Laterally constrained low-rank seismic data completion via cyclic-shear transform

A crucial step in seismic data processing consists in reconstructing the wavefields at spatial locations where faulty or absent sources and/or receivers result in missing data. Several developments in seismic acquisition and interpolation strive to restore signals fragmented by sampling limitations; still, seismic data frequently remain poorly sampled in the source, receiver, or both coordinates. An intrinsic limitation of real-life dense acquisition systems, which are often exceedingly expensive, is that they remain unable to circumvent various physical and environmental obstacles, ultimately hindering a proper recording scheme. In many situations, when the preferred reconstruction method fails to render the actual continuous signals, subsequent imaging studies are negatively affected by sampling artefacts. A recent alternative builds on low-rank completion techniques to deliver superior restoration results on seismic data, paving the way for data kernel compression that can potentially unlock multiple modern processing methods so far prohibited in 3D field scenarios. In this work, we propose a novel transform domain revealing the low-rank character of seismic data that prevents the inherent matrix enlargement introduced when the data are sorted in the midpoint-offset domain and develop a robust extension of the current matrix completion framework to account for lateral physical constraints that ensure a degree of proximity similarity among neighbouring points. Our strategy successfully interpolates missing sources and receivers simultaneously in synthetic and field data

Scattering-based focusing for imaging in highly complex media from band-limited, multicomponent data

Reconstructing the details of subsurface structures deep beneath complex overburden structures, such as subsalt, remains a challenge for seismic imaging. Over the past few years, the Marchenko redatuming approach has proven to reliably retrieve full-wavefield information in the presence of complex overburden effects. When used for redatuming, current practical Marchenko schemes cannot make use of a priori subsurface models with sharp contrasts because of their requirements regarding initial focusing functions, which for sufficiently complex media can result in redatumed fields with significant waveform inaccuracies. Using a scattering framework, we evaluate an alternative form of the Marchenko representation that aims at retrieving only the unknown perturbations to focusing functions and redatumed fields. From this framework, we have developed a two-step practical focusing-based redatuming scheme that first solves an inverse problem for the background focusing functions, which are then used to estimate the perturbations to focusing functions and redatumed fields. In our scheme, initial focusing functions are significantly different from previous approaches because they contain complex waveforms encoding the full transmission response of the a priori model. Our goal is the handling of not only highly complex media but also realistic data ? band-limited, unevenly sampled, free-surface-multiple contaminated data. To that end, we combine the versatility of Rayleigh-Marchenko redatuming with our scattering-based scheme allowing an extended version of the method able to handle single-sided band-limited multicomponent data. This scattering-Rayleigh-Marchenko strategy accurately retrieves wavefields while requiring minimum preprocessing of the data. In support of the new methods, we evaluate a comprehensive set of numerical tests using a complex 2D subsalt model. Our numerical results indicate that the scattering approaches retrieve accurate redatumed fields that appropriately account for the complexity of the a priori model. We find that the improvements in wavefield retrieval translate into measurable improvements in our subsalt images

Genetic control of the innate immune response

BACKGROUND: Susceptibility to infectious diseases is directed, in part, by the interaction between the invading pathogen and host macrophages. This study examines the influence of genetic background on host-pathogen interactions, by assessing the transcriptional responses of macrophages from five inbred mouse strains to lipopolysaccharide (LPS), a major determinant of responses to gram-negative microorganisms. RESULTS: The mouse strains examined varied greatly in the number, amplitude and rate of induction of genes expressed in response to LPS. The response was attenuated in the C3H/HeJlps(d )strain, which has a mutation in the LPS receptor Toll-like receptor 4 (TLR4). Variation between mouse strains allowed clustering into early (C57Bl/6J and DBA/2J) and delayed (BALB/c and C3H/ARC) transcriptional phenotypes. There was no clear correlation between gene induction patterns and variation at the Bcg locus (Slc11A1) or propensity to bias Th1 versus Th2 T cell activation responses. CONCLUSION: Macrophages from each strain responded to LPS with unique gene expression profiles. The variation apparent between genetic backgrounds provides insights into the breadth of possible inflammatory responses, and paradoxically, this divergence was used to identify a common transcriptional program that responds to TLR4 signalling, irrespective of genetic background. Our data indicates that many additional genetic loci control the nature and the extent of transcriptional responses promoted by a single pathogen-associated molecular pattern (PAMP), such as LPS

The effects of climate change on the ecology of fishes

Ocean warming and acidification are set to reshuffle life on Earth and alter ecological processes that underpin the biodiversity, health, productivity, and resilience of ecosystems. Fishes contribute significantly to marine, estuarine, and freshwater species diversity and the functioning of marine ecosystems, and are not immune to climate change impacts. Whilst considerable effort has been placed on studying the effects of climate change on fishes, much emphasis has been placed on their (eco)physiology and at the organismal level. Fishes are affected by climate change through impacts at various levels of biological organisation and through a large variety of traits, making it difficult to make generalisations regarding fish responses to climate change. Here, we briefly review the current state of knowledge of climate change effects on fishes across a wide range of subfields of fish ecology and evaluate these effects at various scales of biological organisation (from genes to ecosystems). We argue that a more holistic synthesis of the various interconnected subfields of fish ecology and integration of responses at different levels of biological organisation are needed for a better understanding of how fishes and their populations and communities might respond or adapt to the multi-stressor effects of climate change. We postulate that studies using natural analogues of climate change, meta-analyses, advanced integrative modelling approaches, and lessons learned from past extreme climate events could help reveal some general patterns of climate change impacts on fishes that are valuable for management and conservation approaches. Whilst these might not reveal many of the underlying mechanisms responsible for observed biodiversity and community change, their insights are useful to help create better climate adaptation strategies for their preservation in a rapidly changing ocean

Transcriptional network dynamics in macrophage activation

AbstractTranscriptional regulatory networks govern cell differentiation and the cellular response to external stimuli. However, mammalian model systems have not yet been accessible for network analysis. Here, we present a genome-wide network analysis of the transcriptional regulation underlying the mouse macrophage response to bacterial lipopolysaccharide (LPS). Key to uncovering the network structure is our combination of time-series cap analysis of gene expression with in silico prediction of transcription factor binding sites. By integrating microarray and qPCR time-series expression data with a promoter analysis, we find dynamic subnetworks that describe how signaling pathways change dynamically during the progress of the macrophage LPS response, thus defining regulatory modules characteristic of the inflammatory response. In particular, our integrative analysis enabled us to suggest novel roles for the transcription factors ATF-3 and NRF-2 during the inflammatory response. We believe that our system approach presented here is applicable to understanding cellular differentiation in higher eukaryotes

Transcript Annotation in FANTOM3: Mouse Gene Catalog Based on Physical cDNAs

The international FANTOM consortium aims to produce a comprehensive picture of the mammalian transcriptome, based upon an extensive cDNA collection and functional annotation of full-length enriched cDNAs. The previous dataset, FANTOM2, comprised 60,770 full-length enriched cDNAs. Functional annotation revealed that this cDNA dataset contained only about half of the estimated number of mouse protein-coding genes, indicating that a number of cDNAs still remained to be collected and identified. To pursue the complete gene catalog that covers all predicted mouse genes, cloning and sequencing of full-length enriched cDNAs has been continued since FANTOM2. In FANTOM3, 42,031 newly isolated cDNAs were subjected to functional annotation, and the annotation of 4,347 FANTOM2 cDNAs was updated. To accomplish accurate functional annotation, we improved our automated annotation pipeline by introducing new coding sequence prediction programs and developed a Web-based annotation interface for simplifying the annotation procedures to reduce manual annotation errors. Automated coding sequence and function prediction was followed with manual curation and review by expert curators. A total of 102,801 full-length enriched mouse cDNAs were annotated. Out of 102,801 transcripts, 56,722 were functionally annotated as protein coding (including partial or truncated transcripts), providing to our knowledge the greatest current coverage of the mouse proteome by full-length cDNAs. The total number of distinct non-protein-coding transcripts increased to 34,030. The FANTOM3 annotation system, consisting of automated computational prediction, manual curation, and final expert curation, facilitated the comprehensive characterization of the mouse transcriptome, and could be applied to the transcriptomes of other species

Research priorities for the sustainability of coral-rich western Pacific seascapes

Nearly a billion people depend on tropical seascapes. The need to ensure sustainable use of these vital areas is recognised, as one of 17 policy commitments made by world leaders, in Sustainable Development Goal (SDG) 14 (‘Life below Water’) of the United Nations. SDG 14 seeks to secure marine sustainability by 2030. In a time of increasing social-ecological unpredictability and risk, scientists and policymakers working towards SDG 14 in the Asia–Pacific region need to know: (1) How are seascapes changing? (2) What can global society do about these changes? and (3) How can science and society together achieve sustainable seascape futures? Through a horizon scan, we identified nine emerging research priorities that clarify potential research contributions to marine sustainability in locations with high coral reef abundance. They include research on seascape geological and biological evolution and adaptation; elucidating drivers and mechanisms of change; understanding how seascape functions and services are produced, and how people depend on them; costs, benefits, and trade-offs to people in changing seascapes; improving seascape technologies and practices; learning to govern and manage seascapes for all; sustainable use, justice, and human well-being; bridging communities and epistemologies for innovative, equitable, and scale-crossing solutions; and informing resilient seascape futures through modelling and synthesis. Researchers can contribute to the sustainability of tropical seascapes by co-developing transdisciplinary understandings of people and ecosystems, emphasising the importance of equity and justice, and improving knowledge of key cross-scale and cross-level processes, feedbacks, and thresholds

Impact of liver tumour burden, alkaline phosphatase elevation, and target lesion size on treatment outcomes with 177Lu-Dotatate: an analysis of the NETTER-1 study

Purpose: To assess the impact of baseline liver tumour burden, alkaline phosphatase (ALP) elevation, and target lesion size on treatment outcomes with 177Lu-Dotatate. Methods: In the phase 3 NETTER-1 trial, patients with advanced, progressive midgut neuroendocrine tumours (NET) were randomised to 177Lu-Dotatate (every 8 weeks, four cycles) plus octreotide long-acting release (LAR) or to octreotide LAR 60 mg. Primary endpoint was progression-free survival (PFS). Analyses of PFS by baseline factors, including liver tumour burden, ALP elevation, and target lesion size, were performed using Kaplan-Meier estimates; hazard ratios (HRs) with corresponding 95% CIs were estimated using Cox regression. Results: Significantly prolonged median PFS occurred with 177Lu-Dotatate versus octreotide LAR 60 mg in patients with low ( 50%) liver tumour burden (HR 0.187, 0.216, 0.145), and normal or elevated ALP (HR 0.153, 0.177), and in the presence or absence of a large target lesion (diameter > 30 mm; HR, 0.213, 0.063). Within the 177Lu-Dotatate arm, no significant difference in PFS was observed amongst patients with low/moderate/high liver tumour burden (P = 0.7225) or with normal/elevated baseline ALP (P = 0.3532), but absence of a large target lesion was associated with improved PFS (P = 0.0222). Grade 3 and 4 liver function abnormalities were rare and did not appear to be associated with high baseline liver tumour burden. Conclusions: 177Lu-Dotatate demonstrated significant prolongation in PFS versus high-dose octreotide LAR in patients with advanced, progressive midgut NET, regardless of baseline liver tumour burden, elevated ALP, or the presence of a large target lesion. Clinicaltrials.gov : NCT01578239, EudraCT: 2011-005049-11

Altered Gene Synchrony Suggests a Combined Hormone-Mediated Dysregulated State in Major Depression

Coordinated gene transcript levels across tissues (denoted “gene synchrony”) reflect converging influences of genetic, biochemical and environmental factors; hence they are informative of the biological state of an individual. So could brain gene synchrony also integrate the multiple factors engaged in neuropsychiatric disorders and reveal underlying pathologies? Using bootstrapped Pearson correlation for transcript levels for the same genes across distinct brain areas, we report robust gene transcript synchrony between the amygdala and cingulate cortex in the human postmortem brain of normal control subjects (n = 14; Control/Permutated data, p<0.000001). Coordinated expression was confirmed across distinct prefrontal cortex areas in a separate cohort (n = 19 subjects) and affected different gene sets, potentially reflecting regional network- and function-dependent transcriptional programs. Genewise regional transcript coordination was independent of age-related changes and array technical parameters. Robust shifts in amygdala-cingulate gene synchrony were observed in subjects with major depressive disorder (MDD, denoted here “depression”) (n = 14; MDD/Permutated data, p<0.000001), significantly affecting between 100 and 250 individual genes (10–30% false discovery rate). Biological networks and signal transduction pathways corresponding to the identified gene set suggested putative dysregulated functions for several hormone-type factors previously implicated in depression (insulin, interleukin-1, thyroid hormone, estradiol and glucocorticoids; p<0.01 for association with depression-related networks). In summary, we showed that coordinated gene expression across brain areas may represent a novel molecular probe for brain structure/function that is sensitive to disease condition, suggesting the presence of a distinct and integrated hormone-mediated corticolimbic homeostatic, although maladaptive and pathological, state in major depression