Objective: The objective is to comparatively assess the impact strength and flexural strength of polyether ether ketone (PEEK) vs. computer-aided design/computer-aided manufacturing (CAD/CAM) polymethyl methacrylate denture base material.
Methods: A total of 90 samples were fabricated with traditional heat cure PMMA, PEEK, and CAD/CAM PMMA and divided into three groups of 30 samples each. The impact strength of all the samples was measured using an Izod impact tester with a pendulum in the air at 23±2°C. A three-point bending test was used in a Universal Testing Machine to assess the flexural strength of all the samples. The impact strength and flexural strength mean values were computed using a one-way ANOVA test.
Result: Impact strength and flexural strength of PEEK (IS=10.22±1.25 kJ/m and FS=120±8.0 MPa) is almost identical to CAD/CAM PMMA sample (IS=9.595±3.313 kJ/m and FS=118.11±5.00 MPa) whereas for conventional heat cure PMMA (IS=4.00±.011 kJ/m and FS=75.4±4.50 MPa) the values are least among the three.
Conclusion: PEEK or CAD/CAM PMMA share almost identical and superior mechanical properties, and both can be used as better alternatives for complete denture fabrication rather than using conventional heat cure PMMA.
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http://dx.doi.org/10.7759/cureus.47929 | DOI Listing |
BMC Health Serv Res
January 2025
Department of International Health, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, 21205, USA.
Background: Since the inception of the ASHAs in the year 2005, their work horizons have increased from Reproductive, Maternal, Newborn, Child, and Adolescent health (RMNCH + A), Communicable and Non-Communicable Diseases (CD & NCD) to oral health, ophthalmologic care, and other supportive community level healthcare services. The present literature lacks comprehensive understanding and synthesis of domain-wise knowledge of ASHAs and the factors affecting their knowledge. Therefore, this study aimed to synthesize and collate the relevant evidence to understand the overall knowledge of ASHAs.
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January 2025
School of Nursing, National Taipei University of Nursing and Health Sciences, Taipei, Taiwan.
Background: The global aging population has increased dynapenia prevalence, leading to mobility issues and poor sleep quality among older adults. Despite its impact, research on sleep quality in dynapenic outpatients is limited. This study investigates how physiological status, community participation, and daily activity function influence sleep quality in this group.
View Article and Find Full Text PDFSci Rep
January 2025
Shanghai Frontiers Science Research Center of Advanced Textiles, College of Textiles, Donghua University, Shanghai, 201620, China.
With the rapid development of industrialization and urbanization, the impact of noise on people's health has become an increasingly serious issue, but it is still a challenge for the reducing the noise due to its complex property. Textiles with many loose porous structures have gained much significant attentions, thus chenille yarns with plush fibers on the surface, and polyester monofilament were chosen to fabricate the integrated knitting yarns, and their fundamental and mechanical properties were fully evaluated. The results showed that the diameter and braiding angle of the blended yarns decreased with the increase of pitch, resulting in a linear correlation of R > 0.
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January 2025
Laboratory of Exercise and Neurobiology, School of Physical Education and Sports Science, South China Normal University, Guangzhou, 510006, Guangdong, China.
Repeated closed-head injuries (rCHI) from activities like contact sports, falls, military combat, and traffic accidents pose a serious risk due to their cumulative impact on the brain. Often, rCHI is not diagnosed until symptoms of irreversible brain damage appear, highlighting the need for preventive measures. This study assessed the prophylactic efficacy of remote photobiomodulation (PBM) targeted at the lungs against rCHI-induced brain injury and associated behavioral deficits.
View Article and Find Full Text PDFJ Thromb Haemost
January 2025
Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini 4, 20090 Pieve Emanuele, Milan, Italy; IRCCS Humanitas Research Hospital - via Manzoni 56, 20089 Rozzano, Milan, Italy. Electronic address:
Artificial intelligence (AI) is rapidly advancing our ability to identify and interpret genetic variants associated with coagulation factor deficiencies. This review introduces AI, with a specific focus on machine learning (ML) methods, and examines its applications in the field of coagulation genetics over the past decade. We observed a significant increase in AI-related publications, with a focus on hemophilia A and B.
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