Ex Vivo Expanded and Activated Natural Killer Cells Prolong the Overall Survival of Mice with Glioblastoma-like Cell-Derived Tumors

Glioblastoma (GBM) is the leading malignant intracranial tumor and is associated with a poor prognosis. Highly purified, activated natural killer (NK) cells, designated as genuine induced NK cells (GiNKs), represent a promising immunotherapy for GBM. We evaluated the anti-tumor effect of GiNKs in association with the programmed death 1(PD-1)/PD-ligand 1 (PD-L1) immune checkpoint pathway. We determined the level of PD-1 expression, a receptor known to down-regulate the immune response against malignancy, on GiNKs. PD-L1 expression on glioma cell lines (GBM-like cell line U87MG, and GBM cell line T98G) was also determined. To evaluate the anti-tumor activity of GiNKs in vivo, we used a xenograft model of subcutaneously implanted U87MG cells in immunocompromised NOG mice. The GiNKs expressed very low levels of PD-1. Although PD-L1 was expressed on U87MG and T98G cells, the expression levels were highly variable. Our xenograft model revealed that the retro-orbital administration of GiNKs and interleukin-2 (IL-2) prolonged the survival of NOG mice bearing subcutaneous U87MG-derived tumors. PD-1 blocking antibodies did not have an additive effect with GiNKs for prolonging survival. GiNKs may represent a promising cell-based immunotherapy for patients with GBM and are minimally affected by the PD-1/PD-L1 immune evasion axis in GBM.     

An aqueous suspension system for phospholipase D-mediated synthesis of PS without toxic organic solvent

Enzymatic synthesis of PS by phospholipase D (PLD)-mediated transphosphatidylation in an aqueous media was investigated. The purpose of this study was to establish a novel synthetic method where no toxic organic solvents were used. An attempt to react soybean lecithin (simply dispersed in an aqueous buffer) with an aqueous solution of l-serine and PLD was unsuccessful, giving only 20% of PS. By contrast, a suspension of lecithin adsorbed on fine powders such as silica was effectively converted into PS in an aqueous solution of l-serine and PLD. After screening various powders for use as the lecithin adsorbent, calcium sulfate was found to be the best with respect to lecithin conversion. In addition, calcium sulfate did not require prior adsorption of lecithin (i.e., the reaction proceeded effectively simply by adding the powder to an aqueous mixture of lecithin, l-serine, and PLD). With this “aqueous suspension system” of calcium sulfate, up to 180 mg/mL lecithin was completely converted, resulting in more than 80% PS in 24 h. The synthesized PS could easily be recovered from the powder by extracting with a mixture of n-hexane, ethanol, and diluted HCl.     

Insights from ab initio molecular dynamics simulations for a multicomponent oxide glass

It remains a challenge to establish structural models of multicomponent oxide glass systems. In this study, we have investigated 68.3SiO₂–16.1B₂O₃–4.2Al₂O₃–11.4Na₂O glass and melt structures by ab initio molecular dynamics (AIMD) simulations. The atomic configurations obtained from AIMD simulations were validated against ¹⁷O solid‐state NMR spectrum under 24.0 T and neutron diffraction data, and excellent agreement was achieved. The bond lengths, angles, and coordination geometries were statistically analyzed for each atomic species. Here we particularly address the role of minor atomic species such as five‐coordinate Si (Si^V) and Al (Al^V). The Si^V–O bond lengths and O–Si^V–O angle distribution in the glass indicated 1.718 Å and three peaks at 90°, 120°, and 175°, which are assigned to a coordination geometry of the trigonal bipyramidal structure. Ring statistic analysis revealed that Si^V and Al^V were found to preferentially contribute to the formation of small ring sizes.     

An adaptive hybrid surrogate model

The determination of complex underlying relationships between system parameters from simulated and/or recorded data requires advanced interpolating functions, also known as surrogates. The development of surrogates for such complex relationships often requires the modeling of high dimensional and non-smooth functions using limited information. To this end, the hybrid surrogate modeling paradigm, where different surrogate models are combined, offers an effective solution. In this paper, we develop a new high fidelity surrogate modeling technique that we call the Adaptive Hybrid Functions (AHF). The AHF formulates a reliable Crowding Distance-Based Trust Region (CD-TR), and adaptively combines the favorable characteristics of different surrogate models. The weight of each contributing surrogate model is determined based on the local measure of accuracy for that surrogate model in the pertinent trust region. Such an approach is intended to exploit the advantages of each component surrogate. This approach seeks to simultaneously capture the global trend of the function as well as the local deviations. In this paper, the AHF combines four component surrogate models: (i) the Quadratic Response Surface Model (QRSM), (ii) the Radial Basis Functions (RBF), (iii) the Extended Radial Basis Functions (E-RBF), and (iv) the Kriging model. The AHF is applied to standard test problems and to a complex engineering design problem. Subsequent evaluations of the Root Mean Squared Error (RMSE) and the Maximum Absolute Error (MAE) illustrate the promising potential of this hybrid surrogate modeling approach.     

Development of reel-to-reel microchip mounting system for fabrication of meter-long LED lighting tapes

We have developed a reel-to-reel microchip mounting system that continuously mounts LED chips and other microchips on meter-long flexible printed circuit board (PCB) tape for 1.2-m-long standard LED light tubes. Mounting microchips on meter-long PCBs is difficult because a large chip mounter is expensive and the chip positioning stage is difficult to move in a meter-wide area with an accuracy of hundreds of micrometers. Hence, we developed a new microchip mounting system that utilizes a small chip mounter and reel winding machines. The system repeatedly moves the long PCB tape by a certain length with the reel winding machines and mounts the chips on it. The PCB tape (which is 5 mm wide) is made by fabricating long PCB tapes which are 25 cm × 26.6 m through a roll-to-roll PCB process and slitting them into meter-long tapes. The reel-to-reel system repeatedly mounts chips by adjusting their positions through image processing of the copper wiring pattern on the PCBs. Our constructed system mounted 24 LED chips with a pitch of 5 cm with an accuracy of 0.082 mm to form a 1.2-m-long LED tape. The luminance of the tape is 12.4 lx at a distance of 1 m, which is the luminance of outdoor corridor lighting. Therefore, this system can be used for meter-long tape lighting.     

A manufacturing XML schema definition and its application to a data management system on the shop floor

Digitization for sharing knowledge on the shop floor in the machinery industry has been given much attention recently. To help engineers use digitization practically and efficiently, this paper proposes a method based on manufacturing case data that has a direct relation to manufacturing operations. The data are represented in XML schema, as it can be easily applied to Web-based systems on the shop floor. The definitions were made for eight manufacturing methods including machining and welding. The derived definitions consist of four divisions of metadata, work-piece, process and evaluation. Three divisions except for the “process” division are common to the manufacturing methods. The average number of elements for a manufacturing method is about 200. The represented schema is also used to convey knowledge such as operation standards and manufacturing troubleshooting on the shop floor. Using the definitions, a data management system is developed. It is a Web-based Q&A system, in which the engineers specify the manufacturing case data mainly by selecting from the candidates. Then, the system fills in the blank portions and/or shows messages to help complete the case data. The proposed method is evaluated through practical scenarios of arc welding and machining.     

(p,q)-Logical completeness for output-coherent sets of (p,q)-Logical functions and an application of the set to image processing

We have previously proposed an idea of p-valued input, q-valued output threshold logic to synthesize many-valued, p-valued, logical networks, and derived the condition for (p, q)-logical completeness for the output-closed set of (p, q)-logical functions. In this paper, the condition for (p, q)-logical completeness for the output-coherent set F of (p, q)-logical functions is described, and the proof is given in almost the same way as for the output-closed set. The output-coherent set F is applied to image processing. That is, a restoration scheme is described for images to which normal random noise is added.     

Concurrent surrogate model selection (COSMOS): optimizing model type,kernel function,and hyper-parameters

This paper presents an automated surrogate model selection framework called the Concurrent Surrogate Model Selection or COSMOS. Unlike most existing techniques, COSMOS coherently operates at three levels, namely: 1) selecting the model type (e.g., RBF or Kriging), 2) selecting the kernel function type (e.g., cubic or multiquadric kernel in RBF), and 3) determining the optimal values of the typically user-prescribed hyper-parameters (e.g., shape parameter in RBF). The quality of the models is determined and compared using measures of median and maximum error, given by the Predictive Estimation of Model Fidelity (PEMF) method. PEMF is a robust implementation of sequential k-fold cross-validation. The selection process undertakes either a cascaded approach over the three levels or a more computationally-efficient one-step approach that solves a mixed-integer nonlinear programming problem. Genetic algorithms are used to perform the optimal selection. Application of COSMOS to benchmark test functions resulted in optimal model choices that agree well with those given by analyzing the model errors on a large set of additional test points. For the four analytical benchmark problems and three practical engineering applications – airfoil design, window heat transfer modeling, and building energy modeling – diverse forms of models/kernels are observed to be selected as optimal choices. These observations further establish the need for automated multi-level model selection that is also guided by dependable measures of model fidelity.