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Medical imaging is a valuable source for facilitating empirical research and provides an accessible gateway for developing novel forensic anthropological methods for analysis including 3D modelling. This is especially critical for the United Kingdom (UK), where methods developed from modern UK populations do not currently exist. This study introduces a new approach to assist in human identification using 3D models of the paranasal sinuses. The models were produced from a database of 500 modern CT scans provided by University College London Hospital. Linear measurements and elliptic Fourier coefficients taken from 1500 three-dimensional models across six ethnic groups assessed by one-way ANOVA and discriminant function analysis showed a range of classification rates with certain rates reaching 75-85.7% (p < 0.05) in correctly classifying age and sex according to size and shape. The findings offer insights into the potential for employing paranasal sinuses as an attribute for establishing the identification of unknown human remains in future crime reconstructions.
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http://dx.doi.org/10.1007/s00414-024-03179-2 | DOI Listing |
Cell Mol Biol (Noisy-le-grand)
September 2025
Medical Microbiology Department, College of Medicine, Ibn Sina University of Medical and Pharmaceutical Sciences, Baghdad, Iraq.
Pseudomonas aeruginosa is a prominent opportunistic pathogen, especially in burn wound infections, and is often associated with high morbidity and mortality due to its multidrug resistance (MDR) characteristics.This study aimed to evaluate the multidrug resistance profile and perform a molecular phylogenetic analysis of P. aeruginosa isolates recovered from human burn infection sample .
View Article and Find Full Text PDFRadiol Med
September 2025
Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141, Milan, Italy.
Metastatic involvement (MB) of the breast from extramammary malignancies is rare, with an incidence of 0.09-1.3% of all breast malignancies.
View Article and Find Full Text PDFFunct Integr Genomics
September 2025
Zhengzhou Research Base, State Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Zhengzhou University/Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Zhengzhou, China.
In this study, a comprehensive genome-wide identification and analysis of the aldo-keto reductase (AKR) gene family was performed to explore the role of Gossypium hirsutumAKR40 under salt stress in cotton. A total of 249 AKR genes were identified with uneven distribution on the chromosomes in four cotton species. The diversity and evolutionary relationship of the cotton AKR gene family was identified using physio-chemical analysis, phylogenetic tree construction, conserved motif analysis, chromosomal localization, prediction of cis-acting elements, and calculation of evolutionary selection pressure under 300 mM NaCl stress.
View Article and Find Full Text PDFBrief Bioinform
August 2025
State Key Laboratory of Animal Biotech Breeding, College of Biological Sciences, China Agricultural University, No. 2 Yuanmingyuan West Road, Haidian District, Beijing 100193, China.
The systematic identification of human-virus protein-protein interactions (PPIs) is a critical step toward elucidating the underlying mechanisms of viral infection, directly informing the development of targeted interventions against existing and emerging viral threats. In this work, we presented DeepGNHV, an end-to-end framework that integrated a pretrained protein language model with structural features derived from AlphaFold2 and leveraged graph attention networks to predict human-virus PPIs. In comparison to other state-of-the-art approaches, DeepGNHV exhibited superior predictive performance, especially when applied to viral proteins absent from the training process, indicating its strong generalization capability for detecting newly emerging virus-related PPIs.
View Article and Find Full Text PDFJ Proteome Res
September 2025
Department of Neurology, West China Hospital, Sichuan University, Chengdu 610207, China.
Myasthenia gravis (MG) presents significant health and economic challenges. To identify novel biomarkers, we analyzed proteomic data from 52,704 UK Biobank individuals, focusing on 1463 baseline proteins with follow-up >10 years. Baseline and potential MG cases were 1:5 matched to controls by using propensity score matching.
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