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This study aims to estimate the connectedness rating (CR) of Korean swine breeding herds. Using 104,380 performance and 83,200 reproduction records from three swine breeds (Yorkshire, Landrace and Duroc), the CR was estimated for two traits: average daily gain (ADG) and number born alive (NBA) in eight breeding herds in the Republic of Korea (hereafter, Korea). The average CR for ADG in the Yorkshire breed ranges from 1.32% to 28.5% depending on the farm. The average CR for NBA in the Yorkshire herd ranges from 0% to 12.79%. A total of 60% of Yorkshire and Duroc herds satisfied the preconditions suggested for genetic evaluation among the herds. The precondition for the genetic evaluation of CR for ADG, as a productive trait, was higher than 3% and that of NBA, as a reproductive trait, was higher than 1.5%. The ADG in the Yorkshire herds showed the highest average CR. However, the average CR of ADG in the Landrace herds was lower than the criterion of the precondition. The prediction error variance of the difference (PEVD) was employed to assess the validation of the CR, as PEVDs exhibit fluctuations that are coupled with the CR across the herds. A certain degree of connectedness is essential to estimate breeding value comparisons between pig herds. This study suggests that it is possible to evaluate the genetic performance together for ADG and NBA in the Yorkshire herds since the preconditions were satisfied for these four herds. It is also possible to perform a joint genetic analysis of the ADG records of all Duroc herds since the preconditions were also satisfied. This study provides new insight into understanding the genetic connectedness of Korean pig breeding herds. CR could be utilized to accelerate the genetic progress of Korean pig breeding herds.

Summary: Currently, there is no effective treatment for obesity and alcohol-associated liver diseases, partially due to the lack of translational human models. Here, we present a protocol to generate 3D human liver spheroids that contain all the liver cell types and mimic “livers in a dish.” We describe strategies to induce metabolic and alcohol-associated hepatic steatosis, inflammation, and fibrosis. We outline potential applications, including using human liver spheroids for experimental and translational research and drug screening to identify potential anti-fibrotic therapies. : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

Liver fibrosis of different etiologies is a serious health problem worldwide. There is no effective therapy available for liver fibrosis except the removal of the underlying cause of injury or liver transplantation. Development of liver fibrosis is caused by fibrogenic myofibroblasts that are not present in the normal liver, but rather activate from liver resident mesenchymal cells in response to chronic toxic or cholestatic injury. Many studies indicate that liver fibrosis is reversible when the causative agent is removed. Regression of liver fibrosis is associated with the disappearance of activated myofibroblasts and resorption of the fibrous scar. In this review, we discuss the results of genetic tracing and cell fate mapping of hepatic stellate cells and portal fibroblasts, their specific characteristics, and potential phenotypes. We summarize research progress in the understanding of the molecular mechanisms underlying the development and reversibility of liver fibrosis, including activation, apoptosis, and inactivation of myofibroblasts.

Skeleton-based human action recognition (HAR) is being utilized in various fields like action classification and abnormal behavior detection. The accurate coordinates of the human joints are a crucial factor for the high performance in skeleton-based HAR. However, the missing joints caused by occlusion and invisibility result in performance degradation. Hence, in this paper, a missing joint reconstruction model is proposed to improve the performance of skeleton-based HAR. The proposed model, based on a denoising graph autoencoder (DGAE), regards missing joints as noise corrupted information and aims to reconstruct them to be close to their original coordinates. When the encoder of the proposed model compresses the noised input into a latent vector, a masking Laplacian matrix is introduced to reduce the effect of the missing joints’ features. The masking Laplacian matrix adjusts the effect of features between a missing joint and its adjacent joints by altering the weights of an adjacent matrix. In the decoder, a Laplacian matrix, which represents the connections among the joints, is utilized to reconstruct an output from the latent vector. The experiment result shows that the proposed model reconstructs the coordinates of missing joints with a marginal error. In addition, the performance of skeleton-based HAR is enhanced by reconstructing the missing joints.

The genus Allium is a well-known model system for cytological research, and its cytological characteristics are considered important for species identification. In this study, we counted chromosome numbers of 21 populations from 12 taxa comprising seven sections (Butomissa, Sacculiferum, Schoenoprasum, Oreiprason, Reticulatobulbosa, Rhizirideum, Tenuissima) and five subgenera (Butomissa, Cepa, Polyprason, Reticulatobulbosa, Rhizirideum) from Kyrgyzstan, Mongolia, and South Korea. The chromosome numbers varied with 2n=16 or 2n=32. New ploidy levels were found in A. karelinii (2n=2x=16) and A. burjaticum (2n=2x=16) from Kyrgyzstan and Mongolia, respectively. Photomicrophotographs of metaphase chromosomes and karyotype analyses of all Allium taxa studied are provided.

Mass spectrometry (MS) has revolutionized clinical chemistry, offering unparalleled capabilities for biomolecule analysis. This review explores the growing significance of mass spectrometry (MS), particularly when coupled with liquid chromatography (LC), in identifying disease biomarkers and quantifying biomolecules for diagnostic and prognostic purposes. The unique advantages of MS in accurately identifying and quantifying diverse molecules have positioned it as a cornerstone in personalized-medicine advancement. MS-based technologies have transformed precision medicine, enabling a comprehensive understanding of disease mechanisms and patient-specific treatment responses. LC-MS has shown exceptional utility in analyzing complex biological matrices, while high-resolution MS has expanded analytical capabilities, allowing the detection of low-abundance molecules and the elucidation of complex biological pathways. The integration of MS with other techniques, such as ion mobility spectrometry, has opened new avenues for biomarker discovery and validation. As we progress toward precision medicine, MS-based technologies will be crucial in addressing the challenges of individualized patient care, driving innovations in disease diagnosis, prognosis, and treatment strategies.

Protein dynamics play a crucial role in biological function, encompassing motions ranging from atomic vibrations to large-scale conformational changes. Recent advancements in experimental techniques, computational methods, and artificial intelligence have revolutionized our understanding of protein dynamics. Nuclear magnetic resonance spectroscopy provides atomic-resolution insights, while molecular dynamics simulations offer detailed trajectories of protein motions. Computational methods applied to X-ray crystallography and cryo-electron microscopy (cryo-EM) have enabled the exploration of protein dynamics, capturing conformational ensembles that were previously unattainable. The integration of machine learning, exemplified by AlphaFold2, has accelerated structure prediction and dynamics analysis. These approaches have revealed the importance of protein dynamics in allosteric regulation, enzyme catalysis, and intrinsically disordered proteins. The shift towards ensemble representations of protein structures and the application of single-molecule techniques have further enhanced our ability to capture the dynamic nature of proteins. Understanding protein dynamics is essential for elucidating biological mechanisms, designing drugs, and developing novel biocatalysts, marking a significant paradigm shift in structural biology and drug discovery.

Therapeutic protein engineering has revolutionized medicine by enabling the development of highly specific and potent treatments for a wide range of diseases. This review examines recent advances in computational and experimental approaches for engineering improved protein therapeutics. Key areas of focus include antibody engineering, enzyme replacement therapies, and cytokine-based drugs. Computational methods like structure-based design, machine learning integration, and protein language models have dramatically enhanced our ability to predict protein properties and guide engineering efforts. Experimental techniques such as directed evolution and rational design approaches continue to evolve, with high-throughput methods accelerating the discovery process. Applications of these methods have led to breakthroughs in affinity maturation, bispecific antibodies, enzyme stability enhancement, and the development of conditionally active cytokines. Emerging approaches like intracellular protein delivery, stimulus-responsive proteins, and de novo designed therapeutic proteins offer exciting new possibilities. However, challenges remain in predicting in vivo behavior, scalable manufacturing, immunogenicity mitigation, and targeted delivery. Addressing these challenges will require continued integration of computational and experimental methods, as well as a deeper understanding of protein behavior in complex physiological environments. As the field advances, we can anticipate increasingly sophisticated and effective protein therapeutics for treating human diseases.

Abstract Post-pandemic health operations have become a near-term reality, discussions around wearables are on the rise. How do wearable health solutions effectively deploy and use this opportunity to fill the gap between wellness and healthcare? In this paper, we will talk about wearable healthcare diagnosis, with a particular focus on monitoring skin hydration using optical multi-wavelength sensor fusion. Continuous monitoring of human skin hydration is a task of paramount importance for maintaining water loss dynamics for fitness lovers as well as for skin beauty, integrity and the health of the entire body. Preserving the appropriate levels of hydration ensures consistency of weight, positively affects psychological state, and proven to result in a decrease in blood pressure as well as the levels of “bad” cholesterol while slowing down the aging processes. Traditional methods for determining the state of water content in the skin do not allow continuous and non-invasive monitoring, which is required for variety of consumer, clinical and cosmetic applications. We present novel sensing technology and a pipeline for capturing, modeling and analysis of the skin hydration phenomena and associated changes therein. By expanding sensing capabilities built into the SmartWatch sensor and combining them with advanced modeling and Machine Learning (ML) algorithms, we identified several important characteristics of photoplethysmography (PPG) signal and spectral sensitivity corresponding to dynamics of skin water content. In a hardware aspect, we newly propose the expansion of SmartWatch capabilities with InfraRed light sources equipped with wavelengths of 970 nm and 1450 nm. Evaluation of the accuracy and characteristics of PPG sensors has been performed with biomedical optics-based simulation framework using Monte Carlo simulations. We performed rigorous validation of the developed technology using experimental and clinical studies. The developed pipeline serves as a tool in the ongoing studies of the next generation of optical sensing technology.

Alcohol-associated liver disease (ALD) is a substantial cause of morbidity and mortality worldwide and represents a spectrum of liver injury beginning with hepatic steatosis (fatty liver) progressing to inflammation and culminating in cirrhosis. Multiple factors contribute to ALD progression and disease severity. Here, we overview several crucial mechanisms related to ALD end-stage outcome development, such as epigenetic changes, cell death, hemolysis, hepatic stellate cells activation, and hepatic fatty acid binding protein 4. Additionally, in this review, we also present two clinically relevant models using human precision-cut liver slices and hepatic organoids to examine ALD pathogenesis and progression.

Objective: Alterations in lipid metabolism are associated with aging and age-related diseases. Chaperone-mediated autophagy (CMA) is a lysosome-dependent process involved in specific protein degradation. Heat shock cognate 71 kDa protein (Hsc70) recognizes cytosolic proteins with KFERQ motif and allows them to enter the lysosome via lysosome-associated membrane glycoprotein 2 isoform A (LAMP2A). CMA deficiency is associated with dysregulated lipid metabolism in the liver. In this study, we examined the effect of CMA on lipid metabolism in the aged liver. Methods: 12-week-old and 88-week-old mice were employed to assess the effect of aging on hepatic CMA activity. We generated CMA-deficient mouse primary hepatocytes using siRNA for Lamp2a and liver-specific LAMP2A knockdown mice via adeno-associated viruses expressing short hairpin RNAs to investigate the influence of CMA on lipid metabolism. Results: We noted aging-induced progression toward fatty liver and a decrease in LAMP2A levels in total protein and lysosomes. The expression of genes associated with fatty acid oxidation was markedly downregulated in the aged liver, as verified in CMA-deficient mouse primary hepatocytes. In addition, the aged liver accumulated nuclear receptor corepressor 1 (NCoR1), a negative regulator of peroxisome proliferator-activated receptor α (PPARα). We found that Hsc70 binds to NCoR1 via the KFERQ motif. Lamp2a siRNA treatment accumulated NCoR1 and decreased the fatty acid oxidation rate. Pharmacological activation of CMA by AR7 treatment increased LAMP2A expression, leading to NCoR1 degradation. A liver-specific LAMP2A knockdown via adeno-associated viruses expressing short hairpin RNAs caused NCoR1 accumulation, inactivated PPARα, downregulated the expression of fatty acid oxidation-related genes and significantly increased liver triglyceride levels. Conclusions: Our results elucidated a novel PPARα regulatory mechanism involving CMA-mediated NCoR1 degradation during aging. These findings demonstrate that CMA dysregulation is crucial for the progression of aging-related fatty liver diseases.

This study presents a newly released algorithm for smartwatches – Sweat loss estimation for running activities. A machine learning model (polynomial Kernel Ridge Regression) is used to estimate the sweat loss in milliliters. A clinical dataset of 748 running tests of 568 people was collected and used for training / validation. The data presents a diversity of factors playing an important role in sweat loss: anthropometric parameters of users, distance, ambient temperature and humidity. The data augmentation technique was implemented. One of the key points of the algorithm is an accelerometer-based model for running distance estimation. The model we developed has a mean absolute percentage error (MAPE) = 7.7% and a coefficient of determination (R2) = 0.95 (at distances in the range of 2–20 km). The performance of the fully automatic sweat loss estimation algorithm provides an average root mean square error (RMSE) = 236 ml; more fundamentally, health-related parameter body weight percentage RMSE (RMSEBWP) = 0.33% and R2 = 0.79. To the best of the authors’ knowledge, the algorithm provides the best performance of any existing solution or described in the literature.

Uric acid (UA), the final metabolite of purine, is primarily excreted through urine to maintain an appropriate concentration in the bloodstream. However, any malfunction in this process can lead to complications due to either deficiency or excess amount of UA. Hence, the development of a sensor platform with a wide-range detection is crucial. To realize this, we fabricated a surface-enhanced Raman spectroscopy (SERS) substrate inspired by a type of starfish with numerous protrusions, Asterias forbesi. The Asterias forbesi-inspired SERS (AF-SERS) substrate utilized an Au@Ag nanostructure and gold nanoparticles to mimic the leg and protrusion morphology of the starfish. This substrate exhibited excellent Raman performance due to numerous hotspots, demonstrating outstanding stability, reproducibility, and repeatability. In laboratory settings, we successfully detected UA down to a concentration of 1.16 nM (limit of detection) and demonstrated selectivity against various metabolites. In the experiments designed for real-world application, the AF-SERS substrate detected a broad range of UA concentrations, covering deficiencies and excesses, in both serum and urine samples. These results underscore the potential of the developed AF-SERS substrate as a practical detection platform for UA in real-world applications.

A public health crisis in the form of a significant incidence of fatal pulmonary disease caused by repeated use of humidifier disinfectants containing polyhexamethylene guanidine phosphate (PHMG) recently arose in Korea. Although the mechanisms of pulmonary fibrosis following respiratory exposure to PHMG are well described, distant-organ effect has not been reported. In this study, we investigated whether intratracheal administration of PHMG affects liver pathophysiology and metabolism. Our PHMG mouse model showed a significant decrease in liver cholesterol level. An mRNA-seq analysis of liver samples revealed an alteration in the gene expression associated with cholesterol biosynthesis and metabolism to bile acids. The expression of genes involved in cholesterol synthesis was decreased in a real-time PCR analysis. To our surprise, we found that the coordinate regulation of cholesterol and bile acid homeostasis was completely disrupted. Despite the decreased cholesterol synthesis and low bile acid levels, the farnesoid X receptor/small heterodimer partner pathway, which controls negative feedback of bile acid synthesis, was activated in PHMG mice. As a consequence, gene expression of Cyp7a1 and Cyp7b1, the rate-limiting enzymes of the classical and alternative pathways of bile acid synthesis, was significantly downregulated. Notably, the changes in gene expression were corroborated by the hepatic concentrations of the bile acids. These results suggest that respiratory exposure to PHMG could cause cholestatic liver injury by disrupting the physiological regulation of hepatic cholesterol and bile acid homeostasis.

Abstract A facile and scalable lithography-free fabrication technique, named solution-processable electrode-material embedding in dynamically inscribed nanopatterns (SPEEDIN), is developed to produce highly durable electronics. SPEEDIN uniquely utilizes a single continuous flow-line manufacturing process comprised of dynamic nanoinscribing and metal nanoparticle solution coating with selective embedding. Nano- and/or micro-trenches are inscribed into arbitrary polymers, and then an Ag nanoparticle solution is dispersed, soft-baked, doctor-bladed, and hard-baked to embed Ag micro- and nanowire structures into the trenches. Compared to lithographically embossed metal structures, the embedded SPEEDIN architectures can achieve higher durability with comparable optical and electrical properties and are robust and power-efficient even under extreme stresses such as scratching and bending. As one tangible application of SPEEDIN, we demonstrate a flexible metal electrode that can operate at 5 V at temperatures up to 300 °C even under the influence of harsh external stimuli. SPEEDIN can be applied to the scalable fabrication of diverse flexible devices that are reliable for heavy-duty operation in harsh environments involving high temperatures, mechanical deformations, and chemical hazards.

Mefenamic acid (MFA) is a commonly prescribed non-steroidal anti-inflammatory drug (NSAID) with anti-inflammatory and analgesic properties. MFA is known to have potent antioxidant properties and a neuroprotective effect against oxidative stress. However, its impact on the liver is unclear. This study aimed to elucidate the antioxidative effects of MFA and their underlying mechanisms. We observed that MFA treatment upregulated the nuclear factor erythroid 2-related factor 2 (Nrf2) pathway. Treatment with various anthranilic acid derivative-class NSAIDs, including MFA, increased the expression of sequestosome 1 (SQSTM1) in HepG2 cells. MFA disrupted the interaction between Kelch-like ECH-associated protein 1 (Keap1) and Nrf2, activating the Nrf2 signaling pathway. SQTM1 knockdown experiments revealed that the effect of MFA on the Nrf2 pathway was masked in the absence of SQSTM1. To assess the cytoprotective effect of MFA, we employed tert-Butyl hydroperoxide (tBHP) as a ROS inducer. Notably, MFA exhibited a protective effect against tBHP-induced cytotoxicity in HepG2 cells. This cytoprotective effect was abolished when SQSTM1 was knocked down, suggesting the involvement of SQSTM1 in mediating the protective effect of MFA against tBHP-induced toxicity. In conclusion, this study demonstrated that MFA exhibits cytoprotective effects by upregulating SQSTM1 and activating the Nrf2 pathway. These findings improve our understanding of the pharmacological actions of MFA and highlight its potential as a therapeutic agent for oxidative stress-related conditions.

The aim of this research is to explore the antecedents of usefulness in the technology acceptance model for a food delivery application system and to confirm the accountability of the technology acceptance model in the area of food delivery application systems. The determinants of usefulness are information quality, swiftness, and food quality. For data collection, this research employs Amazon Mechanical Turk. The number of valid observations is 379. For the data analysis, confirmatory factor analysis and structural equation modeling were primarily implemented. The results indicate that usefulness is positively impacted by information quality, swiftness, and ease of use. Additionally, it is found that attitude is positively influenced by usefulness. Moreover, intention to use is positively affected by usefulness and attitude. This research is worthwhile in that it provides service providers with information for constructing better systems.

Surface-enhanced Raman spectroscopy (SERS) is a potent technique for analyzing and detecting various targets, including toxic ions, pesticides, and biomarkers, at the single-molecule level. The efficiency of SERS techniques relies heavily on the underlying SERS substrate, which is primarily responsible for the strong induction of localized plasmon resonance on nanostructures. Noble metals such as gold and silver were commonly used to fabricate SERS substrates, leveraging the electromagnetic mechanism (EM) to enhance the Raman signal. However, chemically synthesized nanoparticle-based SERS substrates suffer from low uniformity and reproducibility. Furthermore, the high cost associated with noble metals makes most SERS substrates expensive to produce. In this study, we present a straightforward method for fabricating a highly uniform and reproducible SERS substrate using a femtosecond laser-based 3D printer. Notably, our method offers good cost competitiveness since it requires only a minimal amount of gold coating for the SERS signal. Moreover, the proposed method exhibits exceptional versatility in SERS analysis and detection, catering to numerous targets in the field.

Abstract Phosphodiesterase-5 inhibitors (PDE-5i, such as Sildenafil, Tadalafil and Vardenafil, mainly prescribed to treat erectile dysfunction) and their generic drug equivalents have been widely marketed and consumed in Korea. From the concentrations detected in wastewater, we could deduce that relatively large amounts of PDE-5i were consumed without a legal prescription. Thus, PDE-5i’s presence in the environment via sewage is unavoidable, and their environmental fate within a sewage treatment plant (STP) should be evaluated. In this study, we investigated the occurrence of three PDE-5i analogs in the influent and effluent of two STPs and the receiving water bodies. The PDE-5i concentration in total reached 62 ± 12 (STP#1) and 88 ± 37 ng L−1 (STP#2) in the sewage influent; about 70% of it was Sildenafil in both STPs. However, they were hardly removed by the STPs as the removal efficiency of the STPs was less than 10% ± 5%. Therefore, the pharmaceuticals were detected in the receiving water (lower than 7 ng L−1as a total amount) and the concentration slightly increased downstream of the STPs. A simple mass balance model applied for the compounds in the STP effluent and receiving water bodies also confirmed that the discharged PDE-5i were quite persistent. Lastly, we identified temporal and regional patterns in the consumption of the drugs from daily variations of PDE-5i in the influent to these two STPs. For instance, the levels of PDE-5i in the sewage significantly increased on weekends (from Friday to Saturday), and especially in the area where adult-entertainment businesses are common. We estimated that the amount of PDE-5i consumption in this area was 31% higher than that in the area with fewer nightlife spots. Considering that they are pharmaceutically active and resistant to treatment processes within an STP, it is advised that a regular monitoring and management program for PDE-5i should be developed to prevent the discharge of the pharmaceuticals into the water environment.

Effective screening of drugs to treat amyloid oligomeric aggregates associated with Alzheimer’s is needed for drug development. Here the authors report on the creation of an amyloid corona around a plasmonic nanoparticle to monitor amyloid degradation when exposed to potential drugs and demonstrate application.

Abstract We have developed the low-temperature conformal ZnO nanowire fabrication on flexible plastic substrates by utilizing the solution-processible metal seed-assisted hydrothermal ZnO crystallization. Structural evolution of ZnO nanowires controlled by major parameters involving growth temperature, growth time, and seed coating condition, has been systematically investigated towards uniform and large-area growth of conformal ZnO nanowires. Direct ZnO nanowire growth on flexible plastics without undergoing the high-temperature seed sintering has been realized by developing the low-temperature Ag-seeded hydrothermal ZnO nanowire growth. The nanoporous Ag layer favorable for ZnO crystal nucleation and continued nanowire growth can be reduced from the Ag ion solution coating at the temperature as low as 130 °C. This tactfully enables the selective hydrothermal growth of ZnO nanowires on the Ag patterns on flexible plastics. Such an all-solution-processible low-temperature fabrication protocol may provide an essential and practical solution to develop many diverse applications including wearable and transparent electronics, sensors, and photocatalytic devices. As one example, we demonstrate that a transparent UV sensor can be devised based on the ZNW growth on the Ag micromesh electrode.

Recently, there has been a rapid increase in the number of (small-cell) base stations (BSs) to support the massive amount of mobile data traffic and rapidly increasing number of mobile devices in beyond 5G (B5G) wireless communication systems or Internet of Things (IoT) networks. However, many of these BSs tend to waste a considerable amount of energy to support such data traffic and mobile devices. Therefore, the development of an efficient BS status control algorithm is important for realizing energy-efficient IoT networks. To reduce network energy consumption, we herein propose a density clustering-based BS control algorithm for energy-efficient IoT networks (DeCoNet). DBSCAN (Density-Based Spatial Clustering of Applications with Noise) and OPTICS (Ordering Points To Identify the Clustering Structure) are utilized for partitioning high and low user-density regions. To find the effective number of BSs and their appropriate locations considering user-density differences, we utilize parameters obtained after applying density clustering algorithms to derive the thinning radius that is used to adjust the status of BSs in overall cellular IoT networks. Specifically, the average reachability-distance of each cluster in OPTICS and the distance between the outermost border users of each cluster in DBSCAN are used to obtain the radius of each cluster region. Through extensive computer simulations, we show that the proposed algorithms outperform the conventional algorithms in terms of average area throughput, energy efficiency, energy per information bit, and power consumption per unit area.

Processes behind Sudden Stratospheric Warming (SSW), which occurs more frequently in the northern hemispheric polar latitudes and its influence from the stratosphere to the upper atmosphere are well documented. However, physical processes associated with SSW, although it ensues rarely in the southern hemisphere (SH), have a strong influence on the background atmosphere from the stratosphere to the mesosphere and are poorly understood. Using a ground-based meteor radar, satellite-borne Microwave-Limb sounder, and Modern-Era Retrospective Analysis for Research and Applications observations, we identified cooling of Antarctic mesopause by 26 K in response to a 66 K warming in the polar stratosphere during the 2019 minor SSW in the SH. The observed cooling is attributed to the interplay between planetary waves, CO2 infrared cooling, and O3 depletion, rather than adiabatic cooling due to gravity waves alone during SSW. It is proposed that anthropogenic and other sources generating chemical tracers in the lower atmosphere have caused mesospheric cooling and could be transported from the lower atmosphere both vertically and meridionally through residual mean meridional circulation from the tropics. Therefore, our study for the first time demonstrates the effect of lower atmosphere chemistry on the polar mesosphere thermal structure during the 2019 SSW.

Personalized PageRank (PPR) is an important variation of PageRank, which is a widely applied popularity measure for Web search. Unlike the original PageRank, PPR is a node proximity measure that represents the degree of closeness among multiple nodes within a graph. It is also widely applied to diverse domains, such as information retrieval, recommendations, and knowledge discovery, due to its theoretical simplicity and flexibility. However, computing PPR in large graphs using naïve algorithms such as iterative matrix multiplication and matrix inversion is not fast enough for many of these applications. Therefore, devising efficient PPR algorithms has been one of the most important subjects in large-scale graph processing. In this paper, we review the algorithms for efficient PPR computations, organizing them into five categories based on their core ideas. Along with detailed explanations including recent advances and their applications, we provide a multifaceted comparison of the algorithms.

Melanoma is visible unlike other types of cancer, but it is still challenging to diagnose correctly because of the difficulty in distinguishing between benign nevus and melanoma. We conducted a robust investigation of melanoma, identifying considerable differences in local elastic properties between nevus and melanoma tissues by using atomic force microscopy (AFM) indentation of histological specimens. Specifically, the histograms of the elastic modulus of melanoma displayed multimodal Gaussian distributions, exhibiting heterogeneous mechanical properties, in contrast with the unimodal distributions of elastic modulus in the benign nevus. We identified this notable signature was consistent regardless of blotch incidence by sex, age, anatomical site (e.g., thigh, calf, arm, eyelid, and cheek), or cancer stage (I, IV, and V). In addition, we found that the non-linearity of the force-distance curves for melanoma is increased compared to benign nevus. We believe that AFM indentation of histological specimens may technically complement conventional histopathological analysis for earlier and more precise melanoma detection.

A Fabry-Perot interferometer (FPI) for mesospheric observations was installed at King Sejong Station (62.2°S, 58.9°W) in Antarctica in 2017. For the initial validation of the FPI measurements, we compare neutral wind data recorded with the FPI with those from a Meteor Radar (MR) located nearby. The overall characteristics of the FPI and MR winds of both OH 892.0 nm (87 km) and OI 557.7 nm (97 km) airglow layers are similar. The FPI winds of both layers generally match the MR winds well on the observed days, with a few exceptions. The correlation analysis of the FPI and MR wind data shows that the correlation coefficients for the zonal winds at 87 and 97 km are 0.28 and 0.54, respectively, and those for the meridional winds are 0.36 and 0.54, respectively. Based on the assumption that the distribution of the airglow emissions has a Gaussian function with respect to the altitude, we calculated the weighted mean winds from the MR wind profile and compared them with the FPI winds. By adjusting the peak height and full width at half maximum of the Gaussian function, we determined the change of the correlation between the two winds. The best correlation for the OH and OI airglow layers was obtained at a peak height of 88–89 km and 97–98 km, respectively.

Processes that monitor the nucleation of amyloids and characterize the formation of amyloid fibrils are vital to medicine and pharmacology. In this study, we observe the nucleation and formation of lysozyme amyloid fibrils using a facile microfluidic system to generate nanoliter droplets that can control the flow rate and movement of monomer-in-oil emulsion droplets in a T-junction microchannel. Using a fluorescence assay, we monitor the nucleation and growth process of amyloids based on the volume of droplets. Using the microfluidic system, we demonstrate that the lag phase, which is vital to amyloid nucleation and growth, is reduced at a lower droplet volume. Furthermore, we report a peculiar phenomenon of high amyloid formation at the edge of a bullet-shaped droplet, which is likely due to the high local monomer concentration. Moreover, we discovered that amyloid fibrils synthesized in the nanoliter droplets are shorter and thicker than fibrils synthesized from a bulk solution via the conventional heating method. Herein, a facile procedure to observe and characterize the nucleation and growth of amyloid fibrils using nanoliter droplets is presented, which is beneficial for investigating new features of amyloid fibril formation as an unconventional synthetic method for amyloid fibrils.

Incineration plants using solid refused fuel (SRF) should control their air pollution materials to minimize environmental impact. This study evaluated the emission of polychlorinated dibenzo-p-dioxin/dibenzofurans (PCDD/DFs) congener patterns in seven commercial incineration plants in Korea using SRF and biomass SRF (bio-SRF). We examined the reduction rate differences of PCDD/DFs, depending on the air pollutant control device. All seven incineration plants sufficiently managed their dioxin emissions. However, both SRF and bio-SRF incineration plants showed active chlorination reactions and resulted in a large amount of highly chlorinated dioxins. The average dioxin concentration was 0.02 ng international toxic equivalency quantity (I-TEQ)/Sm3. Ratios of 1,2,3,4,6,7,8-HpCDF and 1,2,3,7,8-PeCDF were high in the waste heat boilers of both SRF and bio-SRF incineration plants. The octachlorinated dibenzofuran (OCDF) ratio was only high in the SRF incineration plants. Octachlorodibenzo-p-dioxin (OCDD) and OCDF exhibited high dioxin ratios. SRF incineration plants had a low ratio of OCDF to 1,2,3,4,6,7,8-HpCDF. In addition, the reduction rate of PCDD/DFs was substantially high after treatment with the air pollutant control device.

Hydrogels containing colorimetric nanoparticles have been used for ion sensing, glucose detection, and microbial metabolite analyses. In particular, the rapid chemical reaction owing to both the hydrogel form of water retention and the sensitive color change of nanoparticles enables the rapid detection of target substances. Despite this advantage, the poor dispersibility of nanoparticles and the mechanical strength of nanoparticle–hydrogel complexes have limited their application. In this study, we demonstrate a milliliter agarose gel containing homogeneously synthesized polyaniline nanoparticles (PAni-NPs), referred to as PAni-NP–hydrogel complexes (PNHCs). To fabricate the optimal PNHC, we tested various pH solvents based on distilled water and phosphate-buffered saline and studied the colorimetric response of the PNHC with thickness. The colorimetric response of the prepared PNHC to the changes in the pH of the solution demonstrated excellent linearity, suggesting the possibility of using PNHC as a pH sensor. In addition, it was verified that the PNHC could detect minute pH changes caused by the cancer cell metabolites without cytotoxicity. Furthermore, the PNHC can be stably maintained outside water for approximately 12 h without deformation, indicating that it can be used as a disposable patch-type wearable biosensing platform.

Treatment with nonsteroidal anti-inflammatory drugs (NSAIDs) is associated with various side effects, including cardiovascular and hepatic disorders. Studies suggest that mitochondrial damage and oxidative stress are important mediators of toxicity, yet the underlying mechanisms are poorly understood. In this study, we identified that some NSAIDs, including diclofenac, inhibit autophagic flux in hepatocytes. Further detailed studies demonstrated that diclofenac induced a reactive oxygen species (ROS)-dependent increase in lysosomal pH, attenuated cathepsin activity and blocked autophagosome-lysosome fusion. The reactivation of lysosomal function by treatment with clioquinol or transfection with the transcription factor EB restored lysosomal pH and thus autophagic flux. The production of mitochondrial ROS is critical for this process since scavenging ROS reversed lysosomal dysfunction and activated autophagic flux. The compromised lysosomal activity induced by diclofenac also inhibited the fusion with and degradation of mitochondria by mitophagy. Diclofenac-induced cell death and hepatotoxicity were effectively protected by rapamycin. Thus, we demonstrated that diclofenac induces the intracellular ROS production and lysosomal dysfunction that lead to the suppression of autophagy. Impaired autophagy fails to maintain mitochondrial integrity and aggravates the cellular ROS burden, which leads to diclofenac-induced hepatotoxicity.

Objective This study was intended to identify genes positively selected in Thoroughbred horses (THBs) that potentially contribute to their running performances. Methods The genomes of THB and Jeju horses (JH, Korean native horse) were compared to identify genes positively selected in THB. We performed cross-population extended haplotype homozygosity (XP-EHH) and cross-population composite likelihood ratio test (XP-CLR) statistical methods for our analysis using whole genome resequencing data of 14 THB and 6 JH. Results We identified 98 (XP-EHH) and 200 (XP-CLR) genes that are under positive selection in THB. Gene enrichment analysis identified 72 gene ontology biological process (GO BP) terms. The genes and GO BP terms explained some of THB’s characteristics such as immunity, energy metabolism and eye size and function related to running performances. GO BP terms that play key roles in several cell signaling mechanisms, which affected ocular size and visual functions were identified. GO BP term Eye photoreceptor cell differentiation is among the terms annotated presumed to affect eye size. Conclusion Our analysis revealed some positively selected candidate genes in THB related to their racing performances. The genes detected are related to the immunity, ocular size and function, and energy metabolism.

Due to the ban on the use of food waste as wet swine feed after the outbreak of African swine fever (ASF), 2900 tons/day of food waste and 1083 tons/day of food waste leachate were additionally generated. As an alternative treatment method for food waste leachate, the input of food waste leachate on weekends (5% of food waste leachate inflow, 100 tons/day) and its increased input (merge ratio 21.7%, 227.01 tons/day → 27.8%, 453.71 tons/day) into the digesters operated in a public sewage treatment plant were investigated. Additionally, the feasibility of the method was evaluated by analyzing the operation parameters, evaluating the operation efficiency, and identifying other environmental effects on the sewage treatment plant. In the case of input on weekends, the organic matter decomposition rate and gas production rate decreased by 8.0% and 9.5%, respectively, although the input on weekends was judged to be feasible, considering that the inflow into the WWTP increased by up to 206% due to the long-term (7 weeks) monsoon. In the case of the increased input of food waste leachate, the organic matter decomposition and gas production rates increased by 2.5% and 4.8%, respectively, compared with before the increased input. The results of this study confirmed that the additional input of food waste leachate into existing biogasification facilities is feasible. When performed in a stable manner, the use of food waste for anaerobic digestion is considered an appropriate alternative treatment method to wet feed. This will lead to technological and industrial development.

A network composed of unmanned aerial vehicles (UAVs), serving as base stations (UAV-BS network), is emerging as a promising component in next-generation communication systems. In the UAV-BS network, the optimal positioning of a UAV-BS is an essential requirement to establish line-of-sight (LoS) links for ground users. A novel deep Q-network (DQN)-based learning model enabling the optimal deployment of a UAV-BS is proposed. Moreover, without re-learning of the model and the acquisition of the path information of ground users, the proposed model presents the optimal UAV-BS trajectory while ground users move. Specifically, the proposed model optimizes the trajectory of a UAV-BS by maximizing the mean opinion score (MOS) for ground users who move to various paths. Furthermore, the proposed model is highly practical because, instead of the locations of individual mobile users, an average channel power gain is used as an input parameter. The accuracy of the proposed model is validated by comparing the results of the model with those of a mathematical optimization solver.

Objective Increasing food safety demands in the animal product market have created a need for a system to trace the food distribution process, from the manufacturer to the retailer, and genetic traceability is an effective method to trace the origin of animal products. In this study, we successfully achieved the farm tracing of 6,018 multi-breed pigs, using single nucleotide polymorphism (SNP) markers strictly selected through least absolute shrinkage and selection operator (LASSO) feature selection. Methods We performed farm tracing of domesticated pig (Sus scrofa) from SNP markers and selected the most relevant features for accurate prediction. Considering multi-breed composition of our data, we performed feature selection using LASSO penalization on 4,002 SNPs that are shared between breeds, which also includes 179 SNPs with small between-breed difference. The 100 highest-scored features were extracted from iterative simulations and then evaluated using machine-leaning based classifiers. Results We selected 1,341 SNPs from over 45,000 SNPs through iterative LASSO feature selection, to minimize between-breed differences. We subsequently selected 100 highest-scored SNPs from iterative scoring, and observed high statistical measures in classification of breeding farms by cross-validation only using these SNPs. Conclusion The study represents a successful application of LASSO feature selection on multi-breed pig SNP data to trace the farm information, which provides a valuable method and possibility for further researches on genetic traceability.

AIM: To investigate the change of anterior chamber angle morphology and intraocular pressure (IOP) reduction after cataract surgery in patients with normal-tension glaucoma (NTG) using swept-source optical coherence tomography (SS-OCT). METHODS: This prospective, comparative, observational study recruited patients into two groups. Group 1 was the control group including normal subjects except those with cataracts (cataract group, n=67 eyes of 67 patients), and group 2 was NTG group including patients who were diagnosed with NTG and cataracts (n=43 eyes of 43 patients), which were treated with phacoemulsification and intraocular lens implantation. Before surgery, and at postoperative 1 and 6mo, anterior chamber angles were evaluated by SS-OCT under dark conditions using three-dimensional angle analysis scan protocol. Angle opening distance (AOD), angle recess area (ARA), and trabecular-iris surface area (TISA) at four quadrants (temporal, nasal, superior, and inferior) were calculated automatically by SS-OCT, after the observer marked scleral spurs. RESULTS: A total of 106 patients (54 males and 52 females) were enrolled in the study. Angle parameters, AOD, ARA, and TISA were increased after surgery in both groups. However, changes of angle parameters were only significant in group 2. In group 2, preoperative IOP was 13.2±2.9 mm Hg, and postoperative IOP at 1 and 6mo were 10.5±3.0 and 10.7±2.8 mm Hg, respectively. In group 1, preoperative IOP was 12.4±2.8 mm Hg, and postoperative IOP at 1 and 6mo were 11.6±2.5 and 12.0±2.8 mm Hg, respectively. After cataract surgery, angle parameters changed significantly while IOP significantly reduced and was maintained in group 2 (P

Abstract Background The aim of this work is to evaluate efficacy and tolerability of preservative containing 0.0015% tafluprost and preservative-free 0.0015% tafluprost using a prospective crossover study. Methods Primary open angle glaucoma (POAG) and normotensive glaucoma (NTG) patients were randomized enrolled. Group 1 (“NPT to PT”) patients used preservative-free 0.0015% tafluprost (NPT) for 6 months and then changed to preservative containing 0.0015% tafluprost(PT) for 6 months. Group 2 (“PT to NPT”) patients used preservative containing 0.0015% tafluprost for 6 months and changed to preservative-free 0.0015% tafluprost for 6 months. At 1, 3, 6, 7, 9, and 12 months, we measured intraocular pressure for efficacy and graded corneal erosion, tear break-up time (TBUT), and subjective discomfort. Results A total of 20 patients and 20 eyes were enrolled. In Group 1 and 2, intraocular pressure was well controlled to approximately 14 mmHg (9.38–18.46% decrease). Generally, subjective satisfaction was improved after changing from PT to NPT (p = 0.03) and TBUT using PT was numerically inferior to that using NPT (p = 0.06) but not when changing from NPT to PT. Conclusion Both preservative containing and preservative-free 0.0015% tafluprost reduced intraocular pressure significantly. In addition, changing medication from PT to NPT might improve subjective satisfaction and tear break up time. Trial registration The trial registration number is NCT 03104621 (Apr/1/2017). Retrospectively registered.

Thermal interface materials (TIMs), typically composed of a polymer matrix with good wetting properties and thermally conductive fillers, are applied to the interfaces of mating components to reduce the interfacial thermal resistance. As a filler material, silver has been extensively studied because of its high intrinsic thermal conductivity. However, the high cost of silver and its toxicity has hindered the wide application of silver-based TIMs. Copper is an earth-abundant element and essential micronutrient for humans. In this paper, we present a copper-based multi-dimensional filler composed of three-dimensional microscale copper flakes, one-dimensional multi-walled carbon nanotubes (MWCNTs), and zero-dimensional copper nanoparticles (Cu NPs) to create a safe and low-cost TIM with a high thermal conductivity. Cu NPs synthesized by microwave irradiation of a precursor solution were bound to MWCNTs and mixed with copper flakes and polyimide matrix to obtain a TIM paste, which was stable even in a high-temperature environment. The cross-plane thermal conductivity of the copper-based TIM was 36 W/m/K. Owing to its high thermal conductivity and low cost, the copper-based TIM could be an industrially useful heat-dissipating material in the future.

Milk-related traits (milk yield, fat and protein) have been crucial to selection of Holstein. It is essential to find the current selection trends of Holstein. Despite this, uncovering the current trends of selection have been ignored in previous studies. We suggest a new formula to detect the current selection trends based on single nucleotide polymorphisms (SNP). This suggestion is based on the best linear unbiased prediction (BLUP) and the Fisher’s fundamental theorem of natural selection both of which are trait-dependent. Fisher’s theorem links the additive genetic variance to the selection coefficient. For Holstein milk production traits, we estimated the additive genetic variance using SNP effect from BLUP and selection coefficients based on genetic variance to search highly selective SNPs. Through these processes, we identified significantly selective SNPs. The number of genes containing highly selective SNPs with p-value

In this paper, a novel distributed scheduling scheme for an ad-hoc network is proposed. Specifically, the throughput and the delay of packets with different importance are flexibly adjusted by quantifying the importance as weight factors. In this scheme, each node is equipped with two queues, one for packets with high importance and the other for packets with low importance. The proposed scheduling scheme consists of two procedures: intra-node slot reallocation and inter-node reallocation. In the intra-node slot reallocation, self-fairness is adopted as a key metric, which is a composite of the quantified weight factors and traffic loads. This intra-node slot reallocation improves the throughput and the delay performance. Subsequently, through an inter-node reallocation algorithm adopted from LocalVoting (slot exchange among queues having the same importance), the fairness of traffics with the same importance is enhanced. Thorough simulations were conducted under various traffic load and weight factor settings. The simulation results show that the proposed algorithm can adjust packet delivery performance according to a predefined weight factor. Moreover, compared with conventional algorithms, the proposed algorithm achieves better performance in throughput and delay. The low average delay while attaining the high throughput ensures the excellent performance of the proposed algorithm.

African indigenous cattle breeds have been reared within the continent for millennia. Due to the harsh tropical environmental conditions (e.g. sever disease and parasite prevalence, high temperature, feed and water scarcity) where they evolved, they have developed various levels of tropical environment adaptation attributes. In order to explore the genomic signatures of tropical environment adaptation in African cattle, we compared the whole genomes of East African Indicus cattle breeds with European and Asian Taurine cattle breeds using XP-EHH and XP-CLR population statistical methods. Several genes involved in various biological processes and pathways related to domestication and behavior (dopaminergic and glutamatergic synapse), feeding and metabolism (gastric acid secretion, metabolic pathways), thermotolerance (sphingolipid and Wnt signaling), immune system response (T cell receptor signaling), and growth and reproduction (osteoblast differentiation, fibroblast migration) were identified from our genome analysis. Genes associated with tick and parasite resistance traits such as keratin genes, collagen genes, calcium signaling, and tumor necrosis factor proteins were also identified. The genes and pathways identified in this study improve our understanding of the biological mechanisms of tropical environment adaptation of African Indicus cattle breeds, which may allow us to use them for genomic selection programs. This result presents a basis for further study and may help to develop vaccines for tick and gastrointestinal parasite challenge.

The Thoroughbred horse breed was developed primarily for racing, and has a significant contribution to the qualitative improvement of many other horse breeds. Despite the importance of Thoroughbred racehorses in historical, cultural, and economical viewpoints, there was no temporal and spatial dynamics of them using the mitogenome sequences. To explore this topic, the complete mitochondrial genome sequences of 14 Thoroughbreds and two Przewalski's horses were determined. These sequences were analyzed together along with 151 previously published horse mitochondrial genomes from a range of breeds across the globe using a Bayesian coalescent approach as well as Bayesian inference and maximum likelihood methods. The racing horses were revealed to have multiple maternal origins and to be closely related to horses from one Asian, two Middle Eastern, and five European breeds. Thoroughbred horse breed was not directly related to the Przewalski's horse which has been regarded as the closest taxon to the all domestic horses and the only true wild horse species left in the world. Our phylogenomic analyses also supported that there was no apparent correlation between geographic origin or breed and the evolution of global horses. The most recent common ancestor of the Thoroughbreds lived approximately 8,100-111,500 years ago, which was significantly younger than the most recent common ancestor of modern horses (0.7286 My). Bayesian skyline plot revealed that the population expansion of modern horses, including Thoroughbreds, occurred approximately 5,500-11,000 years ago, which coincide with the start of domestication. This is the first phylogenomic study on the Thoroughbred racehorse in association with its spatio-temporal dynamics. The database and genetic history information of Thoroughbred mitogenomes obtained from the present study provide useful information for future horse improvement projects, as well as for the study of horse genomics, conservation, and in association with its geographical distribution.

This study considers a ultra-dense network (UDN) in which the enormous number of base stations (BSs) are densely deployed to support the massive amount of data traffic generated by many mobile devices. In this paper, we propose an approximate thinning-based judicious network control algorithm for energy-efficient UDNs (ACEnet) to improve the area throughput while diminishing the network energy consumption. The main idea of the proposed ACEnet algorithm is to judiciously adjust the modes of the BSs according to active-user density based on the thinning operation in stochastic geometry framework. The stochastic geometry framework is exploited to analyze the performance of the proposed algorithm, which includes the signal-to-interference-plus-noise ratio (SINR), average achievable rate of users, area throughput, and energy efficiency. Through intensive simulations, it shows that the proposed algorithm outperforms conventional algorithms. We also demonstrate that the analytical results are well matched with the simulation results.

Determination of the conformation (monomer, oligomer, or fibril) of amyloid peptide aggregates in the human brain is essential for the diagnosis and treatment of Alzheimer’s disease (AD). Accordingly, systematic investigation of amyloid conformation using analytical tools is essential for precisely quantifying the relative amounts of the three conformations of amyloid peptide. Here, we developed a reduced graphene oxide (rGO) based multiplexing biosensor that could be used to monitor the relative amounts of the three conformations of various amyloid-β 40 (Aβ40) fluids. The electrical rGO biosensor was composed of a multichannel sensor array capable of individual detection of monomers, oligomers, and fibrils in a single amyloid fluid sample. From the performance test of each sensor, we showed that this method had good analytical sensitivity (1 pg/mL) and a fairly wide dynamic range (1 pg/mL to 10 ng/mL) for each conformation of Aβ40. To verify whether the rGO biosensor could be used to evaluate the relative amounts of the three conformations, various amyloid solutions (monomeric Aβ40, aggregated Aβ40, and disaggregated Aβ40 solutions) were employed. Notably, different trends in the relative amounts of the three conformations were observed in each amyloid solution, indicating that this information could serve as an important parameter in the clinical setting. Accordingly, our analytical tool could precisely detect the relative amounts of the three conformations of Aβ40 and may have potential applications as a diagnostic system for AD.