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Perceptual ability test (PAT) is a valid determinant for spatial perceptions. However, a validated psychomotor skill test for dentistry does not currently exist.Purpose/Objectives: This study aimed to determine whether the results of two wax carving exercises (E1 and E2), PAT, quantitative reasoning (QR), and academic average (AA) tests predict students' performance on dental anatomy practical examinations.Methods: First-year dental students (n = 69) participated in the study. Results of the PAT, QR, and AA were obtained from the Admissions Office. Participants completed wax carving exercises during the first (E1) and last weeks (E2) of the dental anatomy course. Carving instruments, instruction, and rubrics, were provided to participants who were instructed to carve a cube and a semicircle shape into a wax block using the wax subtraction technique. Two calibrated and blinded faculty graded the exercise as ideal, satisfactory, or unsatisfactory in four categories: finish, sharpness, symmetry, and accuracy. During the dental anatomy course, participants completed wax carving practical examinations for a maxillary central incisor and a mandibular first molar. Examinations were graded by calibrated faculty as ideal, satisfactory, or unsatisfactory. The linear mixed effects model assessed influences of independent variables on the practical examinations. Results: estimates of the independent variables on the practical examinations were PAT (0.027), AA (0.088), QR (-0.014), E1 (0.235), and E2 (0.175). Conclusions: wax carving exercises were stronger predictors of performance on the practical examinations than the PAT, AA, and QR. This simple exercise may help identify students early in their preclinical education requiring additional assistance.

Motivation Chromosome conformation capture technologies (Hi-C) revealed extensive DNA folding into discrete 3D domains, such as Topologically Associating Domains and chromatin loops. The correct binding of CTCF and cohesin at domain boundaries is integral in maintaining the proper structure and function of these 3D domains. 3D domains have been mapped at the resolutions of 1 kilobase and above. However, it has not been possible to define their boundaries at the resolution of boundary-forming proteins. Results To predict domain boundaries at base-pair resolution, we developed preciseTAD, an optimized transfer learning framework trained on high-resolution genome annotation data. In contrast to current TAD/loop callers, preciseTAD-predicted boundaries are strongly supported by experimental evidence. Importantly, this approach can accurately delineate boundaries in cells without Hi-C data. preciseTAD provides a powerful framework to improve our understanding of how genomic regulators are shaping the 3D structure of the genome at base-pair resolution. Availability preciseTAD is an R/Bioconductor package available at https://bioconductor.org/packages/preciseTAD/ Supplementary information Supplementary data are available at Bioinformatics online.

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