An Antireflective Nanostructure Array Fabricated by Nanosilver Colloidal Lithography on a Silicon Substrate

An alternative method is presented for fabricating an antireflective nanostructure array using nanosilver colloidal lithography. Spin coating was used to produce the multilayered silver nanoparticles, which grew by self-assembly and were transformed into randomly distributed nanosilver islands through the thermodynamic action of dewetting and Oswald ripening. The average size and coverage rate of the islands increased with concentration in the range of 50–90 nm and 40–65%, respectively. The nanosilver islands were critically affected by concentration and spin speed. The effects of these two parameters were investigated, after etching and wet removal of nanosilver residues. The reflection nearly disappeared in the ultraviolet wavelength range and was 17% of the reflection of a bare silicon wafer in the visible range

Structural basis for DNA damage-induced phosphoregulation of MDM2 RING domain

Phosphorylation of MDM2 by ATM upon DNA damage is an important mechanism for deregulating MDM2, thereby leading to p53 activation. ATM phosphorylates multiple residues near the RING domain of MDM2, but the underlying molecular basis for deregulation remains elusive. Here we show that Ser429 phosphorylation selectively enhances the ubiquitin ligase activity of MDM2 homodimer but not MDM2-MDMX heterodimer. A crystal structure of phospho-Ser429 (pS429)-MDM2 bound to E2–ubiquitin reveals a unique 310-helical feature present in MDM2 homodimer that allows pS429 to stabilize the closed E2–ubiquitin conformation and thereby enhancing ubiquitin transfer. In cells Ser429 phosphorylation increases MDM2 autoubiquitination and degradation upon DNA damage, whereas S429A substitution protects MDM2 from auto-degradation. Our results demonstrate that Ser429 phosphorylation serves as a switch to boost the activity of MDM2 homodimer and promote its self-destruction to enable rapid p53 stabilization and resolve a long-standing controversy surrounding MDM2 auto-degradation in response to DNA damage

Engineered Models of Metastasis with Application to Study Cancer Biomechanics

Three-dimensional complex biomechanical interactions occur from the initial steps of tumor formation to the later phases of cancer metastasis. Conventional monolayer cultures cannot recapitulate the complex microenvironment and chemical and mechanical cues that tumor cells experience during their metastatic journey, nor the complexity of their interactions with other, noncancerous cells. As alternative approaches, various engineered models have been developed to recapitulate specific features of each step of metastasis with tunable microenvironments to test a variety of mechanistic hypotheses. Here the main recent advances in the technologies that provide deeper insight into the process of cancer dissemination are discussed, with an emphasis on three-dimensional and mechanical factors as well as interactions between multiple cell types

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)1.

In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field

EEG artifacts reduction by multivariate empirical mode decomposition and multiscale entropy for monitoring depth of anaesthesia during surgery

Electroencephalography (EEG) has been widely utilized to measure the depth of anaesthesia (DOA) during operation. However, the EEG signals are usually contaminated by artifacts which have a consequence on the measured DOA accuracy. In this study, an effective and useful filtering algorithm based on multivariate empirical mode decomposition and multiscale entropy (MSE) is proposed to measure DOA. Mean entropy of MSE is used as an index to find artifacts-free intrinsic mode functions. The effect of different levels of artifacts on the performances of the proposed filtering is analysed using simulated data. Furthermore, 21 patients' EEG signals are collected and analysed using sample entropy to calculate the complexity for monitoring DOA. The correlation coefficients of entropy and bispectral index (BIS) results show 0.14 ± 0.30 and 0.63 ± 0.09 before and after filtering, respectively. Artificial neural network (ANN) model is used for range mapping in order to correlate the measurements with BIS. The ANN method results show strong correlation coefficient (0.75 ± 0.08). The results in this paper verify that entropy values and BIS have a strong correlation for the purpose of DOA monitoring and the proposed filtering method can effectively filter artifacts from EEG signals. The proposed method performs better than the commonly used wavelet denoising method. This study provides a fully adaptive and automated filter for EEG to measure DOA more accuracy and thus reduce risk related to maintenance of anaesthetic agents.This research was financially supported by the Center for Dynamical Biomarkers and Translational Medicine, National Central University, Taiwan, which is sponsored by Ministry of Science and Technology (Grant Number: NSC102-2911-I-008-001). Also, it was supported by Chung-Shan Institute of Science and Technology in Taiwan (Grant Numbers: CSIST-095-V301 and CSIST-095-V302) and National Natural Science Foundation of China (Grant Number: 51475342)

Intrusion Confinement By Isolation In Information Systems

System protection mechanisms such as access controls can be fooled by authorized but malicious users, masqueraders, and misfeasors. Intrusion detection techniques are therefore used to supplement them. However, damage could have occurred before an intrusion is detected. In many computing systems the requirement for a high degree of soundness of intrusion reporting can yield poor performance in detecting intrusions, and can cause long detection latency. As a result, serious damage can be caused either because many intrusions are never detected or because the average detection latency is too long. The process of bounding the damage caused by intrusions during the process of intrusion detection is referred to as intrusion confinement. We justify the necessity for intrusion confinement during detection by a probabilistic analysis model, and propose a general solution to achieve intrusion confinement. The crux of the solution is to isolate likely suspicious actions before a definite determi..