Asian Americans (AAs) are more likely to use complementary and alternative medicine (CAM) compared to other race/ethnicities, yet previous studies have conflicting results. The 2012 National Health Interview Survey data was analyzed to investigate AA's (n = 2214) CAM use for treatment. AAs were divided into four subgroups: Chinese, Asian Indian, Filipino, and Other Asian. Only 9% of AAs reported using CAM for treatment, with 6% indicating CAM use specifically for chronic conditions. This could be a form of medical pluralism, a mixture of Eastern and Western health approaches. The "Other Asian" subgroup reported highest use of CAM for treatment. Significant predictors included age (≥ 65 years) and high educational attainment (≥ college degree). Sociodemographic factors were also significant predictors within Asian subgroups. Further investigation of this and other forms of medical pluralism among AAs are needed to explore potential cofounders and risks like underreporting, CAM schedules/dosages, cultural influences, and CAM's impact on one's health.
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http://dx.doi.org/10.1007/s10903-019-00936-z | DOI Listing |
Pharmacol Res
January 2025
Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, UK. Electronic address:
There is an urgent need for mechanistically novel and more efficacious treatments for schizophrenia, especially those targeting negative and cognitive symptoms with a more favorable side-effect profile. Drug repurposing-the process of identifying new therapeutic uses for already approved compounds-offers a promising approach to overcoming the lengthy, costly, and high-risk process of traditional CNS drug discovery. This review aims to update our previous findings on the clinical drug repurposing pipeline in schizophrenia.
View Article and Find Full Text PDFJ Hand Surg Eur Vol
January 2025
Department of Orthopedics and Traumatology, Başakşehir Çam ve Sakura City Hospital, İstanbul, Turkey.
Early repair of flexor tendon injuries is ideal, but delays are common. We studied the outcomes of flexor tendon repairs delayed from 5 days to 6 months and carried out under wide-awake local anaesthesia with no tourniquet (WALANT). Twenty-four patients (29 fingers) who underwent primary flexor tendon repair on zone II using a four- to six-strand core suture technique, followed by controlled early active motion therapy.
View Article and Find Full Text PDFBMC Oral Health
January 2025
Department of Periodontics, Affiliated Hospital of Medical School, Nanjing Stomatological Hospital, Research Institute of Stomatology, Nanjing University, Nanjing, China.
Background: The severity of furcation involvement (FI) directly affected tooth prognosis and influenced treatment approaches. However, assessing, diagnosing, and treating molars with FI was complicated by anatomical and morphological variations. Cone-beam computed tomography (CBCT) enhanced diagnostic accuracy for detecting FI and measuring furcation defects.
View Article and Find Full Text PDFAngew Chem Int Ed Engl
January 2025
Oak Ridge National Laboratory, Chemical Sciences Division, UNITED STATES OF AMERICA.
Antimony-119 (119Sb) is one of the most attractive Auger-electron emitters identified to date, but it remains practically unexplored for targeted radiotherapy because no chelators have been identified to stably bind this metalloid in vivo. In a departure from current studies focused on chelator development for Sb(III), we explore the chelation chemistry of Sb(V) using the tris-catecholate ligand TREN-CAM. Through a combination of radiolabeling, spectroscopic, solid-state, and computational studies, the radiochemistry and structural chemistry of TREN-CAM with 1XX/natSb(V) were established.
View Article and Find Full Text PDFCureus
December 2024
Department of Orthodontics, School of Dentistry, Shahid Beheshti University of Medical Sciences, Tehran, IRN.
Background Orthodontic diagnostic workflows often rely on manual classification and archiving of large volumes of patient images, a process that is both time-consuming and prone to errors such as mislabeling and incomplete documentation. These challenges can compromise treatment accuracy and overall patient care. To address these issues, we propose an artificial intelligence (AI)-driven deep learning framework based on convolutional neural networks (CNNs) to automate the classification and archiving of orthodontic diagnostic images.
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