Clinical validation of artificial intelligence-based preoperative virtual reduction for Neer 3- or 4-part proximal humerus fractures.

Background: If reduction images of fractures can be provided in advance with artificial-intelligence (AI)-based technology, it can assist with preoperative surgical planning. Recently, we developed the AI-based preoperative virtual reduction model for orthopedic trauma, which can provide an automatic segmentation and reduction of fractured fragments. The purpose of this study was to validate a quality of reduction model of Neer 3- or 4-part proximal humerus fractures established by AI-based technology.

Deep Learning Model Based on You Only Look Once Algorithm for Detection and Visualization of Fracture Areas in Three-Dimensional Skeletal Images.

Utilizing "You only look once" (YOLO) v4 AI offers valuable support in fracture detection and diagnostic decision-making. The purpose of this study was to help doctors to detect and diagnose fractures more accurately and intuitively, with fewer errors. The data accepted into the backbone are diversified through CSPDarkNet-53.

Automatic segmentation of inconstant fractured fragments for tibia/fibula from CT images using deep learning.

Orthopaedic surgeons need to correctly identify bone fragments using 2D/3D CT images before trauma surgery. Advances in deep learning technology provide good insights into trauma surgery over manual diagnosis. This study demonstrates the application of the DeepLab v3+ -based deep learning model for the automatic segmentation of fragments of the fractured tibia and fibula from CT images and the results of the evaluation of the performance of the automatic segmentation.

Fine-Grained Motion Recognition in At-Home Fitness Monitoring with Smartwatch: A Comparative Analysis of Explainable Deep Neural Networks.

The squat is a multi-joint exercise widely used for everyday at-home fitness. Focusing on the fine-grained classification of squat motions, we propose a smartwatch-based wearable system that can recognize subtle motion differences. For data collection, 52 participants were asked to perform one correct squat and five incorrect squats with three different arm postures (straight arm, crossed arm, and hands on waist).

Recognition of Fine-Grained Walking Patterns Using a Smartwatch with Deep Attentive Neural Networks.

Generally, people do various things while walking. For example, people frequently walk while looking at their smartphones. Sometimes we walk differently than usual; for example, when walking on ice or snow, we tend to waddle.

Catalytic characteristics of titanium oxide/MCM-41 synthesized by liquid phase atomic layer deposition.

Titanium oxide on MCM-41 was synthesized using the atomic layer deposition (ALD) method. BET, XRD, NH3-TPD and EDS were used to study the structural properties of the supported titanium oxides. The surface area of catalysts decreased with increasing of the amount of titanium in precursor solution.

The systemic effects of platelet-rich plasma injection.

Background: Platelet-rich plasma (PRP) is an autologous blood product used to treat acute and chronic tendon, ligament, and muscle injuries in over 86,000 athletes in the United States annually. The World Anti-Doping Agency (WADA) banned intramuscular PRP injections in competitive athletes in 2010 because of concerns that it may increase performance-enhancing growth factors. The ban on PRP was removed in 2011 because of limited evidence for a systemic ergogenic effect of PRP, but the growth factors within PRP remain prohibited.

Preparation of highly dispersed tungsten oxide on MCM-41 via atomic layer deposition and its application to butanol dehydration.

Highly dispersed tungsten oxide on MCM-41 was synthesized using a novel atomic layer deposition (ALD) method. BET, XRD, XPS, NH3-TPD, and pyridine-IR were used to study the physicochemical properties of the supported tungsten oxides. In this study, the maximum loading of tungsten oxide on MCM-41 that could be prepared using the modified ALD method was 27.

Utilization of a by-product produced from oxidative desulfurization process over Cs-mesoporous silica catalysts.

We investigated the use of Cs-mesoporous silica catalysts to upgrade a by-product of oxidative desulfurization (ODS). Cs-mesoporous silica catalysts were characterized through N2 adsorption, XRD, CO2-temperature-programmed desorption, and XRF. Cs-mesoporous silica prepared by the direct incorporation method showed higher catalytic performance than a Cs/MCM-41 catalyst by impregnation method for the catalytic decomposition of sulfone compounds produced from ODS process.

Silk fibroin processing and thrombogenic responses.

Silkworm-derived fibroin, which constitutes the core of the silk filament, is an attractive protein-polymer for biomedical applications. Fibroin can also be processed into a variety of 2-D and 3-D formats to match morphological and structural features to specific applications. The focus of the present research was to correlate the structure of silk fibroin-derived biomaterials with plasma protein adsorption, platelet activation and inflammatory cell (THP-1 cell line) adhesion and activation.

In vivo degradation of three-dimensional silk fibroin scaffolds.

Three-dimensional porous scaffolds prepared from regenerated silk fibroin using either an all-aqueous process or a process involving an organic solvent, hexafluoroisopropanol (HFIP), have shown promise in cell culture and tissue engineering applications. However, their biocompatibility and in vivo degradation have not been fully established. The present study was conducted to systematically investigate how processing method (aqueous vs.

Accurately shaped tooth bud cell-derived mineralized tissue formation on silk scaffolds.

Based on the successful use of silk scaffolds in bone tissue engineering, we examined their utility for mineralized dental tissue engineering. Four types of hexafluoroisopropanol (HFIP) silk scaffolds-(250 and 550 microm diameter pores, with or without arginine-glycine-aspartic acid (RGD) peptide) were seeded with cultured 4-day postnatal rat tooth bud cells and grown in the rat omentum for 20 weeks. Analyses of harvested implants revealed the formation of bioengineered mineralized tissue that was most robust in 550 microm pore RGD-containing scaffolds and least robust in 250 microm pore sized scaffolds without RGD.

Stem cell-based tissue engineering with silk biomaterials.

Silks are naturally occurring polymers that have been used clinically as sutures for centuries. When naturally extruded from insects or worms, silk is composed of a filament core protein, termed fibroin, and a glue-like coating consisting of sericin proteins. In recent years, silk fibroin has been increasingly studied for new biomedical applications due to the biocompatibility, slow degradability and remarkable mechanical properties of the material.

Cartilage tissue engineering with silk scaffolds and human articular chondrocytes.

Adult cartilage tissue has poor capability of self-repair, especially in case of severe cartilage damage due to trauma or age-related degeneration. Autologous cell-based tissue engineering using three-dimensional (3-D) porous scaffolds has provided an option for the repair of full thickness defects in adult cartilage tissue. Mesenchymal stem cells (MSCs) and chondrocytes are the two major cell sources for cartilage tissue engineering.

In vitro cartilage tissue engineering with 3D porous aqueous-derived silk scaffolds and mesenchymal stem cells.

Adult cartilage tissue has limited self-repair capacity, especially in the case of severe damages caused by developmental abnormalities, trauma, or aging-related degeneration like osteoarthritis. Adult mesenchymal stem cells (MSCs) have the potential to differentiate into cells of different lineages including bone, cartilage, and fat. In vitro cartilage tissue engineering using autologous MSCs and three-dimensional (3-D) porous scaffolds has the potential for the successful repair of severe cartilage damage.