Real-time assessment of potential seismic migration within a monitoring network using Red-flag SARA

Magma opening new fluid pathways through the crust can generate migrating seismic sources following the trail of the magma. By using Seismic Amplitude Ratio Analysis (SARA), it is possible to detect this seismic migration simply from the amplitudes of continuous data recorded at different stations in a network, without having to do any picking of seismic phases. In this study, we present a modified method – Red-flag SARA, which adapts SARA for real-time monitoring. Red-flag SARA provides a quantitative tool to analyse amplitude ratios between stations in a network and detect temporal changes in these ratios. Since such changes imply seismic source location variations, Red-flag SARA is a handy tool during seismic crises to quickly answer the question of whether seismic activity, and therefore magma, is migrating or not. We tested Red-flag SARA on synthetic data and validated it using real data from two volcanoes – Piton de la Fournaise, Reunion Island, and Gede, Indonesia, for three scenarios: 1) magma migration ending as intrusion, 2) migration leading to eruption and 3) a burst of seismicity with no magma migration

Accurate detection of uniparental disomy and microdeletions by SNP array analysis in myelodysplastic syndromes with normal cytogenetics.

Progress in the management of patients with myelodysplastic syndromes (MDS) has been hampered by the inability to detect cytogenetic abnormalities in 40-60% of cases. We prospectively analyzed matched pairs of bone marrow and buccal cell (normal) DNA samples from 51 MDS patients by single nucleotide polymorphism (SNP) arrays, and identified somatically acquired clonal genomic abnormalities in 21 patients (41%). Among the 33 patients with normal bone marrow cell karyotypes, 5 (15%) had clonal, somatically acquired aberrations by SNP array analysis, including 4 with segmental uniparental disomies (UPD) and 1 with three separate microdeletions. Each abnormality was detected more readily in CD34+ cells than in unselected bone marrow cells. Paired analysis of bone marrow and buccal cell DNA from each patient was necessary to distinguish true clonal genomic abnormalities from inherited copy number variations and regions with apparent loss of heterozygosity. UPDs affecting chromosome 7q were identified in two patients who had a rapidly deteriorating clinical course despite a low-risk International Prognostic Scoring System score. Further studies of larger numbers of patients will be needed to determine whether 7q UPD detected by SNP array analysis will identify higher risk MDS patients at diagnosis, analogous to those with 7q cytogenetic abnormalities

Die phytochemische Reduktion der Ketone. Biochemische Darstellung optisch-aktiver sekundärer Alkohole

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Monitoring SO2 emission at the Soufriere Hills Volcano: implications for changes in erruptive conditions

FLWINinfo:eu-repo/semantics/publishe

Multi-Channel Auto-Calibration for the Atmospheric Imaging Assembly using Machine Learning

Solar activity plays a quintessential role in influencing the interplanetary medium and space-weather around the Earth. Remote sensing instruments onboard heliophysics space missions provide a pool of information about the Sun's activity via the measurement of its magnetic field and the emission of light from the multi-layered, multi-thermal, and dynamic solar atmosphere. Extreme UV (EUV) wavelength observations from space help in understanding the subtleties of the outer layers of the Sun, namely the chromosphere and the corona. Unfortunately, such instruments, like the Atmospheric Imaging Assembly (AIA) onboard NASA's Solar Dynamics Observatory (SDO), suffer from time-dependent degradation, reducing their sensitivity. Current state-of-the-art calibration techniques rely on periodic sounding rockets, which can be infrequent and rather unfeasible for deep-space missions. We present an alternative calibration approach based on convolutional neural networks (CNNs). We use SDO-AIA data for our analysis. Our results show that CNN-based models could comprehensively reproduce the sounding rocket experiments' outcomes within a reasonable degree of accuracy, indicating that it performs equally well compared with the current techniques. Furthermore, a comparison with a standard "astronomer's technique" baseline model reveals that the CNN approach significantly outperforms this baseline. Our approach establishes the framework for a novel technique to calibrate EUV instruments and advance our understanding of the cross-channel relation between different EUV channels.Comment: 12 pages, 7 figures, 8 tables. This is a pre-print of an article submitted and accepted by A&A Journa

Prospective Study of Metal Fume-Induced Responses of Global Gene Expression Profiling in Whole Blood

Metal particulate inhalation causes pulmonary and cardiovascular diseases. Our previous results showed that systemic responses to short-term occupational welding-fume exposure could be assessed by microarray analyses in whole-blood total RNA sampled before and after exposure. To expand our understanding of the duration of particulate-induced gene expression changes, we conducted a study using a similar population 1 yr after the original study and extended our observations in the postexposure period. We recruited 15 individuals with welding fume exposure and 7 nonexposed individuals. Thirteen of the 22 individuals (9 in exposed group and 4 in nonexposed group) had been monitored in the previous study. Whole-blood total RNA was analyzed at 3 time points, including baseline, immediately following exposure (approximately 5 h after baseline), and 24 h after baseline, using cDNA microarray technology. We replicated the patterns of Gene Ontology (GO) terms associated with response to stimulus, cell death, phosphorus metabolism, localization, and regulation of biological processes significantly enriched with altered genes in the nonsmoking exposed group. Most of the identified genes had opposite expression changes between the exposure and postexposure periods in nonsmoking welders. In addition, we found dose-dependent patterns that were affected by smoking status. In conclusion, short-term occupational exposure to metal particulates causes systemic responses in the peripheral blood. Furthermore, the acute particulate-induced effects on gene expression profiling were transient in nonsmoking welders, with most effects diminishing within 19 h following exposure

The confounded nature of angry men and happy women.

Findings of 7 studies suggested that decisions about the sex of a face and the emotional expressions of anger or happiness are not independent: Participants were faster and more accurate at detecting angry expressions on male faces and at detecting happy expressions on female faces. These findings were robust across different stimulus sets and judgment tasks and indicated bottom-up perceptual processes rather than just top-down conceptually driven ones. Results from additional studies in which neutrally expressive faces were used suggested that the connections between masculine features and angry expressions and between feminine features and happy expressions might be a property of the sexual dimorphism of the face itself and not merely a result of gender stereotypes biasing the perception

Increased entropy of signal transduction in the cancer metastasis phenotype

Studies into the statistical properties of biological networks have led to important biological insights, such as the presence of hubs and hierarchical modularity. There is also a growing interest in studying the statistical properties of networks in the context of cancer genomics. However, relatively little is known as to what network features differ between the cancer and normal cell physiologies, or between different cancer cell phenotypes. Based on the observation that frequent genomic alterations underlie a more aggressive cancer phenotype, we asked if such an effect could be detectable as an increase in the randomness of local gene expression patterns. Using a breast cancer gene expression data set and a model network of protein interactions we derive constrained weighted networks defined by a stochastic information flux matrix reflecting expression correlations between interacting proteins. Based on this stochastic matrix we propose and compute an entropy measure that quantifies the degree of randomness in the local pattern of information flux around single genes. By comparing the local entropies in the non-metastatic versus metastatic breast cancer networks, we here show that breast cancers that metastasize are characterised by a small yet significant increase in the degree of randomness of local expression patterns. We validate this result in three additional breast cancer expression data sets and demonstrate that local entropy better characterises the metastatic phenotype than other non-entropy based measures. We show that increases in entropy can be used to identify genes and signalling pathways implicated in breast cancer metastasis. Further exploration of such integrated cancer expression and protein interaction networks will therefore be a fruitful endeavour.Comment: 5 figures, 2 Supplementary Figures and Table

Community-based therapy for multidrug-resistant tuberculosis in Lima, Peru.

BACKGROUND: Despite the prevalence of multidrug-resistant tuberculosis in nearly all low-income countries surveyed, effective therapy has been deemed too expensive and considered not to be feasible outside referral centers. We evaluated the results of community-based therapy for multidrug-resistant tuberculosis in a poor section of Lima, Peru. METHODS: We describe the first 75 patients to receive ambulatory treatment with individualized regimens for chronic multidrug-resistant tuberculosis in northern Lima. We conducted a retrospective review of the charts of all patients enrolled in the program between August 1, 1996, and February 1, 1999, and identified predictors of poor outcomes. RESULTS: The infecting strains of Mycobacterium tuberculosis were resistant to a median of six drugs. Among the 66 patients who completed four or more months of therapy, 83 percent (55) were probably cured at the completion of treatment. Five of these 66 patients (8 percent) died while receiving therapy. Only one patient continued to have positive cultures after six months of treatment. All patients in whom treatment failed or who died had extensive bilateral pulmonary disease. In a multiple Cox proportional-hazards regression model, the predictors of the time to treatment failure or death were a low hematocrit (hazard ratio, 4.09; 95 percent confidence interval, 1.35 to 12.36) and a low body-mass index (hazard ratio, 3.23; 95 percent confidence interval, 0.90 to 11.53). Inclusion of pyrazinamide and ethambutol in the regimen (when susceptibility was confirmed) was associated with a favorable outcome (hazard ratio for treatment failure or death, 0.30; 95 percent confidence interval, 0.11 to 0.83). CONCLUSIONS: Community-based outpatient treatment of multidrug-resistant tuberculosis can yield high cure rates even in resource-poor settings. Early initiation of appropriate therapy can preserve susceptibility to first-line drugs and improve treatment outcomes

Detecting T-cell Reactivity to Whole Cell Vaccines

BCR-ABL$^+$ K562 cells hold clinical promise as a component of cancer vaccines, either as bystander cells genetically modified to express immunostimulatory molecules, or as a source of leukemia antigens. To develop a method for detecting T-cell reactivity against K562 cell-derived antigens in patients, we exploited the dendritic cell (DC)-mediated cross-presentation of proteins generated from apoptotic cells. We used UVB irradiation to consistently induce apoptosis of K562 cells, which were then fed to autologous DCs. These DCs were used to both stimulate and detect antigen-specific CD8+ T-cell reactivity. As proof-of-concept, we used cross-presented apoptotic influenza matrix protein-expressing K562 cells to elicit reactivity from matrix protein-reactive T cells. Likewise, we used this assay to detect increased anti-CML antigen T-cell reactivity in CML patients that attained long-lasting clinical remissions following immunotherapy (donor lymphocyte infusion), as well as in 2 of 3 CML patients vaccinated with lethally irradiated K562 cells that were modified to secrete high levels of granulocyte macrophage colony-stimulating factor (GM-CSF). This methodology can be readily adapted to examine the effects of other whole tumor cell-based vaccines, a scenario in which the precise tumor antigens that stimulate immune responses are unknown