Characteristics of truncation resonances in periodic bilayer rods and beams with symmetric and asymmetric unit cellsa).

Truncation resonances are resonant frequencies that occur within bandgaps and are a prominent feature of finite phononic crystals. While recent studies have shed light on the existence conditions and modal characteristics of truncation resonances in discrete systems, much remains to be understood about their behavior in continuous structures. To address this knowledge gap, this paper investigates the existence and modal characteristics of truncation resonances in periodic bilayer beams, both numerically and experimentally. Specifically, the effect of symmetry of the unit cells, boundary conditions, material/geometric properties, and the number of unit cells are studied. To this end, we introduce impedance and phase velocity ratios based on the material and geometric properties and show how they affect the existence of truncation resonances, relative location of the truncation resonances within the bandgap, and spatial attenuation or degree of localization of the truncation resonance mode shapes. Finally, the existence and mode shapes of truncation resonances are experimentally validated for both longitudinal and flexural cases using three-dimensional (3D) printed periodic beams. This paper highlights the potential impact of these results on the design of finite phononic crystals for various applications, including energy harvesting and passive flow control.

Open-source image analysis tool for the identification and quantification of cortical interruptions and bone erosions in high-resolution peripheral quantitative computed tomography images of patients with rheumatoid arthritis.

Identification of bone erosions and quantification of erosion volume is important for rheumatoid arthritis diagnosis, and can add important information to evaluate disease progression and treatment effects. High-resolution peripheral quantitative computed tomography (HR-pQCT) is well suited for this purpose, however analysis methods are not widely available. The purpose of this study was to develop an open-source software tool for the identification and quantification of bone erosions using images acquired by HR-pQCT. The collection of modules, Bone Analysis Modules (BAM) - Erosion, implements previously published erosion analysis techniques as modules in 3D Slicer, an open-source image processing and visualization tool. BAM includes a module to automatically identify cortical interruptions, from which erosions are manually selected, and a hybrid module that combines morphological and level set operations to quantify the volume of bone erosions. HR-pQCT images of the second and third metacarpophalangeal (MCP) joints were acquired in patients with RA (XtremeCT, n = 14, XtremeCTII, n = 22). The number of cortical interruptions detected by BAM-Erosion agreed strongly with the previously published cortical interruption detection algorithm for both XtremeCT (r2 = 0.85) and XtremeCTII (r2 = 0.87). Erosion volume assessment by BAM-Erosion agreed strongly (r2 = 0.95) with the Medical Image Analysis Framework. BAM-Erosion provides an open-source erosion analysis tool that produces comparable results to previously published algorithms, with improved options for visualization. The strength of the tool is that it implements multiple image processing algorithms for erosion analysis on a single, widely available, open-source platform that can accommodate future updates.

Automated Placenta Segmentation with a Convolutional Neural Network Weighted by Acoustic Shadow Detection.

Placental assessment through routine obstetrical ultrasound is often limited to documenting its location and ruling out placenta previa. However, many obstetrical complications originate from abnormal focal or global placental development. Technical difficulties in assessing the placenta as well as a lack of established objective criteria to classify echotexture are barriers to diagnosis of pathology by ultrasound imaging. As a first step towards the development of a computer aided placental assessment tool, we developed a fully automated method for placental segmentation using a convolutional neural network. The network contains a novel layer weighted by automated acoustic shadow detection to recognize artifacts specific to ultrasound. In order to develop a detection algorithm usable in different imaging scenarios, we acquired a dataset containing 1364 fetal ultrasound images from 247 patients acquired over 47 months was taken with different machines, operators, and at a range of gestational ages. Mean Dice coefficients for automated segmentation on the full dataset with and without the acoustic shadow detection layer were 0.92±0.04 and 0.91±0.03 when comparing to manual segmentation. Mean Dice coefficients on the subset of images containing acoustic shadows with and without acoustic shadow detection were 0.87±0.04 and 0.75±0.05. The method requires no user input to tune the detection. The automated placenta segmentation method can serve as a preprocessing step for further image analysis in artificial intelligence methods requiring large scale data processing of placental images.

Altered Cortical Dynamics and Cognitive Function upon Haploinsufficiency of the Autism-Linked Excitatory Synaptic Suppressor MDGA2.

Mutations in a synaptic organizing pathway contribute to autism. Autism-associated mutations in MDGA2 (MAM domain containing glycosylphosphatidylinositol anchor 2) are thought to reduce excitatory/inhibitory transmission. However, we show that mutation of Mdga2 elevates excitatory transmission, and that MDGA2 blocks neuroligin-1 interaction with neurexins and suppresses excitatory synapse development. Mdga2(+/-) mice, modeling autism mutations, demonstrated increased asymmetric synapse density, mEPSC frequency and amplitude, and altered LTP, with no change in measures of inhibitory synapses. Behavioral assays revealed an autism-like phenotype including stereotypy, aberrant social interactions, and impaired memory. In vivo voltage-sensitive dye imaging, facilitating comparison with fMRI studies in autism, revealed widespread increases in cortical spontaneous activity and intracortical functional connectivity. These results suggest that mutations in MDGA2 contribute to altered cortical processing through the dual disadvantages of elevated excitation and hyperconnectivity, and indicate that perturbations of the NRXN-NLGN pathway in either direction from the norm increase risk for autism.

A Tetra-Primer Amplification Refractory System Technique for the Cost-Effective and Novel Genotyping of Eight Single-Nucleotide Polymorphisms of the Catechol-O-Methyltransferase Gene.

AIMS: Catechol-O-methyltransferase (COMT) is an enzyme involved in the degradation of catecholamine neurotransmitters. Due to its role in neurotransmitter flux, multiple COMT variants have been associated with the development of psychiatric disorders. Notably, select single-nucleotide polymorphisms (SNPs) of the COMT gene have been implicated in schizophrenia risk, severity, and treatment response. In recognition of the value of a streamlined genotyping method for COMT SNP detection, this study was designed to develop a simple and economical tetra-primer amplification refractory mutation system (T-ARMS) assay for the concurrent detection of eight COMT SNPs: rs4680, rs737865, rs165599, rs2075507, rs4633, rs4818, rs6269, and rs165774. MATERIALS AND METHODS: T-ARMS is a genotyping method that uses polymerase chain reaction (PCR) to amplify a multiplex reaction consisting of two primer pairs. T-ARMS primers are customized to each SNP and designed to generate different-sized allele-specific amplicons. This assay was applied to a total of 39 genomic DNA samples. Genotypic designations across the panel of SNPs were subsequently validated by Sanger sequencing. RESULTS: T-ARMS reliably and unambiguously detected all three genotypes (homozygous wild type, heterozygous, and homozygous mutant) for each of the eight COMT SNPs. CONCLUSIONS: Compared to traditional low-throughput methods that require post-PCR modification or high-throughput technologies that require sophisticated equipment, T-ARMS is a cost-effective and efficient assay that can be easily adapted by any standard molecular diagnostics laboratory. This T-ARMS assay provides a practical and robust method for COMT SNP detection.