I-TevI is a modular intron-encoded endonuclease, consisting of an N-terminal catalytic domain and a C-terminal DNA-binding domain, joined by a 75 amino acid linker. This linker can be divided into three regions, starting at the N terminus: the deletion-intolerant (DI) region; the deletion-tolerant (DT) region; and a zinc finger, which acts as a distance determinant for cleavage. To further explore linker function, we generated deletion and substitution mutants that were tested for their preference to cleave at a particular distance or at the correct sequence. Our results demonstrate that the I-TevI linker is multi-functional, a property that sets it apart from junction sequences in most other proteins. First, the linker DI region has a role in I-TevI cleavage activity. Second, the DT linker region participates in distance determination, as evident from DT mutants that display a phenotype similar to that of the zinc-finger mutants in their selection of a cleavage site. Finally, NMR analysis of a freestanding 56 residue linker segment showed an unstructured stretch corresponding to the DI region and a portion of the DT region, followed by a beta-strand corresponding to the remainder of the DT region and containing a key distance-determining arginine, R129. Mutation of this arginine to alanine abolished distance determination and disrupted the beta-strand, indicating that the structure of the DT linker region has a role in cleavage at a fixed distance.
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http://dx.doi.org/10.1016/j.jmb.2008.04.047 | DOI Listing |
Med Biol Eng Comput
January 2025
Department of Computer Science and Engineering, Shri Shankaracharya Institute of Professional Management and Technology, Raipur, (C.G.), India.
This study presents an advanced methodology for 3D heart reconstruction using a combination of deep learning models and computational techniques, addressing critical challenges in cardiac modeling and segmentation. A multi-dataset approach was employed, including data from the UK Biobank, MICCAI Multi-Modality Whole Heart Segmentation (MM-WHS) challenge, and clinical datasets of congenital heart disease. Preprocessing steps involved segmentation, intensity normalization, and mesh generation, while the reconstruction was performed using a blend of statistical shape modeling (SSM), graph convolutional networks (GCNs), and progressive GANs.
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January 2025
Department of Ophthalmology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
To assess the choroidal vessels in healthy eyes using a novel three-dimensional (3D) deep learning approach. In this cross-sectional retrospective study, swept-source OCT 6 × 6 mm scans on Plex Elite 9000 device were obtained. Automated segmentation of the choroidal layer was achieved using a deep-learning ResUNet model along with a volumetric smoothing approach.
View Article and Find Full Text PDFEnviron Monit Assess
January 2025
Technische Hochschule Nürnberg Georg Simon Ohm, Institute of Hydraulic Engineering and Water Resources Management, Nuremberg, Germany.
Through the mobilization of movable objects due to the extreme hydraulic conditions during a flood event, blockages, damage to infrastructure, and endangerment of human lives can occur. To identify potential hazards from aerial imagery and take appropriate precautions, a change detection tool (CDT) was developed and tested using a study area along the Aisch River in Germany. The focus of the CDT development was on near real-time analysis of point cloud data generated by structure from motion from aerial images of temporally separated surveys, enabling rapid and targeted implementation of measures.
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January 2025
Department of Radiology, Istanbul Training and Research Hospital, University of Health Sciences, Istanbul, Turkey.
Purpose: Cochlear implantation (CI) surgery is essential for restoring hearing in individuals with severe sensorineural hearing loss. Accurate placement of the electrode within the cochlea is essential for successful auditory outcomes and minimizing complications. This study aims to analyze the relationship between the round window niche (RWN) alignment, its visibility during surgery, and the impact on surgical techniques and outcomes.
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January 2025
Key Laboratory of Gas and Fire Control for Mines, Ministry of Education, Xuzhou, 221116, China.
Confined space fires could easily cause serious casualties and property damage, and foam is an effective means of preventing confined space fires. The existing foam generator does not have both momentum and foam expansion rate (FER) and is poorly suited to confined spaces. In order to develop a foam generator suitable for confined space fire protection, an in-depth analysis of the physical foaming characteristics of self-suction foam is required, and the structure of the foam generator is optimized accordingly.
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