Exploring Doping Mechanisms and Modulating Carrier Concentration in Copper Iodide: Applications in Thermoelectric Materials.

Due to its small hole-effective mass, flexibility, and transparency, copper iodide (CuI) has emerged as a promising p-type alternative to the predominantly used n-type metal oxide semiconductors. However, the lack of effective doping methods hinders the utility of CuI in various applications. Sulfur (S)-doping through liquid iodination is previously reported to significantly enhance electrical conductivity up to 511 S cm-1. In this paper, the underlying doping mechanism with various S-dopants is explored, and suggested a method for controlling electrical conductivity, which is important to various applications, especially thermoelectric (TE) materials. Subsequently, electric and TE properties are systematically controlled by adjusting the carrier concentration from 3.0 × 1019 to 4.5 × 1020 cm-3, and accurately measured thermal conductivity with respect to carrier concentration and film thickness. Sulfur-doped CuI (CuI:S) thin films exhibited a maximum power factor of 5.76 µW cm-1 K-2 at a carrier concentration of 1.3 × 1020 cm-3, and a TE figure of merit (ZT) of 0.25. Furthermore, a transparent and flexible TE power generator is developed, with an impressive output power density of 43 nW cm-2 at a temperature differential of 30 K. Mechanical durability tests validated the potential of CuI:S films in transparent and flexible TE applications.

Dynamic multimodal holograms of conjugated organogels via dithering mask lithography.

Polymeric materials have been used to realize optical systems that, through periodic variations of their structural or optical properties, interact with light-generating holographic signals. Complex holographic systems can also be dynamically controlled through exposure to external stimuli, yet they usually contain only a single type of holographic mode. Here, we report a conjugated organogel that reversibly displays three modes of holograms in a single architecture. Using dithering mask lithography, we realized two-dimensional patterns with varying cross-linking densities on a conjugated polydiacetylene. In protic solvents, the organogel contracts anisotropically to develop optical and structural heterogeneities along the third dimension, displaying holograms in the form of three-dimensional full parallax signals, both in fluorescence and bright-field microscopy imaging. In aprotic solvents, these heterogeneities diminish as organogels expand, recovering the two-dimensional periodicity to display a third hologram mode based on iridescent structural colours. Our study presents a next-generation hologram manufacturing method for multilevel encryption technologies.

Cost-Effectiveness Analysis of Smoking Cessation Interventions With Behavioral Support: A Study Based on the Benefits of Smoking Cessation on Outcomes (BENESCO) Model.

INTRODUCTION: Few studies have compared cost-effectiveness of different smoking cessation interventions (SCIs) that include behavioral support, considering smoking-related diseases. Therefore, we compare the cost-effectiveness of SCIs with behavioral support in South Korea using the Benefits of Smoking Cessation on Outcomes (BENESCO) model. AIMS AND METHODS: We used the BENESCO model to estimate the cost and utility of the SCIs with behavioral support, including pharmacist counseling with nicotine replacement therapy (pharmacist+NRT), expert counseling with NRT (expert+NRT), and expert counseling with varenicline (expert+varenicline). The target population was adult smokers who wanted to cease smoking within 1 month. We applied transitional probabilities and epidemiological data from the literature. Medical costs and utilities were calculated using claims and national survey data, respectively. Cost-effectiveness was evaluated within the threshold (17 926 USD per quality-adjusted life years [QALYs]) by incremental cost-effectiveness ratio (ICER). RESULTS: The model cohort included 1 219 390 male and 298 511 female smokers. The pharmacist+NRT group had 32 842 more QALYs gained and 26 689 958 USD less expended than the expert+NRT group. The ICER for the expert+varenicline group versus the pharmacist+NRT and expert+NRT groups was 27 247 and 4074 USD per QALY, respectively. The robustness of the results was confirmed by sensitivity analyses, except for the discount rate and cost of the expert+varenicline group. CONCLUSIONS: In Korea, pharmacist counseling with NRT showed higher QALY gains and lower costs than expert counseling with NRT. Expert counseling with varenicline was more effective for smoking cessation and more cost-effective than expert counseling with NRT but was not cost-effective compared with pharmacist counseling with NRT. IMPLICATIONS: This study provides evidence for decision-making on smoking cessation programs by evaluating the cost-effectiveness of SCIs. Furthermore, we attempted to use the BENESCO model to compare and evaluate the cost-effectiveness of SCIs with behavioral support. It is meaningful because this study showed the availability of using the BENESCO model in the future cost-effectiveness analysis of various SCIs.

Atorvastatin and blood flow regulate expression of distinctive sets of genes in mouse carotid artery endothelium.

Hypercholesterolemia is a well-known pro-atherogenic risk factor and statin is the most effective anti-atherogenic drug that lowers blood cholesterol levels. However, despite systemic hypercholesterolemia, atherosclerosis preferentially occurs in arterial regions exposed to disturbed blood flow (d-flow), while the stable flow (s-flow) regions are spared. Given their predominant effects on endothelial function and atherosclerosis, we tested whether (1) statin and flow regulate the same or independent sets of genes and (2) statin can rescue d-flow-regulated genes in mouse artery endothelial cells in vivo. To test the hypotheses, C57BL/6 J mice (8-week-old male, n=5 per group) were pre-treated with atorvastatin (10mg/kg/day, Orally) or vehicle for 5 days. Thereafter, partial carotid ligation (PCL) surgery to induce d-flow in the left carotid artery (LCA) was performed, and statin or vehicle treatment was continued. The contralateral right carotid artery (RCA) remained exposed to s-flow to be used as the control. Two days or 2 weeks post-PCL surgery, endothelial-enriched RNAs from the LCAs and RCAs were collected and subjected to microarray gene expression analysis. Statin treatment in the s-flow condition (RCA+statin versus RCA+vehicle) altered the expression of 667 genes at 2-day and 187 genes at 2-week timepoint, respectively (P<0.05, fold change (FC)≥±1.5). Interestingly, statin treatment in the d-flow condition (LCA+statin versus LCA+vehicle) affected a limited number of genes: 113 and 75 differentially expressed genes at 2-day and 2-week timepoint, respectively (P<0.05, FC≥±1.5). In contrast, d-flow in the vehicle groups (LCA+vehicle versus RCA+vehicle) differentially regulated 4061 genes at 2-day and 3169 genes at 2-week timepoint, respectively (P<0.05, FC≥±1.5). Moreover, statin treatment did not reduce the number of flow-sensitive genes (LCA+statin versus RCA+statin) compared to the vehicle groups: 1825 genes at 2-day and 3788 genes at 2-week, respectively, were differentially regulated (P<0.05, FC≥±1.5). These results revealed that both statin and d-flow regulate expression of hundreds or thousands of arterial endothelial genes, respectively, in vivo. Further, statin and d-flow regulate independent sets of endothelial genes. Importantly, statin treatment did not reverse d-flow-regulated genes except for a small number of genes. These results suggest that both statin and flow play important independent roles in atherosclerosis development and highlight the need to consider their therapeutic implications for both.

Hierarchically Well-Developed Porous Graphene Nanofibers Comprising N-Doped Graphitic C-Coated Cobalt Oxide Hollow Nanospheres As Anodes for High-Rate Li-Ion Batteries.

Hierarchically well-developed porous graphene nanofibers comprising N-doped graphitic C (NGC)-coated cobalt oxide hollow nanospheres are introduced as anodes for high-rate Li-ion batteries. For this, three strategies, comprising the Kirkendall effect, metal-organic frameworks, and compositing with highly conductive C, are applied to the 1D architecture. In particular, NGC layers are coated on cobalt oxide hollow nanospheres as a primary transport path of electrons followed by graphene-nanonetwork-constituting nanofibers as a continuous and secondary electron transport path. Superior cycling performance is achieved, as the unique nanostructure delivers a discharge capacity of 823 mAh g-1 after 500 cycles at 3.0 A g-1 with a low decay rate of 0.092% per cycle. The rate capability is also noteworthy as the structure exhibits high discharge capacities of 1035, 929, 847, 787, 747, 703, 672, 650, 625, 610, 570, 537, 475, 422, 294, and 222 mAh g-1 at current densities of 0.5, 1.5, 3, 5, 7, 10, 12, 15, 18, 20, 25, 30, 40, 50, 80, and 100 A g-1 , respectively. In view of the highly efficient Li+ ion/electron diffusion and high structural stability, the present nanostructuring strategy has a huge potential in opening new frontiers for high-rate and long-lived stable energy storage systems.

HTRgene: a computational method to perform the integrated analysis of multiple heterogeneous time-series data: case analysis of cold and heat stress response signaling genes in Arabidopsis.

BACKGROUND: Integrated analysis that uses multiple sample gene expression data measured under the same stress can detect stress response genes more accurately than analysis of individual sample data. However, the integrated analysis is challenging since experimental conditions (strength of stress and the number of time points) are heterogeneous across multiple samples. RESULTS: HTRgene is a computational method to perform the integrated analysis of multiple heterogeneous time-series data measured under the same stress condition. The goal of HTRgene is to identify "response order preserving DEGs" that are defined as genes not only which are differentially expressed but also whose response order is preserved across multiple samples. The utility of HTRgene was demonstrated using 28 and 24 time-series sample gene expression data measured under cold and heat stress in Arabidopsis. HTRgene analysis successfully reproduced known biological mechanisms of cold and heat stress in Arabidopsis. Also, HTRgene showed higher accuracy in detecting the documented stress response genes than existing tools. CONCLUSIONS: HTRgene, a method to find the ordering of response time of genes that are commonly observed among multiple time-series samples, successfully integrated multiple heterogeneous time-series gene expression datasets. It can be applied to many research problems related to the integration of time series data analysis.

Venn-diaNet : venn diagram based network propagation analysis framework for comparing multiple biological experiments.

BACKGROUND: The main research topic in this paper is how to compare multiple biological experiments using transcriptome data, where each experiment is measured and designed to compare control and treated samples. Comparison of multiple biological experiments is usually performed in terms of the number of DEGs in an arbitrary combination of biological experiments. This process is usually facilitated with Venn diagram but there are several issues when Venn diagram is used to compare and analyze multiple experiments in terms of DEGs. First, current Venn diagram tools do not provide systematic analysis to prioritize genes. Because that current tools generally do not fully focus to prioritize genes, genes that are located in the segments in the Venn diagram (especially, intersection) is usually difficult to rank. Second, elucidating the phenotypic difference only with the lists of DEGs and expression values is challenging when the experimental designs have the combination of treatments. Experiment designs that aim to find the synergistic effect of the combination of treatments are very difficult to find without an informative system. RESULTS: We introduce Venn-diaNet, a Venn diagram based analysis framework that uses network propagation upon protein-protein interaction network to prioritizes genes from experiments that have multiple DEG lists. We suggest that the two issues can be effectively handled by ranking or prioritizing genes with segments of a Venn diagram. The user can easily compare multiple DEG lists with gene rankings, which is easy to understand and also can be coupled with additional analysis for their purposes. Our system provides a web-based interface to select seed genes in any of areas in a Venn diagram and then perform network propagation analysis to measure the influence of the selected seed genes in terms of ranked list of DEGs. CONCLUSIONS: We suggest that our system can logically guide to select seed genes without additional prior knowledge that makes us free from the seed selection of network propagation issues. We showed that Venn-diaNet can reproduce the research findings reported in the original papers that have experiments that compare two, three and eight experiments. Venn-diaNet is freely available at: http://biohealth.snu.ac.kr/software/venndianet.

StressGenePred: a twin prediction model architecture for classifying the stress types of samples and discovering stress-related genes in arabidopsis.

BACKGROUND: Recently, a number of studies have been conducted to investigate how plants respond to stress at the cellular molecular level by measuring gene expression profiles over time. As a result, a set of time-series gene expression data for the stress response are available in databases. With the data, an integrated analysis of multiple stresses is possible, which identifies stress-responsive genes with higher specificity because considering multiple stress can capture the effect of interference between stresses. To analyze such data, a machine learning model needs to be built. RESULTS: In this study, we developed StressGenePred, a neural network-based machine learning method, to integrate time-series transcriptome data of multiple stress types. StressGenePred is designed to detect single stress-specific biomarker genes by using a simple feature embedding method, a twin neural network model, and Confident Multiple Choice Learning (CMCL) loss. The twin neural network model consists of a biomarker gene discovery and a stress type prediction model that share the same logical layer to reduce training complexity. The CMCL loss is used to make the twin model select biomarker genes that respond specifically to a single stress. In experiments using Arabidopsis gene expression data for four major environmental stresses, such as heat, cold, salt, and drought, StressGenePred classified the types of stress more accurately than the limma feature embedding method and the support vector machine and random forest classification methods. In addition, StressGenePred discovered known stress-related genes with higher specificity than the Fisher method. CONCLUSIONS: StressGenePred is a machine learning method for identifying stress-related genes and predicting stress types for an integrated analysis of multiple stress time-series transcriptome data. This method can be used to other phenotype-gene associated studies.

In silico experiment system for testing hypothesis on gene functions using three condition specific biological networks.

Determining functions of a gene requires time consuming, expensive biological experiments. Scientists can speed up this experimental process if the literature information and biological networks can be adequately provided. In this paper, we present a web-based information system that can perform in silico experiments of computationally testing hypothesis on the function of a gene. A hypothesis that is specified in English by the user is converted to genes using a literature and knowledge mining system called BEST. Condition-specific TF, miRNA and PPI (protein-protein interaction) networks are automatically generated by projecting gene and miRNA expression data to template networks. Then, an in silico experiment is to test how well the target genes are connected from the knockout gene through the condition-specific networks. The test result visualizes path from the knockout gene to the target genes in the three networks. Statistical and information-theoretic scores are provided on the resulting web page to help scientists either accept or reject the hypothesis being tested. Our web-based system was extensively tested using three data sets, such as E2f1, Lrrk2, and Dicer1 knockout data sets. We were able to re-produce gene functions reported in the original research papers. In addition, we comprehensively tested with all disease names in MalaCards as hypothesis to show the effectiveness of our system. Our in silico experiment system can be very useful in suggesting biological mechanisms which can be further tested in vivo or in vitro. AVAILABILITY: http://biohealth.snu.ac.kr/software/insilico/.

Automatic Prediction of Atrial Fibrillation Based on Convolutional Neural Network Using a Short-term Normal Electrocardiogram Signal.

BACKGROUND: In this study, we propose a method for automatically predicting atrial fibrillation (AF) based on convolutional neural network (CNN) using a short-term normal electrocardiogram (ECG) signal. METHODS: We designed a CNN model and optimized it by dropout and normalization. One-dimensional convolution, max-pooling, and fully-connected multiple perceptron were used to analyze the short-term normal ECG. The ECG signal was preprocessed and segmented to train and evaluate the proposed CNN model. The training and test sets consisted of the two AF and one normal dataset from the MIT-BIH database. RESULTS: The proposed CNN model for the automatic prediction of AF achieved a high performance with a sensitivity of 98.6%, a specificity of 98.7%, and an accuracy of 98.7%. CONCLUSION: The results show the possibility of automatically predicting AF based on the CNN model using a short-term normal ECG signal. The proposed CNN model for the automatic prediction of AF can be a helpful tool for the early diagnosis of AF in healthcare fields.

Estimation of Arterial Blood Pressure Based on Artificial Intelligence Using Single Earlobe Photoplethysmography during Cardiopulmonary Resuscitation.

This study investigates the feasibility of estimation of blood pressure (BP) using a single earlobe photoplethysmography (Ear PPG) during cardiopulmonary resuscitation (CPR). We have designed a system that carries out Ear PPG for estimation of BP. In particular, the BP signals are estimated according to a long short-term memory (LSTM) model using an Ear PPG. To investigate the proposed method, two statistical analyses were conducted for comparison between BP measured by the micromanometer-based gold standard method (BPMEAS) and the Ear PPG-based proposed method (BPEST) for swine cardiac model. First, Pearson's correlation analysis showed high positive correlations (r = 0.92, p < 0.01) between BPMEAS and BPEST. Second, the paired-samples t-test on the BP parameters (systolic and diastolic blood pressure) of the two methods indicated no significant differences (p > 0.05). Therefore, the proposed method has the potential for estimation of BP for CPR biofeedback based on LSTM using a single Ear PPG.

Disturbed Flow Promotes Arterial Stiffening Through Thrombospondin-1.

BACKGROUND: Arterial stiffness and wall shear stress are powerful determinants of cardiovascular health, and arterial stiffness is associated with increased cardiovascular mortality. Low and oscillatory wall shear stress, termed disturbed flow (d-flow), promotes atherosclerotic arterial remodeling, but the relationship between d-flow and arterial stiffness is not well understood. The objective of this study was to define the role of d-flow on arterial stiffening and discover the relevant signaling pathways by which d-flow stiffens arteries. METHODS: D-flow was induced in the carotid arteries of young and old mice of both sexes. Arterial stiffness was quantified ex vivo with cylindrical biaxial mechanical testing and in vivo from duplex ultrasound and compared with unmanipulated carotid arteries from 80-week-old mice. Gene expression and pathway analysis was performed on endothelial cell-enriched RNA and validated by immunohistochemistry. In vitro testing of signaling pathways was performed under oscillatory and laminar wall shear stress conditions. Human arteries from regions of d-flow and stable flow were tested ex vivo to validate critical results from the animal model. RESULTS: D-flow induced arterial stiffening through collagen deposition after partial carotid ligation, and the degree of stiffening was similar to that of unmanipulated carotid arteries from 80-week-old mice. Intimal gene pathway analyses identified transforming growth factor-ß pathways as having a prominent role in this stiffened arterial response, but this was attributable to thrombospondin-1 (TSP-1) stimulation of profibrotic genes and not changes to transforming growth factor-ß. In vitro and in vivo testing under d-flow conditions identified a possible role for TSP-1 activation of transforming growth factor-ß in the upregulation of these genes. TSP-1 knockout animals had significantly less arterial stiffening in response to d-flow than wild-type carotid arteries. Human arteries exposed to d-flow had similar increases TSP-1 and collagen gene expression as seen in our model. CONCLUSIONS: TSP-1 has a critical role in shear-mediated arterial stiffening that is mediated in part through TSP-1's activation of the profibrotic signaling pathways of transforming growth factor-ß. Molecular targets in this pathway may lead to novel therapies to limit arterial stiffening and the progression of disease in arteries exposed to d-flow.

Accelerated atherosclerosis development in C57Bl6 mice by overexpressing AAV-mediated PCSK9 and partial carotid ligation.

Studying the role of a particular gene in atherosclerosis typically requires a time-consuming and often difficult process of generating double knockouts or transgenics on ApoE-/- or LDL receptor (LDLR)-/- background. Recently, it was reported that adeno-associated-virus-8 (AAV8)-mediated overexpression of PCSK9 (AAV8-PCSK9) rapidly induced hyperlipidemia. However, using this method in C57BL6 wild-type (C57) mice, it took ~3 months to develop atherosclerosis. Our partial carotid ligation model is used to rapidly develop atherosclerosis by inducing disturbed flow in the left common carotid artery within 2 weeks in ApoE-/- or LDLR-/- mice. Here, we combined these two approaches to develop an accelerated model of atherosclerosis in C57 mice. C57 mice were injected with AAV9-PCSK9 or AAV9-luciferase (control) and high-fat diet was initiated. A week later, partial ligation was performed. Compared to the control, AAV-PCSK9 led to elevated serum PCSK9, hypercholesterolemia, and rapid atherosclerosis development within 3 weeks as determined by gross plaque imaging, and staining with Oil-Red-O, Movat's pentachrome, and CD45 antibody. These plaque lesions were comparable to the atherosclerotic lesions that have been previously observed in ApoE-/- or LDLR-/- mice that were subjected to partial carotid ligation and high-fat diet. Next, we tested whether our method can be utilized to rapidly determine the role of a particular gene in atherosclerosis. Using eNOS-/- and NOX1-/y mice on C57 background, we found that the eNOS-/- mice developed more advanced lesions, while the NOX1-/y mice developed less atherosclerotic lesions as compared to the C57 controls. These results are consistent with the previous findings using double knockouts (eNOS-/-_ApoE-/- and NOX1-/y_ApoE-/-). AAV9-PCSK9 injection followed by partial carotid ligation is an effective and time-saving approach to rapidly induce atherosclerosis. This accelerated model is well-suited to quickly determine the role of gene(s) interest without generating double or triple knockouts.

Comparison of joint kinematics and pedaling force in the young and the elderly.

[Purpose] Proper pedaling posture can improve muscle strength and cardiopulmonary function. To investigate proper pedaling posture for the elderly, this study compared the pedaling efficiency of the elderly with that of the young by using an index of effectiveness (IE) and kinematic results. [Subjects and Methods] Eight adults in their twenties and eight in their seventies participated in 3-min, 40 rpm cycle pedaling tests, with the same load and cadence. The joint angle, range of motion (ROM), and IE were compared by measuring 3-dimensional motion and 3-axis pedal-reaction force during 4 pedaling phases (Phase 1: 330-30°, Phase 2: 30-150°, Phase 3: 150-210°, and Phase 4: 210-330°). [Results] The knee and ankle ROM, maximum knee extension, and maximum ankle dorsiflexion in the elderly were significantly decreased compared with those in the young. Moreover, there were significant differences in IE for the total phase, Phase 1, and Phase 4 between the elderly and young. IE of the young was greater than that of the elderly, except in Phase 3. [Conclusion] Joint movement in the elderly during pedaling was limited. This study provides information that will facilitate the proposal of an efficient pedaling method for the elderly.

Fall- and BBS-related differences in muscle strength and postural balance of the elderly.

[Purpose] The purpose of this study was to compare the differences in muscle strength and postural balance between fallers and non-fallers. We also compared the difference between normal and impaired balance groups using the same subjects and the same variables. [Subjects and Methods] Seventy-one healthy elderly females (age: 75.1 ± 75 years; weight: 57.3 ± 57 kg; height: 150.1 ± 15 cm) who had high levels of physical activity participated [25 fallers (FG) vs. 46 non-fallers (NG); and 52 healthy balance group (HBG) and 19 impaired balance group (IBG) subjects]. To compare the groups, the muscle strengths of 9 muscle groups, and 20 variables of the instrumented standing balance assessment (2 area variables, 9 time-domain variables, and 9 frequency-domain variables) were assessed. [Results] The FG and NG could only be categorized based on the frequency-domain variables of the instrumented standing balance assessment. On the other hand, there were significant differences between HBG and IBG in height, 6 muscle strength, and 2 time-domain variables of the instrumented standing balance assessment. [Conclusion] These results suggest that muscle strength and standing balance are reflected in physical balance ability (i.e., BBS); however they are in sufficient for determining the actual occurrence of falls.

The development and evaluation of a program for leg-strengthening exercises and balance assessment using Kinect.

[Purpose] In this study, a program was developed for leg-strengthening exercises and balance assessment using Microsoft Kinect. [Subjects and Methods] The program consists of three leg-strengthening exercises (knee flexion, hip flexion, and hip extension) and the one-leg standing test (OLST). The program recognizes the correct exercise posture by comparison with the range of motion of the hip and knee joints and provides a number of correct action examples to improve training. The program measures the duration of the OLST and presents this as the balance-age. The accuracy of the program was analyzed using the data of five male adults. [Results] In terms of the motion recognition accuracy, the sensitivity and specificity were 95.3% and 100%, respectively. For the balance assessment, the time measured using the existing method with a stopwatch had an absolute error of 0.37 sec. [Conclusion] The developed program can be used to enable users to conduct leg-strengthening exercises and balance assessments at home.

A study on balance assessment according to the levels of difficulty in postural control.

[Purpose] This study aimed to determine appropriate measures for assessing balance ability according to difficulty level during standing tasks. [Subjects and Methods] The subjects were 56 old (>65 years) and 30 young (20-30 years) adults. By using the Berg balance scale, the subjects were divided into three groups: 29 healthy older (Berg score≥52), 27 impaired older (Berg score≥40), and 30 healthy young (Berg score≥55). One inertial measurement unit sensor was attached at the waist, and the subjects performed standing tasks (1 min/task) with six difficulty levels: eyes open and eyes closed on firm ground, one foam, and two foams. Thirty-nine (24 time-domain, 15 frequency-domain) measures were calculated by using acceleration data. The slope of each derived measure was calculated through the least-squares method. [Results] Five (95% ellipse sway area, root mean squares [anterior-posterior and resultant directions], and mean distance [anterior-posterior and resultant directions] in time domain) of the 39 measures showed significant differences among the groups under specific standing conditions. The slopes of derived measures showed significant differences among the groups and significant correlations with the Berg scores. [Conclusion] The slope according to the difficulty level can be used to assess and discriminate standing balance ability.

Effects of low light on the stability of the head and pelvis of the healthy elderly.

[Purpose] The purpose of this study was to evaluate the changes in body stability of the elderly while walking on even surface ground under low light. [Subjects] Ten young males and ten elderly males participated in this experiment. [Methods] Each subject walked along a 7 m walkway five times at their preferred walking speed under normal (>300 lux, NORM) and low light conditions (<5 lux, LOW). To compare the changes in body stability, the root mean square of acceleration (RMSacc) at the head and pelvis was used. [Results] The results show that the body stability of young adults showed a similar RMSacc in all directions at the head and pelvis between the normal and low light walking conditions. In contrast, the RMSacc in all directions at the head and pelvis during low light walking by elderly adults was significantly greater than that of normal light walking. [Conclusion] It was confirmed that, despite walking on even ground, low light condition affects the body stability of the elderly. To clearly evaluate the effect of low light with aging on gait pattern, further study will be necessary to perform additional experiments under various environmental conditions to investigate walking speed, multi-tasking, stairs, and uneven walkway performance.

The long elusive IgM Fc receptor, FcµR.

IgM exists as both a monomer on the surface of B cells and a pentamer secreted by plasma cells. Both pre-immune "natural" and antigen-induced "immune" IgM antibodies are important for protective immunity and for immune regulation of autoimmune processes by recognizing pathogens and self-antigens. Effector proteins interacting with the Fc portion of IgM, such as complement and complement receptors, have thus far been proposed but fail to fully account for the IgM-mediated protection and regulation. A major reason for this deficit in our understanding of IgM function seems to be lack of data on a long elusive Fc receptor for IgM (FcµR). We have recently identified a bona fide FcµR in both humans and mice. In this article we briefly review what we have learned so far about FcµR.

Anti-inflammatory and antiatherogenic role of BMP receptor II in endothelial cells.

OBJECTIVE: Atherosclerosis is an inflammatory disease with multiple underlying metabolic and physical risk factors. Bone morphogenic protein 4 (BMP4) expression is increased in endothelium in atherosclerosis-prone regions and is known to induce endothelial inflammation, endothelial dysfunction, and hypertension. BMP actions are mediated by 2 different types of BMP receptors (BMPRI and BMPRII). Here, we show a surprising finding that loss of BMPRII expression causes endothelial inflammation and atherosclerosis. APPROACH AND RESULTS: Using BMPRII siRNA and BMPRII(+/-) mice, we found that specific knockdown of BMPRII, but not other BMP receptors (Alk1, Alk2, Alk3, Alk6, ActRIIa, and ActRIIb), induced endothelial inflammation in a ligand-independent manner by mechanisms mediated by reactive oxygen species, nuclear factor-KappaB, and reduced nicotinamide adenine dinucleotide phosphate oxidases. Further, BMPRII(+/-)ApoE(-/-) mice developed accelerated atherosclerosis compared with BMPRII(+/+)ApoE(-/-) mice. Interestingly, we found that multiple proatherogenic stimuli, such as hypercholesterolemia, disturbed flow, prohypertensive angiotensin II, and the proinflammatory cytokine (tumor necrosis factor-α), downregulated BMPRII expression in endothelium, whereas antiatherogenic stimuli, such as stable flow and statin treatment, upregulated its expression in vivo and in vitro. Moreover, BMPRII expression was significantly diminished in human coronary advanced atherosclerotic lesions. Also, we were able to rescue the endothelial inflammation induced by BMPRII knockdown by overexpressing the BMPRII wild type, but not by the BMPRII short form lacking the carboxyl-terminal tail region. CONCLUSIONS: These results suggest that BMPRII is a critical, anti-inflammatory, and antiatherogenic protein that is commonly targeted by multiple pro- and antiatherogenic factors. BMPRII may be used as a novel diagnostic and therapeutic target in atherosclerosis.