Drought-induced susceptibility for Cenangium ferruginosum leads to progression of Cenangium-dieback disease in Pinus koraiensis

Recently, the occurrence of "Cenangium-dieback" has been frequent and devastating. Cenangium-dieback is caused by an endophytic fungus Cenangium ferruginosum in stressed pine trees. Progression of the disease in terms of molecular interaction between host and pathogen is not well studied and there is a need to develop preventive strategies. Thus, we simulated disease conditions and studied the associated transcriptomics, metabolomics, and hormonal changes. Pinus koraiensis seedlings inoculated with C. ferruginosum were analyzed both under drought and well-watered conditions. Transcriptomic analysis suggested decreased expression of defense-related genes in C. ferruginosum-infected seedlings experiencing water-deficit. Further, metabolomic analysis indicated a decrease in the key antimicrobial terpenoids, flavonoids, and phenolic acids. Hormonal analysis revealed a drought-induced accumulation of abscisic acid and a corresponding decline in the defense-associated jasmonic acid levels. Pathogen-associated changes were also studied by treating C. ferruginosum with metabolic extracts from pine seedlings (with and without drought) and polyethylene glycol to simulate the effects of direct drought. From RNA sequencing and metabolomic analysis it was determined that drought did not directly induce pathogenicity of C. ferruginosum. Collectively, we propose that drought weakens pine immunity, which facilitates increased C. ferruginosum growth and results in conversion of the endophyte into the phytopathogen causing dieback

Seismic Vulnerability Assessment and Mapping of Gyeongju, South Korea Using Frequency Ratio, Decision Tree, and Random Forest

The main purpose of this study was to compare the prediction accuracies of various seismic vulnerability assessment and mapping methods. We applied the frequency ratio (FR), decision tree (DT), and random forest (RF) methods to seismic data for Gyeongju, South Korea. A magnitude 5.8 earthquake occurred in Gyeongju on 12 September 2016. Buildings damaged during the earthquake were used as dependent variables, and 18 sub-indicators related to seismic vulnerability were used as independent variables. Seismic data were used to construct a model for each method, and the models’ results and prediction accuracies were validated using receiver operating characteristic (ROC) curves. The success rates of the FR, DT, and RF models were 0.661, 0.899, and 1.000, and their prediction rates were 0.655, 0.851, and 0.949, respectively. The importance of each indicator was determined, and the peak ground acceleration (PGA) and distance to epicenter were found to have the greatest impact on seismic vulnerability in the DT and RF models. The constructed models were applied to all buildings in Gyeongju to derive prediction values, which were then normalized to between 0 and 1, and then divided into five classes at equal intervals to create seismic vulnerability maps. An analysis of the class distribution of building damage in each of the 23 administrative districts showed that district 15 (Wolseong) was the most vulnerable area and districts 2 (Gangdong), 18 (Yangbuk), and 23 (Yangnam) were the safest areas

Electrocardiogram Risk Score and Prevalence of Subclinical Atherosclerosis: A Cross-Sectional Study

Integrated abnormal electrocardiogram (ECG) parameters predict the risk of cardiovascular disease (CVD); however, its relationship with subclinical CVD is unknown. We aimed to evaluate the association between the integrated ECG risk score and the prevalence of coronary artery calcium (CAC). A cross-sectional study comprised 134,802 participants with no known CVD who underwent ECG and CAC computed tomography. The ECG risk score was the sum of five ECG abnormalities: heart rate of >80 beats, QRS of >110 ms, left ventricular hypertrophy, T-wave inversion, and prolonged QTc. A multinomial regression model was used to estimate the prevalence ratios (PRs) and their 95% confidence intervals (CIs) for prevalent CAC. The prevalence of CAC progressively increased as the ECG risk score increased. After adjustment for conventional CVD risk factors and other confounders, the multivariable-adjusted PRs (95% CI) for a CAC of 1–100 in the 1, 2, and ≥3 ECG risk score groups were 1.06 (1.02–1.10), 1.12 (1.03–1.22), and 1.19 (1.00–1.42), respectively, while the corresponding PRs for a CAC of >100 were 1.03 (0.95–1.12), 1.44 (1.25–1.66), and 1.75 (1.33–2.29), respectively. Integrative ECG scoring may help identify individuals requiring lipid-lowering medications, even in young and asymptomatic populations

Light Trapping Color Filters for Semitransparent Solar Cells

Semitransparent colorful solar cells equipped with photonically tailored Fabry–Perot (FP) cavities as the back electrode have garnered attention for their prospective application in building integrated photovoltaics (BIPVs). These cells transmit colored light at the FP resonance while reflecting nonresonant light back into the cell, a significant portion of which is also lost into air. Herein, we present a method to enhance light trapping in colorful semitransparent solar cells using closely packed Ag-coated silica particles on a thin Ag layer. This structure simultaneously acts as an effective FP cavity and color filter, scattering off-resonant light to high angles while transmitting the targeted colors. We show that the high-angle scattering originates from antiparallel out-of-plane electric dipoles unique to our design, which promote light trapping. When applied onto a dye-sensitized solar cell (DSSC), our effective Fabry–Perot (EFP) color filters provided a maximum of ∼7% more short-circuit current density (Jsc) than those from DSSCs equipped with planar filters. Furthermore, compared to bare DSSCs and DSSCs including conventional scattering layers, DSSCs equipped with EFP filters showed a maximum of 14.6 and 5.9% higher cell efficiencies (η), respectively. The ability to filter color and improve light trapping suggests alternative pathways for engineering colorful semitransparent solar cells

Land-Cover-Change Detection with Aerial Orthoimagery Using SegNet-Based Semantic Segmentation in Namyangju City, South Korea

In this study, we classified land cover using SegNet, a deep-learning model, and we assessed its classification accuracy in comparison with the support-vector-machine (SVM) and random-forest (RF) machine-learning models. The land-cover classification was based on aerial orthoimagery with a spatial resolution of 1 m for the input dataset, and Level-3 land-use and land-cover (LULC) maps with a spatial resolution of 1 m as the reference dataset. The study areas were the Namhan and Bukhan River Basins, where significant urbanization occurred between 2010 and 2012. The hyperparameters were selected by comparing the validation accuracy of the models based on the parameter changes, and they were then used to classify four LU types (urban, crops, forests, and water). The results indicated that SegNet had the highest accuracy (91.54%), followed by the RF (52.96%) and SVM (50.27%) algorithms. Both machine-learning models showed lower accuracy than SegNet in classifying all land-cover types, except forests, with an overall-accuracy (OA) improvement of approximately 40% for SegNet. Next, we applied SegNet to detect land-cover changes according to aerial orthoimagery of Namyangju city, obtained in 2010 and 2012; the resulting OA values were 86.42% and 78.09%, respectively. The reference dataset showed that urbanization increased significantly between 2010 and 2012, whereas the area of land used for forests and agriculture decreased. Similar changes in the land-cover types in the reference dataset suggest that urbanization is in progress. Together, these results indicate that aerial orthoimagery and the SegNet model can be used to efficiently detect land-cover changes, such as urbanization, and can be applied for LULC monitoring to promote sustainable land management

Effect of SMAD7 gene overexpression on TGF-β1-induced profibrotic responses in fibroblasts derived from Peyronie′s plaque

Transforming growth factor-β1 (TGF-β1) has been identified as one of the most important fibrogenic cytokines associated with Peyronie's disease (PD). The mothers against decapentaplegic homolog 7 (SMAD7) is an inhibitory Smad protein that blocks TGF-β signaling pathway. The aim of this study was to examine the anti-fibrotic effect of the SMAD7 gene in primary fibroblasts derived from human PD plaques. PD fibroblasts were pretreated with the SMAD7 gene and then stimulated with TGF-β1. Treated fibroblasts were used for Western blotting, fluorescent immunocytochemistry, hydroxyproline determination, and terminal deoxynucleotidyl transferase-mediated deoxyuridine triphosphate nick-end labeling assays. Overexpression of the SMAD7 gene inhibited TGF-β1-induced phosphorylation and nuclear translocation of SMAD2 and SMAD3, transdifferentiation of fibroblasts into myofibroblasts, and quashed TGF-β1-induced production of extracellular matrix protein and hydroxyproline. Overexpression of the SMAD7 gene decreased the expression of cyclin D1 (a positive cell cycle regulator) and induced the expression of poly (ADP-ribose) polymerase 1, which is known to terminate Smad-mediated transcription, in PD fibroblasts. These findings suggest that the blocking of the TGF-β pathway by use of SMAD7 may be a promising therapeutic strategy for the treatment of PD

Silica-nanoparticle reinforced lubricant-infused copper substrates with enhanced lubricant retention for maintenance-free heat exchangers

Copper substrates are widely used in heat exchangers due to their low cost and high thermal conductivity. While copper substrates have been modified to exhibit non-wetting property via lubricant infusion to enhance condensation heat transfer efficiency, these engineered surfaces often lack chemical robustness and lubricant retention, limiting their long-term use without maintenance. In this work, we present a new strategy in which omniphobic and chemically inert fluorocarbon oil is infused into a nanostructured copper substrate reinforced with silica nanoparticles (SiNP) to achieve enhanced durability and acid-resistive properties. We demonstrate that the assembly of SiNP layer prior to lubricant infusion serves as a physical barrier and provides additional anchoring points for the lubricant to retain via capillary force. Moreover, we show that SiNP-reinforced liquid-infused surface (LIS) exhibits excellent non-wetting and self-cleaning properties, leading to enhanced stability against acid exposure as well as dust, oil, and microbial contamination. Based on the excellent long-term stability in heat transfer performance even under harsh environmental challenges, we envision that the SiNP-reinforced LIS presented in this work will provide new insight in the design of robust and maintenance-free lubricant-infused surfaces for energy and environmental applications.11Nsci

Surface-Embedding of Mo Microparticles for Robust and Conductive Biodegradable Fiber Electrodes: Toward 1D Flexible Transient Electronics

Fiber-based implantable electronics are one of promising candidates for in vivo biomedical applications thanks to their unique structural advantages. However, development of fiber-based implantable electronic devices with biodegradable capability remains a challenge due to the lack of biodegradable fiber electrodes with high electrical and mechanical properties. Here, a biocompatible and biodegradable fiber electrode which simultaneously exhibits high electrical conductivity and mechanical robustness is presented. The fiber electrode is fabricated through a facile approach that incorporates a large amount of Mo microparticles into outermost volume of a biodegradable polycaprolactone (PCL) fiber scaffold in a concentrated manner. The biodegradable fiber electrode simultaneously exhibits a remarkable electrical performance (≈43.5 Ω cm−1), mechanical robustness, bending stability, and durability for more than 4000 bending cycles based on the Mo/PCL conductive layer and intact PCL core in the fiber electrode. The electrical behavior of the biodegradable fiber electrode under the bending deformation is analyzed by an analytical prediction and a numerical simulation. In addition, the biocompatible properties and degradation behavior of the fiber electrode are systematically investigated. The potential of biodegradable fiber electrode is demonstrated in various applications such as an interconnect, a suturable temperature sensor, and an in vivo electrical stimulator. © 2023 The Authors. Advanced Science published by Wiley-VCH GmbH.TRU