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The antioxidant defense system in malignant cells, which involves antioxidant enzymes and antioxidant molecules, is an innate barrier to photodynamic therapy (PDT). Because of the complexity of the endogenous antioxidant mechanisms of these cells, simply inhibiting individual antioxidant pathways has a limited effect on improving the lethality of ROS. To enhance the efficacy of PDT for tumor treatment, a versatile nanoparticle (NP)-based drug is developed, which the authors call PZB NP, containing the glutathione inhibitor l-buthionine sulfoximine (BSO) and the heme oxygenase 1 (HO-1) inhibitor protoporphyrin zinc(II) (ZnPP) to suppress the innate antioxidant defense system of cancer cells in a two-pronged manner. BSO reduces intracellular glutathione levels to minimize ROS elimination and protein protection during PDT, and ZnPP inhibits the ROS-stimulated upregulation of the antioxidant HO-1, thus preventing ROS removal by cells after PDT. Thus, BSO and ZnPP synergistically suppress the antioxidant defense systems of cancer cells both during and after protoporphyrin-IX-mediated PDT in a two-pronged manner, resulting in tumor cell death through excess oxidative pressure. The results demonstrate that the construction of nanodrugs having dual antioxidation defense suppression properties is a promising route for the development of highly efficient ROS-based therapies.

To meet the world's ever growing energy demand, the E&P industry is developing new technologies to find and drill for hydrocarbons in more challenging environments such as deep water or deep targets, and to enter areas of the world that had previously been closed to exploration activities, such as the Arctic. While the Arctic was looked at geologically several times in the last century, the technological challenges that it presents restricted activities to the periphery of this vast collection of basins. Despite the significant resource estimates shown in Figure 1, the extreme environmental conditions combined with the vast remoteness of this region have limited exploration and development efforts to date.

Various reverse time migration (RTM) angle gather generation techniques have been developed to address poor subsalt data quality and multiarrival induced problems in gathers from Kirchhoff migration. But these techniques introduce new problems, such as inaccuracies in 2D subsurface angle gathers and edge diffraction artifacts in 3D subsurface angle gathers. The unique rich-azimuth data set acquired over the Shenzi field in the Gulf of Mexico enabled the generally artifact-free generation of 3D subsurface angle gathers. Using this data set, we carried out suprasalt tomography and salt model building steps and then produced 3D angle gathers to update the subsalt velocity. We used tilted transverse isotropy RTM with extended image condition to generate full 3D subsurface offset domain common image gathers, which were subsequently converted to 3D angle gathers. The angle gathers were substacked along the subsurface azimuth axis into azimuth sectors. Residual moveout analysis was carried out, and ray-based tomography was used to update velocities. The updated velocity model resulted in improved imaging of the subsalt section. We also applied residual moveout and selective stacking to 3D angle gathers from the final migration to produce an optimized stack image.

The field of subsalt imaging has evolved rapidly in the last decade, thanks in part to the availability of low cost massive computing infrastructure, and also to the development of new seismic acquisition techniques that try to mitigate the problems caused by the presence of salt. This paper serves as an introduction to the special Geophysics section on Subsalt Imaging for E&P. The purpose of the special section is to bring together practitioners of subsalt imaging in the wider sense, i.e., not only algorithm developers, but also the interpretation community that utilizes the latest technology to carry out subsalt exploration and development. The purpose of the paper is in many ways pedagogical and historical. We address the question of what subsalt imaging is and discuss the physics of the subsalt imaging problem, especially the illumination issue. After a discussion of the problem, we then give a review of the main algorithms that have been developed and implemented within the last decade, namely Kirchhoff and Beam imaging, one-way wavefield extrapolation methods and the full two-way reverse time migration. This review is not meant to be exhaustive, and is qualitative to make it accessible to a wide audience. For each method and algorithm we highlight the benefits and the weaknesses. We then address the imaging conditions that are a fundamental part of each imaging algorithm. While we dive into more technical detail, the section should still be accessible to a wide audience. Gathers of various sorts are introduced and their usage explained. Model building and velocity update strategies and tools are presented next. Finally, the last section shows a few results from specific algorithms. The latest techniques such as waveform inversion or the “dirty salt” techniques will not be covered, as they will be elaborated upon by other authors in the special section. With the massive effort that the industry has devoted to this field, much remains to be done to give interpreters the accurate detailed images of the subsurface that are needed. In that sense the salt is still winning, although the next decade will most likely change this situation.

This article covers recent developments in the depth-imaging technology known as reverse time migration (RTM). RTM will be compared to Kirchhoff, beam, and other wave-equation migration techniques. Special emphasis will be placed on the practical application of this technology to reduce exploration cycle time and risk. Recent trends such as TTI anisotropy and wide-azimuth applications will also be discussed.

Feature selection is problematic when the number of potential features is very large. Absent distribution knowledge, to select a best feature set of a certain size requires that all feature sets of that size be examined. This paper considers the question in the context of variable selection for prediction based on the coefficient of determination (CoD). The CoD varies between 0 and 1, and measures the degree to which prediction is improved by using the features relative to prediction in the absence of the features. It examines the following heuristic: if we wish to find feature sets of size m with CoD exceeding δ, what is the effect of only considering a feature set if it contains a subset with CoD exceeding λ δ | max{θ1,θ2,...,θv} < λ), where θ is the CoD of the feature set and θ1,θ2,...,θv are the CoDs of the subsets. Such probabilities allow a rigorous analysis of the following decision procedure: the feature set is examined if max{θ1,θ2,...,θv} ≥ λ. Computational saving increases as λ increases, but the probability of missing desirable feature sets increases as the increment δ - λ decreases; conversely, computational saving goes down as λ decreases, but the probability of missing desirable feature sets decreases as δ - λ increases. The paper considers various loss measures pertaining to omitting feature sets based on the criteria. After specializing the matter to binary features, it considers a simulation model, and then applies the theory in the context of microarray-based genomic CoD analysis. It also provides optimal computational algorithms.

Building on previous work reported elsewhere [Zhou, 2001, 2002, O’brien, 2001], we present some new developments in our Prestack Wave Equation Depth Migration and the results obtained by applying it to both classic and newly acquired SEG/EAGE 3-D Salt Model datasets. The migration improvements include a new imaging condition that addresses amplitude and obliquity issues such as source ghosting and the requirements of “true-amplitude” imaging. The new dataset is composed of 63 OBC-like shots with higher frequency content and attenuated surface-related multiples. The coverage contains a full azimuthal range and 6.5km of offset. We believe the results represent a level of sub-salt imaging quality rarely seen from this model in the published literature.

GLEAMS is a robust, stable and accurate image capture and quantification method for microarrays. It is capable of fully and automatically detecting and quantifying the expression spots. This can be done in a batch mode, without human intervention, achieving a high throughput of parallel data processing. Simple to use visual tools are provided to estimate parameters and to submit, monitor and control jobs execution. The un-supervised batch auto-alignment is based on a novel method requiring only knowledge of the number of rows and columns of dots in the array. Distances between dots along rows and columns are estimated from the image's auto- correlation function. This is also used to align the array and the sides of the image. Applying intensity and geometric constraints to the cross-correlation function between the image and a template sub-array, the location of the sub-arrays can be determined. Carefully implemented, the algorithm can approach human vision in its sensitivity and accuracy in finding the general positions of dots in a micro-array image. Subsequent spot quantification uses Ostu's thresholding method followed by some morphological operations, including the application of a constraining shape mask. Segmentation techniques are applied to detect and remove speckles from the targets and to ensure the veracity of the data extracted.

Summary We present a practical implementation of the one-way wave equation based 3-D prestack implicit finite-difference depth migration(IFDM). Conventional aspects of IFDM, including the Crank-Nicholson method, the continued-fraction expansion of the square-root operator, the compact implicit finite difference stencil, the x-y operator split, and Zhiming Li's error compensation, are combined to produce a downward continuation process with accurate kinematic and dynamic response up to 90°, even when the velocity field varies laterally by a factor of 2 or more. This downward continuation method is combined with appropriate aperture and imaging conditions to produce, from shot-gathered full-azimuth prestack data, depth-migrated image gathers in the conventional offset domain. A computationally highly efficient parallel implementation has been achieved without any sacrifice in accuracy. Introduction Even sophisticated Kirchhoff prestack depth migration techniques are faced with many theoretical and practical difficulties. These include the limitations of the high frequency and single arrival approximations, as well as the problems with amplitude control based on simplified geometrical or statistical considerations. It has long been known that the solution to these problems is a wave equation based method. Due to the difficulties associated with imaging with the full acoustic wave equation(Claerbout), most attention has been focused on the one-way or paraxial wave equation. However, because of its high computational cost, even full solutions to the one-way equation have been considered impractical when 3-D prestack migrated image gathers are desired. This situation has forced researchers to seek various additional approximations to the one-way equation that can significantly increase computational efficiency. One class of such approaches limits accurate wave propagation angle to 75° from vertical, when lateral velocity variation is severe. Another approach is the reduction of dimensionality through the common azimuth approximation (Biondi). Even after such approximations, the wave equation based methods are still generally capable of producing images better than those from Kirchhoff migrations(Vaillant). Basing our technique on the Salvo software(Ober), we have developed a practical one-way wave-equation migration system that has wide angle (up to 90°) accuracy for any realistic velocity contrast and can handle full-azimuth wave propagation and data acquisition. While this method employs a series of approximations to the one-way equation, the error introduced by each approximation, as well as any numerical error inherent in finite differences, are collected and compensated for. The result is a solution to the one-way equation that has no error of significance in the context of seismic imaging. Compared to both common Kirchhoff migrations and double- square-root(DSR) based wave-equation methods, finite difference(FD) shot migrations require less memory, disk, and network resources, which in modern computing environments often overshadow raw CPU cost. It can scale to massive, distributed-memory environments as well as large shared- memory computers, with no loss in efficiency. This method also does not require data regularization, velocity model smoothing, or other quality compromising preprocessing steps. More importantly, our implementation proves to be efficient enough to produce offset-domain 3-D depth-migrated image gathers at a computational cost that is competitive with high- end Kirchhoff migration. Additionally, it offers potential savings in the cost of data acquisition and transmission, which is often geared toward Kirchhoff migrations, and therefore retains more data redundancy than necessary to generate high quality images.

An integrated approach to the extraction, storage, processing and analysis of microarray gene expression data