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In this paper, a new method for calculating effective atomic radii within the generalized Born (GB) model of implicit solvation is proposed, for use in computer simulations of bio-molecules. First, a new formulation for the GB radii is developed, in which smooth kernels are used to eliminate the divergence in volume integrals intrinsic in the model. Next, the Fast Fourier Transform (FFT) algorithm is applied to integrate smoothed functions, taking advantage of the rapid spectral decay provided by the smoothing. The total cost of the proposed algorithm scales as O(N(3)logN + M) where M is the number of atoms comprised in a molecule, and N is the number of FFT grid points in one dimension, which depends only on the geometry of the molecule and the spectral decay of the smooth kernel but not on M. To validate our algorithm, numerical tests are performed for three solute models: one spherical object for which exact solutions exist and two protein molecules of differing size. The tests show that our algorithm is able to reach the accuracy of other existing GB implementations, while offering much lower computational cost.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2598740 | PMC |
http://dx.doi.org/10.1016/j.jcp.2008.08.015 | DOI Listing |
Am J Vet Res
December 2024
Department of Small Animal Surgery, ONIRIS Nantes-Atlantic College of Veterinary Medicine, Food Science, and Engineering, Nantes, France.
Objective: To study the morphology of canine and feline femurs and tibias in lateral radiographic projections and assess their compatibility with either a straight or a curved full-length interlocking nail (ILN).
Methods: Lateral projection radiographs of 50 tibias and 50 femurs (10 cats and 40 dogs per bone) were used to measure the minimum and maximum radius of curvature of an ILN compatible with each bone. These radii were defined by cranial and caudal endosteal points at the proximal entry point of the nail, at the isthmus, and at the most distal point of the ILN insertion into the femoral or tibial metaphysis.
Machine learning has emerged as a promising approach for predicting molecular properties of proteins, as it addresses limitations of experimental and traditional computational methods. Here, we introduce GSnet, a graph neural network (GNN) trained to predict physicochemical and geometric properties including solvation free energies, diffusion constants, and hydrodynamic radii, based on three-dimensional protein structures. By leveraging transfer learning, pre-trained GSnet embeddings were adapted to predict solvent-accessible surface area (SASA) and residue-specific p values, achieving high accuracy and generalizability.
View Article and Find Full Text PDF3D Print Med
December 2024
Department of Biomedical Engineering, Medical Additive Manufacturing Research Group (Swiss MAM), University of Basel, Allschwil, Switzerland.
The most common surgical procedure to manage the malunion of the bones is corrective osteotomy. The current gold standard for securing the bone segments after osteotomy is the use of titanium plates and allografts which have disadvantages such as possible allergic reaction, additional operations such as extraction of the graft from other sites and removal operation. The utilization of resorbable materials presents an opportunity to mitigate these drawbacks but has not yet been thoroughly researched in the literature.
View Article and Find Full Text PDFCureus
November 2024
General Physician, AlJaber Eye and ENT Hospital, Al-Ahsa, SAU.
Corneal curvature (CC) is a crucial ocular optical system parameter, indicating the shape of the cornea expressed in radii. This study aims to investigate the relationship between CC, age, gender, refractive errors, and central corneal thickness (CCT) in Saudi Arabia, a field lacking in research. Data were gathered from Imam Medical Center in Riyadh and Dr.
View Article and Find Full Text PDFMaterials (Basel)
December 2024
Tianjin Key Laboratory of Advanced Joining Technology, School of Materials Science and Engineering, Tianjin University, Tianjin 300072, China.
High-temperature CMAS corrosion has become a crucial factor inhibiting the further development of thermal barrier coatings (TBCs) because of the increasing service temperature of aero-engines. Herein, a novel mid-entropy rare-earth hafnate (YGdYb)HfO (YGYbH) was prepared by ultrafast high-temperature sintering (UHS) technology, and its CMAS corrosion behavior and mechanism were investigated. During corrosion, the CaRE(SiO)O apatite phase with a lower formation enthalpy and entropy-stabilized effect had a more intense tendency to be generated, which improves the density and stability of the reaction layer, hindering the further penetration of molten CMAS.
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