Radar Recorded Child Vital Sign Public Dataset and Deep Learning-Based Age Group Classification Framework for Vehicular Application.

The ongoing intense development of short-range radar systems and their improved capability of measuring small movements make these systems reliable solutions for the extraction of human vital signs in a contactless fashion. The continuous contactless monitoring of vital signs can be considered in a wide range of applications, such as remote healthcare solutions and context-aware smart sensor development. Currently, the provision of radar-recorded datasets of human vital signs is still an open issue. In this paper, we present a new frequency-modulated continuous wave (FMCW) radar-recorded vital sign dataset for 50 children aged less than 13 years. A clinically approved vital sign monitoring sensor was also deployed as a reference, and data from both sensors were time-synchronized. With the presented dataset, a new child age-group classification system based on GoogLeNet is proposed to develop a child safety sensor for smart vehicles. The radar-recorded vital signs of children are divided into several age groups, and the GoogLeNet framework is trained to predict the age of unknown human test subjects.

Enhanced Electrochemical Performance of Micro-Supercapacitors Via Laser-Scribed Cobalt/Reduced Graphene Oxide Hybrids.

The evolution of "smart life," which connects all internet-of-things (IoT) microdevices and microsensors under wireless communication grids, requires microscale energy storage devices with high power and energy density and long-term cyclability to integrate them with sustainable power generators. Instead of Li-ion batteries with a short lifetime, pseudocapacitors with longer or infinite cyclability and high-power density have been considered as efficient energy storage devices for IoT. However, the design and fabrication of microscale pseudocapacitors have difficulties in patterning microscale electrodes when loading active materials at specific points of the electrodes using conventional microfabrication methods. Here, we developed a facile, one-step fabrication method of micro-supercapacitors (MSCs) through the in situ formation of Co metals and the reduced graphene oxides (rGOs) in a one-pot laser scribing process. The prepared Co/rGO MSC thus exhibited four times higher capacitance than the rGO MSC, due to the Faradaic charge capacitance behavior of the Co/rGO composites.

Highly Luminous N3--Substituted Li2MSiO4-δN2/3δ:Eu2+ (M = Ca, Sr, and Ba) for White NUV Light-Emitting Diodes.

The N3--substituted Li2MSiO4:Eu2+ (M = Ca, Sr, and Ba) phosphors were systematically prepared and analyzed. Secondary-ion mass spectroscopy measurements revealed that the average N3- contents are 0.003 for Ca, 0.009 for Sr, and 0.032 for Ba. Furthermore, the N3- incorporation in the host lattices was corroborated by infrared and X-ray photoelectron spectroscopies. From the photoluminescence spectra of Li2MSiO4:Eu2+ (M = Ca, Sr, and Ba) phosphors before and after N3- doping, it was verified that the enhanced emission intensity of the phosphors is most likely due to the N3- doping. In Li2MSiO4:Eu2+ (M = Ca, Sr, and Ba) phosphors, the maximum wavelengths of the emission band were red-shifted in the order Ca < Ba < Sr, which is not consistent with the trend of crystal field splitting: Ba < Sr < Ca. This discrepancy was clearly explained by electron-electron repulsions among polyhedra, LiO4-MO n , SiO4-MO n , and MO n -M'O n associated with structural difference in the host lattices. Therefore, the energy levels associated with the 4f65d energy levels of Eu2+ are definitely established in the following order: Li2CaSiO4:Eu2+ > Li2BaSiO4:Eu2+ > Li2SrSiO4:Eu2+. Furthermore, using the Williamson-Hall (W-H) method, the determined structural strains of Li2MSiO4:Eu2+ (M = Ca, Sr, and Ba) phosphors revealed that the increased compressive strain after N3- doping induces the enhanced emission intensity of these phosphors. White light-emitting diodes made by three N3--doped phosphors and a 365 nm emitting InGaN chip showed the (0.333, 0.373) color coordinate and high color-rendering index (R a = 83). These phosphor materials may provide a platform for development of new efficient phosphors in solid-state lighting field.

Longitudinal Pure-Tone Threshold Changes in the Same Subjects: Analysis of Factors Affecting Hearing.

OBJECTIVES: To investigate the change of hearing threshold over time and analyze factors that could affect hearing, this longitudinal study of pure-tone threshold changes in the same subjects at a 9-year interval was performed. STUDY DESIGN: Retrospective longitudinal study in a single center (n = 1,978). METHODS: A total of 1,978 subjects were included; they received pure-tone audiometry at a 9-year interval. The degree of the threshold changes was examined and compared between age groups. The subjects' data, such as the level of cholesterol, were analyzed to find risk factors on hearing. RESULTS: The average of the threshold changes was 3.35 dB in the 20s to 30s; 4.38 dB in the 30s to 40s; 5.75 dB in the 40s to 50s; 7.21 dB in the 50s to 60s; and 10.00 dB in the 60s to 70s (all P < 0.05). If the low-density lipoprotein cholesterol (LDL-C) was maintained below 100 mg/dl, the difference in the weighted four-frequency average was 5.45 dB, whereas it was 6.15 dB in the subjects whose LDL-C was over 100 mg/dl (P = 0.032, age-adjusted). In current smokers, the thresholds increased more than in never- or ex-smokers (P = 0.026 in the weighted four-frequency average and P = 0.011 at 8,000 Hz, age-adjusted). CONCLUSION: The degree of the threshold changes exhibited an exponential increase with age. Cessation of smoking is advisable to prevent increased aggravation of hearing. Strict management of the low-density lipoprotein cholesterol may have a positive effect on hearing. LEVEL OF EVIDENCE: 3 Laryngoscope, 129:470-476, 2019.

Variable Selection and Joint Estimation of Mean and Covariance Models with an Application to eQTL Data.

In genomic data analysis, it is commonplace that underlying regulatory relationship over multiple genes is hardly ascertained due to unknown genetic complexity and epigenetic regulations. In this paper, we consider a joint mean and constant covariance model (JMCCM) that elucidates conditional dependent structures of genes with controlling for potential genotype perturbations. To this end, the modified Cholesky decomposition is utilized to parametrize entries of a precision matrix. The JMCCM maximizes the likelihood function to estimate parameters involved in the model. We also develop a variable selection algorithm that selects explanatory variables and Cholesky factors by exploiting the combination of the GCV and BIC as benchmarks, together with Rao and Wald statistics. Importantly, we notice that sparse estimation of a precision matrix (or equivalently gene network) is effectively achieved via the proposed variable selection scheme and contributes to exploring significant hub genes shown to be concordant to a priori biological evidence. In simulation studies, we confirm that our model selection efficiently identifies the true underlying networks. With an application to miRNA and SNPs data from yeast (a.k.a. eQTL data), we demonstrate that constructed gene networks reproduce validated biological and clinical knowledge with regard to various pathways including the cell cycle pathway.

Highly Luminous and Thermally Stable Mg-Substituted Ca2-xMgxSiO4:Ce (0 ≤ x ≤ 1) Phosphor for NUV-LEDs.

Blue-emitting Ca2-xMgxSiO4:Ce (0.0 ≤ x ≤ 1.0) phosphors were successfully synthesized and characterized. Rietveld refinement revealed that four main phases exist within the solid-solution range of CaO-MgO-SiO2, namely, ß-Ca2SiO4 (Mg (x) = 0.0), Ca14Mg2(SiO4)8 (Mg (x) = 0.25), Ca3Mg(SiO4)2 (Mg (x) = 0.5), and CaMgSiO4 (Mg (x) = 1.0). The variation of the IR modes was more prominent with increasing Mg2+ content in the Ca2-xMgxSiO4 materials. The sharing of O atoms of the SiO4-tetrahedra by the MgO6-octahedra induced weakening of the Si-O bonds, which resulted in the red shift of the [SiO4] internal modes and appearance of a Mg-O stretching vibration at ∼418 cm-1. Raman measurement revealed that the change of the Ca-O bond lengths because of the Mg2+-substitution directly reflected the frequency shift of the Si-O stretching-Raman modes. Notably, the thermal stability of Ca2-xMgxSiO4:Ce (Mg (x) > 0.0) phosphors was superior to that of ß-Ca2SiO4:Ce (Mg (x) = 0.0) as confirmed by temperature-dependent photoluminescence (PL) measurements. This indicated that Mg2+ ions play an important role in enhancement of the thermal stability. In combination with the results from PL and electroluminescence (EL), it was elucidated that the luminous efficiency of Ca2-xMgxSiO4:Ce (Mg (x) = 0.1) was approximately twice as much as ß-Ca2SiO4:Ce (Mg (x) = 0.00), directly indicating a "Mg2+-substitution effect". The large enhancements of PL, EL, and thermal stability because of Mg2+-substitution may provide a platform in the discovery of more efficient phosphors for NUV-LEDs.

Node-Structured Integrative Gaussian Graphical Model Guided by Pathway Information.

Up to date, many biological pathways related to cancer have been extensively applied thanks to outputs of burgeoning biomedical research. This leads to a new technical challenge of exploring and validating biological pathways that can characterize transcriptomic mechanisms across different disease subtypes. In pursuit of accommodating multiple studies, the joint Gaussian graphical model was previously proposed to incorporate nonzero edge effects. However, this model is inevitably dependent on post hoc analysis in order to confirm biological significance. To circumvent this drawback, we attempt not only to combine transcriptomic data but also to embed pathway information, well-ascertained biological evidence as such, into the model. To this end, we propose a novel statistical framework for fitting joint Gaussian graphical model simultaneously with informative pathways consistently expressed across multiple studies. In theory, structured nodes can be prespecified with multiple genes. The optimization rule employs the structured input-output lasso model, in order to estimate a sparse precision matrix constructed by simultaneous effects of multiple studies and structured nodes. With an application to breast cancer data sets, we found that the proposed model is superior in efficiently capturing structures of biological evidence (e.g., pathways). An R software package nsiGGM is publicly available at author's webpage.

Erratum to: Meta-analytic support vector machine for integrating multiple omics data.

[This corrects the article DOI: 10.1186/s13040-017-0126-8.].

Meta-analytic support vector machine for integrating multiple omics data.

BACKGROUND: Of late, high-throughput microarray and sequencing data have been extensively used to monitor biomarkers and biological processes related to many diseases. Under this circumstance, the support vector machine (SVM) has been popularly used and been successful for gene selection in many applications. Despite surpassing benefits of the SVMs, single data analysis using small- and mid-size of data inevitably runs into the problem of low reproducibility and statistical power. To address this problem, we propose a meta-analytic support vector machine (Meta-SVM) that can accommodate multiple omics data, making it possible to detect consensus genes associated with diseases across studies. RESULTS: Experimental studies show that the Meta-SVM is superior to the existing meta-analysis method in detecting true signal genes. In real data applications, diverse omics data of breast cancer (TCGA) and mRNA expression data of lung disease (idiopathic pulmonary fibrosis; IPF) were applied. As a result, we identified gene sets consistently associated with the diseases across studies. In particular, the ascertained gene set of TCGA omics data was found to be significantly enriched in the ABC transporters pathways well known as critical for the breast cancer mechanism. CONCLUSION: The Meta-SVM effectively achieves the purpose of meta-analysis as jointly leveraging multiple omics data, and facilitates identifying potential biomarkers and elucidating the disease process.

Clinical Characteristics of Bilateral versus Unilateral Chronic Subdural Hematoma.

OBJECTIVE: Chronic subdural hematoma (CSDH) is a common intracranial hemorrhage that is associated with significant morbidity. Bilateral lesions are occasionally found in neurosurgical practice. The purpose of this study is to analyze clinical characteristics of bilateral CSDH compared with unilateral CSDH. METHODS: Between January 2005 and January 2013, the authors treated 114 surgical patients with CSDH. Clinical presentations, precipitating factors, computed tomography (CT) findings, postoperative complications, and outcomes of patients were retrospectively analyzed in the bilateral and unilateral CSDH groups. RESULTS: Bilateral CSDH was identified in 28 (24.6%) of the 114 CSDH patients. The mean age was 77.85 years in the bilateral CSDH group. The frequency of altered consciousness as a presenting symptom was significantly higher in the bilateral CSDH, and that of hemiparesis was significantly higher in the unilateral CSDH (p=0.015). Diabetes mellitus was more common in the bilateral CSDH (p=0.001). CT scans revealed significant differences in the degree of midline shift (p=0.001). The mean modified Rankin scale at discharge was 1.5 in the bilateral CSDH group and 0.6 in the unilateral group (p=0.019). CONCLUSION: Bilateral CSDH showed different clinical characteristics from unilateral CSDH. Bilateral CSDH is prone to occurrence in the patient of old and diabetics. The patients of bilateral CSDH seem to reveal worse mental status and neurologic sign than unilateral CSDH in both baseline and postoperative state.

Cauda equina syndrome caused by pseudogout involving the lumbar intervertebral disc.

Calcium pyrophosphate dihydrate (CPPD) deposition disease, also known as pseudogout, is a disease that causes inflammatory arthropathy in peripheral joints, however, symptomatic involvement of the intervertebral disc is uncommon. Herein, we describe a 59-yr-old patient who presented with cauda equina syndrome. Magnetic resonance imaging of the patient showed an epidural mass-like lesion at the disc space of L4-L5, which was compressing the thecal sac. Biopsy of the intervertebral disc and epidural mass-like lesion was determined to be CPPD deposits. We reviewed previously reported cases of pseudogout involving the lumbar intervertebral disc and discuss the pathogenesis and treatment of the disease.

LW6, a novel HIF-1 inhibitor, promotes proteasomal degradation of HIF-1alpha via upregulation of VHL in a colon cancer cell line.

Hypoxia-inducible factor HIF-1 is responsible for radiation resistance and poor prognosis in cancer therapy. As part of our drug discovery program, a novel HIF inhibitor, LW6, was identified as a small compound that inhibits the accumulation of HIF-1alpha. We found that LW6 decreased HIF-1alpha protein expression without affecting HIF-1beta expression. MG132, a proteasome inhibitor, protected HIF-1alpha from LW6-induced proteasomal degradation, indicating that LW6 affects the stability of the HIF-1alpha protein. We found that LW6 promoted the degradation of wild type HIF-1alpha, but not of a DM-HIF-1alpha with modifications of P402A and P564A, at hydroxylation sites in the oxygen-dependent degradation domain (ODDD). LW6 did not affect the activity of prolyl hydroxylase (PHD), but induced the expression of von Hippel-Lindau (VHL), which interacts with prolyl-hydroxylated HIF-1alpha for proteasomal degradation. In the presence of LW6, knockdown of VHL did not abolish HIF-1alpha protein accumulation, indicating that LW6 degraded HIF-1alpha via regulation of VHL expression. In mice carrying xenografts of human colon cancer HCT116 cells, LW6 demonstrated strong anti-tumor efficacy in vivo and caused a decrease in HIF-1alpha expression in frozen-tissue immunohistochemical staining. These data suggest that LW6 may be valuable in the development of a HIF-1alpha inhibitor for cancer treatment.