Combination of Near-Infrared Photoimmunotherapy Using Trastuzumab and Small Protein Mimetic for HER2-Positive Breast Cancer

Near-infrared photoimmunotherapy (NIR-PIT) is a promising cancer therapy based on a monoclonal antibody conjugated to a photosensitizer (IR700Dye) that is activated by near-infrared light irradiation. We previously reported on the use of NIR-PIT with a small protein mimetic, the Affibody molecule (6–7 kDa), instead of a monoclonal antibody. In this study, we investigated a combination of NIR-PIT for HER2-positive breast cancer cells (SK-BR3, MDA-MB361, and JIMT1) with HER2 Affibody-IR700Dye conjugate and trastuzumab-IR700Dye conjugate. HER2 Affibody and trastuzumab target different epitopes of the HER2 protein and do not compete. In vitro, the combination of NIR-PIT using both HER2 Affibody-IR700Dye conjugate and trastuzumab-IR700Dye conjugate induced necrotic cell death of HER2-positive breast cancer cells without damage to HER2-negative breast cancer cells (MCF7). It was more efficient than NIR-PIT using either the HER2 Affibody-IR700Dye conjugate alone or the trastuzumab-IR700Dye conjugate alone. Additionally, this combination of NIR-PIT was significantly effective against HER2 low-expressing cancer cells, trastuzumab-resistant cells (JIMT1), and brain metastatic cells of breast cancer (MDA-MB361). Furthermore, in vivo imaging exhibited the strong fluorescence intensity of both HER2 Affibody-IR700Dye conjugates and trastuzumab-Alexa488 conjugates in HER2-positive tumor, indicating that both HER2 Affibody and trastuzumab specifically bind to HER2-positive tumors without competing with each other. In conclusion, the combination of NIR-PIT using both HER2 Affibody and trastuzumab expands the targeting scope of NIR-PIT for HER2-positive breast cancer.     

Crystallization and thermomechanical properties of PLA composites: Effects of additive types and heat treatment

This research work has concerned a study on thermomechanical and crystallization properties of poly(lactic acid) (PLA) composites containing three different types of additives; namely: kenaf fiber (20 pph), Cloisite30B nanoclay (5 pph), and hexagonal boron nitrile (h‐BN; 5 pph). The composites were prepared using a twin screw extruder before molding. Crystallization behaviors of the various composites were also examined using a differential scanning calorimetry. By adding the additives, tensile modulus of the polymer composites increased, whereas their tensile strength and elongation values decreased as compared to those of the neat PLA. Heat distortion temperature (HDT) values of the materials slightly increased, for about 3–5°C. However, after annealing at 100°C, HDT values of the fabricated PLA composites rapidly increased with annealing time before reaching a plateau after 10 min. The HDT values of above 120°C were achieved when 20 pph kenaf fiber was used as an additive. The above results were in a good agreement with DSC thermograms of the composites, indicating that percentage crystallinity of the materials increased on annealing and crystallization rate of the PLA/kenaf system was the highest. © 2012 Wiley Periodicals, Inc. J. Appl. Polym. Sci., 2013     

杂质Fe对A1-Zn-In牺牲阳极性能的影响

炼制Fe杂质含量不同的6种Al-Zn-In阳极,采用恒电流方去评价了其电化学性能,并通过扫描电镜观察其溶解的微观形貌,探讨了Fe杂质含量对阳极电化学性能的影响规律与机制.结果表明,随着Fe杂质含量的升高,Al-Zn-In阳极的电流效率呈先增加后降低趋势,原因足少量的Fe可增加阳极的活化点,而过量的Fe则作为阴极相引发电偶腐蚀使得阳极呈局部腐蚀溶解.     

瞬态工况下柴油机燃烧模型参数变化研究

为了研究零维燃烧模型中特征参数在瞬态工况下的变化规律,对涡轮增压柴油机在转速1500r／min负载由30％额定功率在5s内均匀增加到100％的瞬态工况下的缸内压力、进气流量、燃油流量等参数进行了测量,用三次Wiebe函数模拟了加载过程中每循环的燃烧放热率,利用非线性回归方程求解出了Wiebe函数中的特征参数,并对其在瞬态工况下的变化规律进行了分析,提出了三次Wiebe函数特征参数选取的经验公式,可以用来预测瞬态工况下的放热规律。     

彩色显像管低熔点封接玻璃高压击穿

本文叙述了彩色显像管屏锥封接工艺过程中低熔点玻璃高压击穿的特征及分布状况，分析了击穿机理，总结了有效择策措施，收到了显著效果。     

Embodying Learning Effect in Performance Prediction

Predicting performance of contractors is of interest to both academics and practitioners. The physical execution of a project is critical to the overall success of the development. Having a competent contractor that can deliver is most desirable. In this aspect, a significant number of performance prediction models have been developed. Multiple regression and neural networks are typically used as the analytical tools in these prediction models. This paper reports a study that employs a learning curve approach to perform the prediction task. It is suggested that this approach can accommodate the changes in performance as experience accumulates. Thus a performance pattern is projected in addition to the project final outcome. A two-step approach suggested by Everett and Farghal was adopted for this study. First, the learning curve model that best represents a contractors’ performance was explored using the least-square curve fitting analysis. Second, prediction analysis was performed by comparing the actual performance data with their respective prediction results obtained from extrapolation on the selected learning curve. The three-parameter hyperbolic model was found to provide the most reliable prediction on performance in this study.     

Preparation of a reticulated polyurethane foam grafted with poly(acrylic acid) through atmospheric pressure plasma treatment and its lysozyme immobilization

We successfully introduced peroxide groups onto the surface of PU(Polyurethane) foam(10 PPI) through one atmospheric pressure plasma treatment and sequentially grafted PAAc(poly(acrylic acid)) on the surface of PU through radical copolymerization. The plasma treatment can generate large amount of peroxides on the surface of PU foam and the peroxide groups act as initiators for further grafting of PAAc in the monomer solution. To introduce large amount of peroxides on the surface of PU foam, we studied the effect of plasma rf-power and treatment time on the maximum grafting of PAAc. Through this study, we found that the optimum plasma treatment condition was the rf-power of 100 W and the treatment time of 100 s. On the other hand, we also studied the effect of graft reaction conditions such as temperature, monomer concentration and reaction time on the change of grafting degree (GD). The GD increased with increasing temperature and increased with reaction time before it leveled off at 3 h after reaction started. At low concentration of AAc, the GD was very low but it showed a maximum at the monomer concentration between 60 and 70%. The surface of the modified PU foam was qualitatively and quantitatively analyzed through the use of FT-IR and weight measurement, respectively. We also observed the surface change before and after plasma induced graft co-polymerization through photo and SEM analysis. Finally, we confirmed that the PU foams grafted with PAAc successfully immobilized lysozyme and other proteins from hen egg white.     

Dissolved oxygen control and monitoring implementation in the liquid lead-bismuth eutectic loop: HELIOS

A 12 m tall LBE coolant loop, named as HELIOS, has been developed by thermal-hydraulic scaling of the PEACER-300MWe. Thermo-hydraulic experiment and materials test are the principal purposes of HELIOS operation. In this study, an yttria stabilized zirconia (YSZ) based oxygen sensor that was hermetically sealed for long-term applications using the electromagnetically swaged metal-ceramic joining method, have been developed for high temperature oxygen control application over a long period of time. The rugged electrode design has been calibrated to absolute metal-oxide equilibrium by using a first principle of detecting pure metal-oxide transition using electrochemical impedance spectroscopy (EIS). During the materials tests in HELIOS, dissolved oxygen concentration was administered at the intended condition of 10⁻⁶ wt% by direct gas bubbling with Ar + 4%H₂, Ar + 5%O₂ and/or pure Ar while corrosion tests were conducted for up to 1000 h with inspection after each 333 h. During the total 1000 h corrosion test, oxygen concentration was measured by oxygen sensor. The result confirmed that the direct gas bubbling method is a viable and practical option for controlling oxygen concentration in large loops including HELIOS.     

Identification of the light nuclei component of cosmic rays with the PAMELA experiment

The PAMELA (Payload for Antimatter Matter Exploration and Light nuclei Astrophysics) experiment is a satellite-borne apparatus that will make long duration measurements of the cosmic radiation with a particular focus on antiparticles and light nuclei. The main scientific objective of the PAMELA mission is to investigate the nature of the dark matter that pervades the universe, the apparent absence of cosmological antimatter, the origin and evolution of matter in the Galaxy. Specifically PAMELA will measure the cosmic-ray antiproton and positron spectra over the largest energy range ever achieved and will search for antinuclei with unprecedented sensitivity. Furthermore, it will measure the light nuclear component of cosmic rays from Hydrogen up to Oxygen in the interval 200 MeV/n–150 GeV/n. Accurate measurements of the elemental composition are required in order to understand the origin, propagation and lifetime of the cosmic radiation. The primary cosmic rays (e.g. C, N and O), produced at the sources, propagate through the interstellar medium giving information about the composition at the source. Secondary elements (e.g. Li, Be, and B) are tracers of amount of matter traversed by the cosmic rays. The relative abundances of the constituents of galactic cosmic rays provide information about cosmic-ray transport within the Galaxy. PAMELA consists of a magnetic spectrometer, a Time-of-Flight and trigger system, an electromagnetic calorimeter, an anticoincidence system, a shower tail catcher scintillator and a neutron detector. The combination of these devices allows antiparticles to be reliably identified from a large background of other charged particles. This paper reviews the capability of the PAMELA subdetectors to identify light nuclei. Analysis techniques to discriminate light-charged particles will be presented.