Drag on particles in a nematic suspension by a moving nematic-isotropic interface

We report the first clear demonstration of drag on colloidal particles by a moving nematic-isotropic interface. The balance of forces explains our observation of periodic, strip-like structures that are produced by the movement of these particles

Symmetry Nonrestoration in a Gross-Neveu Model with Random Chemical Potential

We study the symmetry behavior of the Gross-Neveu model in three and two dimensions with random chemical potential. This is equivalent to a four-fermion model with charge conjugation symmetry as well as Z_2 chiral symmetry. At high temperature the Z_2 chiral symmetry is always restored. In three dimensions the initially broken charge conjugation symmetry is not restored at high temperature, irrespective of the value of the disorder strength. In two dimensions and at zero temperature the charge conjugation symmetry undergoes a quantum phase transition from a symmetric state (for weak disorder) to a broken state (for strong disorder) as the disorder strength is varied. For any given value of disorder strength, the high-temperature behavior of the charge conjugation symmetry is the same as its zero-temperature behavior. Therefore, in two dimensions and for strong disorder strength the charge conjugation symmetry is not restored at high temperature.Comment: 16 pages, 3 figure

Identifying Early Changes in Myocardial Microstructure in Hypertensive Heart Disease

The transition from healthy myocardium to hypertensive heart disease is characterized by a series of poorly understood changes in myocardial tissue microstructure. Incremental alterations in the orientation and integrity of myocardial fibers can be assessed using advanced ultrasonic image analysis. We used a modified algorithm to investigate left ventricular myocardial microstructure based on analysis of the reflection intensity at the myocardial-pericardial interface on B-mode echocardiographic images. We evaluated the extent to which the novel algorithm can differentiate between normal myocardium and hypertensive heart disease in humans as well as in a mouse model of afterload resistance. The algorithm significantly differentiated between individuals with uncomplicated essential hypertension (N = 30) and healthy controls (N = 28), even after adjusting for age and sex (P = 0.025). There was a trend in higher relative wall thickness in hypertensive individuals compared to controls (P = 0.08), but no difference between groups in left ventricular mass (P = 0.98) or total wall thickness (P = 0.37). In mice, algorithm measurements (P = 0.026) compared with left ventricular mass (P = 0.053) more clearly differentiated between animal groups that underwent fixed aortic banding, temporary aortic banding, or sham procedure, on echocardiography at 7 weeks after surgery. Based on sonographic signal intensity analysis, a novel imaging algorithm provides an accessible, non-invasive measure that appears to differentiate normal left ventricular microstructure from myocardium exposed to chronic afterload stress. The algorithm may represent a particularly sensitive measure of the myocardial changes that occur early in the course of disease progression

MLPerf Inference Benchmark

Machine-learning (ML) hardware and software system demand is burgeoning. Driven by ML applications, the number of different ML inference systems has exploded. Over 100 organizations are building ML inference chips, and the systems that incorporate existing models span at least three orders of magnitude in power consumption and five orders of magnitude in performance; they range from embedded devices to data-center solutions. Fueling the hardware are a dozen or more software frameworks and libraries. The myriad combinations of ML hardware and ML software make assessing ML-system performance in an architecture-neutral, representative, and reproducible manner challenging. There is a clear need for industry-wide standard ML benchmarking and evaluation criteria. MLPerf Inference answers that call. In this paper, we present our benchmarking method for evaluating ML inference systems. Driven by more than 30 organizations as well as more than 200 ML engineers and practitioners, MLPerf prescribes a set of rules and best practices to ensure comparability across systems with wildly differing architectures. The first call for submissions garnered more than 600 reproducible inference-performance measurements from 14 organizations, representing over 30 systems that showcase a wide range of capabilities. The submissions attest to the benchmark's flexibility and adaptability.Comment: ISCA 202

Urinary MicroRNA Profiling in the Nephropathy of Type 1 Diabetes

Background: Patients with Type 1 Diabetes (T1D) are particularly vulnerable to development of Diabetic nephropathy (DN) leading to End Stage Renal Disease. Hence a better understanding of the factors affecting kidney disease progression in T1D is urgently needed. In recent years microRNAs have emerged as important post-transcriptional regulators of gene expression in many different health conditions. We hypothesized that urinary microRNA profile of patients will differ in the different stages of diabetic renal disease. Methods and Findings: We studied urine microRNA profiles with qPCR in 40 T1D with >20 year follow up 10 who never developed renal disease (N) matched against 10 patients who went on to develop overt nephropathy (DN), 10 patients with intermittent microalbuminuria (IMA) matched against 10 patients with persistent (PMA) microalbuminuria. A Bayesian procedure was used to normalize and convert raw signals to expression ratios. We applied formal statistical techniques to translate fold changes to profiles of microRNA targets which were then used to make inferences about biological pathways in the Gene Ontology and REACTOME structured vocabularies. A total of 27 microRNAs were found to be present at significantly different levels in different stages of untreated nephropathy. These microRNAs mapped to overlapping pathways pertaining to growth factor signaling and renal fibrosis known to be targeted in diabetic kidney disease. Conclusions: Urinary microRNA profiles differ across the different stages of diabetic nephropathy. Previous work using experimental, clinical chemistry or biopsy samples has demonstrated differential expression of many of these microRNAs in a variety of chronic renal conditions and diabetes. Combining expression ratios of microRNAs with formal inferences about their predicted mRNA targets and associated biological pathways may yield useful markers for early diagnosis and risk stratification of DN in T1D by inferring the alteration of renal molecular processes. © 2013 Argyropoulos et al

Probing inhibitory effects of destruxins from Metarhizium anisopliae using insect cell based impedance spectroscopy : Inhibition vs chemical structure

A noninvasive technique based on electric cell-substrate impedance sensing (ECIS) was demonstrated for on-line probing inhibitory effects of five destruxins on Spodoptera frugiperda Sf9 insect cells. Such chemically structurally similar cyclic hexadepsipeptides, were isolated and purified from the fungus Metarhizium anisopliae. Based on a response function, the inhibitory effect of the destruxins was established from determining the half-inhibition concentration (ECIS50), i.e., the level at which 50% inhibition of the cell response was obtained. Probing by cell based impedance spectroscopy indicated that only a slight change in their chemical structures provoked a significant effect on inhibition. Destruxin B was most inhibitory but replacement of a single methyl group with hydrogen (destruxin B2) or addition of a hydroxylgroup (destruxin C) significantly reduced the inhibition. The removal of one methyl group and one hydrogen (destruxin A) lowered the inhibitory effect even more whereas the formation of an epoxy ring (destruxin E) in the structure nullified the inhibitory effect.NRC publication: Ye

Absolute Quantitation of Met Using Mass Spectrometry for Clinical Application: Assay Precision, Stability, and Correlation with <i>MET</i> Gene Amplification in FFPE Tumor Tissue

Background: Overexpression of Met tyrosine kinase receptor is associated with poor prognosis. Overexpression, and particularly MET amplification, are predictive of response to Met-specific therapy in preclinical models. Immunohistochemistry (IHC) of formalin-fixed paraffin-embedded (FFPE) tissues is currently used to select for ‘high Met’ expressing tumors for Met inhibitor trials. IHC suffers from antibody non-specificity, lack of quantitative resolution, and, when quantifying multiple proteins, inefficient use of scarce tissue.Methods: After describing the development of the Liquid-Tissue-Selected Reaction Monitoring-mass spectrometry (LT-SRM-MS) Met assay, we evaluated the expression level of Met in 130 FFPE gastroesophageal cancer (GEC) tissues. We assessed the correlation of SRM Met expression to IHC and mean MET gene copy number (GCN)/nucleus or MET/CEP7 ratio by fluorescence in situ hybridization (FISH).Results: Proteomic mapping of recombinant Met identified 418TEFTTALQR426 as the optimal SRM peptide. Limits of detection (LOD) and quantitation (LOQ) for this peptide were 150 and 200 amol/µg tumor protein, respectively. The assay demonstrated excellent precision and temporal stability of measurements in serial sections analyzed one year apart. Expression levels of 130 GEC tissues ranged (MET GCN and MET/CEP7 ratio as determined by FISH (n = 30; R2 = 0.898). IHC did not correlate well with SRM (n = 44; R2 = 0.537) nor FISH GCN (n = 31; R2 = 0.509). A Met SRM level of ≥1500 amol/µg was 100% sensitive (95% CI 0.69–1) and 100% specific (95% CI 0.92–1) for MET amplification.Conclusions: The Met SRM assay measured the absolute Met levels in clinical tissues with high precision. Compared to IHC, SRM provided a quantitative and linear measurement of Met expression, reliably distinguishing between non-amplified and amplified MET tumors. These results demonstrate a novel clinical tool for efficient tumor expression profiling, potentially leading to better informed therapeutic decisions for patients with GEC.</p