Identification of In Vitro Metabolites of Synthetic Phenolic Antioxidants BHT,BHA, and TBHQ by LC-HRMS/MS

Butylated hydroxytoluene (BHT) and its analogs, butylated hydroxyanisole (BHA) and tert-butyl-hydroquinone (TBHQ), are widely used synthetic preservatives to inhibit lipid oxidation in the food, cosmetic and pharmaceutical industries. Despite their widespread use, little is known about their human exposure and related biotransformation products. The metabolism of these compounds was investigated using in vitro incubations with human and rat liver fractions. Liquid chromatography coupled to high-resolution tandem mass spectrometry was employed to detect and characterize stable and reactive species formed via oxidative metabolism, as well as phase II conjugates. Several oxidative metabolites have been detected, as well as glutathione, glucuronide, and sulfate conjugates, many of which were not previously reported. A combination of accurate mass measurements, MS/MS fragmentation behavior, and isotope-labeling studies were used to elucidate metabolite structures.     

EGFR-Binding Peptides: From Computational Design towards Tumor-Targeting of Adeno-Associated Virus Capsids

The epidermal growth factor receptor (EGFR) plays a central role in the progression of many solid tumors. We used this validated target to analyze the de novo design of EGFR-binding peptides and their application for the delivery of complex payloads via rational design of a viral vector. Peptides were computationally designed to interact with the EGFR dimerization interface. Two new peptides and a reference (EDA peptide) were chemically synthesized, and their binding ability characterized. Presentation of these peptides in each of the 60 capsid proteins of recombinant adeno-associated viruses (rAAV) via a genetic based loop insertion enabled targeting of EGFR overexpressing tumor cell lines. Furthermore, tissue distribution and tumor xenograft specificity were analyzed with systemic injection in chicken egg chorioallantoic membrane (CAM) assays. Complex correlations between the targeting of the synthetic peptides and the viral vectors to cells and in ovo were observed. Overall, these data demonstrate the potential of computational design in combination with rational capsid modification for viral vector targeting opening new avenues for viral vector delivery and specifically suicide gene therapy.     

大口径光学元件装夹转运结构设计及分析

为了实现大口径光学元件的安全装夹、转运,通过光学元件开槽与不开槽两种装夹方式的分析,得出开槽夹紧转运方式将带来微裂纹、应力集中、成本高等缺陷,提出了利用摩擦力克服光学零件的重力和惯性力的低应力装夹转运方案。通过对光学元件低应力夹紧结构设计,并利用有限元分析方法,得到不开槽装夹方式下,光学元件的最大主应力为1.11 MPa,最大切应力为0.73 MPa,远低于光学元件破坏的强度极限,且受力均匀,无应力集中现象。     

A self-adaptive synthetic over-sampling technique for imbalanced classification

Traditionally, in supervised machine learning, (a significant) part of the available data (usually 50%-80%) is used for training and the rest—for validation. In many problems, however, the data are highly imbalanced in regard to different classes or does not have good coverage of the feasible data space which, in turn, creates problems in validation and usage phase. In this paper, we propose a technique for synthesizing feasible and likely data to help balance the classes as well as to boost the performance in terms of confusion matrix as well as overall. The idea, in a nutshell, is to synthesize data samples in close vicinity to the actual data samples specifically for the less represented (minority) classes. This has also implications to the so-called fairness of machine learning. In this paper, we propose a specific method for synthesizing data in a way to balance the classes and boost the performance, especially of the minority classes. It is generic and can be applied to different base algorithms, for example, support vector machines, k-nearest neighbour classifiers deep neural, rule-based classifiers, decision trees, and so forth. The results demonstrated that (a) a significantly more balanced (and fair) classification results can be achieved and (b) that the overall performance as well as the performance per class measured by confusion matrix can be boosted. In addition, this approach can be very valuable for the cases when the number of actual available labelled data is small which itself is one of the problems of the contemporary machine learning.     

Recent Biophysical Issues About the Preparation of Solute-Filled Lipid Vesicles

Here we report some recent biophysical issues on the preparation of solute-filled lipid vesicles and their relevance to the construction of “synthetic cells.” First, we introduce the “semi-synthetic minimal cells” as the liposome-based cell-like systems, which contain a minimal number of biomolecules required to display simple and complex biological functions. Next, we focus on recent aspects related to the construction of synthetic cells. Emphasis is given to the interplay between the methods of synthetic cell preparation and the physics of solute encapsulation. We briefly introduce the notion of structural and compositional “diversity” in synthetic cell populations.     

Change detection in synthetic aperture radar images based on unsupervised artificial immune systems

In this paper, we propose a novel change detection method for synthetic aperture radar images based on unsupervised artificial immune systems. After generating the difference image from the multitemporal images, we take each pixel as an antigen and build an immune model to deal with the antigens. By continuously stimulating the immune model, the antigens are classified into two groups, changed and unchanged. Firstly, the proposed method incorporates the local information in order to restrain the impact of speckle noise. Secondly, the proposed method simulates the immune response process in a fuzzy way to get an accurate result by retaining more image details. We introduce a fuzzy membership of the antigen and then update the antibodies and memory cells according to the membership. Compared with the clustering algorithms we have proposed in our previous works, the new method inherits immunological properties from immune systems and is robust to speckle noise due to the use of local information as well as fuzzy strategy. Experiments on real synthetic aperture radar images show that the proposed method performs well on several kinds of difference images and engenders more robust result than the other compared methods.     

A side-sensitive synthetic coefficient of variation chart

Control charts for monitoring the coefficient of variation (γ) are useful for processes with an inconsistent mean (μ) and a standard deviation (σ) which changes with μ, by monitoring the consistency in the ratio σ over μ. The synthetic-γ chart is one of the charts proposed to monitor γ, and its attractiveness lie in waiting until a second point to fall outside the control limits before a decision is made. However, existing synthetic-γ charts do not differentiate between the points falling outside the upper control limit (UCL) and lower control limit (LCL). Hence, this paper proposes a side-sensitive synthetic-γ chart, where successive nonconforming samples must either fall above the UCL or below the LCL. Formulae to compute the average run length (ARL), the standard deviation of the run length (SDRL) and expected average run length (EARL) are derived using the Markov chain approach, and the algorithms to obtain the optimal charting parameters are proposed. Subsequently, the optimal charting parameters, ARL, SDRL and EARL values for various numerical examples are shown. Comparisons show that the side-sensitive synthetic-γ chart consistently outperforms the existing synthetic-γ chart, especially for small shifts. The proposed chart also consistently outperforms the Shewhart-γ chart, while showing comparable or better performance than the Exponentially Weighted Moving Average (EWMA) chart for most shift sizes, except for very small shifts. Finally, this paper shows the implementation of the proposed chart on an industrial example.     

An Artificial Skyrmion Platform with Robust Tunability in Synthetic Antiferromagnetic Multilayers

Magnetic skyrmions are topologically nontrivial spin structures, and their existence in ferromagnetically coupled multilayers has been widely reported with a disordered arrangement. Here, a nucleation scenario of ordered skyrmions in nanostructured synthetic antiferromagnetic (SAF) multilayers is proposed and experimentally demonstrated using direct magnetization imaging, indirect magnetometer and magnetoresistance measurement, and micromagnetic simulation. Instead of relying on Dzyaloshinskii–Moriya interaction, the antiferromagnetic interlayer exchange coupling in the SAF multilayers fulfills the role of nucleation and stabilization of skyrmions. The robustness of the proposed skyrmion nucleation scenario is examined against temperature from 4.5 to 300 K and device size from 400 to 1200 nm. Interestingly, these synthetic skyrmions still behave well with a size less than 100 nm. The higher stability than generic magnetic domains can be attributed to topological protection. The results thus provide an artificial skyrmion platform to meet the functional needs of high density and designable arrangement in magnonic and spintronic applications.     

Fourier transform ion cyclotron resonance mass spectrometry at the true cyclotron frequency

Ion cyclotron resonance (ICR) cells provide stability and coherence of ion oscillations in crossed electric and magnetic fields over extended periods of time. Using the Fourier transform enables precise measurements of ion oscillation frequencies. These precisely measured frequencies are converted into highly accurate mass-to-charge ratios of the analyte ions by calibration procedures. In terms of resolution and mass accuracy, Fourier transform ICR mass spectrometry (FT-ICR MS) offers the highest performance of any MS technology. This is reflected in its wide range of applications. However, in the most challenging MS application, for example, imaging, enhancements in the mass accuracy of fluctuating ion fluxes are required to continue advancing the field. One approach is to shift the ion signal power into the peak corresponding to the true cyclotron frequency instead of the reduced cyclotron frequency peak. The benefits of measuring the true cyclotron frequency include increased tolerance to electric fields within the ICR cell, which enhances frequency measurement precision. As a result, many attempts to implement this mode of FT-ICR MS operation have occurred. Examples of true cyclotron frequency measurements include detection of magnetron inter-harmonics of the reduced cyclotron frequency (i.e., the sidebands), trapping field-free (i.e., screened) ICR cells, and hyperbolic ICR cells with quadrupolar ion detection. More recently, ICR cells with spatially distributed ion clouds have demonstrated attractive performance characteristics for true cyclotron frequency ion detection. Here, we review the corresponding developments in FT-ICR MS over the past 40 years.