.
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