Mechanistic investigations reveal that dibromobimane extrudes sulfur from biological sulfhydryl sources other than hydrogen sulfide

Hydrogen sulfide (H₂S) has emerged as an important biological signaling molecule in the last decade. During the growth of this field, significant controversy has arisen centered on the physiological concentrations of H₂S. Recently, a monobromobimane (mBB) method has been developed for the quantification of different biologically-relevant sulfide pools. Based on the prevalence of the mBB method for sulfide quantification, we expand on this method to report the use of dibromobimane (dBB) for sulfide quantification. Reaction of H₂S with dBB results in formation of highly-fluorescent bimane thioether (BTE), which is readily quantifiable by HPLC. Additionally, the reaction of sulfide with dBB to form BTE is significantly faster than the reaction of sulfide with mBB to form sulfide dibimane. Using the dBB method, BTE levels as low as 0.6 pM can be detected. Upon use of the dBB method in wild-type and CSE^–/– mice, however, dBB reports significantly higher sulfide levels than those measured using mBB. Further investigation revealed that dBB is able to extract sulfur from other sulfhydryl sources including thiols. Based on mechanistic studies, we demonstrate that dBB extracts sulfur from thiols with α- or β-hydrogens, thus leading to higher BTE formation than from sulfide alone. Taken together, the dBB method is a highly sensitive method for H₂S but is not compatible for use in studies in which other thiols are present.     

Cytotoxicity of guanine-based degradation products contributes to the antiproliferative activity of guanine-rich oligonucleotides

Guanine-rich oligonucleotides (GROs) have attracted considerable attention as anticancer agents, because they exhibit cancer-selective antiproliferative activity and can form G-quadruplex structures with higher nuclease resistance and cellular uptake. Recently, a GRO, AS1411 has reached phase II clinical trials for acute myeloid leukemia and renal cell carcinoma. The antiproliferative activity of GROs has been associated with various protein targets; however the real mechanisms of action remain unclear. In this study, we showed evidence that antiproliferative activity of GROs (including AS1411) is mainly contributed by the cytotoxicity of their guanine-based degradation products, such as monophosphate deoxyguanosine (dGMP), deoxyguanosine (dG) and guanine. The GROs with lower nuclease resistance exhibited higher antiproliferative activity. Among nucleotides, nucleosides and nucleobases, only guanine-based compounds showed highly concentration-dependent cytotoxicity. Our results suggest that it is necessary to reconsider the cancer-selective antiproliferative activity of GROs. Since guanine-based compounds are endogenous substances in living organisms, systematic studies of the cytotoxicity of these compounds will provide new information for the understanding of certain diseases and offer useful information for drug design.     

A pH-activatable and aniline-substituted photosensitizer for near-infrared cancer theranostics

This work reports a newly designed pH-activatable and aniline-substituted aza-boron-dipyrromethene as a trifunctional photosensitizer to achieve highly selective tumor imaging, efficient photodynamic therapy (PDT) and therapeutic self-monitoring through encapsulation in a cRGD-functionalized nanomicelle. The diethylaminophenyl is introduced in to the structure for pH-activatable near-infrared fluorescence and singlet oxygen (¹O₂) generation, and bromophenyl is imported to increase the ¹O₂ generation efficiency upon pH activation by virtue of its heavy atom effect. After encapsulation, the nanoprobe can target α_vβ₃ integrin-rich tumor cells via cRGD and is activated by physiologically acidic pH for cancer discrimination and PDT. The fascinating advantage of the nanoprobe is near-infrared implementation beyond 800 nm, which significantly improves the imaging sensitivity and increases the penetration depth of the PDT. By monitoring the fluorescence decrease in the tumor region after PDT, the therapeutic efficacy is demonstrated in situ and in real time, which provides a valuable and convenient self-feedback function for PDT efficacy tracking. Therefore, this rationally designed and carefully engineered nanoprobe offers a new paradigm for precise tumor theranostics and may provide novel opportunities for future clinical cancer treatment.     

Algorithm of Barrier Objective Penalty Function

In this paper, an algorithm of barrier objective penalty function for inequality constrained optimization is studied and a conception–the stability of barrier objective penalty function is presented. It is proved that an approximate optimal solution may be obtained by solving a barrier objective penalty function for inequality constrained optimization problem when the barrier objective penalty function is stable. Under some conditions, the stability of barrier objective penalty function is proved for convex programming. Specially, the logarithmic barrier function of convex programming is stable. Based on the barrier objective penalty function, an algorithm is developed for finding an approximate optimal solution to an inequality constrained optimization problem and its convergence is also proved under some conditions. Finally, numerical experiments show that the barrier objective penalty function algorithm has better convergence than the classical barrier function algorithm.     

Hexagram-like CoS-MoS<Subscript>2</Subscript> composites with enhanced activity for hydrogen evolution reaction

Hexagram-like CoS-MoS₂ composites were prepared on indium tin oxide (ITO) conductive glasses via cyclic voltammetry electrodeposition using Co(NO₃)₂ and (NH₄)₂MoS₂ as precursors and tested for application in hydrogen evolution reaction (HER). The structure of CoS-MoS₂ composites was characterized by X-ray diffraction (XRD), scanning electron microscope (SEM), and X-ray photoelectron spectrum (XPS). Electrochemical characterizations indicate that CoS-MoS₂ composites exhibit more excellent catalytic activity and stability than MoS₂. Compared with pure MoS₂, the hexagram-like CoS-MoS₂ composites with increased specific surface area improved the density of exposed active sites, and the Co binding S edges in CoS-MoS₂ composites promote the number of highly catalytic edge sites and decreased the binding energy △G _H. Moreover, the effects of different substrates on the CoS-MoS₂ composites were also investigated. Our further understanding of this highly active hydrogen evolution catalyst can facilitate the development of economical electrochemical hydrogen production systems.     

广义线性多乘积问题的完全多项式时间近似算法

本文针对广义线性多乘积极小化问题,通过一系列的线性规划问题的解提出一种求其全局最优解的完全多项式时间近似算法,并给出该算法的计算复杂性,且数值算例验证该算法是可行的.     

Perfect contrast XOR-based visual cryptography schemes via linear algebra

XOR-based visual cryptography scheme (XVCS) was proposed to solve the poor visual quality problem without darkening the background in the reconstructed secret image. However, investigations on XVCS are not sufficient. In this paper, we focus on the traditional model of VCS for general access structures and exploit some extended capabilities for XVCS. Our main contributions are: (1) we put forward constructions of perfect contrast XVCS using the linear algebraic technique without any assumptions such as participants may carry multiple shares or prior information about the shares are to be submitted during the secret reconstruction phase; (2) for some restricted access structures, we achieve perfect contrast and perfect pixel expansion, namely both 1, which is impossible for any OR-based visual cryptography scheme (OVCS); (3) for general access structures, we achieve perfect contrast with smaller pixel expansion compared with many of the results in the literature; (4) Theoretical analysis on the proposed constructions are provided, as well as extensive experimental results and comparisons for demonstrating the effectiveness and advantages of our constructions.     

Directional Frames for Image Recovery: Multi-scale Discrete Gabor Frames

Sparsity-driven image recovery methods assume that images of interest can be sparsely approximated under some suitable system. As discontinuities of 2D images often show geometrical regularities along image edges with different orientations, an effective sparsifying system should have high orientation selectivity. There have been enduring efforts on constructing discrete frames and tight frames for improving the orientation selectivity of tensor product real-valued wavelet bases/frames. In this paper, we studied the general theory of discrete Gabor frames for finite signals, and constructed a class of discrete 2D Gabor frames with optimal orientation selectivity for sparse image approximation. Besides high orientation selectivity, the proposed multi-scale discrete 2D Gabor frames also allow us to simultaneously exploit sparsity prior of cartoon image regions in spatial domain and the sparsity prior of textural image regions in local frequency domain. Using a composite sparse image model, we showed the advantages of the proposed discrete Gabor frames over the existing wavelet frames in several image recovery experiments.     

Bayesian Model Assessment in Joint Modeling of Longitudinal and Survival Data With Applications to Cancer Clinical Trials

Joint models for longitudinal and survival data are routinely used in clinical trials or other studies to assess a treatment effect while accounting for longitudinal measures such as patient-reported outcomes. In the Bayesian framework, the deviance information criterion (DIC) and the logarithm of the pseudo-marginal likelihood (LPML) are two well-known Bayesian criteria for comparing joint models. However, these criteria do not provide separate assessments of each component of the joint model. In this article, we develop a novel decomposition of DIC and LPML to assess the fit of the longitudinal and survival components of the joint model, separately. Based on this decomposition, we then propose new Bayesian model assessment criteria, namely, ΔDIC and ΔLPML, to determine the importance and contribution of the longitudinal (survival) data to the model fit of the survival (longitudinal) data. Moreover, we develop an efficient Monte Carlo method for computing the conditional predictive ordinate statistics in the joint modeling setting. A simulation study is conducted to examine the empirical performance of the proposed criteria and the proposed methodology is further applied to a case study in mesothelioma. Supplementary materials for this article are available online.