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Dihydroavenanthramide D Enhances Skin Barrier Function through Upregulation of Epidermal Tight Junction Expression.
Curr Issues Mol Biol
August 2024
LG Household & Health Care (LG H&H) R&D Center, 70 Magokjoongang 10-ro, Gangseo-gu, Seoul 07795, Republic of Korea.
Skin barrier dysfunction and thin epidermis are hallmarks of sensitive skin and contribute to premature aging. Avenanthramides are the primary bioactive components of colloidal oatmeal, a commonly used treatment to enhance skin barrier function. This study investigated the relationship between skin barrier function and epidermal characteristics and explored the potential of dihydroavenanthramide D (dhAvD), a synthetic avenanthramide, to improve the skin barrier.
View Article and Find Full Text PDFAortic growth after arch reconstruction with patch augmentation: a 2-decade experience.
Interdiscip Cardiovasc Thorac Surg
December 2023
Department of Cardiac Surgery, Boston Children's Hospital, Boston, MA, USA.
Objectives: Optimal aortic sizing during aortic arch reconstruction remains unknown. Negative effects of arch under- or oversizing are well-published. We aimed to characterize longitudinal aortic growth after patch-augmented arch reconstruction to identify the initial reconstructed arch size that results in normal mid-term arch dimensions.
View Article and Find Full Text PDFDeep Learning Reconstruction Enables Prospectively Accelerated Clinical Knee MRI.
Radiology
April 2023
From the Department of Radiology, New York University Grossman School of Medicine, 650 1st Ave, New York, NY 10016 (P.M.J., D.J.L., J.S.B., M.K., G.C., E.A., M.S., W.R.W., L.C., D.K.S., M.P.R., F.K.); Meta AI Research (FAIR), Menlo Park, Calif (J.Z., C.L.Z., A.S.); Meta AI Research, New York, NY (M.M.); Institute of Computer Graphics and Vision, Graz University of Technology, Graz, Austria (T.P.); and Faculty of Engineering, Friedrich Alexander University Erlangen-Nurnberg (FAU), Erlangen, Germany (F.K.).
Background MRI is a powerful diagnostic tool with a long acquisition time. Recently, deep learning (DL) methods have provided accelerated high-quality image reconstructions from undersampled data, but it is unclear if DL image reconstruction can be reliably translated to everyday clinical practice. Purpose To determine the diagnostic equivalence of prospectively accelerated DL-reconstructed knee MRI compared with conventional accelerated MRI for evaluating internal derangement of the knee in a clinical setting.
View Article and Find Full Text PDFExploring the Acceleration Limits of Deep Learning Variational Network-based Two-dimensional Brain MRI.
Radiol Artif Intell
November 2022
Department of Radiology, NYU School of Medicine-NYU Langone Health, New York, NY (A.R., E.L., D.K.S., Y.W.L.); Meta AI, Facebook, 770 Broadway, 2nd Floor, New York, NY 10003 (M.J.M.); Stealth, New York, NY (T.M.); Department of Artificial Intelligence Research, Meta AI, Facebook, Menlo Park, Calif (A.S.); and Department Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany (F.K.).
Article Synopsis
- The study assesses the effectiveness of deep learning techniques in reconstructing brain MRI images with significant acceleration, targeting both general-purpose imaging and potential screenings.
- During the research, a model was trained on nearly 5,900 MRI images, demonstrating that radiologists found images to be of sufficient quality for general use at up to 4× acceleration and for screening at up to 14× acceleration.
- The results indicate that deep learning enables substantial image acceleration while maintaining quality, especially highlighting a higher threshold for screenings compared to standard diagnostic imaging.
Patient-reported impairment following TKA is reduced when a computationally simulated predicted ideal alignment is achieved.
Knee Surg Sports Traumatol Arthrosc
March 2023
360MedCare, Suite 3, Building 1/20 Bridge St, Pymble, Sydney, NSW, 2073, Australia.
Purpose: Joint dynamics following Total Knee Arthroplasty (TKA) may influence patient-reported outcome. Simulations allow many knee alignment approaches to a single patient to be considered prior to surgery. The simulated kinematics can be matched to patient-reported outcome to predict kinematic patterns most likely to give the best outcome.
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