Development of a kinetic model of hydrogen absorption and desorption in magnesium and analysis of the rate-determining step

Mg is promising as a new light-weight and low-cost hydrogen-storage material. We construct a numerical model to represent the hydrogen dynamics on Mg, comprising dissociative adsorption, desorption, bulk diffusion, and chemical reaction. Our calculation shows a good agreement with experimental data for hydrogen absorption and desorption on Mg. Our model clarifies the evolution of the rate-determining processes as absorption and desorption proceed. Furthermore, we investigate the optimal condition and materials design for efficient hydrogen storage in Mg. By properly understanding the rate-determining processes using our model, one can determine the design principle for high-performance hydrogen-storage systems

A Heterothermic Kinetic Model of Hydrogen Absorption in Metals with Subsurface Transport

A versatile numerical model for hydrogen absorption into metals was developed. Our model addresses the kinetics of surface adsorption, subsurface transport (which plays an important role for metals with active surfaces), and bulk diffusion processes. This model can allow researchers to perform simulations for various conditions, such as different material species, dimensions, structures, and operating conditions. Furthermore, our calculation scheme reflects the relationship between the temperature changes in metals caused by the heat of adsorption and absorption and the temperature-dependent kinetic parameters for simulation precision purposes. We demonstrated the numerical fitting of the experimental data for various Pd temperatures and sizes, with a single set of kinetic parameters, to determine the unknown kinetic constants. Using the developed model and determined kinetic constants, the transitions of the rate-determining steps on the conditions of metal-hydrogen systems are systematically analyzed. Conventionally, the temperature change of metals during hydrogen adsorption and absorption has not been a favorable phenomenon because it can cause errors when numerically estimating the hydrogen absorption rates. However, by our calculation scheme, the experimental data obtained under temperature changing conditions can be positively used for parameter fitting to efficiently and accurately determine the kinetic constants of the absorption process, even from a small number of experimental runs. In addition, we defined an effectiveness factor as the ratio between the actual absorption rate and the virtually calculated non-bulk-diffusion-controlled rate, to evaluate the quantitative influence of each individual transport process on the overall absorption process. Our model and calculation scheme may be a useful tool for designing high-performance hydrogen storage systems

Biomechanical effects of offset placement of dental implants in the edentulous posterior mandible

Background: Proper implant placement is very important for long-term implant stability. Recently, numerous biomechanical studies have been conducted to clarify the relationship between implant placement and peri-implant stress. The placement of multiple implants in the edentulous posterior mandible has been studied by geometric analysis, three-dimensional finite element analysis (FEA), model experimentation, etc. Offset placement is a technique that reduces peri-implant load. However, few studies have used multiple analyses to clarify the value of the offset placement under identical conditions.The present study aimed to clarify the biomechanical effects of offset placement on the peri-implant bone in edentulous posterior mandibles by comparative investigation using FEA and model experimentation with strain gauges.Methods: Three implants were embedded in an artificial mandible in the parts corresponding to the first premolar, the second premolar, and the first molar. A titanium superstructure was mounted to prepare models (experimental models). Three load points (buccal, central, and lingual) were established on the part of the superstructure corresponding to the first molar. Three types of experimental models, each with a different implant placement, were prepared. In one model, the implants were placed in a straight line; in the other two, the implants in the parts corresponding to the second premolar and the first molar were offset each by a 1-mm increment to the buccal or lingual side. Four strain gauges were applied to the peri-implant bone corresponding to the first molar.The experimental models were imaged by micro-computed tomography (CT), and FEA models were constructed from the CT data. A vertical load of 100 N was applied on the three load points in the experimental models and in the FEA models. The extent of compressed displacement and the strain in the peri-implant bone were compared between the experimental models and the FEA models Results: Both experimental and FEA models suffered the least compressed displacement during central loading in all placements. The greatest stress and compressive strain was on the load side in all types of placements.Conclusions: Offset placement may not necessarily be more biomechanically effective than straight placement in edentulous posterior mandibles.Keywords: Offset placement, Three-dimensional finite element analysis, FEA, Amount of compressed displacement, Stress distribution, Strain gaug

A biomechanical investigation of mandibular molar implants: reproducibility and validity of a finite element analysis model

Background: Three-dimensional finite element analysis (FEA) is effective in analyzing stress distributions around dental implants. However, FEA of living tissue involves many conditions, and the structures and behaviors are complex; thus, it is difficult to ensure the validity of the results. To verify reproducibility and validity, we embedded implants in experimental models and constructed FEA models; implant displacements were compared under various loading conditions. Methods: Implants were embedded in the molar regions of artificial mandibles to fabricate three experimental models. A titanium superstructure was fabricated and three loading points (buccal, central, and lingual) were placed on a first molar. A vertical load of 100 N was applied to each loading point and implant displacements were measured. Next, the experimental models were scanned on micro computed tomography (CT) and three-dimensional FEA software was used to construct two model types. A model where a contact condition was assumed for the implant and artificial mandible (a contact model) was constructed, as was a model where a fixation condition was assumed (a fixation model). The FEA models were analyzed under similar conditions as the experimental models; implant displacements under loading conditions were compared between the experimental and FEA models. Reproducibility of the models was assessed using the coefficient of variation (CV), and validity was assessed using a correlation coefficient.Results: The CV of implant displacement was 5–10% in the experimental and FEA models under loading conditions. Absolute values of implant displacement under loading were smaller in FEA models than the experimental model, but the displacement tendency at each loading site was similar. The correlation coefficient between the experimental and contact models for implant displacement under loading was 0.925 (p < 0.01). The CVs of equivalent stress values in the FEA models were 0.52–45.99%.Conclusions: Three-dimensional FEA models were reflective of experimental model displacements and produced highly valid results. Three-dimensional FEA is effective for investigating the behavioral tendencies of implants under loading conditions. However, the validity of the absolute values was low and the reproducibility of the equivalent stresses was inferior; thus, the results should be interpreted with caution

Reduction of T-Box 15 gene expression in tumor tissue is a prognostic biomarker for patients with hepatocellular carcinoma

Genome-wide analysis is widely applied to detect molecular alterations during oncogenesis and tumor progression. We analyzed DNA methylation profiles of hepatocellular carcinoma (HCC), and investigated the clinical role of most heypermethylated of tumor, encodes T-box 15 (TBX15), which was originally involved in mesodermal differentiation. We conducted a genome-wide analysis of DNA methylation of tumor and non-tumor tissue of 15 patients with HCC, and revealed TBX15 was the most hypermethylated gene of tumor (Beta-value in tumor tissue = 0.52 compared with non-tumor tissue). Another validation set, which comprised 58 HCC with radical resection, was analyzed to investigate the relationships between tumor phenotype and TBX15 mRNA expression. TBX15 mRNA levels in tumor tissues were significantly lower compared with those of nontumor tissues (p < 0.0001). When we assigned a cutoff value = 0.5-fold, the overall survival 5-year survival rates of the low-expression group (n = 17) were significantly shorter compared with those of the high-expression group (n = 41) (43.3% vs. 86.2%, p = 0.001). Multivariate analysis identified low TBX15 expression as an independent prognostic factor for overall and disease-free survival. Therefore, genome-wide DNA methylation profiling indicates that hypermethylation and reduced expression of TBX15 in tumor tissue represents a potential biomarker for predicting poor survival of patients with HCC

Intraoperative Perfusion Assessment in Enhanced Reality Using Quantitative Optical Imaging: An Experimental Study in a Pancreatic Partial Ischemia Model

To reduce the risk of pancreatic fistula after pancreatectomy, a satisfactory blood flow at the pancreatic stump is considered crucial. Our group has developed and validated a real-time computational imaging analysis of tissue perfusion, using fluorescence imaging, the fluorescence-based enhanced reality (FLER). Hyperspectral imaging (HSI) is another emerging technology, which provides tissue-specific spectral signatures, allowing for perfusion quantification. Both imaging modalities were employed to estimate perfusion in a porcine model of partial pancreatic ischemia. Perfusion quantification was assessed using the metrics of both imaging modalities (slope of the time to reach maximum fluorescence intensity and tissue oxygen saturation (StO2), for FLER and HSI, respectively). We found that the HSI-StO2 and the FLER slope were statistically correlated using the Spearman analysis (R = 0.697; p = 0.013). Local capillary lactate values were statistically correlated to the HSI-StO2 and to the FLER slope (R = −0.88; p < 0.001 and R = −0.608; p = 0.0074). HSI-based and FLER-based lactate prediction models had statistically similar predictive abilities (p = 0.112). Both modalities are promising to assess real-time pancreatic perfusion. Clinical translation in human pancreatic surgery is currently underway