Vitamin K antagonists have been the only available oral anticoagulant therapy for decades until the recent introduction of novel (new) oral anticoagulants. This breakthrough provides patients with alternative treatment choices that have predictable pharmacokinetics and do not require routine coagulation monitoring. Though more convenient from patient perspective, these drugs have distinct pharmacological properties that are particularly important to recognize when transitioning anticoagulant therapies. The following review focuses on transitioning to and from the novel oral anticoagulants, employing a practical pharmacokinetic- and pharmacodynamic-based approach.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1007/s11239-014-1060-y | DOI Listing |
Introduction: Age-associated depletion in nicotinamide adenine dinucleotide (NAD+) concentrations has been implicated in metabolic, cardiovascular, and neurodegenerative disorders. Supplementation with NAD+ precursors, such as nicotinamide riboside (NR), offers a potential therapeutic avenue against neurodegenerative pathologies in aging, Alzheimer's disease, and related dementias. A crossover, double-blind, randomized placebo (PBO) controlled trial was conducted to test the safety and efficacy of 8 weeks' active treatment with NR (1 g/day) on cognition and plasma AD biomarkers in older adults with subjective cognitive decline and mild cognitive impairment.
View Article and Find Full Text PDFBackground: Continuous anticoagulation based on the CHA2DS2-VASc score is recommended to prevent embolism caused by atrial fibrillation (AF), but it does not consider AF episodes. The Apple Watch's continuous heart rhythm monitoring and fast-acting direct oral anticoagulants (DOACs) could enable precise, episode-tailored anticoagulation, reducing bleeding risks while preventing stroke. This study evaluates Apple Watch-guided personalized anticoagulation therapy, adjusting DOAC usage based on real-time AF detection.
View Article and Find Full Text PDFCureus
December 2024
Orthodontics, Sardar Begum Dental College and Hospital, Gandhara University, Peshawar, PAK.
Background Orthodontic treatment, while primarily focusing on correcting dental alignment and occlusion, has been increasingly validated for its potential impact on broader aspects of oral health and general well-being: its potential influence on body weight. While the mechanical effects of orthodontic appliances are well documented in the literature, their potential behavioral impact on weight loss remains underexplored. Beyond its primary role in correcting dental alignment, our study has unveiled a lesser-known benefit: its potential to aid in weight reduction among individuals who have already struggled through conventional methods.
View Article and Find Full Text PDFPest Manag Sci
January 2025
College of Materials and Chemistry and School of Plant Protection, Anhui Agricultural University, Hefei, China.
Background: Development of novel chiral antifungal agents for effective control of plant pathogens is urgently needed. In this study, a series of pyrazol-5-yl-benzamide derivatives containing chiral oxazoline moiety were rationally designed and developed based on molecular docking.
Results: The in vitro antifungal assay results indicated that compounds (rac)-4h (R = Et), (S)-4 h (R = S-Et) and (R)-4 h (R = R-Et) exhibited remarkable antifungal activities against Valsa mali with median effective concentration (EC) values of 0.
Oral Dis
January 2025
State Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases & Department of Head and Neck Oncology Surgery, West China Hospital of Stomatology, Sichuan University, Chengdu, Sichuan, China.
Objectives: This study introduces a novel classification approach that combines convolutional neural network (CNN) and Raman mapping to differentiate between tongue squamous cell carcinoma (TSCC) and non-tumorous tissue, as well as to identify different histological grades of TSCC.
Materials And Methods: In this study, 240 Raman mappings data from 30 tissue samples were collected from 15 patients who had undergone surgical resection for TSCC. A total of 18,000 sub-mappings extracted from Raman mappings were then used to train and test a CNN model, which extracted feature representations that were subsequently processed through a fully connected network to perform classification tasks based on the Raman mapping data.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!