Acceleration of Solar Wind Ions by Nearby Interplanetary Shocks: Comparison of Monte Carlo Simulations with Ulysses Observations

The most stringent test of theoretical models of the first-order Fermi mechanism at collisionless astrophysical shocks is a comparison of the theoretical predictions with observational data on particle populations. Such comparisons have yielded good agreement between observations at the quasi-parallel portion of the Earth's bow shock and three theoretical approaches, including Monte Carlo kinetic simulations. This paper extends such model testing to the realm of oblique interplanetary shocks: here observations of proton and alpha particle distributions made by the SWICS ion mass spectrometer on Ulysses at nearby interplanetary shocks are compared with test particle Monte Carlo simulation predictions of accelerated populations. The plasma parameters used in the simulation are obtained from measurements of solar wind particles and the magnetic field upstream of individual shocks. Good agreement between downstream spectral measurements and the simulation predictions are obtained for two shocks by allowing the the ratio of the mean-free scattering length to the ionic gyroradius, to vary in an optimization of the fit to the data. Generally small values of this ratio are obtained, corresponding to the case of strong scattering. The acceleration process appears to be roughly independent of the mass or charge of the species.Comment: 26 pages, 6 figures, AASTeX format, to appear in the Astrophysical Journal, February 20, 199

Cooper pair sizes in 11Li and in superfluid nuclei: a puzzle?

We point out a strong influence of the pairing force on the size of the two neutron Cooper pair in $^{11}$Li, and to a lesser extent also in $^6$He. It seems that these are quite unique situations, since Cooper pair sizes of stable superfluid nuclei are very little influenced by the intensity of pairing, as recently reported. We explore the difference between $^{11}$Li and heavier superfulid nuclei, and discuss reasons for the exceptional situation in $^{11}$Li.Comment: 9 pages. To be published in J. of Phys. G special issue on Open Problems in Nuclear Structure (OPeNST

Deep Learning Enables Fast and Accurate Imputation of Gene Expression

A question of fundamental biological significance is to what extent the expression of a subset of genes can be used to recover the full transcriptome, with important implications for biological discovery and clinical application. To address this challenge, we propose two novel deep learning methods, PMI and GAIN-GTEx, for gene expression imputation. In order to increase the applicability of our approach, we leverage data from GTEx v8, a reference resource that has generated a comprehensive collection of transcriptomes from a diverse set of human tissues. We show that our approaches compare favorably to several standard and state-of-the-art imputation methods in terms of predictive performance and runtime in two case studies and two imputation scenarios. In comparison conducted on the protein-coding genes, PMI attains the highest performance in inductive imputation whereas GAIN-GTEx outperforms the other methods in in-place imputation. Furthermore, our results indicate strong generalization on RNA-Seq data from 3 cancer types across varying levels of missingness. Our work can facilitate a cost-effective integration of large-scale RNA biorepositories into genomic studies of disease, with high applicability across diverse tissue types

Simultaneous quantification of 12 different nucleotides and nucleosides released from renal epithelium and in human urine samples using ion-pair reversed-phase HPLC

Nucleotides and nucleosides are not only involved in cellular metabolism but also act extracellularly via P1 and P2 receptors, to elicit a wide variety of physiological and pathophysiological responses through paracrine and autocrine signalling pathways. For the first time, we have used an ion-pair reversed-phase high-performance liquid chromatography ultraviolet (UV)-coupled method to rapidly and simultaneously quantify 12 different nucleotides and nucleosides (adenosine triphosphate, adenosine diphosphate, adenosine monophosphate, adenosine, uridine triphosphate, uridine diphosphate, uridine monophosphate, uridine, guanosine triphosphate, guanosine diphosphate, guanosine monophosphate, guanosine): (1) released from a mouse renal cell line (M1 cortical collecting duct) and (2) in human biological samples (i.e., urine). To facilitate analysis of urine samples, a solid-phase extraction step was incorporated (overall recovery rate ? 98 %). All samples were analyzed following injection (100 ?l) into a Synergi Polar-RP 80 Å (250 × 4.6 mm) reversed-phase column with a particle size of 10 ?m, protected with a guard column. A gradient elution profile was run with a mobile phase (phosphate buffer plus ion-pairing agent tetrabutylammonium hydrogen sulfate; pH 6) in 2-30 % acetonitrile (v/v) for 35 min (including equilibration time) at 1 ml min(-1) flow rate. Eluted compounds were detected by UV absorbance at 254 nm and quantified using standard curves for nucleotide and nucleoside mixtures of known concentration. Following validation (specificity, linearity, limits of detection and quantitation, system precision, accuracy, and intermediate precision parameters), this protocol was successfully and reproducibly used to quantify picomolar to nanomolar concentrations of nucleosides and nucleotides in isotonic and hypotonic cell buffers that transiently bathed M1 cells, and urine samples from normal subjects and overactive bladder patients

Energy Partitioning Constraints at Kinetic Scales in Low- Turbulence

Turbulence is a fundamental physical process through which energy injected into a system at large scales cascades to smaller scales. In collisionless plasmas, turbulence provides a critical mechanism for dissipating electromagnetic energy. Here we present observations of plasma fluctuations in low- turbulence using data from NASAs Magnetospheric Multiscale mission in Earths magnetosheath. We provide constraints on the partitioning of turbulent energy density in the fluid, ion-kinetic, and electron-kinetic ranges. Magnetic field fluctuations dominated the energy density spectrum throughout the fluid and ion-kinetic ranges, consistent with previous observations of turbulence in similar plasma regimes. However, at scales shorter than the electron inertial length, fluctuation power in electron kinetic energy significantly exceeded that of the magnetic field, resulting in an electron-motion-regulated cascade at small scales. This dominance should be highly relevant for the study of turbulence in highly magnetized laboratory and astrophysical plasmas

Wave-Particle Energy Exchange Directly Observed in a Kinetic Alfven-Branch Wave

Alfven waves are fundamental plasma wave modes that permeate the universe. At small kinetic scales they provide a critical mechanism for the transfer of energy between electromagnetic fields and charged particles. These waves are important not only in planetary magnetospheres, heliospheres, and astrophysical systems, but also in laboratory plasma experiments and fusion reactors. Through measurement of charged particles and electromagnetic fields with NASAs Magnetospheric Multiscale (MMS) mission, we utilize Earths magnetosphere as a plasma physics laboratory. Here we confirm the conservative energy exchange between the electromagnetic field fluctuations and the charged particles that comprise an undamped kinetic Alfven wave. Electrons confined between adjacent wave peaks may have contributed to saturation of damping effects via non-linear particle trapping. The investigation of these detailed wave dynamics has been unexplored territory in experimental plasma physics and is only recently enabled by high-resolution MMS observations

Hypergraph factorization for multi-tissue gene expression imputation

Integrating gene expression across tissues and cell types is crucial for understanding the coordinated biological mechanisms that drive disease and characterize homoeostasis. However, traditional multi-tissue integration methods either cannot handle uncollected tissues or rely on genotype information, which is often unavailable and subject to privacy concerns. Here we present HYFA (hypergraph factorization), a parameter-efficient graph representation learning approach for joint imputation of multi-tissue and cell-type gene expression. HYFA is genotype agnostic, supports a variable number of collected tissues per individual, and imposes strong inductive biases to leverage the shared regulatory architecture of tissues and genes. In performance comparison on Genotype–Tissue Expression project data, HYFA achieves superior performance over existing methods, especially when multiple reference tissues are available. The HYFA-imputed dataset can be used to identify replicable regulatory genetic variations (expression quantitative trait loci), with substantial gains over the original incomplete dataset. HYFA can accelerate the effective and scalable integration of tissue and cell-type transcriptome biorepositories

Strengthening the Reporting of Observational Studies in Epidemiology-Nutritional Epidemiology (STROBE-nut): An Extension of the STROBE Statement.

Concerns have been raised about the quality of reporting in nutritional epidemiology. Research reporting guidelines such as the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement can improve quality of reporting in observational studies. Herein, we propose recommendations for reporting nutritional epidemiology and dietary assessment research by extending the STROBE statement into Strengthening the Reporting of Observational Studies in Epidemiology-Nutritional Epidemiology (STROBE-nut).Recommendations for the reporting of nutritional epidemiology and dietary assessment research were developed following a systematic and consultative process, coordinated by a multidisciplinary group of 21 experts. Consensus on reporting guidelines was reached through a three-round Delphi consultation process with 53 external experts. In total, 24 recommendations for nutritional epidemiology were added to the STROBE checklist.When used appropriately, reporting guidelines for nutritional epidemiology can contribute to improve reporting of observational studies with a focus on diet and health