Wavelet spectral analysis of the free surface of turbulent flows

This work demonstrates the applicability of the wavelet directional method as a means of characterizing the free surface dynamics in shallow turbulent flows using a small number of sensors. The measurements are obtained with three conductance wave probes in a laboratory flume, in a range of subcritical flow conditions where the Froude number was smaller than one, and the bed was homogeneously rough. The characteristic spatial scale of the surface elevation is found to correspond to the wavelength of stationary waves oriented against the flow. The spectrum of the dominant distribution of waves is characterized in terms of an angular spreading function. A new procedure to estimate the mean surface velocity based on measurements of the surface elevation at only two locations is proposed. The results can inform the development of more accurate models of the surface behaviour, with applications for the remote sensing of rivers and open channel flows

Frequency-wavenumber spectrum of the free surface of shallow turbulent flows over a rough boundary

Data on the frequency-wavenumber spectra and dispersion relation of the dynamic water surface in an open channel flow are very scarce. In this work, new data on the frequency-wavenumber spectra were obtained in a rectangular laboratory flume with a rough bottom boundary, over a range of subcritical Froude numbers. These data were used to study the dispersion relation of the surface waves in such shallow turbulent water flows. The results show a complex pattern of surface waves, with a range of scales and velocities. When the mean surface velocity is faster than the minimum phase velocity of gravity-capillary waves, the wave pattern is dominated by stationary waves that interact with the static rough bed. There is a coherent three-dimensional pattern of radially propagating waves with the wavelength approximately equal to the wavelength of the stationary waves. Alongside these waves, there are freely propagating gravity-capillary waves that propagate mainly parallel to the mean flow, both upstream and downstream. In the flow conditions where the mean surface velocity is slower than the minimum phase velocity of gravity-capillary waves, patterns of non-dispersive waves are observed. It is suggested that these waves are forced by turbulence. The results demonstrate that the free surface carries information about the underlying turbulent flow. The knowledge obtained in this study paves the way for the development of novel airborne methods of non-invasive flow monitoring

Uncoupling of growth inhibition and differentiation in dexamethasone-treated human rhabdomyosarcoma cells.

The effects of dexamethasone, a synthetic glucocorticoid, and of N,N-dimethylformamide on in vitro growth and differentiation and on proto-oncogene expression of human rhabdomyosarcoma cells were studied. RD/18 clone cells (derived from the embryonal rhabdomyosarcoma cell line RD) treated with 100 nM dexamethasone showed an almost complete block of differentiation: about 5% myosin-positive cells were observed after 2 weeks of culture in dexamethasone-supplemented differentiation medium, compared to 20% of untreated cultures. Dexamethasone also induced a 20-30% growth inhibition and a more flattened morphology. The treatment with N,N-dimethylformamide induced a significantly increased proportion of myosin-positive cells (reaching about 30%) and a 40% growth inhibition. Induction of differentiation inversely correlated with the levels of c-myc proto-oncogene expression: after a 2 week culture dexamethasone-treated cells showed the highest c-myc expression and N,N-dimethylformamide-treated cells the lowest. Culture conditions per se down-modulated c-erbB1 and up-regulated c-jun expression, with no relationship to the differentiation pattern. Other proto-oncogenes were not expressed (c-sis, N-myc, c-mos, c-myb) or were not modulated (c-fos, c-raf). Therefore dexamethasone and N,N-dimethylformamide, both causing a decreased growth rate, showed opposing actions on myogenic differentiation and on c-myc proto-oncogene expression of human rhabdomyosarcoma cells

Artificial Intelligence for Thyroid Nodule Characterization: Where Are We Standing?

Machine learning (ML) is an interdisciplinary sector in the subset of artificial intelligence (AI) that creates systems to set up logical connections using algorithms, and thus offers predictions for complex data analysis. In the present review, an up-to-date summary of the current state of the art regarding ML and AI implementation for thyroid nodule ultrasound characterization and cancer is provided, highlighting controversies over AI application as well as possible benefits of ML, such as, for example, training purposes. There is evidence that AI increases diagnostic accuracy and significantly limits inter-observer variability by using standardized mathematical algorithms. It could also be of aid in practice settings with limited sub-specialty expertise, offering a second opinion by means of radiomics and computer-assisted diagnosis. The introduction of AI represents a revolutionary event in thyroid nodule evaluation, but key issues for further implementation include integration with radiologist expertise, impact on workflow and efficiency, and performance monitoring

Reconstruction of the frequency-wavenumber spectrum of water waves with an airborne acoustic Doppler array for non-contact river monitoring

This work presents a novel method to reconstruct the frequency-wavenumber spectrum of water waves based on the complex acoustic Doppler spectra of scattered sound measured with an array of microphones. The reconstruction is based on a first-order small-roughness-amplitude expansion of the acoustic wave scattering equation, which is discretized and inverted by means of a singular value decomposition. An analogy of this approach to the first-order Bragg scattering problem is demonstrated by means of a stationary phase expansion. The approach enables the reconstruction of the dispersion relation of water waves when the ratio between roughness height and acoustic wavelength is less than 0.1, and when the surface wavelength is larger than 1/2 of the acoustic wavelength. The method is validated against synthetic data and data from laboratory and field experiments, to demonstrate its applicability to two-and three-dimensional complex patterns of water waves, and specifically to the surface deformations that arise naturally in a turbulent open-channel flow. Fitting the reconstructed data with the analytical dispersion relation enables the non-contact estimate of the underlying flow velocity for hydraulic conditions where the coexistence of different types of turbulence-forced and freely propagating water waves would limit the accuracy of standard non-contact Doppler velocimetry approaches, paving the way for robust and accurate non-contact river monitoring using acoustics

Doppler spectra of airborne sound backscattered by the free surface of a shallow turbulent water flow

Measurements of the Doppler spectra of airborne ultrasound backscattered by the rough dynamic surface of a shallow turbulent flow are presented in this paper. The interpretation of the observed acoustic signal behavior is provided by means of a Monte Carlo simulation based on the Kirchhoff approximation and on a linear random-phase model of the water surface elevation. Results suggest that the main scattering mechanism is from capillary waves with small amplitude. Waves that travel at the same velocity of the flow, as well as dispersive waves that travel at a range of velocities, are detected, studied and used in the acoustic Doppler analysis. The dispersive surface waves are not observed when the flow velocity is slow compared to their characteristic velocity. Relatively wide peaks in the experimental spectra also suggest the existence of nonlinear modulations of the short capillary waves, or their propagation in a wide range of directions. The variability of the Doppler spectra with the conditions of the flow can affect the accuracy of the flow velocity estimations based on backscattering Doppler. A set of different methods to estimate this velocity accurately and remotely at different ranges of flow conditions is suggested

The Effect of Epstein-Barr Virus Latent Membrane Protein 2 Expression on the Kinetics of Early B Cell Infection

Infection of human B cells with wild-type Epstein-Barr virus (EBV) in vitro leads to activation and proliferation that result in efficient production of lymphoblastoid cell lines (LCLs). Latent Membrane Protein 2 (LMP2) is expressed early after infection and previous research has suggested a possible role in this process. Therefore, we generated recombinant EBV with knockouts of either or both protein isoforms, LMP2A and LMP2B (Δ2A, Δ2B, Δ2A/Δ2B) to study the effect of LMP2 in early B cell infection. Infection of B cells with Δ2A and Δ2A/Δ2B viruses led to a marked decrease in activation and proliferation relative to wild-type (wt) viruses, and resulted in higher percentages of apoptotic B cells. Δ2B virus infection showed activation levels comparable to wt, but fewer numbers of proliferating B cells. Early B cell infection with wt, Δ2A and Δ2B viruses did not result in changes in latent gene expression, with the exception of elevated LMP2B transcript in Δ2A virus infection. Infection with Δ2A and Δ2B viruses did not affect viral latency, determined by changes in LMP1/Zebra expression following BCR stimulation. However, BCR stimulation of Δ2A/Δ2B cells resulted in decreased LMP1 expression, which suggests loss of stability in viral latency. Long-term outgrowth assays revealed that LMP2A, but not LMP2B, is critical for efficient long-term growth of B cells in vitro. The lowest levels of activation, proliferation, and LCL formation were observed when both isoforms were deleted. These results suggest that LMP2A appears to be critical for efficient activation, proliferation and survival of EBV-infected B cells at early times after infection, which impacts the efficient long-term growth of B cells in culture. In contrast, LMP2B did not appear to play a significant role in these processes, and long-term growth of infected B cells was not affected by the absence of this protein. © 2013 Wasil et al

Evaluation of polygenic risk scores for breast and ovarian cancer risk prediction in BRCA1 and BRCA2 mutation carriers

Background: Genome-wide association studies (GWAS) have identified 94 common single-nucleotide polymorphisms (SNPs) associated with breast cancer (BC) risk and 18 associated with ovarian cancer (OC) risk. Several of these are also associated with risk of BC or OC for women who carry a pathogenic mutation in the high-risk BC and OC genes BRCA1 or BRCA2. The combined effects of these variants on BC or OC risk for BRCA1 and BRCA2 mutation carriers have not yet been assessed while their clinical management could benefit from improved personalized risk estimates. Methods: We constructed polygenic risk scores (PRS) using BC and OC susceptibility SNPs identified through population-based GWAS: for BC (overall, estrogen receptor [ER]-positive, and ER-negative) and for OC. Using data from 15 252 female BRCA1 and 8211 BRCA2 carriers, the association of each PRS with BC or OC risk was evaluated using a weighted cohort approach, with time to diagnosis as the outcome and estimation of the hazard ratios (HRs) per standard deviation increase in the PRS. Results: The PRS for ER-negative BC displayed the strongest association with BC risk in BRCA1 carriers (HR = 1.27, 95% confidence interval [CI] = 1.23 to 1.31, P = 8.2 x 10(53)). In BRCA2 carriers, the strongest association with BC risk was seen for the overall BC PRS (HR = 1.22, 95% CI = 1.17 to 1.28, P = 7.2 x 10(-20)). The OC PRS was strongly associated with OC risk for both BRCA1 and BRCA2 carriers. These translate to differences in absolute risks (more than 10% in each case) between the top and bottom deciles of the PRS distribution; for example, the OC risk was 6% by age 80 years for BRCA2 carriers at the 10th percentile of the OC PRS compared with 19% risk for those at the 90th percentile of PRS. Conclusions: BC and OC PRS are predictive of cancer risk in BRCA1 and BRCA2 carriers. Incorporation of the PRS into risk prediction models has promise to better inform decisions on cancer risk management

Suppressive Effects on the Immune Response and Protective Immunity to a JEV DNA Vaccine by Co-administration of a GM-CSF-Expressing Plasmid in Mice

As a potential cytokine adjuvant of DNA vaccines, granulocyte-macrophage colony–stimulating factor (GM-CSF) has received considerable attention due to its essential role in the recruitment of antigen-presenting cells, differentiation and maturation of dendritic cells. However, in our recent study of a Japanese encephalitis virus (JEV) DNA vaccine, co-inoculation of a GM-CSF plasmid dramatically suppressed the specific IgG response and resulted in decreased protection against JEV challenge. It is known that GM-CSF has been used in clinic to treat neutropenia for repopulating myeloid cells, and as an adjuvant in vaccine studies; it has shown various effects on the immune response. Therefore, in this study, we characterized the suppressive effects on the immune response to a JEV DNA vaccine by the co-administration of the GM-CSF-expressing plasmid and clarified the underlying mechanisms of the suppression in mice. Our results demonstrated that co-immunization with GM-CSF caused a substantial dampening of the vaccine-induced antibody responses. The suppressive effect was dose- and timing-dependent and likely related to the immunogenicity of the antigen. The suppression was associated with the induction of immature dendritic cells and the expansion of regulatory T cells but not myeloid-derived suppressor cells. Collectively, our findings not only provide valuable information for the application of GM-CSF in clinic and using as a vaccine adjuvant but also offer further insight into the understanding of the complex roles of GM-CSF