Different but Synergistic Effects of Union and Manager Leadership on Member Job Satisfaction.

Existing research has tended to overlook the diverse roles of union leadership in contributing to member attitudes. Drawing on the social information processing theory, this study examines how union leaders' (shop stewards) service-oriented leadership relates to member job satisfaction. To clarify the mechanism underlying this relationship, this study focuses on union instrumentality as a mediator. The research also examines managers' ethical leadership as a conditional factor in the relationship between union leaders' service-oriented leadership and member job satisfaction through union instrumentality. To test our hypothesis, this study analyzed the results of a survey of 603 respondents from two branches of the Korean Metal Workers' Union. The findings of this study indicate that union instrumentality is the link between service-oriented union leadership and member job satisfaction. Additionally, the strength of the mediated relationship between the aforementioned factors through union instrumentality is contingent on managerial ethical leadership. This study contributes to an integrated understanding of the way in which service-oriented union stewards and ethical managers influence member job satisfaction through their leadership.

Identifying regions of excess injury risks associated with distracted driving: A case study in Central Ohio, USA.

This study examines the latent influence of spatial locations on the relative risks of crash injuries associated with distracted driving (DD) and identifies regions of excess risks for policy intervention. Using a sample of aggregated injury and fatal DD crash records for the period 2015-2019 across 1,024 census block groups in Central Ohio (i.e., the Columbus Metropolitan Area) in the United States, we investigate the role of latent effects along with several covariates such as land-use mix, sociodemographic features, and the built environment. To this end, we specifically leverage a full Bayesian hierarchical formulation with conditional autoregressive priors to account for uncertainty (i.e., spatially structured random effects) stemming from adjacent census block groups. Furthermore, we consider uncorrelated random effects from upper-level administrative units within which each block group is nested (i.e., census tracts and counties). Our analysis reveals that (1) addressing spatial correlation improves the model's performance, (2) block-group-level variability substantially explains the residual random fluctuation, and (3) intersection density appears negatively associated with the relative risks of crash injuries, while more diversified land use can increase injury risk. Based on these findings, we present spatial clusters with twice the relative risks compared to other block groups, suggesting that policies be devised to mitigate severe injuries due to DD and therefore enhance public health.

Spatiotemporal Associations between Local Safety Level Index and COVID-19 Infection Risks across Capital Regions in South Korea.

This study aims to provide an improved understanding of the local-level spatiotemporal evolution of COVID-19 spread across capital regions of South Korea during the second and third waves of the pandemic (August 2020~June 2021). To explain transmission, we rely upon the local safety level indices along with latent influences from the spatial alignment of municipalities and their serial (temporal) correlation. Utilizing a flexible hierarchical Bayesian model as an analytic operational framework, we exploit the modified BYM (BYM2) model with the Penalized Complexity (PC) priors to account for latent effects (unobserved heterogeneity). The outcome reveals that a municipality with higher population density is likely to have an elevated infection risk, whereas one with good preparedness for infectious disease tends to have a reduction in risk. Furthermore, we identify that including spatial and temporal correlations into the modeling framework significantly improves the performance and explanatory power, justifying our adoption of latent effects. Based on these findings, we present the dynamic evolution of COVID-19 across the Seoul Capital Area (SCA), which helps us verify unique patterns of disease spread as well as regions of elevated risk for further policy intervention and for supporting informed decision making for responding to infectious diseases.

Local-level spatiotemporal dynamics of COVID-19 transmission in the Greater Seoul Area, Korea: a view from a Bayesian perspective.

OBJECTIVES: The purpose of this study was to enhance the understanding of the local-level spatiotemporal dynamics of COVID-19 transmission in the Greater Seoul Area (GSA), Korea, after its initial outbreak in January 2020. METHODS: Using the weekly aggregates of coronavirus disease 2019 (COVID-19) cases of 77 municipalities in the GSA, we examined the relative risks of COVID-19 infection across local districts over 50 consecutive weeks in 2020. To this end, we employed a spatiotemporal generalized linear mixed model under the hierarchical Bayesian framework. This allowed us to empirically examine the random effects of spatial alignments, temporal autocorrelation, and spatiotemporal interaction, along with fixed effects. Specifically, we utilized the conditional autoregressive and the weakly informative penalized complexity priors for hyperparameters of the random effects. RESULTS: Spatiotemporal interaction dominated the overall variability of random influences, followed by spatial correlation, whereas the temporal correlation appeared to be small. Considering these findings, we present dynamic changes in the spread of COVID-19 across local municipalities in the GSA as well as regions at elevated risk for further policy intervention. CONCLUSIONS: The outcomes of this study can contribute to advancing our understanding of the local-level COVID-19 spread dynamics within densely populated regions in Korea throughout 2020 from a different perspective, and will contribute to the development of regional safety planning against infectious diseases.

Exploring the effects of PM2.5 and temperature on COVID-19 transmission in Seoul, South Korea.

With a recent surge of the new severe acute respiratory syndrome-coronavirus 2 (SARS-Cov-2, COVID-19) in South Korea, this study attempts to investigate the effects of environmental conditions such as air pollutants (PM2.5) and meteorological covariate (Temperature) on COVID-19 transmission in Seoul. To account for unobserved heterogeneity in the daily confirmed cases of COVID-19 across 25 contiguous districts within Seoul, we adopt a full Bayesian hierarchical approach for the generalized linear mixed models. A formal statistical analysis suggests that there exists a positive correlation between a 7-day lagged effect of PM2.5 concentration and the number of confirmed COVID-19 cases, which implies an elevated risk of the infectious disease. Conversely, temperature has shown a negative correlation with the number of COVID-19 cases, leading to reduction in relative risks. In addition, we clarify that the random fluctuation in the relative risks of COVID-19 mainly originates from temporal aspects, whereas no significant evidence of variability in relative risks is observed in terms of spatial alignment of the 25 districts. Nevertheless, this study provides empirical evidence using model-based formal assessments regarding COVID-19 infection risks in 25 districts of Seoul from a different perspective.

Developing Crash Severity Model Handling Class Imbalance and Implementing Ordered Nature: Focusing on Elderly Drivers.

Along with the rapid demographic change, there has been increased attention to the risk of vehicle crashes relative to older drivers. Due to senior involvement and their physical vulnerability, it is crucial to develop models that accurately predict the severity of senior-involved crashes. However, the challenge is how to cope with an imbalanced severity class distribution and the ordered nature of crash severities, as these can complicate the classification of the severity of crashes. In that regard, this study investigates the influence of implementing ordinal nature and handling imbalanced class distribution on the prediction performance. Using vehicle crash data in Ohio, U.S., as an example, the eight machine learning classifiers (logistic and ordered logistic regressions and random forest and ordered random forest with or without handling imbalanced classes) are suggested and then compared with their respective performances. The analysis outcomes show that balancing strategy enhances performance in predicting severe crashes. In contrast, the effects of implementing ordinal nature vary across models. Specifically, the ordered random forest classifier without balancing appears to be superior in terms of overall prediction accuracy, and the ordered random forest with balancing outperforms others in predicting severer crashes.

Clinical and Microbiological Efficacy of Pyrophosphate Containing Toothpaste: A Double-Blinded Placebo-Controlled Randomized Clinical Trial.

(1) Background: Dental calculus works as a niche wherein pathogenic bacteria proliferate in the oral cavity. Previous studies revealed the anticalculus activity of pyrophosphates, however there was no clinical study that evaluated microbiome changes associated with calculus inhibition. Therefore, the aim of this randomized clinical trial was to evaluate the calculus inhibition of pyrophosphate-containing toothpaste and its effect on oral microbiome changes. (2) Methods: Eighty subjects with a calculus index ≥2 on the lingual of the mandibular anterior tooth were randomly allocated to the test group that pyrophosphate-containing toothpaste was given to or the placebo control group. Full mouth debridement and standardized tooth brushing instruction were given before the allocation. Plaque index, gingival index, calculus index, probing depth, and bleeding on probing were measured at the baseline, and at 4, 8 and 12 weeks. Genomic DNA was extracted from the plaque samples collected at the baseline and at 12 weeks, and 16S ribosomal RNA gene amplicon sequencing was applied for microbiome analysis. (3) Results: None of the clinical parameters showed significant differences by visits or groups, except the plaque index of the test group, which reduced significantly between 4 and 12 weeks. A significant difference of microbiome between the baseline and 12 weeks was observed in the test group. Between baseline and 12 weeks, the proportion of Spirochetes decreased in the control group, and the proportions of Proteobacteria, Fusobacteria and Spirochetes in the phylum level and the proportions of Haemophilus, Fusobacterium and Capnocytophaga in the genus level decreased in the test group. In the test group, as plaque index decreased, Streptococcus increased, and Fusobacterium and Haemophilus parainfluenza decreased. (4) Conclusion: The use of pyrophosphate-containing toothpaste effectively inhibited the dysbiosis of the oral microbiome and the proliferation of pathogenic species in periodontal disease. Clinically, plaque formation in the pyrophosphate-containing toothpaste group was effectively decreased, however there was no significant change in calculus deposition.

Biochemical activity of magnesium ions on human osteoblast migration.

Magnesium is well known as a biodegradable biomaterial that has been reported to promote bone remodeling in several studies; however, the underlying biological mechanism remains unclear. In the present study, the role of magnesium ions in the migration of U-2 OS cells, which are osteoblast-like cell lines, was investigated. Magnesium treatment did not significantly alter the global transcriptome of U-2 OS cells, but increased the protein expression level of SNAI2, an epithelial-mesenchymal transition (EMT) marker. In addition, it was confirmed that the junctional site localization of Zona-occludens 1 (ZO-1), a representative tight junction protein, was destroyed by magnesium treatment; furthermore, it was determined that cytoplasmic localization increased, and alkaline phosphatase (ALP) activity increased. The obtained results on the mechanism by which magnesium is involved in osteoblast migration, which is important for fracture healing, will contribute to the understanding of the bone-formation process in patients with osteoporosis and musculoskeletal injury.

Fall Detection for the Elderly Based on 3-Axis Accelerometer and Depth Sensor Fusion with Random Forest Classifier.

In this paper, we propose a new fall detection method that combines 3-axis accelerometer and depth sensors. By combining vision and acceleration-derived features we managed to minimize the false detection rate that is considerably higher when the decision is based on just one type of feature. Also, using machine learning has led to good generalization performance. In addition, we newly created fall database that are more realistic than previous ones. Experiment results show that the proposed method can efficiently detect falls.

Direct modification of spermatogonial stem cells using lentivirus vectors in vivo leads to efficient generation of transgenic rats.

Spermatogonial stem cells (SSCs) transmit genetic information to the next progeny in males. Thus, SSCs are a potential target for germline modifications to generate transgenic animals. In this study, we report a technique for the generation of transgenic rats by in vivo manipulation of SSCs with a high success rate. SSCs in juvenile rats were transduced in vivo with high titers of lentivirus harboring enhanced green fluorescent protein and mated with wild-type females to create founder rats. These founder rats expressed the transgene and passed on the transgene with an overall success rate of 50.0%. Subsequent generations of progeny from the founder rats both expressed and passed on the transgene. Thus, direct modification of SSCs in juvenile rats is an effective means of generating transgenic rats through the male germline. This technology could be adapted to larger animals, in which existing methods for gene modification are inadequate or inapplicable, resulting in the generation of transgenic animals in a variety of species.

The effect of an ex vivo boosted immune cell therapy on canine atopic dermatitis: an open, uncontrolled pilot study.

BACKGROUND: Canine atopic dermatitis (cAD) is associated with an imbalance between multiple T lymphocytes and cytokines. Ex vivo boosted immune cell (EBIC) therapy is the sequential administration of ex vivo cultured and activated lymphocytes to patients to improve immune function. OBJECTIVE: This pilot study aimed to assess the safety of EBIC therapy and demonstrate its efficacy as a novel treatment for cAD. ANIMALS: Ten dogs with AD. METHODS AND MATERIALS: The phenotypes of the immune cells before and after ex vivo culture were analysed by flow cytometry. EBICs (1.0-5.0 × 108 cells/animal) were administered to dogs every two weeks, with a total of six injections. The cAD extent and severity index (CADESI)-03 and pruritus scores were calculated to evaluate the efficacy of EBIC therapy for cAD. For safety assessment, regular blood examination was conducted, and any adverse events recorded. The serum levels of interleukin (IL)-4, IL-10, IL-31 and interferon-gamma (IFN-γ) were evaluated. RESULTS: The cells expanded by an average of 57.52-fold and the proportions of CD8+ cells and IFN-γ-producing cells significantly increased after ex vivo culture. Sequential EBIC therapy improved CADESI-03, and pruritus scores significantly. After stopping treatment the improvement rates increased for the CADESI score and were maintained for the pruritus score. There were no significant changes in cytokine levels. No significant adverse events were observed. CONCLUSIONS AND CLINICAL SIGNIFICANCE: EBIC therapy is a safe and efficient treatment for cAD. This therapy could correct the immunological imbalance in dogs with AD by infusing activated T lymphocytes.

Intracellular delivery of a native functional protein using cell-penetrating peptide functionalized cubic MSNs with ultra-large mesopores.

The intracellular delivery of functional proteins in their native forms into cells is a theme of paramount importance in research owing to their diverse biological applications. Porous inorganic nanoparticles are emerging as efficient nanocarriers for the delivery of small molecules and drugs. To expand the range of cargos from small molecules to large native functional proteins, cubic mesoporous silica nanoparticles (cMSNs) with a Pm3n pore symmetry with an average particle dimension of 180 nm were prepared. The as-prepared cMSNs were subsequently etched with a methanolic solution of Ca(NO3)2 to expand their mesopores and simultaneously remove the template. The original mesopores with a pore dimension of 2.41 nm partially collapsed and combined into ultra-large mesopores with an average pore diameter of 13.89 nm without perturbing the original cubic symmetry of the remaining mesopores. The maximum pore dimension was around 60 nm. Various techniques including powder X-ray diffraction, transmission electron microscopy, and electron tomography identified the unique three-dimensional structure of pore-enlarged cMSNs (Ca-cMSNs). Moreover, their surfaces were functionalized with a guanidinium-rich cell-penetrating R8-azido-peptide (p-azidophenylalanine-GSGSGGRRRRRRRR) through the click reaction. The intracellular delivery of functional proteins such as Cre recombinase into human TE671(LoxP-LacZ) cells was realized by using R8-Ca-cMSNs as native protein delivery synthetic nanocarriers. The delivery efficiency when using the R8-Ca-cMSNs significantly enhanced compared to that when using Ca-cMSNs without surface-bound cell-penetrating peptides.

Plasma-Functionalized Solution: A Potent Antimicrobial Agent for Biomedical Applications from Antibacterial Therapeutics to Biomaterial Surface Engineering.

Deadly diseases caused by pathogenic bacteria and viruses have increasingly victimized humans; thus, the importance of disinfection has increased in medical settings as well as in food and agricultural industries. Plasma contains multiple bactericidal agents, including reactive species, charged particles, and photons, which can have synergistic effects. In particular, the chemicals formed in aqueous solution during plasma exposure have the potential for high antibacterial activity against various bacterial infections. Here, we report the antibiotic potency of plasma-treated water (PTW). To illustrate the applicability of PTW for disinfecting biological substances, an Escherichia coli biofilm was used. We sought to identify the chemical species in PTW and investigate their separate effects on biofilm removal. Dielectric barrier discharge in ambient air was used to prepare the PTW and treat the biofilm directly. Hydrogen peroxide, ozone, and nitrites were identified as the long-lived reactive species in the PTW, whereas hydroxyl radicals and superoxide anions were identified as the short-lived reactive species in the PTW; all these species showed an ability to disinfect in biofilm removal.

Magnesium ions enhance infiltration of osteoblasts in scaffolds via increasing cell motility.

Magnesium (Mg) ions are the most abundant intracellular divalent cations and play a pivotal role in numerous cellular processes. Biodegradable Mg-containing materials, including scaffolds, are promising candidates for orthopedic applications. Here, we investigated the effect of Mg ions on the cellular properties of osteoblasts. Cytotoxicity tests on osteoblasts confirmed that no cytotoxic effects were found up to a supplementing Mg ion concentration of 10 mM. Mg ions at a concentration of 5 mM increased the migration and invasiveness of osteoblasts. To investigate the stimulatory effect of Mg ions on cell motility in scaffolds, we fabricated 10 wt% Mg ion-containing polycaprolactone (PCL) scaffolds, using the wire-network molding (WNM) technique. Mg ion-containing scaffolds persistently released Mg ions at a concentration of 5 mM in the media after pre-incubation. Furthermore, increased cell motility was confirmed in Mg ion-containing scaffolds by quantification of genomic DNA and protein content. Our results provide an important basis for the function of Mg ions and their effect on cell motility, and propose a novel role for Mg ions in scaffold applications.

Vertebrae localization in CT using both local and global symmetry features.

Automatic vertebrae segmentation and localization in CT images are essential in many medical treatments such as disease diagnosis and surgical planning. However, vertebra is one of the most complex organs to locate precisely due to its complex shape, deformation and occlusion by other organs. In this paper, we propose to incorporate local appearance features with global translational symmetry and local reflection symmetry features. Symmetrical structure of each vertebra provides strong cue for accurate localization. In order to efficiently investigate 3-dimensional reflection symmetry in CT images, we propose a Sphere Surface Expansion method and iterative optimization framework. Quantitative and qualitative evaluations show that the proposed method outperforms existing localization method.

Effects of minimal exposures to atmospheric pressure plasma on the activity of Salmonella Typhimurium: Deactivation of bacterial motility and suppression of host-cell invasion.

Atmospheric pressure plasma (APP) has been shown effective in sterilization by reducing the number of viable microbes during surface cleaning, food processing, or human tissue treatment. For safe conduct, the majority of previous research focused on complete abolition of microbes, which may require severe treatments. Our aim is to investigate the minimal treatment conditions necessary for effective inactivation of bacteria in such a manner that the APP treated bacteria would not be able to harm the host cells. For this, we ought to identify the objective criteria to make the bacteria dysfunctional. We choose the motile properties and the host-cell invasion capability as two measures to quantify the pathogenic state of bacteria. In this paper, we investigated how the APP treatment in a minimal dosage affects the activity of Salmonella Typhimurium. At 100 W and 15 kHz for 20 s, the APP treatment effectively suppressed active "run and tumble" type motility and induced formation of abnormally long structures. With 20 s exposure, the bacterial cells failed to cause pyroptosis in the host cells with >90% survival after 12 h of co-incubation. Our results suggest novel measures to evaluate the functional pathogenic state for identifying safe APP treatment conditions.

Identification and characterization of the RNA-binding protein Rbfox3 in zebrafish embryo.

Rbfox3, an RNA-binding fox protein, binds to the antibody to pan-neuronal marker, neuronal nuclei (NeuN). Rbfox3 is expressed in neural tissues across a wide range of species including mammals, birds, and amphibians. However, the molecular identity of Rbfox3 in the zebrafish is largely unknown. In this study, we cloned two zebrafish Rbfox3 genes, Rbfox3a and Rbfox3b. We also cloned the Rbfox3-d31 isoform, which excludes a 93-nucleotide alternative exon within the RNA-recognition motif in both, Rbfox3a and Rbfox3b. Multiple protein sequence alignment revealed that the amino acid sequence for residues 1-20 of the zebrafish Rbfox3, which is the epitope region of NeuN antibody, was different from that of other species. Therefore, NeuN antibody lost its function as a neuronal marker antibody in zebrafish. Reverse transcriptase-polymerase chain reaction showed that both Rbfox3-d31 transcripts were abundant in the early blastula stage, after which they dramatically reduced, suggesting that these isoforms exist mainly as maternal transcripts. In contrast, full-length Rbfox3 transcripts were detected from the 24 h post-fertilization embryo, expression was also maintained at a constant level. Furthermore, full-length Rbfox3-expressing cells were located within the central nervous system during later stages of the zebrafish embryo. Our study provides insight into the molecular structure of zebrafish Rbfox3 as a step towards genetic association studies investigating the developmental role of Rbfox3.

Rapid drug susceptibility test of Mycobacterium tuberculosis using microscopic time-lapse imaging in an agarose matrix.

Tuberculosis (TB) is a major global health problem, and multi-drug-resistant TB (MDR-TB) and extensively drug-resistant TB (XDR-TB) are spreading throughout the world. However, conventional drug susceptibility test (DST) methods, which rely on the detection of the colony formation on a solid medium, require 1-2 months to the result. A rapid and accurate DST is necessary to identify patients with drug-resistant TB and treat them with appropriate drugs. Here, we used microscopic imaging of Mycobacterium tuberculosis (MTB) immobilized in an agarose matrix for a rapid DST. The agarose matrix, which was molded in a microfluidic chip, was inoculated with MTB, and TB drugs in liquid culture medium diffused throughout the agarose to reach the MTB immobilized in the agarose matrix. After the responses of MTB to drugs were tracked with an automated microscopic system, an image-processing program automatically determined the susceptibility and resistance of MTB to specific doses of TB drugs. The automatic DST system was able to assess the drug susceptibility of various drug-resistant clinical TB strains within 9 days with an accuracy comparable to that of conventional method. Our rapid DST method based on microscopic time-lapse imaging greatly reduces the time required for a DST and can be used to rapidly and accurately treat TB patients.