Primary aldosteronism (PA) is one of the most common causes of secondary hypertension and is potentially curable. However, a large number of patients still undergo persistent hypertension (PHT) after unilateral adrenal surgery. This research retrospectively studied the factors associated with this clinical difficulty and established a prediction model for the postoperative PHT; Methods: 353 patients from 2014 to 2021 with PA undergoing unilateral adrenal surgery were enrolled in this study. Clinical and biochemical characteristics were reviewed and the associating factors were examined using univariate and multivariate analysis. A nomogram-based prediction model was established correspondingly; results: 46.2% (163/190) of patients had post-surgical PHT. Multivariate analysis suggested that BMI ≥ 25, diabetes, duration of hypertension, male gender, and ARR were independent predictors of PHT after surgery. The prediction model based on the nomogram showed good discrimination ability (the C index of the training group and the validation group were 0.783 and 0.769, respectively), and the calibration curves and the Hosmer-Lemeshow test were good as well. Clinical usefulness was quantified using the decision curve analysis; This nomogram is an integration of the clinical and biochemical data of patients before surgery, and is a reliable tool with high accuracy for predicting the postoperative PHT in patients with PA.
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http://dx.doi.org/10.1038/s41598-023-39028-2 | DOI Listing |
J Chem Inf Model
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School of Information Science & Engineering, Lanzhou University, Lanzhou 730000, China.
Efficient and accurate drug-target affinity (DTA) prediction can significantly accelerate the drug development process. Recently, deep learning models have been widely applied to DTA prediction and have achieved notable success. However, existing methods often encounter several common issues: first, the data representations lack sufficient information; second, the extracted features are not comprehensive; and third, most methods lack interpretability when modeling drug-target binding.
View Article and Find Full Text PDFAlzheimers Dement
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Department of Neurology, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan.
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Soft Matter
January 2025
SUPA and School of Physics and Astronomy, The University of Edinburgh, Peter Guthrie Tait Road, Edinburgh EH9 3FD, UK.
Recent theory and experiments have shown how the buildup of a high-concentration polymer layer at a one-dimensional solvent-air interface can lead to an evaporation rate that scales with time as and that is insensitive to the ambient humidity. Using phase field modelling we show that this scaling law constitutes a naturally emerging robust regime, diffusion-limited evaporation (DLE). This regime dominates the dynamical state diagram of the system, which also contains regions of constant and arrested evaporation, confirming and extending understanding of recent experimental observations and theoretical predictions.
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January 2025
Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States.
Rapid validation of newly predicted materials through autonomous synthesis requires real-time adaptive control methods that exploit physics knowledge, a capability that is lacking in most systems. Here, we demonstrate an approach to enable real-time control of thin film synthesis by combining optical diagnostics with a Bayesian state estimation method. We developed a physical model for film growth and applied the direct filter (DF) method for real-time estimation of nucleation and growth rates during pulsed laser deposition (PLD).
View Article and Find Full Text PDFFront Public Health
January 2025
School of Epidemiology and Public Health, University of Ottawa, Ottawa, ON, Canada.
Introduction: HIV self-testing (HIVST) is an innovative strategy that has been shown to increase uptake of HIV testing compared to conventional facility-based testing. HIVST implementation with digital-based supports may help facilitate testing accessibility and linkage to care after a reactive self-test. Economic evidence around community-based implementation of HIVST is growing; however, economic evidence around digital-based HIVST approaches remains limited.
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