This study investigates the reliability and precision of anthropometric measurements collected from 3D images and acquired under different conditions of head rotation. Various sources of error were examined, and the equivalence between craniofacial data generated from alternative head positions was assessed. 3D captures of a mannequin head were obtained with a stereophotogrammetric system (Face Shape 3D MaxiLine). Image acquisition was performed with no rotations and with various pitch, roll, and yaw angulations. On 3D images, 14 linear distances were measured. Various indices were used to quantify error magnitude, among them the acquisition error, the mean and the maximum intra- and inter-operator measurement error, repeatability and reproducibility error, the standard deviation, and the standard error of errors. Two one-sided tests (TOST) were performed to assess the equivalence between measurements recorded in different head angulations. The maximum intra-operator error was very low (0.336 mm), closely followed by the acquisition error (0.496 mm). The maximum inter-operator error was 0.532 mm, and the highest degree of error was found in reproducibility (0.890 mm). Anthropometric measurements from alternative acquisition conditions resulted in significantly equivalent TOST, with the exception of Zygion (l)-Tragion (l) and Cheek (l)-Tragion (l) distances measured with pitch angulation compared to no rotation position. Face Shape 3D Maxiline has sufficient accuracy for orthodontic and surgical use. Precision was not altered by head orientation, making the acquisition simpler and not constrained to a critical precision as in 2D photographs.
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http://dx.doi.org/10.3390/ijerph18084276 | DOI Listing |
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January 2025
Department of Genetics and Molecular Biology, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran;
Common variable immunodeficiency (CVID) is the most common symptomatic and heterogeneous type of inborn errors of immunity (IEI). However, the pathogenesis process of this disease is often unknown. Epigenetic modifications may be involved in unresolved patients.
View Article and Find Full Text PDFBioinformatics
January 2025
Department of Biological Sciences, University of Illinois at Chicago, Illinois 60607, United States.
Motivation: Recent advancements in parallel sequencing methods have precipitated a surge in publicly available short-read sequence data. This has encouraged the development of novel computational tools for the de novo assembly of transcriptomes from RNA-seq data. Despite the availability of these tools, performing an end-to-end transcriptome assembly remains a programmatically involved task necessitating familiarity with best practices.
View Article and Find Full Text PDFBioinformatics
January 2025
Department of Computer Science, City University of Hong Kong, Hong Kong, China.
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January 2025
Stanford Hospital, Stanford, CA, United States.
Background: Inhalational anesthetic agents are a major source of potent greenhouse gases in the medical sector, and reducing their emissions is a readily addressable goal. Nitrous oxide (NO) has a long environmental half-life relative to carbon dioxide combined with a low clinical potency, leading to relatively large amounts of NO being stored in cryogenic tanks and H cylinders for use, increasing the chance of pollution through leaks. Building on previous findings, Stanford Health Care's (SHC's) NO emissions were analyzed at 2 campuses and targeted for waste reduction as a precursor to system-wide reductions.
View Article and Find Full Text PDFPsychol Methods
January 2025
Department of Human Development, Cornell University.
Intensive longitudinal data, increasingly common in social and behavioral sciences, often consist of multivariate time series from multiple individuals. Dynamic factor analysis, combining factor analysis and time series analysis, has been used to uncover individual-specific processes from single-individual time series. However, integrating these processes across individuals is challenging due to estimation errors in individual-specific parameter estimates.
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