Breast-Lesion Characterization using Textural Features of Quantitative Ultrasound Parametric Maps

© 2017 The Author(s). This study evaluated, for the first time, the efficacy of quantitative ultrasound (QUS) spectral parametric maps in conjunction with texture-analysis techniques to differentiate non-invasively benign versus malignant breast lesions. Ultrasound B-mode images and radiofrequency data were acquired from 78 patients with suspicious breast lesions. QUS spectral-analysis techniques were performed on radiofrequency data to generate parametric maps of mid-band fit, spectral slope, spectral intercept, spacing among scatterers, average scatterer diameter, and average acoustic concentration. Texture-analysis techniques were applied to determine imaging biomarkers consisting of mean, contrast, correlation, energy and homogeneity features of parametric maps. These biomarkers were utilized to classify benign versus malignant lesions with leave-one-patient-out cross-validation. Results were compared to histopathology findings from biopsy specimens and radiology reports on MR images to evaluate the accuracy of technique. Among the biomarkers investigated, one mean-value parameter and 14 textural features demonstrated statistically significant differences (p < 0.05) between the two lesion types. A hybrid biomarker developed using a stepwise feature selection method could classify the legions with a sensitivity of 96%, a specificity of 84%, and an AUC of 0.97. Findings from this study pave the way towards adapting novel QUS-based frameworks for breast cancer screening and rapid diagnosis in clinic

Aggression in toddlerhood: the roles of parental beliefs, parenting behavior and precursors of theory of mind

Parental beliefs, parenting behavior, and precursors of theory of mind have been related uniquely to each other and to early aggression, but have not yet been studied simultaneously. The present study combined these risk factors in the prediction of aggression during toddlerhood using a sample of 152 mother–child dyads. At 20 months, mothers' parental beliefs (parental self‐efficacy and perceived parental impact) were examined with the Parental Cognitions and Conduct Toward the Infant Scale. Maternal parenting behavior (sensitivity, intrusiveness, and successful positive engagement) was observed during free play and teaching tasks, and children's precursors of theory of mind were assessed using a visual perspectives task and an imitation task. At 30 months, child aggression was examined using the Child Behavior Checklist. A regression analysis indicated that lower parental self‐efficacy and lower imitation skills predicted more aggressive behavior. When estimating the indirect effects using bootstrapping, a final model was found indicating that lower perceived parental impact was related to less successful positive engagement, which, in turn, was associated with children's poorer imitation abilities which predicted more aggressive behavior. It can be concluded that aggression during toddlerhood is predicted significantly by interrelated parental beliefs, parenting behavior, and children's early social cognitive abilities

Divalent Metal Ions Tune the Self-Splicing Reaction of the Yeast Mitochondrial Group II Intron Sc.ai5γ

Group II introns are large ribozymes, consisting of six functionally distinct domains that assemble in the presence of Mg2+ to the active structure catalyzing a variety of reactions. The first step of intron splicing is well characterized by a Michaelis–Menten-type cleavage reaction using a two-piece group II intron: the substrate RNA, the 5′-exon covalently linked to domains 1, 2, and 3, is cleaved upon addition of domain 5 acting as a catalyst. Here we investigate the effect of Ca2+, Mn2+, Ni2+, Zn2+, Cd2+, Pb2+, and [Co(NH3)6]3+ on the first step of splicing of the Saccharomyces cerevisiae mitochondrial group II intron Sc.ai5γ. We find that this group II intron is very sensitive to the presence of divalent metal ions other than Mg2+. For example, the presence of only 5% Ca2+ relative to Mg2+ results in a decrease in the maximal turnover rate k cat by 50%. Ca2+ thereby has a twofold effect: this metal ion interferes initially with folding, but then also competes directly with Mg2+ in the folded state, the latter being indicative of at least one specific Ca2+ binding pocket interfering directly with catalysis. Similar results are obtained with Mn2+, Cd2+, and [Co(NH3)6]3+. Ni2+ is a much more powerful inhibitor and the presence of either Zn2+ or Pb2+ leads to rapid degradation of the RNA. These results show a surprising sensitivity of such a large multidomain RNA on trace amounts of cations other than Mg2+ and raises the question of biological relevance at least in the case of Ca2+

Photo-antagonism of the GABAA receptor

Neurotransmitter receptor trafficking is fundamentally important for synaptic transmission and neural network activity. GABAA receptors and inhibitory synapses are vital components of brain function, yet much of our knowledge regarding receptor mobility and function at inhibitory synapses is derived indirectly from using recombinant receptors, antibody-tagged native receptors and pharmacological treatments. Here we describe the use of a set of research tools that can irreversibly bind to and affect the function of recombinant and neuronal GABAA receptors following ultraviolet photoactivation. These compounds are based on the competitive antagonist gabazine and incorporate a variety of photoactive groups. By using site-directed mutagenesis and ligand-docking studies, they reveal new areas of the GABA binding site at the interface between receptor β and α subunits. These compounds enable the selected inactivation of native GABAA receptor populations providing new insight into the function of inhibitory synapses and extrasynaptic receptors in controlling neuronal excitation

Quantifying the efficiency of hydroxyapatite mineralising peptides

We present a non-destructive analytical calibration tool to allow quantitative assessment of individual calcium phosphates such as hydroxyapatite (HAP) from mixtures including brushite. Many experimental approaches are used to evaluate the mineralising capabilities of biomolecules including peptides. However, it is difficult to quantitatively compare the efficacy of peptides in the promotion of mineralisation when inseparable mixtures of different minerals are produced. To address this challenge, a series of hydroxyapatite and brushite mixtures were produced as a percent/weight (0–100%) from pure components and multiple (N=10) XRD patterns were collected for each mixture. A linear relationship between the ratio of selected peak heights and the molar ratio was found. Using this method, the mineralising capabilities of three known hydroxyapatite binding peptides, CaP(S) STLPIPHEFSRE, CaP(V) VTKHLNQISQSY and CaP(H) SVSVGMKPSPRP, was compared. All three directed mineralisation towards hydroxyapatite in a peptide concentration dependent manner. CaP(V) was most effective at inducing hydroxyapatite formation at higher reagent levels (Ca2+ = 200mM), as also seen with peptide-silk chimeric materials, whereas CaP(S) was most effective when lower concentrations of calcium (20mM) and phosphate were used. The approach can be extended to investigate HAP mineralisation in the presence of any number of mineralisation promoters or inhibitors

Low-energy Pion-nucleon Scattering

This paper contains the results of an analysis of recent low-energy pion-nucleon scattering experiments. Obtained are phase shifts, the pion-nucleon coupling constant and an estimate of the Sigma term.Comment: 30 pages, 11 figures, LaTe

Conformational changes in α7 acetylcholine receptors underlying allosteric modulation by divalent cations

Allosteric modulation of membrane receptors is a widespread mechanism by which endogenous and exogenous agents regulate receptor function. For example, several members of the nicotinic receptor family are modulated by physiological concentrations of extracellular calcium ions. In this paper, we examined conformational changes underlying this modulation and compare these with changes evoked by ACh. Two sets of residues in the α7 acetylcholine receptor extracellular domain were mutated to cysteine and analyzed by measuring the rates of modification by the thiol-specific reagent 2-aminoethylmethane thiosulfonate. Using Ba2+ as a surrogate for Ca2+, we found a divalent-dependent decrease the modification rates of cysteine substitutions at M37 and M40, residues at which rates were also slowed by ACh. In contrast, Ba2+ had no significant effect at N52C, a residue where ACh increased the rate of modification. Thus divalent modulators cause some but not all of the conformational effects elicited by agonist. Cysteine substitution of either of two glutamates (E44 or E172), thought to participate in the divalent cation binding site, caused a loss of allosteric modulation, yet Ba2+ still had a significant effect on modification rates of these residues. In addition, the effect of Ba2+ at these residues did not appear to be due to direct occlusion. Our data demonstrate that modulation by divalent cations involves substantial conformational changes in the receptor extracellular domain. Our evidence also suggests the modulation occurs via a binding site distinct from one which includes either (or both) of the conserved glutamates at E44 or E172

Deconvolution of 1D NMR spectra : a deep learning-based approach

The analysis of nuclear magnetic resonance (NMR) spectra to detect peaks and characterize their parameters, often referred to as deconvolution, is a crucial step in the quantification, elucidation, and verification of the structure of molecular systems. However, deconvolution of 1D NMR spectra is a challenge for both experts and machines. We propose a robust, expert-level quality deep learning-based deconvolution algorithm for 1D experimental NMR spectra. The algorithm is based on a neural network trained on synthetic spectra. Our customized pre-processing and labeling of the synthetic spectra enable the estimation of critical peak parameters. Furthermore, the neural network model transfers well to the experimental spectra and demonstrates low fitting errors and sparse peak lists in challenging scenarios such as crowded, high dynamic range, shoulder peak regions as well as broad peaks. We demonstrate in challenging spectra that the proposed algorithm is superior to expert results