Adaptation to Endoplasmic Reticulum Stress Enhances Resistance of Oral Cancer Cells to Cisplatin by Up-Regulating Polymerase η and Increasing DNA Repair Efficiency

Endoplasmic reticulum (ER) stress response is an adaptive program to cope with cellular stress that disturbs the function and homeostasis of ER, which commonly occurs during cancer progression to late stage. Late-stage cancers, mostly requiring chemotherapy, often develop treatment resistance. Chemoresistance has been linked to ER stress response; however, most of the evidence has come from studies that correlate the expression of stress markers with poor prognosis or demonstrate proapoptosis by the knockdown of stress-responsive genes. Since ER stress in cancers usually persists and is essentially not induced by genetic manipulations, we used low doses of ER stress inducers at levels that allowed cell adaptation to occur in order to investigate the effect of stress response on chemoresistance. We found that prolonged tolerable ER stress promotes mesenchymal–epithelial transition, slows cell-cycle progression, and delays the S-phase exit. Consequently, cisplatin-induced apoptosis was significantly decreased in stress-adapted cells, implying their acquisition of cisplatin resistance. Molecularly, we found that proliferating cell nuclear antigen (PCNA) ubiquitination and the expression of polymerase η, the main polymerase responsible for translesion synthesis across cisplatin-DNA damage, were up-regulated in ER stress-adaptive cells, and their enhanced cisplatin resistance was abrogated by the knockout of polymerase η. We also found that a fraction of p53 in stress-adapted cells was translocated to the nucleus, and that these cells exhibited a significant decline in the level of cisplatin-DNA damage. Consistently, we showed that the nuclear p53 coincided with strong positivity of glucose-related protein 78 (GRP78) on immunostaining of clinical biopsies, and the cisplatin-based chemotherapy was less effective for patients with high levels of ER stress. Taken together, this study uncovers that adaptation to ER stress enhances DNA repair and damage tolerance, with which stressed cells gain resistance to chemotherapeutics.     

Structure and crystallization behavior of complex mold flux glasses in the system CaO-Na2O-Li2O-CaF2-B2O3-SiO2: A multi-nuclear NMR spectroscopic study

The structure of mold flux glasses in the system CaO-(Na,Li)₂O-SiO₂-CaF₂ with unusually high modifier contents, stabilized by the addition of ∼4 mol% B₂O₃, is studied using ⁷Li, ²³Na, ¹⁹F, ¹¹B, and ²⁹Si magic-angle-spinning (MAS), and ⁷Li{¹⁹F} and ²³Na{¹⁹F} rotational echo double-resonance (REDOR) nuclear magnetic resonance (NMR) spectroscopy. When taken together, the spectroscopic results indicate that the structure of these glasses consists primarily of dimeric [Si₂O₇]⁻⁶ units that are linked to the (Ca,Na,Li)-O coordination polyhedra, and are interspersed with chains of corner-shared BO₃ units. The F atoms in the structure are exclusively bonded to Ca atoms, forming Ca(O,F)_n coordination polyhedra. This structural scenario is shown to be consistent with the crystallization of cuspidine (3CaO·2SiO₂·CaF₂) from the parent melts on slow supercooling. The progressive addition of Li to a Na-containing base composition results in a corresponding increase in the undercooling required for the nucleation of cuspidine in the melt, which is attributed to the frustrated local structure caused by the mixing of alkali ions.     

Photocatalytic degradation and heat reflectance recovery of waterborne acrylic polymer/ZnO nanocomposite coating

This work aims to clarify the photocatalytic degradation mechanism and heat reflectance recovery performance of waterborne acrylic polymer/ZnO nanocomposite coating. To fabricate the nanocomposite coating, ZnO nanoparticles (nano-ZnO) were dispersed into acrylic polymer matrix at the various concentrations from 1 to 6% (by total weight of resin solids). The photocatalytic degradation of nanocomposite coating under ultraviolet (UV) light irradiation has been investigated by monitoring its weight loss and chemical/microstructural/morphological changes. As the topcoat layer, its heat reflectance recovery has been evaluated under UV/condensation exposure by using an artificial dirty mixture of 85 wt% nanoclay, 10 wt% silica particles (1–5 μm), 1 wt% carbon black, and 2 wt% engine oil. After 108-cycle UV/condensation exposure, infrared spectra and weight loss analysis indicated that the maximal degradation for nanocomposite coating is observed at 1 wt% nano-ZnO. On the other hand, after 96 hr of UV light exposure, the nanocomposite coating with1 wt% nano-ZnO could restore effectively the reflective index of solar-heat reflectance coating (from 58.45 to 80.78%). Finally, the photodegradation mechanism of this waterborne acrylic polymer coating has been proposed as the UV-induced formation of CC CO conjugated double bonds. As a result, its self-cleaning phenomenon can be achieved as the recovery of heat reflectance.     

Advanced Surface of Fibrous Activated Carbon Immobilized with FeO/TiO2 for Photocatalytic Evolution of Hydrogen under Visible Light

FeO-doped TiO₂ nanoparticle photocatalysts were immobilized onto the surface of fibrous activated carbon (ACF) via a sol-gel process. As an adsorbent and photocatalyst, FeO-TiO₂ on immobilized ACFs (FeO-TiO₂/ACF) greatly improved the photocatalysis rate of hydrogen production as compared with pure TiO₂ and ACF-TiO₂ under UV irradiation and visible light. The addition of ACFs surface significantly reduced the photogenerated pairs of electrons-hole recombination, thereby promoting the photocatalysis action of doped photo-metal oxides of FeO-TiO₂. Co-doping of FeO onto the lattice of the TiO₂ approach can improve the absorption activity of visible light through photo-metal oxide of TiO₂ and further enhance hydrogen production under visible light. The photocatalytic fabrics (FeO-TiO₂/ACF) were effortlessly split out from the experimental solution for re-utilization and exhibited high stability even after five complete regeneration cycles.     

Automatic brain tissue segmentation in MR images using hybrid atlas forest based on confidence-weighted probability matrix

The segmentation of specific tissues in an MR brain image for quantitative analysis can assist the disease diagnosis and medical research. Therefore, a robust and accurate method for automatic segmentation is necessary. Atlas-based-method is a common and effective method of automatic segmentation where an atlas refers to a pair of image consist of an intensity image and its corresponding label image. Apart from the general multi-atlas-based methods, which propagate labels through the single atlas then fuse them, we proposed a hybrid atlas forest based on confidence-weighted probability matrix to consider the atlases set as a whole and treat each voxel differently. In the framework, we first register the atlas to the image space of target and calculate the confidence of voxels in the registered atlas. Then, a confidence-weighted probability matrix is generated and it augments to the intensity image of the atlas or target for providing spatial information of the target tissue. Third, a hybrid atlas forest is trained to gather the features and correlation information among the atlases in the dataset. Finally, the segmentation of the target tissues is predicted by the trained hybrid atlas forest. The segment performance and the components efficiency of the proposed method are evaluated on the two public datasets. Based on the experiment results and quantitative comparisons, our method can gather spatial information and correlation among the atlases to obtain an accurate segmentation.