Objectives: The main purpose of this article was to clarify the relationship of anterior bone and tooth morphology with NPC. The anatomical features of the NPC region in three dimensions from coronal, axial, and sagittal directions were analyzed using CBCT and the effects of age, gender, sagittal root positions (SRPs) of central teeth, anterior overbite depth (AOD), central incisor (CI)/palatal plane (PP) angle, NPC/PP angle, and collum angles (CA) on NPC were evaluated in a group of the Turkish population.
Materials And Methods: In this retrospective study, CBCTs of a total of 330 individuals between the ages of 17 and 82 were evaluated. The effects of SRP, AOD, CI/PP angle, NPC/PP angle and CA on the anatomical features of NPC were examined on the basis of age and gender. Descriptive statistics, Kolmogorov-Smirnov, Chi-square, Wilcoxon, Mann-Whitney-U, Kruskal-Wallis, and Spearman correlation tests were used. p values of < 0.05 were accepted as statistically significant.
Results: While the SRPs, CI/PP angle, NPC/PP angle, CA, and age did not differ statistically according to NPC shape (p > 0.05), NPC shape varied according to gender and AOD (p < 0.05). It was found that cylindrical NPC (32.8%) was more common in females, while conical-shaped NPC (30.7%) was more common in males (p < 0.01). While most conical NPC was detected in individuals with Class I overbite depth, cylindrical NPCs were found in Class II and III individuals (p < 0.01).
Conclusions: The results showed that gender and AOD are influential factors on NPC shape. While conical-shaped NPC is more common in individuals with bite depth incisal, cylindrical-shaped NPC is more likely to be seen in individuals with middle and cervical thirds.
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http://dx.doi.org/10.1007/s11282-022-00647-6 | DOI Listing |
Purpose: To explore the anatomical features of left iliac vein (LIV) in non-thrombotic venous leg ulcers (VLUs) and to identify the impact of these anatomical features on VLUs based on computed tomography venography (CTV).
Methods: This is a retrospective, single-center study of a database (2021-2023) of 431 patients with non-thrombotic chronic venous insufficiency. According to CEAP clinical (C) classifications, cases of C6 and C2 were included for analysis as case and control groups.
Int J Gynecol Pathol
January 2025
Department of Pathology, Belfast Health and Social Care Trust, Belfast, Northern Ireland, UK.
Pure ductal-type mesonephric remnants in the uterine cervix are rare. We report an unusual case in a 31-yr-old of cervical mesonephric remnants of predominantly ductal type exhibiting seminal vesicle-like differentiation in a female-to-male transgender patient receiving long-term testosterone therapy. To the best of our knowledge, this phenomenon has not been previously reported.
View Article and Find Full Text PDFCraniofacial development gives rise to the complex structures of the face and involves the interplay of diverse cell types. Despite its importance, our understanding of human-specific craniofacial developmental mechanisms and their genetic underpinnings remains limited. Here, we present a comprehensive single-nucleus RNA sequencing (snRNA-seq) atlas of human craniofacial development from craniofacial tissues of 24 embryos that span six key time points during the embryonic period (4-8 post-conception weeks).
View Article and Find Full Text PDFStudy Objectives: Sleep deficiency is associated with Alzheimer's disease (AD) pathogenesis. We examined the association of sleep architecture with anatomical features observed in AD: (1) atrophy of hippocampus, entorhinal, inferior parietal, parahippocampal, precuneus, and cuneus regions ("AD-vulnerable regions") and (2) cerebral microbleeds.
Methods: In 271 participants of the Atherosclerosis Risk in the Communities Study, we examined the association of baseline sleep architecture with anatomical features identified on brain MRI 13∼17 years later.
Bone Rep
March 2025
Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, United States of America.
High resolution peripheral quantitative computed tomography (HRpQCT) offers detailed bone geometry and microarchitecture assessment, including cortical porosity, but assessing chronic kidney disease (CKD) bone images remains challenging. This proof-of-concept study merges deep learning and machine learning to 1) improve automatic segmentation, particularly in cases with severe cortical porosity and trabeculated endosteal surfaces, and 2) maximize image information using machine learning feature extraction to classify CKD-related skeletal abnormalities, surpassing conventional DXA and CT measures. We included 30 individuals (20 non-CKD, 10 stage 3 to 5D CKD) who underwent HRpQCT of the distal and diaphyseal radius and tibia and contributed data to develop and validate four different AI models for each anatomical site.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!