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Irreversible perturbations in Langevin dynamics have been widely recognized for their role in accelerating convergence in simulations of multi-modal distributions π (θ) . A commonly used and easily computed standard irreversible perturbation is J ∇ log π (θ) , where J is a skew-symmetric matrix. However, Langevin dynamics employing a fixed-scale standard irreversible perturbation encounter a trade-off between local exploitation and global exploration, associated with small and large scales of standard irreversible perturbation, respectively. To address this trade-off, we introduce the adaptive irreversible perturbations Langevin dynamics, where the scale of the standard irreversible perturbation changes adaptively. Through numerical examples, we demonstrate that adaptive irreversible perturbations in Langevin dynamics can enhance performance compared to fixed-scale irreversible perturbations. [ABSTRACT FROM AUTHOR]

Background: Atrioventricular block (AVB) is thought to be a rare cardiovascular complication of the coronavirus disease 2019 (COVID-19), though limited data are available beyond case reports. We aim to describe the baseline characteristics, proteomics profile, and outcomes for patients with COVID-19-related AVB., Methods: We prospectively recruited patients diagnosed with COVID-19-related AVB between November 2022 and March, 2023. Inclusion criteria were hospitalization for COVID-19 with the diagnosis of AVB. A total of 24 patients diagnosed with COVID-19 without AVB were recruited for control. We analyzed patient characteristics and outcomes and performed a comparative proteomics analysis on plasma samples of those patients and controls., Results: A total of 17 patients diagnosed with COVID-19-related AVB and 24 individuals diagnosed with COVID-19 infection without AVB were included. Among patients with COVID-19-related AVB, the proportion of concurrent pneumonia was significantly higher than controls (7/17 versus 2/24, p < 0.05). All 17 AVB patients (9 of permanent AVB, 8 of paroxysmal AVB) received permanent pacemaker implantation. No procedural-related complication occurred. In laboratory tests, the level of biomarkers indicating myocardial damage were substantially higher than controls, including high-sensitivity cardiac troponin-I (median 0.005 versus 0.002 ng/mL, p < 0.05), myoglobulin (median 39.0 versus 27.6 ng/mL, p < 0.05), and MB isoenzyme of creatine kinase (median 1.2 versus 0.8 U/L, p < 0.05). The level of N-terminal pro-b-type natriuretic peptide (median 241.0 versus 33.5 pg/mL, p < 0.05), C-reactive protein (median 4.8 versus 2.0 mg/L, p < 0.05), D-dimer (median 1.2 versus 0.2 µg/mL, p < 0.05), left ventricular end-diastolic diameter (median 49.3 versus 45.7 mm, p < 0.05) in patients with COVID-19-related AVB were significantly higher than controls. The level of albumin (median 41.9 versus 44.5 g/L, p < 0.05) was significantly lower than controls. In comparative proteomics analysis, we identified 397 human proteins. Several significantly altered plasma proteins related to inflammatory response (Serum amyloid A protein, C-reactive protein, Protein Adenosine 5'-monophosphate-activated protein kinase (AMPK), Alpha-2-macroglobulin), complement and coagulation cascades (Tetranectin, haptoglobin), and immune response (Neutrophil defensin 3, Fibrinogen beta chain) may contribute to the pathogenesis of COVID-19-related AVB., Conclusions: Patients with COVID-19-related AVB are more prone to have myocardial damage and concurrent pneumonia. Through laboratory tests and comparative proteomics analysis, we identified several differential expressed proteins (Serum amyloid A protein, Tetranectin, Neutrophil defensin 3) releated to the inflammatory response, complement and coagulation cascades, and immune response, which provides evidence of potential biomarkers and sheds light on the pathogenesis of COVID-19-related AVB., Competing Interests: The authors declare no conflict of interest., (Copyright: © 2024 The Author(s). Published by IMR Press.)

Parameter identification involves the estimation of undisclosed parameters within a system based on observed data and mathematical models. In this investigation, we employ DAISY to meticulously examine the structural identifiability of parameters of a within-host SARS-CoV-2 epidemic model, taking into account an array of observable datasets. Furthermore, Monte Carlo simulations are performed to offer a comprehensive practical analysis of model parameters. Lastly, sensitivity analysis is employed to ascertain that decreasing the replication rate of the SARS-CoV-2 virus and curbing the infectious period are the most efficacious measures in alleviating the dissemination of COVID-19 amongst hosts., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)