Green's theorem in seismic imaging across the scales

The earthquake seismology and seismic exploration communities have developed a variety of seismic imaging methods for passive- and active-source data. Despite the seemingly different approaches and underlying principles, many of those methods are based in some way or another on Green's theorem. The aim of this paper is to discuss a variety of imaging methods in a systematic way, using a specific form of Green's theorem (the homogeneous Green's function representation) as a common starting point. The imaging methods we cover are time-reversal acoustics, seismic interferometry, back propagation, source–receiver redatuming and imaging by double focusing. We review classical approaches and discuss recent developments that fully account for multiple scattering, using the Marchenko method. We briefly indicate new applications for monitoring and forecasting of responses to induced seismic sources, which are discussed in detail in a companion paper.</p

Filtering Deterministic Layer Effects in Imaging

Sensor array imaging arises in applications such as nondestructive evaluation of materials with ultrasonic waves, seismic exploration, and radar. The sensors probe a medium with signals and record the resulting echoes, which are then processed to determine the location and reflectivity of remote reflectors. These could be defects in materials such as voids, fault lines or salt bodies in the earth, and cars, buildings, or aircraft in radar applications. Imaging is relatively well understood when the medium through which the signals propagate is smooth, and therefore nonscattering. But in many problems the medium is heterogeneous, with numerous small inhomogeneities that scatter the waves. We refer to the collection of inhomogeneities as clutter, which introduces an uncertainty in imaging because it is unknown and impossible to estimate in detail. We model the clutter as a random process. The array data is measured in one realization of the random medium, and the challenge is to mitigate cumulative clutter scattering so as to obtain robust images that are statistically stable with respect to different realizations of the inhomogeneities. Scatterers that are not buried too deep in clutter can be imaged reliably with the coherent interferometric (CINT) approach. But in heavy clutter the signal-to-noise ratio (SNR) is low and CINT alone does not work. The “signal,” the echoes from the scatterers to be imaged, is overwhelmed by the “noise,” the strong clutter reverberations. There are two existing approaches for imaging at low SNR: The first operates under the premise that data are incoherent so that only the intensity of the scattered field can be used. The unknown coherent scatterers that we want to image are modeled as changes in the coefficients of diffusion or radiative transport equations satisfied by the intensities, and the problem becomes one of parameter estimation. Because the estimation is severely ill-posed, the results have poor resolution, unless very good prior information is available and large arrays are used. The second approach recognizes that if there is some residual coherence in the data, that is, some reliable phase information is available, it is worth trying to extract it and use it with well-posed coherent imaging methods to obtain images with better resolution. This paper takes the latter approach and presents a first attempt at enhancing the SNR of the array data by suppressing medium reverberations. It introduces filters, or annihilators of layer backscatter, that are designed to remove primary echoes from strong, isolated layers in a medium with additional random layering at small, subwavelength scales. These strong layers are called deterministic because they can be imaged from the data. However, our goal is not to image the layers, but to suppress them and thus enhance the echoes from compact scatterers buried deep in the medium. Surprisingly, the layer annihilators work better than intended, in the sense that they suppress not only the echoes from the deterministic layers, but also multiply scattered ones in the randomly layered structure. Following the layer annihilators presented here, other filters of general, nonlayered heavy clutter have been developed. We review these more recent developments and the challenges of imaging in heavy clutter in the introduction in order to place the research presented here in context. We then present in detail the layer annihilators and show with analysis and numerical simulations how they work

The SPINK gene family and celiac disease susceptibility

The gene family of serine protease inhibitors of the Kazal type (SPINK) are functional and positional candidate genes for celiac disease (CD). Our aim was to assess the gut mucosal gene expression and genetic association of SPINK1, -2, -4, and -5 in the Dutch CD population. Gene expression was determined for all four SPINK genes by quantitative reverse-transcription polymerase chain reaction in duodenal biopsy samples from untreated (n = 15) and diet-treated patients (n = 31) and controls (n = 16). Genetic association of the four SPINK genes was tested within a total of 18 haplotype tagging SNPs, one coding SNP, 310 patients, and 180 controls. The SPINK4 study cohort was further expanded to include 479 CD cases and 540 controls. SPINK4 DNA sequence analysis was performed on six members of a multigeneration CD family to detect possible point mutations or deletions. SPINK4 showed differential gene expression, which was at its highest in untreated patients and dropped sharply upon commencement of a gluten-free diet. Genetic association tests for all four SPINK genes were negative, including SPINK4 in the extended case/control cohort. No SPINK4 mutations or deletions were observed in the multigeneration CD family with linkage to chromosome 9p21-13 nor was the coding SNP disease-specific. SPINK4 exhibits CD pathology-related differential gene expression, likely derived from altered goblet cell activity. All of the four SPINK genes tested do not contribute to the genetic risk for CD in the Dutch population

LocoMMotion: a prospective, non-interventional, multinational study of real-life current standards of care in patients with relapsed and/or refractory multiple myeloma

Despite treatment advances, patients with multiple myeloma (MM) often progress through standard drug classes including proteasome inhibitors (PIs), immunomodulatory drugs (IMiDs), and anti-CD38 monoclonal antibodies (mAbs). LocoMMotion (ClinicalTrials.gov identifier: NCT04035226) is the first prospective study of real-life standard of care (SOC) in triple-class exposed (received at least a PI, IMiD, and anti-CD38 mAb) patients with relapsed/refractory MM (RRMM). Patients (N = 248; ECOG performance status of 0–1, ≥3 prior lines of therapy or double refractory to a PI and IMiD) were treated with median 4.0 (range, 1–20) cycles of SOC therapy. Overall response rate was 29.8% (95% CI: 24.2–36.0). Median progression-free survival (PFS) and median overall survival (OS) were 4.6 (95% CI: 3.9–5.6) and 12.4 months (95% CI: 10.3–NE). Treatment-emergent adverse events (TEAEs) were reported in 83.5% of patients (52.8% grade 3/4). Altogether, 107 deaths occurred, due to progressive disease (n = 74), TEAEs (n = 19), and other reasons (n = 14). The 92 varied regimens utilized demonstrate a lack of clear SOC for heavily pretreated, triple-class exposed patients with RRMM in real-world practice and result in poor outcomes. This supports a need for new treatments with novel mechanisms of action

A Multi-Platform Flow Device for Microbial (Co-) Cultivation and Microscopic Analysis

Novel microbial cultivation platforms are of increasing interest to researchers in academia and industry. The development of materials with specialized chemical and geometric properties has opened up new possibilities in the study of previously unculturable microorganisms and has facilitated the design of elegant, high-throughput experimental set-ups. Within the context of the international Genetically Engineered Machine (iGEM) competition, we set out to design, manufacture, and implement a flow device that can accommodate multiple growth platforms, that is, a silicon nitride based microsieve and a porous aluminium oxide based microdish. It provides control over (co-)culturing conditions similar to a chemostat, while allowing organisms to be observed microscopically. The device was designed to be affordable, reusable, and above all, versatile. To test its functionality and general utility, we performed multiple experiments with Escherichia coli cells harboring synthetic gene circuits and were able to quantitatively study emerging expression dynamics in real-time via fluorescence microscopy. Furthermore, we demonstrated that the device provides a unique environment for the cultivation of nematodes, suggesting that the device could also prove useful in microscopy studies of multicellular microorganisms