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Abstract Background Androgenetic alopecia (AGA) is a common form of hair loss. Androgens, such as testosterone and dihydrotestosterone, are the main causes of AGA. Extracellular vesicles (EVs) derived from mesenchymal stem cells (MSCs) can reduce AGA. However, preparing therapeutic doses of MSCs for clinical use is challenging. Induced pluripotent stem cell-derived MSCs (iMSCs) are homogenous and easily expandable, enabling scalable production of EVs. Hyaluronic acid (HA) can exert various functions including free radical scavenging, immune regulation, and cell migration. Herein, we examined whether hyaluronic acid (HA) stimulation of iMSCs could produce EVs with enhanced therapeutic outcomes for AGA. Methods EVs were collected from iMSCs primed with HA (HA–iMSC–EVs) or without HA (iMSC–EVs). The characteristics of EVs were examined using dynamic light scattering, cryo-transmission electron microscopy, immunoblotting, flow cytometry, and proteomic analysis. In vitro, we compared the potential of EVs in stimulating the survival of hair follicle dermal papilla cells undergoing testosterone-mediated AGA. Additionally, the expression of androgen receptor (AR) and relevant growth factors as well as key proteins of Wnt/β-catenin signaling pathway (β-catenin and phosphorylated GSK3β) was analyzed. Subsequently, AGA was induced in male C57/BL6 mice by testosterone administration, followed by repeated injections of iMSC–EVs, HA–iMSC–EVs, finasteride, or vehicle. Several parameters including hair growth, anagen phase ratio, reactivation of Wnt/β-catenin pathway, and AR expression was examined using qPCR, immunoblotting, and immunofluorescence analysis. Results Both types of EVs showed typical characteristics for EVs, such as size distribution, markers, and surface protein expression. In hair follicle dermal papilla cells, the mRNA levels of AR, TGF-β, and IL-6 increased by testosterone was blocked by HA–iMSC–EVs, which also contributed to the augmented expression of trophic genes related to hair regrowth. However, no notable changes were observed in the iMSC–EVs. Re-activation of Wnt/β-catenin was observed in HA–iMSC–EVs but not in iMSC–EVs, as shown by β-catenin stabilization and an increase in phosphorylated GSK3β. Restoration of hair growth was more significant in HA–iMSC–EVs than in iMSC–EVs, and was comparable to that in mice treated with finasteride. Consistently, the decreased anagen ratio induced by testosterone was reversed by HA–iMSC–EVs, but not by iMSC–EVs. An increased expression of hair follicular β-catenin protein, as well as the reduction of AR was observed in the skin tissue of AGA mice receiving HA–iMSC–EVs, but not in those treated with iMSC–EVs. Conclusions Our results suggest that HA–iMSC–EVs have potential to improve AGA by regulating growth factors/cytokines and stimulating AR-related Wnt/β-catenin signaling.

Abstract Background Several genetic studies have been undertaken to elucidate the intricate interplay between genetics and drug responses in bipolar disorder (BD). However, there has been notably limited research on biomarkers specifically linked to valproate, with only a few studies investigating integrated proteomic and genomic factors in response to valproate treatment. Therefore, this study aimed to identify biological markers for the therapeutic response to valproate treatment in BD. Patients with BD in remission were assessed only at baseline, whereas those experiencing acute mood episodes were evaluated at three points (baseline, 8 ± 2 weeks, and 6 ± 1 months). The response to valproate treatment was measured using the Alda scale, with individuals scoring an Alda A score ≥ 5 categorized into the acute-valproate responder (acute-VPAR) group. We analyzed 158 peptides (92 proteins) from peripheral blood samples using multiple reaction monitoring mass spectrometry, and proteomic result-guided candidate gene association analyses, with 1,627 single nucleotide variants (SNVs), were performed using the Korean chip. Results The markers of 37 peptides (27 protein) showed temporal upregulation, indicating possible association with response to valproate treatment. A total of 58 SNVs in 22 genes and 37 SNVs in 16 genes showed nominally significant associations with the Alda A continuous score and the acute-VPAR group, respectively. No SNVs reached the genome-wide significance threshold; however, three SNVs (rs115788299, rs11563197, and rs117669164) in the secreted phosphoprotein 2 gene reached a gene-based false discovery rate-corrected significance threshold with response to valproate treatment. Significant markers were associated with the pathophysiological processes of bipolar disorders, including the immune response, acute phase reaction, and coagulation cascade. These results suggest that valproate effectively suppresses mechanisms associated with disease progression. Conclusions The markers identified in this study could be valuable indicators of the underlying mechanisms associated with response to valproate treatment.

Abstract Background Despite advancements in chronic myeloid leukemia (CML) therapy with tyrosine kinase inhibitors (TKIs), resistance and intolerance remain significant challenges. Leukemia stem cells (LSCs) and TKI-resistant cells rely on altered mitochondrial metabolism and oxidative phosphorylation. Targeting rewired energy metabolism and inducing non-apoptotic cell death, along with the release of damage-associated molecular patterns (DAMPs), can enhance therapeutic strategies and immunogenic therapies against CML and prevent the emergence of TKI-resistant cells and LSC persistence. Methods Transcriptomic analysis was conducted using datasets of CML patients' stem cells and healthy cells. DNA damage was evaluated by fluorescent microscopy and flow cytometry. Cell death was assessed by trypan blue exclusion test, fluorescent microscopy, flow cytometry, colony formation assay, and in vivo Zebrafish xenografts. Energy metabolism was determined by measuring NAD+ and NADH levels, ATP production rate by Seahorse analyzer, and intracellular ATP content. Mitochondrial fitness was estimated by measurements of mitochondrial membrane potential, ROS, and calcium accumulation by flow cytometry, and morphology was visualized by TEM. Bioinformatic analysis, real-time qPCR, western blotting, chemical reaction prediction, and molecular docking were utilized to identify the drug target. The immunogenic potential was assessed by high mobility group box (HMGB)1 ELISA assay, luciferase-based extracellular ATP assay, ectopic calreticulin expression by flow cytometry, and validated by phagocytosis assay, and in vivo vaccination assay using syngeneic C57BL/6 mice. Results Transcriptomic analysis identified metabolic alterations and DNA repair deficiency signatures in CML patients. CML patients exhibited enrichment in immune system, DNA repair, and metabolic pathways. The gene signature associated with BRCA mutated tumors was enriched in CML datasets, suggesting a deficiency in double-strand break repair pathways. Additionally, poly(ADP-ribose) polymerase (PARP)1 was significantly upregulated in CML patients’ stem cells compared to healthy counterparts. Consistent with the CML patient DNA repair signature, treatment with the methylated indolequinone MAC681 induced DNA damage, mitochondrial dysfunction, calcium homeostasis disruption, metabolic catastrophe, and necroptotic-like cell death. In parallel, MAC681 led to PARP1 degradation that was prevented by 3-aminobenzamide. MAC681-treated myeloid leukemia cells released DAMPs and demonstrated the potential to generate an immunogenic vaccine in C57BL/6 mice. MAC681 and asciminib exhibited synergistic effects in killing both imatinib-sensitive and -resistant CML, opening new therapeutic opportunities. Conclusions Overall, increasing the tumor mutational burden by PARP1 degradation and mitochondrial deregulation makes CML suitable for immunotherapy.

IntroductionIn this longitudinal study, we examine the potential costs and benefits of humility for well-being and civic trust among immigrants in a pluralistic democracy.MethodsWith data from 14,864 immigrant participants from a nationwide random sample in New Zealand, we used multilevel modeling to examine the associations of general humility (i.e., honesty-humility modesty) with well-being (life satisfaction and meaning) and civic trust (trust in police) over time in contexts with varying levels of ethnic deprivation and perceived religious discrimination. We hypothesized that (a) humility would correlate positively with well-being and civic trust (Hypothesis 1), (b) these associations would be attenuated in the contexts where perceptions of ethnic deprivation and religious discrimination are high (Hypothesis 2), and (c) these interaction effects would become more pronounced when cultural identities are salient (Hypothesis 3).ResultsMultilevel modeling revealed partial support for these hypotheses. Although humility correlated positively with well-being and trust in police over time, the two-way and three-way interactions did not yield substantial support for Hypotheses 2 and 3, respectively. The context of religious discrimination did, however, marginally attenuate the positive association between humility and trust in police.DiscussionCollectively, these results demonstrate that humility is associated with multiple benefits to well-being and civic trust and has few—if any—potential drawbacks.

Abstract Rice, feeding a significant portion of the world, poses unique proteomic challenges critical to agricultural research and global food security. The complexity of the rice proteome, influenced by various genetic and environmental factors, demands specialized analytical approaches for effective study. The central challenges in rice proteomics lie in developing custom methods suited to the unique aspects of rice biology. These include data preprocessing, method selection, and result validation, all of which are essential for advancing rice research. Our aim is to decode these proteomic intricacies to facilitate breakthroughs in strain improvement, disease resistance, and yield optimization, all vital for combating global food insecurity. To achieve this, we have created the RiceProteomeDB (RPDB), a React + Django database, offering a streamlined and comprehensive platform for the analysis of rice proteomics data. RiceProteomeDB (RPDB) simplifies proteomics data management and analysis. It offers features for data organization, preprocessing, method selection, result validation, and data sharing. Researchers can access processed rice proteomics data, conduct analyses, and explore experimental conditions. The user-friendly web interface enhances navigation and interaction. RPDB fosters collaboration by enabling data sharing and proper acknowledgment of sources, contributing to proteomics research and knowledge dissemination. Availability and implementation: Web application: http://riceproteome.plantprofile.net/ . The web application’s source code, user’s manual, and sample data: https://github.com/dongu7610/Riceproteome .

Abstract With the advent of 5G and the Internet of Things (IoT), there is a high demand for lightweight and flexible electromagnetic interference (EMI) shielding membranes with multifunctional capabilities. However, the rapid advancement of technology has led to environmental deterioration, emphasizing the significance of eco‐friendly and sustainable materials for EMI shielding. In this study, a novel environment‐friendly EMI shielding membrane with electric thermotherapy function and antibacterial properties is developed. The membrane substrate utilizes recycled polyethylene terephthalate (rPET) and is sequentially coated with synthesized FeCo@C nanoparticles (NPs) and silver nanowires (Ag NWs). The membrane is then dip‐coated with PDMS to modify the surface superhydrophobicity. Experimental results affirm that the developed environment‐friendly EMI shielding membrane possesses exceptional shielding efficiency (68 dB) and can be effectively utilized for safe and low‐voltage thermotherapy (137 °C by 2 V) while exhibiting antibacterial properties.

Abstract This study quantitatively analyzes the data of 3D seam shapes that alter according to easing conditions. By numerically approaching easing, which is only taught using traditional methods, this study suggests a method of analyzing the changes in 3D surface area, volume, and seam shape. The 3D data of the completed samples were obtained through a 3D scanner, the solid shapes were analyzed using reverse engineering, and a new program was developed. The shape, area, and volume of the data were analyzed, and the deformation rate was measured using the radius of curvature. Linear seam lines were bent because of the mechanical pushing inflicted by the garment with easing. The area increased dramatically as the ease amount increased when the seam lines were short, whereas it was relatively unaffected when seam lines were long. The radii of curvature for curved seam lines show that, for all samples, the waveform is high at the center where the seam is. The peak value did not increase for curved seams when the ease amount increased. The sum of the areas increased with a larger radius of curvature for the curved seams. It is a crucial reference for easing in garments regarding quantitative changes in seam shapes and volumes according to easing type and amount.

Abstract Background Microbiota-gut-brain axis interacts with one another to regulate brain functions. However, whether the impacts of gut dysbiosis on limbic white matter (WM) tracts contribute to the neuropsychiatric symptoms (NPS) in patients with amyloid-positive amnestic mild cognitive impairment (aMCI+), have not been explored yet. This study aimed to investigate the mediation effects of limbic WM integrity on the association between gut microbiota and NPS in patients with aMCI+. Methods Twenty patients with aMCI + and 20 healthy controls (HCs) were enrolled. All subjects underwent neuropsychological assessments and their microbial compositions were characterized using 16S rRNA Miseq sequencing technique. Amyloid deposition inspected by positron emission tomography imaging and limbic WM tracts (i.e., fornix, cingulum, and uncinate fasciculus) detected by diffusion tensor imaging were additionally measured in patients with aMCI+. We employed a regression-based mediation analysis using Hayes’s PROCESS macro in this study. Results The relative abundance of genera Ruminococcus and Lactococcus was significantly decreased in patients with aMCI + versus HCs. The relative abundance of Ruminococcus was negatively correlated with affective symptom cluster in the aMCI + group. Notably, this association was mediated by WM integrity of the left cingulate gyrus. Conclusions Our findings suggest Ruminococcus as a potential target for the management of affective impairments in patients with aMCI+.

Abstract Due to the development of sequence technology and decreased cost, many whole genome sequences have been obtained. As a result, extensive genetic variations have been discovered from many populations and germplasms to understand the genetic diversity of soybean (Glycine max [L.] Merr.). However, assessing the quality of variation is essential because the published variants were collected using different bioinformatic methods and parameters. Furthermore, despite the enhanced genome contiguity and more efficient filling of “N” stretches in the new reference genome, there remains a dearth of endeavors to verify the caliber of variations present in it. The primary goal of this research was to discern a dependable set of SNPs that can withstand reconciliation across multiple reference genomes. Additionally, the investigation aimed to reconfirm the variations through the utilization of numerous whole genome sequencing data obtained from publicly available databases. Based on the result, we created datasets that comprised the thoroughly verified SNP coordinates between the reference assemblies. The resulting “SoyDBean” database is now publicly accessible through the following URL: http://soydbean.plantprofile.net/ .

Abstract We report on advanced in-situ magneto-transport measurements in a transmission electron microscope. The approach allows for concurrent magnetic imaging and high resolution structural and chemical characterization of the same sample. Proof-of-principle in-situ Hall measurements on presumably undemanding nickel thin films supported by micromagnetic simulations reveal that in samples with non-trivial structures and/or compositions, detailed knowledge of the latter is indispensable for a thorough understanding and reliable interpretation of the magneto-transport data. The proposed in-situ approach is thus expected to contribute to a better understanding of the Hall signatures in more complex magnetic textures.

Abstract The genus Sophora (Fabaceae) includes medicinal plants that have been used in East Asian countries since antiquity. Sophora flavescens is a perennial herb indigenous to China, India, Japan, Korea, and Russia. Its dried roots have antioxidant, anti-inflammatory, antibacterial, apoptosis-modulating, and antitumor efficacy. The congeneric S. koreensis is endemic to Korea and its genome is less than half the size of that of S. flavescens. Nevertheless, this discrepancy can be used to assemble and validate the S. flavescens genome. A comparative genomic study of the two genomes can disclose the recent evolutionary divergence of the polymorphic phenotypic profiles of these species. Here, we used the PacBio sequencing platform to sequence and assemble the S. koreensis and S. flavescens genomes. We inferred that it was mainly small-scale duplication that occurred in S. flavescens. A KEGG analysis revealed pathways that might regulate the pharmacologically important secondary metabolites in S. flavescens and S. koreensis. The genome assemblies of Sophora spp. could be used in comparative genomics and data mining for various plant natural products.

Fire blight disease, caused by Erwinia amylovora, is a devastating affliction in apple cultivation worldwide. Chemical pesticides have exhibited limited effectiveness in controlling the disease, and biological control options for treating fruit trees are limited. Therefore, a relatively large-scale survey is necessary to develop microbial agents for apple trees. Here we collected healthy apple trees from across the country to identify common and core bacterial taxa. We analyzed the endophytic bacterial communities in leaves and twigs and discovered that the twig bacterial communities were more conserved than those in the leaves, regardless of the origin of the sample. This finding indicates that specific endophytic taxa are consistently present in healthy apple trees and may be involved in vital functions such as disease prevention and growth. Furthermore, we compared the community metabolite pathway expression rates of these endophyte communities with those of E. amylovora infected apple trees and discovered that the endophyte communities in healthy apple trees not only had similar community structures but also similar metabolite pathway expression rates. Additionally, Pseudomonas and Methylobacterium-Methylorobrum were the dominant taxa in all healthy apple trees. Our findings provide valuable insights into the potential roles of endophytes in healthy apple trees and inform the development of strategies for enhancing apple growth and resilience. Moreover, the similarity in cluster structure and pathway analysis between healthy orchards was mutually reinforcing, demonstrating the power of microbiome analysis as a tool for identifying factors that contribute to plant health.

Abstract Ferrous gluconate and calcium gluconate are used as food acidity regulators in South Korea, Japan, the European Union (EU), and other countries. A simultaneous analytical method was developed to quantify ferrous gluconate and calcium gluconate in food using ultra-performance liquid chromatography–tandem mass spectrometry. The limits of detection and quantification of ferrous gluconate were 1.1 and 3.5 mg/kg, respectively, while those of calcium gluconate were 1.4 and 4.8 mg/kg, respectively. The recoveries of ferrous gluconate from processed olives were in the range of 97.7–109.7%, while those of calcium gluconate from beverages were in the range of 94.3–110.8%. The developed simultaneous analytical method was applied to real samples from South Korea, which found ferrous gluconate concentrations of 0.031–0.065 g/kg in processed olives and calcium gluconate concentrations of 3.8–7.8 g/kg in beverages.

An investigation of comprehensive service requirements and their importance across various stakeholders is needed to develop systematic swallowing healthcare services. The present study examined the service requirements and their importance in developing comprehensive swallowing healthcare services from diverse stakeholders, including healthy seniors, individuals at risk, patients, guardians, and medical professionals, within the context of dysphagia. A series of survey-based interviews with 35 participants from the 5 stakeholder groups identified a comprehensive array of requirements pertinent to swallowing healthcare. Subsequently, a larger survey of 125 participants was administered using a 7-point Likert scale to evaluate the perceived importance of the identified requirements. A total of 46 distinct requirements were identified across the prevention/screening, evaluation/diagnosis, and treatment/training stages of swallowing healthcare. Accessibility, customization, usability, practicality, and information availability were features commonly identified across the three stages. Evaluation of the importance of these requirements yielded ratings ranging from 5.0 to 6.6. Significantly higher ratings were found for requirements associated with the evaluation/diagnosis and treatment/training stages, underscoring the stakeholder groups’ pronounced preference for services directed at these specific stages of the healthcare continuum. The study offers insights into the multifaceted requirements of stakeholders in swallowing healthcare, emphasizing the necessity for personalized, easily accessible, and comprehensive services. These findings serve as a foundational framework on targeted interventions and tailored services designed to address the diverse requirements of stakeholders for swallowing healthcare.

Membrane distillation (MD) is a process driven by the vapor pressure difference dependent on temperature variation, utilizing a hydrophobic porous membrane. MD operates at low pressure and temperature, exhibiting resilience to osmotic pressure. However, a challenge arises as the membrane performance diminishes due to temperature polarization (TP) occurring on the membrane surface. The vacuum MD process leverages the application of a vacuum to generate a higher vapor pressure difference, enhancing the flux and mitigating TP issues. Nevertheless, membrane fouling leads to decreased performance, causing membrane wetting and reducing the ion removal efficiency. This study investigates membrane fouling phenomena induced by various silica nanoparticle sizes (400, 900, and 1300 nm). The patterns of membrane fouling, as indicated by the flux reduction, vary depending on the particle size. Distinct MD performances are observed with changes in the feed water temperature and flow rate. When examining the membrane fouling mechanism for particles with a porosity resembling actual particulate materials, a fouling form similar to the solid type is noted. Therefore, this study elucidates the impact of particulate matter on membrane fouling under diverse conditions.

Fertilizers are widely used to improve the quality of fruits and vegetables. However, the overuse of fertilizers has become an issue because it causes environmental problems and negatively affects productivity and fruit quality. In this study, we examined the effects of nitrogen, phosphorus, and potassium (NPK) fertilizer levels on the metabolism of cucumber fruit in low- and high-nutrient soils using mass-spectrometry-based metabolomics approaches. Cucumber metabolite content was notably different depending on the initial soil nutrient status. Most amino acids and phenylpropanoids were abundant in the cucumbers raised in low-nutrient soil, whereas organic acids, some amino acids (aspartate, glutamate, and ornithine), and carbohydrates were comparatively higher in fruits from high-nutrient soil. The fertilizer supply resulted in an alteration in the metabolite profile, while no change in fruit yield was observed in either low- or high-nutrient soils. Fertilizer treatment perturbed the metabolite contents in cucumbers from low-nutrient soil. In contrast, treatment with higher concentrations of fertilizer in high-nutrient soil increased phenylpropanoid content in the cucumbers, while most metabolites decreased. In conclusion, fertilization levels should be carefully determined, considering culture conditions such as the original soil status, to increase product yield and fruit quality and avoid environmental problems.

This paper presents an effective method to boost the RSSI, the received signal strength on a moving path of LoRa wireless networking without change in digital circuitry or power amplifiers. Replacing the wire antenna as the conventionally used sensor by a printed Yagi-Uda antenna as a novel one designed to have a higher gain signifies increments of the RSSI at distant positions in the LoRa system with the same battery. The electromagnetic properties of the novel antenna are given by observing its beam-patterns in the anechoic chamber following the design procedures and fabrication. And the field-test for the radio link is conducted to see the proposed antenna enhance the RSSI at positions along the street of a wide-open area for LoRa communication. The RSSI has risen by more than 10 dB at distances from 200m to 700m with DLP-RFS1280 as the LoRa device in comparison to the conventional configuration in the device.

Abstract Background Clinical staging of bipolar disorder (BD) requires application of real-world data, as the next step in hypothesis. This study used the staging model to analyze the long-term course of BD in Korean patients based on clinical features and treatment responses to map the progression of bipolar illness from its early phase after the onset of illness. Methods A total of 136 patients diagnosed with BD-I (n = 62) or BD-II (n = 74) were recruited. Their progressive stages were retrospectively evaluated. A multi-state model was used to calculate the probability of progression to each stage. Hazard ratios of covariates expected to influence different courses of BD were calculated. Using the Alda score, long-term responses to mood stabilizers depending on the current stage were compared. Results Several sub-populations showed varied courses during the first five years after the onset of illness, with 41.5% remaining in stage 2 and 53% progressing to higher stages with shortened time for transition. Profiles of patients with BD-I and BD-II were different, suggesting biologically distinct groups. Comorbid psychiatric disorders, such as obsessive-compulsive disorder (OCD) and bulimia nervosa (BN) were associated with a recurrent course (stage 3a or 3b) or a malignant course (stage 3c or 4). Early age of onset, shorter duration of illness, older age at the start of medication, and poor response to lithium affected the illness progression. Conclusion We were able to apply the stage model based on episode recurrence patterns in early illness courses of Korean patients with BD. The stage progression pattern differed from the early phase in BD-I and BD-II patients. Psychotic comorbidity, age at onset, age at starting psychiatric treatment showed associations with the illness progression.

Recent advancements in energy conversion and storage systems have placed a spotlight on the role of multi-functional electrodes employing conductive substrates. These substrates, however, often face obstacles due to intricate and expensive production methods, as well as limitations in thickness. This research introduces a novel, economical approach using graphite felt as a versatile electrode. A method to enhance the typically low conductivity of graphite felt was devised, incorporating interfacial chemical tuning and the electrodeposition of a highly conductive nickel layer. This technique facilitates the integration of diverse transition metal-based active sites, aiming to refine the catalytic activity for specific electrochemical reactions. A key finding is that a combination of a nickel-rich cathode and an iron-rich anode can effectively optimize alkaline water electrolysis for hydrogen production at the ampere scale. Furthermore, the addition of sulfur improves the bi-functional oxygen-related redox reactions, rendering it ideal for air cathodes in solid-state zinc–air batteries. The assembled battery exhibits impressive performance, including a peak power density of 62.9 mW cm−2, a minimal voltage gap in discharge–charge polarization, and a lifecycle surpassing 70 h. This advancement in electrode technology signifies a significant leap in energy storage and conversion, offering a sustainable and efficient solution for future energy systems.

Faces and bodies both provide cues to age and cuteness, but little work has explored their interaction in cuteness perception. This study examines the interplay of facial and bodily cues in the perception of cuteness, particularly when these cues convey conflicting age information. Participants rated the cuteness of face–body composites that combined either a child or adult face with an age-congruent or incongruent body alongside manipulations of the head-to-body height ratio (HBR). The findings from two experiments indicated that child-like facial features enhanced the perceived cuteness of adult bodies, while child-like bodily features generally had negative impacts. Furthermore, the results showed that an increased head size significantly boosted the perceived cuteness for child faces more than for adult faces. Lastly, the influence of the HBR was more pronounced when the outline of a body’s silhouette was the only available information compared to when detailed facial and bodily features were presented. This study suggests that body proportion information, derived from the body’s outline, and facial and bodily features, derived from the interior surface, are integrated to form a unitary representation of a whole person in cuteness perception. Our findings highlight the dominance of facial features over bodily information in cuteness perception, with facial attributes serving as key references for evaluating face–body relationships and body proportions. This research offers significant insights into social cognition and character design, particularly in how people perceive entities with mixed features of different social categories, underlining the importance of congruency in perceptual elements.

Mitochondrial methionyl-tRNA synthetase (MARS2) canonically mediates the formation of fMet-tRNAifMet for mitochondrial translation initiation. Mitochondrial calcium uniporter (MCU) is a major gate of Ca2+ flux from cytosol into the mitochondrial matrix. We found that MARS2 interacts with MCU and stimulates mitochondrial Ca2+ influx. Methionine binding to MARS2 would act as a molecular switch that regulates MARS2-MCU interaction. Endogenous knockdown of MARS2 attenuates mitochondrial Ca2+ influx and induces p53 upregulation through the Ca2+-dependent CaMKII/CREB signaling. Subsequently, metabolic rewiring from glycolysis into pentose phosphate pathway is triggered and cellular reactive oxygen species level decreases. This metabolic switch induces inhibition of epithelial-mesenchymal transition (EMT) via cellular redox regulation. Expression of MARS2 is regulated by ZEB1 transcription factor in response to Wnt signaling. Our results suggest the mechanisms of mitochondrial Ca2+ uptake and metabolic control of cancer that are exerted by the key factors of the mitochondrial translational machinery and Ca2+ homeostasis.

This study was conducted to investigate the possibility of using gaze entropy to evaluate an operator's situation awareness in an emergency accident situation of a nuclear power plant. Gaze entropy can be an effective measure for evaluating an operator's situation awareness at a nuclear power plant because it can express gaze movement as a single comprehensive number. In order to determine the relationship between situation awareness and gaze entropy for an emergency accident situation of a nuclear power plant, an experiment was conducted to measure situation awareness and gaze entropy using simulators created for emergency accident situations LOCA, SGTR, SLB, and LOV. The experiment was to judge the accident situation of nuclear power plants presented in the simulator. The results showed that situation awareness and Shannon, dwell time, and Markov entropy had a significant negative correlation, while visual attention entropy (VAE) did not show any significant correlation with situation awareness. The results determined that Shannon entropy, dwell time entropy, and Markov entropy could be used as measures to evaluate situation awareness.

Abstract Background The use of smokeless tobacco has increased worldwide among young people. This study aimed to investigate the association between smokeless tobacco use and cigarette smoking amount in adult smoker groups stratified by age. Method 2013–2015 National Health Interview Survey was used. A total of 19,635 subjects were included in our analysis. Propensity score matching was used to adjust for selection and any other bias. Generalized estimating equation was used to analyze the association between smokeless tobacco use and cigarette smoking amount by age. Results All 580 smokeless tobacco users were matched to 2,900 non-smokeless tobacco users. Among those who were aged under 30, smokeless tobacco use was positively associated with the number of cigarettes used per day. Smokeless tobacco users who were aged under 30 and tried quitting smoking used more cigarettes than those who did non-smokeless tobacco users. Conclusions The present study revealed that among those who were aged under 30, smokeless tobacco use was positively associated with the number of cigarettes used per day. This study could contribute to understand the behaviors and tendencies of smoking in young adulthood and to establish effective smoking cessation methods for their age.

Fine-grained image recognition aims to classify fine subcategories belonging to the same parent category, such as vehicle model or bird species classification. This is an inherently challenging task because a classifier must capture subtle interclass differences under large intraclass variances. Most previous approaches are based on supervised learning, which requires a large-scale labeled dataset. However, such large-scale annotated datasets for fine-grained image recognition are difficult to collect because they generally require domain expertise during the labeling process. In this study, we propose a self-supervised transfer learning method based on Vision Transformer (ViT) to learn finer representations without human annotations. Interestingly, it is observed that existing self-supervised learning methods using ViT (e.g., DINO) show poor patch-level semantic consistency, which may be detrimental to learning finer representations. Motivated by this observation, we propose a consistency loss function that encourages patch embeddings of the overlapping area between two augmented views to be similar to each other during self-supervised learning on fine-grained datasets. In addition, we explore effective transfer learning strategies to fully leverage existing self-supervised models trained on large-scale labeled datasets. Contrary to the previous literature, our findings indicate that training only the last block of ViT is effective for self-supervised transfer learning. We demonstrate the effectiveness of our proposed approach through extensive experiments using six fine-grained image classification benchmark datasets, including FGVC Aircraft, CUB-200-2011, Food-101, Oxford 102 Flowers, Stanford Cars, and Stanford Dogs. Under the linear evaluation protocol, our method achieves an average accuracy of 78.5%, outperforming the existing transfer learning method, which yields 77.2%.

Balanced nutrients are essential for healthy plant growth, but there is no sensor available to monitor essential nutrients such as N and K. Electrical conductivity (EC) is one of the key parameters that could be adopted to monitor nutrient contents because soil EC is influenced by the available nutrients. Therefore, the main objective of this study was to examine the effects of different basal fertilizers, including inorganic, organic, and compost fertilizers, and the application ratio of basal and additional fertilizers on nutrient contents with an EC sensor. The applied basal and additional fertilizer ratios were N 30:70, K 40:60, and N 20:80, K 20:80, respectively, for each fertilizer treatment. The results showed that the EC sensor value was positively associated with water content. The soil EC response increased with inorganic fertilizer and fertigation, and it was positively correlated with soluble nutrients and exchangeable ammonium. The correlation coefficients between sensor EC and soluble nutrients, nitrate, and ammonium nitrogen were 0.87, 0.86, and 0.65, respectively. The principal component analysis (PCA) also elucidated that inorganic fertilizer was positively associated with sensor EC, soluble Na, Ca, Mg, and nitrate among variables. This work suggests that soil available nutrients, especially N, could be monitored with an EC sensor, and the soil nutrient status could be regulated to promote better plant growth.

Abstract Heavy metal-responsive operons were used for the generation of Escherichia coli cell-based biosensors. The selectivity and specificity of the biosensors were determined based on the interaction between heavy metals and regulatory proteins; thereby, the modulating target selectivity of biosensors could be achieved by changing target sensing properties of regulatory proteins. The results of this study demonstrated that Pb(II)-sensing biosensors could be generated from an arsenic-responsive genetic system, which was originally used for arsenic-sensing biosensors. The amino acids around to As(III)-binding sites of ArsR were mutated and cysteine residues were relocated to modulate the metal selectivity. In addition, genes encoding metal ion-translocating P-type ATPases, such as copA and zntA, were deleted to enhance the specificity by increasing the intercellular levels of divalent metal ions. Based on the results, channel protein deleted E. coli cells harboring a pair of recombinant genes, engineered ArsR and arsAp::egfp, showed enhanced responses upon Pb exposure and could be used to quantify the amount of Pb(II) in artificially contaminated water and plants grown in media containing Pb(II). Although we focused on generating Pb(II)-specific biosensors in this study, the proposed strategy has a great potential for the generation of diverse heavy metal-sensing biosensors and risk assessment of heavy metals in environmental samples as well as in plants.

Escherichia coli uses manganese [Mn(II)] as an essential trace element; thus, it has a genetic system that regulates cellular Mn(II) levels. Several genes in the mnt-operon of E. coli respond to intercellular Mn(II) levels, and transcription is regulated by a transcription factor (MntR) that interacts with Mn(II). This study aimed to develop Mn(II)-sensing biosensors based on mnt-operon genetic systems. Additionally, the properties of biosensors developed based on the promoter regions of mntS, mntH, and mntP were investigated. MntR represses the transcription of MntS and MntH after binding with Mn(II), while it induces MntP transcription. Thus, Mn(II) biosensors that decrease and increase signals could be obtained by fusing the promoter regions of mntS/mntH and mntP, with egfp encoding an enhanced green fluorescent protein. However, only the biosensor-based mntS:egfp responded to Mn(II) exposure. Further, E. coli harboring PmntS:egfp showed a concentration-dependent decrease in fluorescence signals. To enhance the sensitivity of the biosensor toward Mn(II), E. coli containing a deleted MntP gene that encodes Mn(II) exporter, was used as a host cell for biosensor development. The sensitivity toward Mn(II) increased by two times on using E. coli-mntP, and the biosensor could quantify 0.01–10 μM of Mn(II). Further, the applicability of Mn(II) in artificially contaminated water samples was quantified and showed >95% accuracy. The newly developed Mn(II) biosensors could detect and quantify the residual Mn(II) from mancozeb in soil samples, with the quantification accuracy being approximately 90%. To the best of our knowledge, this is the first Mn (II)-specific bacterial cell-based biosensor that serves as a valuable tool for monitoring and assessing the risks of Mn(II) in environmental systems.

Abstract Background Providing care for patients with dementia can negatively influence the physical health and health behaviours of family caregivers. A better understanding of the factors associated with health check-up and cancer screening participation is vital for developing effective interventions. Thus, this study aimed to identify factors associated with health check-up and cancer screening participation among family caregivers of patients with dementia. Methods This was a cross-sectional study that analysed the data of 2,414 family caregivers of patients with dementia collected by the Korea Community Health Survey in 2017. A binomial logistic regression analysis was performed to identify demographic, socioeconomic, and health status factors associated with health check-up and cancer screening participation among family caregivers of patients with dementia. Results Health check-up and cancer screening rates among family caregivers of patients with dementia were 68.7% and 61.4%, respectively, which were significantly lower than the rates for individuals who were not caregivers of patients with dementia. Those with lower education levels had lower odds ratios (OR) for both health check-up (OR: 0.60) and cancer screening (OR: 0.59) participation. In addition, symptoms of depression were associated with lower participation (health check-up OR: 0.67; cancer screening OR: 0.65). Conclusions More targeted disease prevention and management strategies must be developed for family caregivers of patients with dementia, particularly those with depressive symptoms and lower education levels.

Huntington’s disease (HD) is a late-onset neurological disorder for which therapeutics are not available. Its key pathological mechanism involves the proteolysis of polyglutamine-expanded (polyQ-expanded) mutant huntingtin (mHTT), which generates N-terminal fragments containing polyQ, a key contributor to HD pathogenesis. Interestingly, a naturally occurring spliced form of HTT mRNA with truncated exon 12 encodes an HTT (HTTΔ12) with a deletion near the caspase-6 cleavage site. In this study, we used a multidisciplinary approach to characterize the therapeutic potential of targeting HTT exon 12. We show that HTTΔ12 was resistant to caspase-6 cleavage in both cell-free and tissue lysate assays. However, HTTΔ12 retained overall biochemical and structural properties similar to those of wt-HTT. We generated mice in which HTT exon 12 was truncated and found that the canonical exon 12 was dispensable for the main physiological functions of HTT, including embryonic development and intracellular trafficking. Finally, we pharmacologically induced HTTΔ12 using the antisense oligonucleotide (ASO) QRX-704. QRX-704 showed predictable pharmacology and efficient biodistribution. In addition, it was stable for several months and inhibited pathogenic proteolysis. Furthermore, QRX-704 treatments resulted in a reduction of HTT aggregation and an increase in dendritic spine count. Thus, ASO-induced HTT exon 12 splice switching from HTT may provide an alternative therapeutic strategy for HD.

Effect of water supply to metabolites in tomato fruit was compared in two soils with different nutrient conditions, i.e., either limited or excess. Two types of soil nutrient condition, type A: nutrient-limited and type B: nutrient-excess, were prepared as follows; type A is a low nutrient-containing soil without a replenishment of starved nitrogen and phosphorous, type B is a high nutrient-containing soil exceeding the recommended fertilization. Soil water was adjusted either at −30 kPa (sufficient) or −80 kPa (limited). For harvested tomato fruits, we examined primary and secondary metabolites using non-targeted mass spectrometry based metabolomics. The fruit production and leaf SPAD were greatly dependent on soil nutrient levels, by contrast, the level of lycopene remained unchanged by different levels of water and nutrient supply. The perturbation of metabolites by water supply was clear in the nutrient-excess soil. In particular, limited water supply strongly decreased primary metabolites including sugars and amino acids. We demonstrated that water stress differently shifted primary metabolites of tomato fruits in two soils with different nutrient conditions via non-targeted mass spectrometry-based metabolomics. In conclusion, we suggest that the limited water supply in soils with surplus nutrient is not a recommendable way for tomato ‘cv. Super Dotaerang’ production if fruit nutritional quality such as sugars and amino acids is in the consideration, although there was no disadvantage in fruit yield.

Brain doping is a novel form of doping that involves stimulating specific brain regions to enhance sports performance. However, to the best of our knowledge, there is currently no established provision or detection method for it. As brain stimulation ultimately induces alterations in neurochemical concentrations, this study aimed to develop a diagnostic strategy for brain doping. We successfully developed and validated a sensitive simultaneous analysis method for 23 neurochemicals present in urine. Simple derivatization was employed to overcome ionization efficiency, enabling the effective detection of all the target compounds within 5 min. Additionally, we developed an animal model system using rats to replicate brain-doping scenarios and establish a diagnostic strategy. Behavior tests confirmed improved sports performance in the brain stimulation group. By examining changes in the distribution patterns of the target substances in urine samples, we observed that neurochemicals could be used as potential biomarkers for brain-doping diagnosis. The developed method allows the effective simultaneous analysis of multiple neurochemicals in biological samples and is expected to have various applications, including doping control. Thus, changes in the distribution pattern of neurochemicals could serve as a basis for brain-doping diagnosis.

Halim Park and Jin Hwa Park et al. report the nuclear genome sequence of the duckweed Wolffia australiana, the smallest known flowering plant. The genome assembly represents an improvement over a recently published genome and highlights genome rearrangements that may be linked to its specialized aquatic adaptations.

Bacterial cell-based biosensors have been widely developed for detecting environmental toxic materials. The znt-operon in Escherichia coli is a Zn(II)-responsive genetic system and is employed in Zn(II), Cd(II), and Hg(II)-sensing biosensors. In this study, point mutations were introduced in the regulatory protein ZntR to modulate its target selectivity, and metal ion-exporting genes, such as copA and zntA, in host cells were deleted to increase cellular metal ion levels and enhance specificity. Thus, the overall responses of the E. coli cell-based biosensors toward metal(loid) ions were increased, and their selectivity, which was originally for Cd(II) and Hg(II), was shifted to Pb(II). The gene encoding ZntA, known as the Zn(II)-translocating P-type ATPase, showed an impact on the ability of E. coli to export Pb(II), whereas copA deletion showed no significant impact. Noteworthily, the newly generated biosensors employing ZntR Cys115Ile showed the capacity to detect under 5 nM Pb(II) in solution, without response to other tested metal ions within 0–100 nM. To understand the marked effect of single point mutations on ZntR, computational modeling was employed. Although it did not provide clear answers, changes in the sequences of the metal-binding loops of ZntR modulated its transcriptional strength and target selectivity. In summary, the approaches proposed in this study can be valuable to generate new target-sensing biosensors with superior selectivity and specificity, which can in turn broaden the applicability of cell-based biosensors to monitor Pb(II) in environmental systems.

Although microplastics (MPs) are intrinsically toxic and function as vectors for organic micropollutants, their discharge from wastewater treatment plant effluents and human activity remains unknown owing to the limitations of detection and treatment technologies. It is imperative to quantify MPs from human activities involving the consumption of various plastic products. This study warns that contact lenses can generate MPs and nanoplastics (NPs) after being discharged into aquatic environments. Identification via micro-Fourier transform infrared spectroscopy revealed that the fragmented particles (from a few tens to a few hundred micrometres) could not be detected as poly(2-hydroxyl methacrylate), the component of contact lenses, owing to changes in its chemical properties. After the degradation process, the median size of the contact lens particles decreased from 313 to 85 µm. Approximately 300,600 g of contact lens waste is discharged into sewage systems daily in the United States of America (USA), where 45 million people wear contact lenses and throw away one-fifth of them every day. Contact lens waste (1 g) has the potential to release 5653.3–17,773.3 particles of MPs. This implies that the currently reported MP amounts in the environmental matrix exclude significant amounts of MPs and NPs from discharged contact lenses. The identification method should be examined, and a registration of the disposal process should be established.

Text-to-SQL is a task that converts natural language questions into SQL queries. Recent text-to-SQL models employ two decoding methods: sketch-based and generation-based, but each has its own shortcomings. The sketch-based method has limitations in performance as it does not reflect the relevance between SQL elements, while the generation-based method may increase inference time and cause syntactic errors. Therefore, we propose a novel decoding method, Hybrid decoder, which combines both methods. This reflects inter-SQL element information and defines elements that can be generated, enabling the generation of syntactically accurate SQL queries. Additionally, we introduce a Value prediction module for predicting values in the WHERE clause. It simplifies the decoding process and reduces the size of vocabulary by predicting values at once, regardless of the number of conditions. The results of evaluating the significance of Hybrid decoder indicate that it improves performance by effectively incorporating mutual information among SQL elements, compared to the sketch-based method. It also efficiently generates SQL queries by simplifying the decoding process in the generation-based method. In addition, we design a new evaluation measure to evaluate if it generates syntactically correct SQL queries. The result demonstrates that the proposed model generates syntactically accurate SQL queries.

GloSea5, a seasonal forecast system of the UK Met Office, shows reasonable skill among state-of-the-art operational seasonal forecast systems. However, the average surface temperature (T2m) in winter (December–February) of GloSea5 is particularly low in East Asia. To improve the seasonal forecast skill over East Asia, we focused on the high skill score of global teleconnection patterns simulated by GloSea5. Among the well-predicted teleconnection patterns, we selected those highly correlated with the East Asian T2m: East Atlantic (EA), Polar/Eurasia (PE), East Atlantic/Western Russia (EAWR), and West Pacific (WP) patterns. A multiple linear regression model was constructed using the selected teleconnection indices as predictors. These results are promising. The statistical skill-score evaluation of the constructed linear regression model using the anomaly correlation coefficient (ACC), root mean squared error (RMSE), and mean-squared skill score (MSSS) showed an improvement in the predicted T2m of East Asia, where the values of ACC and MSSS increased by 0.25 and 0.37, respectively, and the RMSE decreased by 0.63 compared to the dynamic forecast model results. These results suggest that a well-designed combined statistical and dynamical approach for seasonal prediction can be beneficial for some regions where the predictability of the dynamic model exhibits a low value.

Deep segmentation networks generally consist of an encoder to extract features from an input image and a decoder to restore them to the original input size to produce segmentation results. In an ideal setting, the trained encoder should possess the semantic embedding capability, which maps a pair of features close to each other when they belong to the same class, and maps them distantly if they correspond to different classes. Recent deep segmentation networks do not directly deal with the embedding behavior of the encoder. Accordingly, we cannot expect that the features embedded by the encoder will have the semantic embedding property. If the model can be trained to have the embedding ability, it will further enhance the performance as restoring from those features is much easier for the decoder. To this end, we propose supervised contrastive embedding, which employs feature-wise contrastive loss for the feature map to enhance the segmentation performance on medical images. We also introduce a boundary-aware sampling strategy, which focuses on the features corresponding to image patches located at the boundary area of the ground-truth annotations. Through extensive experiments on lung segmentation in chest radiographs, liver segmentation in computed tomography, and brain tumor and spinal cord gray matter segmentation in magnetic resonance images, it is demonstrated that the proposed method helps to improve the segmentation performance of popular U-Net, U-Net++, and DeepLabV3+ architectures. Furthermore, it is confirmed that the robustness on domain shifts can be enhanced for segmentation models by the proposed contrastive embedding.

Abstract Background Plants have adapted to survive under adverse conditions or exploit favorable conditions in response to their environment as sessile creatures. In a way of plant adaptation, plant hormones have been evolved to efficiently use limited resources. Plant hormones including auxin, jasmonic acid, salicylic acid, and ethylene have been studied to reveal their role in plant adaptation against their environment by phenotypic observation with experimental design such as mutation on hormone receptors and treatment / non-treatment of plant hormones along with other environmental conditions. With the development of Next Generation Sequencing (NGS) technology, it became possible to score the total gene expression of the sampled plants and estimate the degree of effect of plant hormones in gene expression. This allowed us to infer the signaling pathway through plant hormones, which greatly stimulated the study of functional genomics using mutants. Due to the continued development of NGS technology and analytical techniques, many plant hormone-related studies have produced and accumulated NGS-based data, especially RNAseq data have been stored in the sequence read archive represented by NCBI, EBI, and DDBJ. Description Here, hormone treatment RNAseq data of Arabidopsis (Col0), wild-type genotype, were collected with mock, SA, and MeJA treatments. The genes affected by hormones were identified through a machine learning approach. The degree of expression of the affected gene was quantified, visualized in boxplot using d3 (data-driven-document), and the database was built by Django. Conclusion Using this database, we created a web application ( http://pgl.gnu.ac.kr/hormoneDB/ ) that lists hormone-related or hormone-affected genes and visualizes the boxplot of the gene expression of selected genes. This web application eventually aids the functional genomics researchers who want to gather the cases of the gene responses by the hormones.

Abstract This study collected fundamental data on the current status of construction workers’ clothes in South Korea, and categorized it based on construction site environment and job position. The study was conducted via a survey of 102 construction workers comprising both managers and laborers. In addition, a detailed interview-based questionnaire was used to ask three workers at the construction site to adopt working postures and identify the most uncomfortable parts of their workwear. Construction working environments are influenced by seasonal changes and have been recognized as places where dangerous hazards may occur. Workers in the construction industry felt that their faces were the hottest parts of their bodies in summer and their hands were the coldest in winter. With respect to the clothing worn for work, the results showed that most managers wore company-supplied workwear but laborers did not. When personally purchasing workwear, managers bought items at outdoor shops, whereas laborers purchased theirs at local markets. Both laborers and managers indicated a need for new workwear designs with a greater emphasis on function. In the in-depth interviews, the respondents noted that they felt discomfort from the clothing in their backs, upper arms, thighs, knees, and hips as a result of their primary work postures. Furthermore, they noted the need for pockets of appropriate size and position according to their work. The functional requirements demanded from construction workwear were classified based on the study’s results.

For the purpose of breeding documentation, researchers and breeders kept handwritten records of the breeding history, including parental information and breeding methods. The cultivars were used again as parents for further breeding, and modern cultivars of rice have a wide range of alleles from many generations of parents and ancestors. To understand such a breeding history, it is necessary to ask around for relevant information, which is then usually documented in Excel or Word by multiple breeders or breeding institutes. Here, we constructed RicePedigree, which contains the breeding history of rice based on the documents provided by the Rural Development Administration (RDA) in Korea. We devised a simple method for collecting a breeding history and storing it in a database. RicePedigree is a web-based application on the database that facilitates researchers’ and breeders’ utilization of the breeding history of rice. Based on the query cultivar name, it will return a hierarchical tree of breeding histories and a list of cultivars and breeding lines that contain query cultivars in their breeding histories. This app would be a good way to review and keep track of information about current and future cultivars.

In the 21st century, humanity is facing unprecedented climate and food crises caused by population growth, urbanization, environmental pollution, and carbon emissions. As a response to the climate and food crisis, the following concept has emerged: smart urban agriculture that can reduce carbon emissions from buildings and achieve self-sufficiency in food. Various architectural designs that include smart farms are being explored worldwide. Nevertheless, the concept does not seem to have gained sufficient popular traction. This study attempted to materialize the concept by presenting types and characteristics from an architectural planning and design perspective by examining cases of smart farm constructions worldwide. After collecting 171 smart farm cases from around the world and building a database in terms of city, architecture, environment, and crops, the types were classified through SOM analysis, an artificial neural network-based cluster analysis methodology. As a result of the analysis, smart farm types were classified into seven types, and the characteristics of architectural planning and design were extracted for each type. It is meaningful that a specific form was presented so that planning and design can be easily accessed according to the situation placed through the type of smart farm.

Wolffia globosa is the smallest angiosperm in the world and can be found in Asia and parts of America. Also, it is commonly used as food in Southeast Asia. In this study, the complete chloroplast genome of the Wolffia globosa was assembled from the whole genome Illumina sequencing data. The assembled genome size is 169,405 bp in length, which composed of a large single copy region (LSC) of 92,171 bp, a small single copy (SSC) regions of 13,570 bp and separated by a pair of inverted repeat (IR) regions of 31,810 bp each. It encodes a total of 113 genes, including 78 protein-coding genes, 31 tRNA genes, and 4 rRNA genes. There are 22 duplicated genes in the predicted gene catalog. The overall GC content is 35.9% while the GC content of the LSC, SSC, and IR regions are 33.8%, 31.1%, and 40.0%, separately. Based on Bayesian phylogenetic analysis, it represents that Wolffia globosa was closely related to Wolffia australiana.

Abstract Background The development of next generation sequencer (NGS) and the analytical methods allowed the researchers to profile their samples more precisely and easier than before. Especially for agriculture, the certification of the genomic background of their plant materials would be important for the reliability of seed market and stable yield as well as for quarantine procedure. However, the analysis of NGS data is still difficult for non-computational researchers or breeders to verify their samples because majority of current softwares for NGS analysis require users to access unfamiliar Linux environment. Main body Here, we developed a web-application, “Soybean-VCF2Genomes”, http://pgl.gnu.ac.kr/soy_vcf2genome/ to map single sample variant call format (VCF) file against known soybean germplasm collection for identification of the closest soybean accession. Based on principal component analysis (PCA), we simplified genotype matrix for lowering computational burden while maintaining accurate clustering. With our web-application, users can simply upload single sample VCF file created by more than 10x resequencing strategy to find the closest samples along with linkage dendrogram of the reference genotype matrix. Conclusion The information of the closest soybean cultivar will allow breeders to estimate relative germplasmic position of their query sample to determine soybean breeding strategies. Moreover, our VCF2Genomes scheme can be extended to other plant species where the whole genome sequences of core collection are publicly available.

Objective To compare the risk of depressive symptoms in adults with physical disabilities between rehabilitation-receivers and non-receivers. Methods A total of 3,568 adults with physical disabilities were retrieved from the 2014 Korean National Survey on People with Disabilities database. Four covariate adjustment methods (a multivariable regression model, inverse probability of treatment weighting [IPTW] adjusted for normalized weight, IPTW with stabilized weight, and greedy algorithm with 1:1 propensity score matching) were used to estimate the odds of having depressive symptoms. The dependent variable was depressive symptoms and the independent variable was the use of rehabilitation services. Baseline covariates were 19 demographic variables and 10 chronic condition variables. Results The four covariate adjustment methods revealed that adults with physical disabilities receiving rehabilitation services had a higher risk of depressive symptoms than those who did not receive these services (adjusted odds ratio, 1.191–1.294). Conclusion Our findings suggest that adults with physical disabilities receiving rehabilitation services have higher risk of developing depressive symptoms. Therefore, rehabilitation professionals need to pay attention to depressive symptoms and establish therapeutic strategies that can reduce such risk in rehabilitation settings.

Microorganisms are omnipresent and inseparable from our life. Many of them are beneficial to humans, while some are not. Importantly, foods and beverages are susceptible to microbial contamination, with their toxins causing illnesses and even death in some cases. Therefore, monitoring and detecting harmful microorganisms are critical to ensuring human health and safety. For several decades, many methods have been developed to detect and monitor microorganisms and their toxicants. Conventionally, nucleic acid analysis and antibody-based analysis were used to detect pathogens. Additionally, diverse chromatographic methods were employed to detect toxins based on their chemical and structural properties. However, conventional techniques have several disadvantages concerning analysis time, sensitivity, and expense. With the advances in biotechnology, new approaches to detect pathogens and toxins have been reported to compensate for the disadvantages of conventional analysis from different research fields, including electrochemistry, nanotechnology, and molecular biology. Among them, we focused on the recent studies of transcription factor (TF)-based biosensors to detect microorganisms and discuss their perspectives and applications. Additionally, the other biosensors for detecting microorganisms reported in recent studies were also introduced in this review.

In this paper, a novel thin and flexible antenna is proposed for earbuds to gain an improvement in their wireless signal-sensing capability as a film-based artificial magnetic conductor (AMC) structure. As antenna designs for earbuds face challenges of being embedded beneath the top cover of the earbud, conformal to curved surfaces, and very close to metallic ground and touch-panel parts, as well as scarce degrees of freedom from feeding conditions and functional degradation by human tissue, unlike conventional techniques such as quasi quarter-wavelength radiators on LDS and epoxy molding compounds (relatively thick and pricy), an antenna of a metal pattern on a film is made with another film layer as the AMC to mitigate problems of the antenna in a small and curved space of an insert-molded wireless device. The antenna was designed, fabricated, and embedded in earbud mockups to work for the 2.4 GHz Bluetooth RF link, and its functions were verified by RF and antenna measurement, showing that it could overcome the limitations in impedance matching with only lumped elements and poor radiation by the ordinary schemes. The input reflection coefficient and antenna efficiency were 10 dB and 9% better than other methods. In particular, the on-film AMC antenna (OFAA) presents robustness against deterioration by the human tissue, when it is placed in the ear phantom at the workbench and implemented in an in situ test using a large zorb ball mimicking a realistic sensing environment. This yielded an RSSI enhancement of 20–30 dB.

We previously showed that a synthetic peptide (S2-P) corresponding to a portion of the human syndecan-2 (SDC2) sequence can bind to the pro-domain of matrix metalloproteinase-7 (MMP-7) to inhibit colon cancer activities. Since S2-P had a relatively weak binding affinity for the MMP-7 pro-domain, we herein modified the amino acid sequence of S2-P to improve the anticancer potential. On the basis of the interaction structure of S2-P and MMP-7, four peptides were generated by replacing amino acids near Tyr 51, which is critical for the interaction. The SDC2-mimetic peptides harboring an Ala-to-Asp substitution at the C-terminal side of Tyr 51 (S2-D) or with an Ala-to-Phe substitution at the N-terminal side of Tyr 51 and an Ala-to-Asp substitution at the C-terminal side of Tyr 51 (S2-FE) showed improved interaction affinities for the MMP-7 pro-domain. Compared to S2-P, S2-FE was better able to inhibit the SDC2–MMP-7 interaction, the cell surface localization of MMP-7, the gelatin degradation activity of MMP-7, and the cancer activities (cell migration, invasion, and colony-forming activity) of human HCT116 colon cancer cells in vitro. In vivo, S2-FE inhibited the primary tumor growth and lung metastasis of CT26 mouse colon cancer cells in a xenograft mouse model. Together, these data suggest that S2-FE could be useful therapeutic anticancer peptides for colon cancer.

In this paper, a novel chip antenna and its function in wireless connectivity are presented for Bluetooth (BLT) earphones. The chip antenna is a metamaterial so compact (3, that when it is mounted on the realistic PCB, it can be held in the enclosure of the BLT earphone. This setting does not degrade the resonance (S11 < −10 dB) of the proposed antenna. As two earphones in a pair are demanded to communicate with each other, one shares an RF signal with the other and they take turns as the master and slave. The received signal sensing is conducted with the latest model of human head-ear-phantom located between the earphones to mimic the real use-case and cross-head interference. Electromagnetic simulation of the antenna is done and verified by fabrication and measurement. Particularly, received-signal strength indications between the proposed antennas in the earphones are experimentally obtained as −67.5 dBm and −70 dBm without and with the head-ear-phantom, respectively, much greater than −120 dBm, the limit of detection, and implying acceptable connectivity and invulnerability over cross-head-interference problems.

Amelogenesis imperfecta (AI) is a collection of rare genetic disorders affecting the quantity and/or quality of the tooth enamel. AI can be classified into three major types according to the clinical phenotype: hypoplastic, hypocalcified, and hypomatured. Among them, the hypocalcified type shows the weakest physical properties, leaving rough and discolored enamel surfaces after tooth eruption. To date, mutations in the FAM83H gene are responsible for the autosomal-dominant hypocalcified AI. In this study, we recruited a four-generation Colombian family with hypocalcified AI and identified a recurrent nonsense mutation in the FAM83H gene (NM_198488.5:c.1289C>A, p.(Ser430 *)) by candidate gene sequencing. Cephalometric analyses revealed the anterior open bite that occurred in the proband is not correlated with the AI in this family.