Resolution-enhanced X-ray fluorescence microscopy via deep residual networks

Multimodal hard X-ray scanning probe microscopy has been extensively used to study functional materials providing multiple contrast mechanisms. For instance, combining ptychography with X-ray fluorescence (XRF) microscopy reveals structural and chemical properties simultaneously. While ptychography can achieve diffraction-limited spatial resolution, the resolution of XRF is limited by the X-ray probe size. Here, we develop a machine learning (ML) model to overcome this problem by decoupling the impact of the X-ray probe from the XRF signal. The enhanced spatial resolution was observed for both simulated and experimental XRF data, showing superior performance over the state-of-the-art scanning XRF method with different nano-sized X-ray probes. Enhanced spatial resolutions were also observed for the accompanying XRF tomography reconstructions. Using this probe profile deconvolution with the proposed ML solution to enhance the spatial resolution of XRF microscopy will be broadly applicable across both functional materials and biological imaging with XRF and other related application areas

Cancer cells exploit an orphan RNA to drive metastatic progression.

Here we performed a systematic search to identify breast-cancer-specific small noncoding RNAs, which we have collectively termed orphan noncoding RNAs (oncRNAs). We subsequently discovered that one of these oncRNAs, which originates from the 3' end of TERC, acts as a regulator of gene expression and is a robust promoter of breast cancer metastasis. This oncRNA, which we have named T3p, exerts its prometastatic effects by acting as an inhibitor of RISC complex activity and increasing the expression of the prometastatic genes NUPR1 and PANX2. Furthermore, we have shown that oncRNAs are present in cancer-cell-derived extracellular vesicles, raising the possibility that these circulating oncRNAs may also have a role in non-cell autonomous disease pathogenesis. Additionally, these circulating oncRNAs present a novel avenue for cancer fingerprinting using liquid biopsies

Long-lived pressure-driven coherent structures in KSTAR plasmas

Highly coherent structures associated with an extremely long-lived saturated magnetohydrodynamic instability have been observed in KSTAR tokamak under a long-pulse and steady-state operation. They persist essentially unchanged for the full duration of a discharge up to 40 s, much longer than any dynamical or dissipative time scales in the system. Analysis of the data, supported by numerical simulations, indicates that they may be associated with a pressure-driven mode causing some degradation in the toroidal rotation, electron, and ion energy confinement. Published by AIP Publishing.open1121Ysciescopu

Complex systems and the technology of variability analysis

Characteristic patterns of variation over time, namely rhythms, represent a defining feature of complex systems, one that is synonymous with life. Despite the intrinsic dynamic, interdependent and nonlinear relationships of their parts, complex biological systems exhibit robust systemic stability. Applied to critical care, it is the systemic properties of the host response to a physiological insult that manifest as health or illness and determine outcome in our patients. Variability analysis provides a novel technology with which to evaluate the overall properties of a complex system. This review highlights the means by which we scientifically measure variation, including analyses of overall variation (time domain analysis, frequency distribution, spectral power), frequency contribution (spectral analysis), scale invariant (fractal) behaviour (detrended fluctuation and power law analysis) and regularity (approximate and multiscale entropy). Each technique is presented with a definition, interpretation, clinical application, advantages, limitations and summary of its calculation. The ubiquitous association between altered variability and illness is highlighted, followed by an analysis of how variability analysis may significantly improve prognostication of severity of illness and guide therapeutic intervention in critically ill patients

The self-organizing fractal theory as a universal discovery method: the phenomenon of life

A universal discovery method potentially applicable to all disciplines studying organizational phenomena has been developed. This method takes advantage of a new form of global symmetry, namely, scale-invariance of self-organizational dynamics of energy/matter at all levels of organizational hierarchy, from elementary particles through cells and organisms to the Universe as a whole. The method is based on an alternative conceptualization of physical reality postulating that the energy/matter comprising the Universe is far from equilibrium, that it exists as a flow, and that it develops via self-organization in accordance with the empirical laws of nonequilibrium thermodynamics. It is postulated that the energy/matter flowing through and comprising the Universe evolves as a multiscale, self-similar structure-process, i.e., as a self-organizing fractal. This means that certain organizational structures and processes are scale-invariant and are reproduced at all levels of the organizational hierarchy. Being a form of symmetry, scale-invariance naturally lends itself to a new discovery method that allows for the deduction of missing information by comparing scale-invariant organizational patterns across different levels of the organizational hierarchy

Endpoint inequalities for spherical multilinear convolutions

Write sigma = (sigma(1), ..., sigma(n)) for an element of the sphere Sigma(n-1) and let d sigma denote Lebesgue measure on Sigma(n-1). For functions f(1), ..., f(n) on R, define T( f(1), ..., f(n))(x) = integral(Sigma n-1) f(1)(x - sigma(1)) ... f(n)(x - sigma(n)) d sigma, x is an element of R. Let R = R(n) denote the closed convex hull in R-2 of the points (0, 0), (1/n, 1), ((n + 1)/(n + 2), 1), ((n + 1)/(n + 3), 2/(n + 3)), ((n - 1)/(n + 1), 0). We show that if n >= 3, then the inequality parallel to T(f(1), ..., f(n))parallel to(q) = 3 in Oberlin's previous work. A negative result is given along with some positive results, when n = 2. thus narrowing the gap in the necessary and sufficient conditions in this case. (C) 1998 Academic Press.X11sciescopu