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Integrating Retinal Segmentation Metrics with Machine Learning for Predictions from Mouse SD-OCT Scans.
Curr Eye Res
January 2025
Department of Ophthalmology, Edward S. Harkness Eye Institute, Columbia University, Vagelos College of Physicians and Surgeons, New York, NY, USA.
Purpose: This study aimed to initially test whether machine learning approaches could categorically predict two simple biological features, mouse age and mouse species, using the retinal segmentation metrics.
Methods: The retinal layer thickness data obtained from C57BL/6 and DBA/2J mice were processed for machine learning after segmenting mouse retinal SD-OCT scans. Twenty-two models were trained to predict the mouse groups.
-Functionalization of Pillar[4]arene[1]benzoquinone Monoxime via Selective 1,4-Addition of Grignard Reagents.
Org Lett
January 2025
School of Physical Science and Technology, Shanghai Tech University, Shanghai 201210, P. R. China.
-functionalization of pillar[]arenes has been a formidable challenge, partially due to the fragility of their macrocyclic skeletons. In this concise report, we describe a facile synthetic method for monoarylation/alkylation at the position to the oxime functionality in pillar[4]arene[1]benzoquinone monoxime () via addition of Grignard reagents. The described method enables the creation of various mono--alkyl/aryl-substituted pillar[5]arene derivatives that were previously inaccessible.
View Article and Find Full Text PDFCost-Utility Analysis of LifeVest® in Post-Myocardial Infarction Patients at Risk of Sudden Cardiac Death in England.
Pharmacoecon Open
January 2025
Optimax Access Ltd, Kenneth Dibben House, Enterprise Rd, Chilworth, Southampton University Science Park, Southampton, UK.
Background: Patients with a left ventricular ejection fraction ≤ 35% are at increased risk of sudden cardiac death (SCD) within the first months after a myocardial infarction (MI). The wearable cardioverter defibrillator (WCD) is an established, safe and effective solution which can protect patients from SCD during the first months after an MI, when the risk of SCD is at its peak. This study aimed to evaluate the cost-effectiveness of WCD combined with guideline-directed medical therapy (GDMT) compared to GDMT alone, after MI in the English National Health Service (NHS).
View Article and Find Full Text PDFDenseSeg: joint learning for semantic segmentation and landmark detection using dense image-to-shape representation.
Int J Comput Assist Radiol Surg
January 2025
Medical Informatics, University of Lübeck, Ratzeburger Allee 160, 23562, Lübeck, Germany.
Purpose: Semantic segmentation and landmark detection are fundamental tasks of medical image processing, facilitating further analysis of anatomical objects. Although deep learning-based pixel-wise classification has set a new-state-of-the-art for segmentation, it falls short in landmark detection, a strength of shape-based approaches.
Methods: In this work, we propose a dense image-to-shape representation that enables the joint learning of landmarks and semantic segmentation by employing a fully convolutional architecture.
Innovative microbial activators for enhanced bioremediation of oil-contaminated soils: mechanistic insights.
World J Microbiol Biotechnol
January 2025
College of Chemistry and Chemical Engineering, Xi'an Shiyou University, Xi'an, 710065, China.
This paper developed an efficient microbial activator formula and conducted an in-depth study on its efficacy and mechanism in promoting the degradation of petroleum hydrocarbons in oil-contaminated soil. A 60-day microbial remediation experiment conducted on oily soil revealed that the microbial activators significantly boosted the activities of dehydrogenase and catalase, subsequently speeding up the degradation of petroleum hydrocarbons in the soil. The overall degradation rate reached as high as 71.
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