CDKN2A is the most common, most penetrant gene whom germline mutations predisposing to cutaneous familial melanoma (FAM). Multiple primary melanoma (MPM), early age at onset, >2 affected members and pancreatic cancer are consistent features predicting positive test. However, the impact that cumulative clinical features have on the likelihood of molecular testing is unknown. In this work, genotype-phenotype correlations focused on selected clinical features were performed in 100 Italian FAM unrelated patients. Molecular studies of CDKN2A mutations were performed by direct sequencing. Statistical study included multiple correspondence analysis, uni- and multivariate analyses, and individual patient's probability calculation. MPM, >2 affected family members, Breslow thickness >0.4mm, and age at onset ≤41 years were the unique independent features predicting positive CDKN2A screening. The rate of positive testing ranged from 93.2% in the presence of all of them, to 0.4% in their absence. The contribution of each of them was quantified accordingly, with MPM being the most significant. These findings confirm previous data and add novel insights for the role of accurate patients' selection in CDKN2A screening.
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http://dx.doi.org/10.1016/j.canep.2011.07.007 | DOI Listing |
Tissue Eng Part A
January 2025
C. Wayne McIlwraith Translational Medicine Institute, Colorado State University, Fort Collins, Colorado, USA.
Scaffolds made from cartilage extracellular matrix are promising materials for articular cartilage repair, attributed to their intrinsic bioactivity that may promote chondrogenesis. While several cartilage matrix-based scaffolds have supported chondrogenesis and/or , it remains a challenge to balance the biological response (e.g.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
Knight Foundation of Computing & Information Sciences, Florida International University, Miami, FL, United States.
Background: Digital biomarkers are increasingly used in clinical decision support for various health conditions. Speech features as digital biomarkers can offer insights into underlying physiological processes due to the complexity of speech production. This process involves respiration, phonation, articulation, and resonance, all of which rely on specific motor systems for the preparation and execution of speech.
View Article and Find Full Text PDFUltrasound J
January 2025
Department of Veterinary Clinical and Diagnostic Sciences, Faculty of Veterinary Medicine, University of Calgary, Calgary, AB, Canada.
Background: Lung ultrasound (LUS) is increasingly utilized in veterinary medicine to assess pulmonary conditions. However, the characterization of pleural line and subpleural fields using different ultrasound transducers, specifically high-frequency linear ultrasound transducers (HFLUT) and curvilinear transducers (CUT), remains underexplored in canine patients. This study aimed to evaluate inter-rater agreement in the characterization of pleural line and subpleural fields using B- and M-mode ultrasonography in dogs with and without respiratory distress.
View Article and Find Full Text PDFInsights Imaging
January 2025
Medical Research Department, Qingdao Hospital, University of Health and Rehabilitation Sciences (Qingdao Municipal Hospital), Qingdao, P. R. China.
Objective: To develop an automatic segmentation model to delineate the adnexal masses and construct a machine learning model to differentiate between low malignant risk and intermediate-high malignant risk of adnexal masses based on ovarian-adnexal reporting and data system (O-RADS).
Methods: A total of 663 ultrasound images of adnexal mass were collected and divided into two sets according to experienced radiologists: a low malignant risk set (n = 446) and an intermediate-high malignant risk set (n = 217). Deep learning segmentation models were trained and selected to automatically segment adnexal masses.
Biol Trace Elem Res
January 2025
Department of Geriatrics, The Second Affiliated Hospital, Nanjing Medical University, Nanjing, 210011, China.
Several studies have reported associations between specific heavy metals and essential trace elements and acute myocardial infarction (AMI). However, there is limited understanding of the relationships between trace elements and AMI in real-life co-exposure scenarios, where multiple elements may interact simultaneously. This cross-sectional study measured serum levels of 56 trace elements using inductively coupled plasma mass spectrometry.
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