Particulate matter, including airborne pathogens, is of particular concern because it can cause the spread of diseases through aerosol transmission. In this study, a new concept is proposed: on-demand antiviral electrostatic precipitators (ESPs) with electrothermal-based antiviral surfaces. We applied electrothermal-based antiviral surfaces to air-purifying applications and demonstrated that the proposed method is effective with regard to collecting airborne virus particles on collection plates in a two-stage ESP. With alternating current power, MS2 bacteriophage and H1N1 viruses were completely deactivated after exposure to 50 °C for 30 min. This remarkable antiviral performance via electrothermal effects indicates that on-demand platforms for self-antiviral surfaces can perform sterilization immediately without generating secondary pollutants, thus effectively preventing the spread of infectious microorganisms in public places. We believe that the results of this study can provide useful guidelines for the design and realization of practical and wearable devices for antiviral air-purifying applications.

Previous studies have mainly focused more on how diabetes affects the valve than the myocardium in aortic stenosis (AS). In the pressure-overloaded heart, myocardial fibrosis is an important driver of the progression from compensated hypertrophy to heart failure. Using comprehensive noninvasive imaging and plasma proteomics, we investigated whether and how diabetes aggravates the remodeling of the myocardium and its relation with prognosis in AS patients.

Invasive nostocalean cyanobacteria (INC) were first reported in tropical regions and are now globally spreading rapidly due to climate change, appearing in temperate regions. INC require continuous monitoring for water resource management because of their high toxin production potential. However, it is difficult to analyze INC under a microscope because of their morphological similarity to nostocalean cyanobacteria such as the genus Aphanizomenon. This study calculates the gene copy number per cell for each target gene through quantitative gene analysis on the basis of genus-specific primers of genera Cylindrospermopsis, Sphaerospermopsis, and Cuspidothrix, and the toxin primers of anatoxin-a, saxitoxin, and cylindrospermopsin. In addition, quantitative gene analysis was performed at eight sites in the Nakdong River to assess the appearance of INC and their toxin production potential. Genera Cylindrospermopsis and Sphaerospermopsis did not exceed 100 cells mL-1 at the maximum, with a low likelihood of related toxin occurrence. The genus Cuspidothrix showed the highest cell density (1759 cells mL-1) among the INC. Nakdong River has potential for the occurrence of anatoxin-a through biosynthesis by genus Cuspidothrix because the appearance of this genus coincided with that of the anatoxin-a synthesis gene (anaF) and the detection of the toxin by ELISA.

The diagnosis of myocarditis traditionally relies on invasive endomyocardial biopsy but none of the imaging studies so far are specific for infiltration of the inflammatory cells itself. We synthesized 68Ga-2-(p-isothiocyanatobenzyl)-1,4,7-triazacyclononane-1,4,7-triacetic acid (NOTA) mannosylated human serum albumin (MSA) by conjugating human serum albumin with mannose, followed by conjugation with NOTA and labeling it with 68Ga. The efficacy of 68Ga-NOTA-MSA positron emission tomography (PET) for imaging myocardial inflammation was tested in a rat myocarditis model. A significant number of mannose receptor-positive inflammatory cells infiltrated the myocardium in both human and rat myocarditis tissue. 68Ga-NOTA-MSA uptake was upregulated in organs of macrophage accumulation, such as liver, spleen, bone marrow and myocardium (0.32 (0.31~0.33) for normal versus 1.02 (0.86~1.06) for myocarditis (median (range), SUV); n=4~6 per group, p-value=0.01). 68Ga-NOTA-MSA uptake in the left ventricle was upregulated in myocarditis compared with normal rats (2.29 (1.42~3.40) for normal versus 4.18 (3.43~6.15) for myocarditis (median (range), average standard uptake value ratio against paraspinal muscle); n=6 per group, p-value<0.01), which was downregulated in rats with cyclosporine-A treated myocarditis (3.69 (2.59~3.86) for myocarditis versus 2.28 (1.76~2.60) for cyclosporine-A treated myocarditis; n=6 per group, p-value<0.01). The specificity of the tracer was verified by administration of excess non-labeled MSA. 68Ga-NOTA-MSA uptake was significantly enhanced earlier in the evolution of myocarditis before any signs of inflammation could be seen on echocardiography. These results demonstrate the potential utility of visualizing infiltration of mannose receptor-positive macrophages with 68Ga-NOTA-MSA PET in the early diagnosis of as well as in the monitoring of treatment response of myocarditis.

The zinc finger protein CTCF has been invoked in establishing boundaries between genes, thereby controlling spatial and temporal enhancer activities. However, there is limited genetic evidence to support the concept that these boundaries restrict the search space of enhancers. We have addressed this question in the casein locus containing five mammary and two non-mammary genes under the control of at least seven putative enhancers. We have identified two CTCF binding sites flanking the locus and two associated with a super-enhancer. Individual deletion of these sites from the mouse genome did not alter expression of any of the genes. However, deletion of the border CTCF site separating the Csn1s1 mammary enhancer from neighboring genes resulted in the activation of Sult1d1 at a distance of more than 95 kb but not the more proximal and silent Sult1e1 gene. Loss of this CTCF site led to de novo interactions between the Sult1d1 promoter and several enhancers in the casein locus. Our study demonstrates that only one out of the four CTCF sites in the casein locus had a measurable in vivo activity. Studies on additional loci are needed to determine the biological role of CTCF sites associated with enhancers.

Y- and Si-based oxide nanopowders were synthesized by a hydrothermal reaction of Y or Si powders with NaOH or LiOH aqueous solution. Nanoparticles with different morphology such as elongated nanospheres, flower-like nanoparticles and nanowires were produced by a control of processing parameters, in particular, the starting composition of solution. The preliminary result of electrochemical examination showed that the hydrothermally processed nanowires exhibit high initial capacities of Li-ion storage: 653 mAh/g for Y(2)O(3) nanowires as anode materials and 186 mAh/g for Li(2)Si(2)O(5) nanowires as cathode materials in a Li secondary cell. Compared to the powder with elongated sphere or flower-like shapes, the nanowires showed a higher Li-ion capacity and a better cycle property.

The geographical range of invasive cyanobacteria with high toxigenic potential is widening because of eutrophication and global warming, thus, monitoring their appearance is necessary for safe water quality control. Most invasive cyanobacteria are nostocalean species, and their accurate identification by classical morphological methods may be problematic. In this study, we developed polymerase chain reaction (PCR) primers to selectively identify five invasive cyanobacterial genera, namely, Chrysosporum, Cuspidothrix, Cylindrospermopsis, Raphidiopsis, and Sphaerospermopsis, using genetic markers such as rbcLX, rpoB, rpoC1, and cpcBA, and determined the amplification conditions for each pair of primers. The primer performances were verified on single or mixed nostocalean cyanobacterial isolates. The five primers allowed selective identification of all the target genera. In field samples collected during summer, when cyanobacteria flourished in the Nakdong River, the respective PCR product was observed in all samples where the target genus was detected by microscopic analysis. Besides, weak bands corresponding to Sphaerospermopsis and Raphidiopsis were observed in some samples in which these genera were not detected by microscopy, suggesting that the cell densities were below the detection limit of the microscopic method used. Thus, the genus-specific primers developed in this study enable molecular monitoring to supplement the current microscopy-based monitoring.

Coronary computed tomography angiography (CCTA) is widely used as a first-line noninvasive modality that frequently exhibits no or nonobstructive coronary artery disease (CAD) in clinical practice, along with abnormal left ventricular (LV) geometry on echocardiography. However, the combined prognostic value of these findings has not been well elucidated. Therefore, we aimed to evaluate the prognostic implications of abnormal LV geometry in individuals with no or nonobstructive CAD.

Although CRISPR/Cas9 genome editing has provided numerous opportunities to interrogate the functional significance of any given genomic site, there is a paucity of data on the extent of molecular scars inflicted on the mouse genome. Here we interrogate the molecular consequences of CRISPR/Cas9-mediated deletions at 17 sites in four loci of the mouse genome. We sequence targeted sites in 632 founder mice and analyse 54 established lines. While the median deletion size using single sgRNAs is 9 bp, we also obtain large deletions of up to 600 bp. Furthermore, we show unreported asymmetric deletions and large insertions of middle repetitive sequences. Simultaneous targeting of distant loci results in the removal of the intervening sequences. Reliable deletion of juxtaposed sites is only achieved through two-step targeting. Our findings also demonstrate that an extended analysis of F1 genotypes is required to obtain conclusive information on the exact molecular consequences of targeting events.

Temporal trends of the prevalence and incidence of hypertrophic cardiomyopathy (HCM) have not been well established in Asian populations. Using the Korean National Health Insurance Services database, we identified patients with a confirmed diagnosis of HCM between 2010 and 2016. The annual prevalence and incidence of HCM, and their clinical characteristics were investigated. The prevalence of HCM has increased from 0.016% (n = 6313) in 2010 to 0.031% (n = 13,035) in 2016. During a 7-year period, 13,229 patients were newly diagnosed with HCM. The incidence rate increased from 4.15 (per 100,000 person-years) in 2010 to 5.6 in 2016. The prevalence and incidence of HCM increased with age and peaked during the 70s, with male predominance in all age groups. Chest pain is the most frequent clinical presentation followed by shortness of breath and syncope. Hypertension and dyslipidemia were the two most common comorbidities. Heart failure and atrial fibrillation was diagnosed in about 1/3 and 1/4 of patients with HCM, respectively. The prevalence and incidence of HCM gradually increased from 2010 to 2016, possibly due to heightened recognition of the disease. Given the progressively high incidence of HCM with age and high prevalence of coexisting modifiable risk factors, continued efforts are required to increase awareness regarding HCM-related symptoms and potential complications.

Background Rapid coronary plaque progression (RPP) is associated with incident cardiovascular events. To date, no method exists for the identification of individuals at risk of RPP at a single point in time. This study integrated coronary computed tomography angiography-determined qualitative and quantitative plaque features within a machine learning (ML) framework to determine its performance for predicting RPP. Methods and Results Qualitative and quantitative coronary computed tomography angiography plaque characterization was performed in 1083 patients who underwent serial coronary computed tomography angiography from the PARADIGM (Progression of Atherosclerotic Plaque Determined by Computed Tomographic Angiography Imaging) registry. RPP was defined as an annual progression of percentage atheroma volume ≥1.0%. We employed the following ML models: model 1, clinical variables; model 2, model 1 plus qualitative plaque features; model 3, model 2 plus quantitative plaque features. ML models were compared with the atherosclerotic cardiovascular disease risk score, Duke coronary artery disease score, and a logistic regression statistical model. 224 patients (21%) were identified as RPP. Feature selection in ML identifies that quantitative computed tomography variables were higher-ranking features, followed by qualitative computed tomography variables and clinical/laboratory variables. ML model 3 exhibited the highest discriminatory performance to identify individuals who would experience RPP when compared with atherosclerotic cardiovascular disease risk score, the other ML models, and the statistical model (area under the receiver operating characteristic curve in ML model 3, 0.83 [95% CI 0.78-0.89], versus atherosclerotic cardiovascular disease risk score, 0.60 [0.52-0.67]; Duke coronary artery disease score, 0.74 [0.68-0.79]; ML model 1, 0.62 [0.55-0.69]; ML model 2, 0.73 [0.67-0.80]; all P<0.001; statistical model, 0.81 [0.75-0.87], P=0.128). Conclusions Based on a ML framework, quantitative atherosclerosis characterization has been shown to be the most important feature when compared with clinical, laboratory, and qualitative measures in identifying patients at risk of RPP.

Cell-free DNA (cfDNA) sequencing has demonstrated great potential for early cancer detection. However, most large-scale studies have focused only on either targeted methylation sites or whole-genome sequencing, limiting comprehensive analysis that integrates both epigenetic and genetic signatures. In this study, we present a platform that enables simultaneous analysis of whole-genome methylation, copy number, and fragmentomic patterns of cfDNA in a single assay. Using a total of 950 plasma (361 healthy and 589 cancer) and 240 tissue samples, we demonstrate that a multifeature cancer signature ensemble (CSE) classifier integrating all features outperforms single-feature classifiers. At 95.2% specificity, the cancer detection sensitivity with methylation, copy number, and fragmentomic models was 77.2%, 61.4%, and 60.5%, respectively, but sensitivity was significantly increased to 88.9% with the CSE classifier (p value < 0.0001). For tissue of origin, the CSE classifier enhanced the accuracy beyond the methylation classifier, from 74.3% to 76.4%. Overall, this work proves the utility of a signature ensemble integrating epigenetic and genetic information for accurate cancer detection.