Our objective was to explore the utility of salivary telomere length (sTL) as an early indicator of neighborhood-level social environmental risk during child development. We therefore tested the hypothesis that sTL would be associated with markers of social stress exposure in children. Children age 4-14 from 87 neighborhoods were recruited through five urban schools in New Orleans, Louisiana, U.S. Data were collected at the level of the child, family/household, and neighborhood. DNA was obtained from saliva using commercially available kits and sTL was determined for 104 children using quantitative PCR. Analysis was performed on 99 children who had complete data including sTL, social environmental stress, and additional covariates. The mean sTL value was 7.4 T/S (telomere signal/single-copy signal) ratio units (±2.4, range = 2.5-18.0), and 4.7% of the variance in sTL was attributed to differences across neighborhoods. Children living in neighborhoods characterized by high disorder had an sTL value 3.2 units lower than children not living in high disordered environments (p < 0.05) and their odds of having low relative sTL (defined as <1 standard deviation below standardized Z-score mean) values was 3.43 times that of children not living in high disorder environments (adjusted OR = 3.43, 95% CI = 1.22, 9.62). Our findings are consistent with previous studies in adults demonstrating a strong link between psychosocial stress and sTL obtained from peripheral blood, consistent with previous studies in youth demonstrating an association between early life stress and sTL obtained from buccal cell DNA and offer increased support for the hypothesis that sTL represents a non-invasive biological indicator of psychosocial stress exposure (i.e., neighborhood disorder) able to reflect differences in stress exposure levels even in young children.
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http://dx.doi.org/10.1016/j.socscimed.2013.02.030 | DOI Listing |
Biomimetics (Basel)
January 2025
Department of Healthcare Sciences, Faculty of Dental Laboratory Science and Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Republic of Korea.
This study evaluated the internal and marginal accuracy (trueness and precision) of zirconia laminate veneers fabricated using the DLP printing and milling method, employing 3D analysis software program. The maxillary central incisor tooth of a typodont model was prepared by a dentist and scanned using a desktop scanner. An anatomical zirconia laminate was designed using computer-aided design (CAD) software and saved in a standard tessellation language (STL) format.
View Article and Find Full Text PDFJ Mech Behav Biomed Mater
January 2025
Department of Civil and Environmental Engineering, University of Connecticut, Storrs, CT, 06269, USA. Electronic address:
This study aims to investigate the effects of material compatibility, variable cooling rates, and crown geometry on thermal stress development in porcelain-veneered lithium disilicate (PVLD) and porcelain-veneered zirconia (PVZ) dental crown systems, and subsequently anticipate parameters for their optimum performance. An anatomically correct 3D crown model was developed from STL files generated using 3D scans of the experimental crown sample. Next, the viscoelastic finite element model (VFEM) based on the 3D crown model was developed and validated for anatomically correct bilayer PVLD and PVZ crown systems.
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January 2025
Department of Reconstructive Dentistry, UZB University Center for Dental Medicine Basel, University of Basel, 4058 Basel, Switzerland.
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View Article and Find Full Text PDFJ Clin Med
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Mandibular gingival squamous cell carcinoma (SCC) is the second most common oral cancer after tongue cancer. As these carcinomas often invade the mandible early, accurately defining the resection extent is important. This report highlights the use of preoperative virtual surgery data, computer-aided design and manufacturing (CAD/CAM) technology, surgical guidance, and extended reality (XR) support in achieving highly accurate marginal mandibulectomy without recurrence or metastasis.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Seamless Trans-X Lab (STL), School of Integrated Technology, Yonsei University, Incheon 21983, Republic of Korea.
In the domain of autonomous driving, trajectory prediction plays a pivotal role in ensuring the safety and reliability of autonomous systems, especially when navigating complex environments. Unfortunately, trajectory prediction suffers from uncertainty problems due to the randomness inherent in the driving environment, but uncertainty quantification in trajectory prediction is not widely addressed, and most studies rely on deep ensembles methods. This study presents a novel uncertainty-aware multimodal trajectory prediction (UAMTP) model that quantifies aleatoric and epistemic uncertainties through a single forward inference.
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