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Summary: Low doses of general anesthetics like ketamine and dexmedetomidine have anxiolytic properties independent of their sedative effects, but the underlying mechanisms remain unclear. We discovered a population of GABAergic neurons in the oval division of the bed nucleus of the stria terminalis that are activated by multiple anesthetics and the anxiolytic drug diazepam (ovBNSTGA). The majority of ovBNSTGA neurons express neurotensin receptor 1 (Ntsr1) and form circuits with brain regions known to regulate anxiety and stress responses. Optogenetic activation of ovBNSTGA or ovBNSTNtsr1 neurons significantly attenuated anxiety-like behaviors in both naive animals and mice with inflammatory pain, while inhibition of these cells elevated anxiety. Activation of these neurons decreased heart rate and increased heart rate variability, suggesting that they reduce anxiety by modulating autonomic responses. Our study identifies ovBNSTGA/ovBNSTNtsr1 neurons as a common neural substrate mediating the anxiolytic effect of low-dose anesthetics and a potential therapeutic target for treating anxiety-related disorders.

Mobile robots often follow humans in warehouse environments or indoor office spaces. A mobile robot requires a control system that stably follows humans without colliding with them. A human-following robot is composed of target detection, target tracking, and control. Conventional 2D laser-based human following systems exploit information from 2D planar laser data to detect human legs through machine learning methods, such as support vector data description and random forest. However, in crowded or cluttered environments, 2D LiDAR data is limited by the lack of features that distinguish human legs from obstacles. Due to the lack of features, false-positive detection is a problem in crowded or cluttered environments. Recent studies using 3D LiDAR have used sensors mounted at an elevated height to measure the overall shape of a person to extract features. Typical mobile robots are mounted in the bottom due to the vibration of the sensors, so there is a cost problem that additional sensors are required. We propose a framework for human following using 3D LiDAR. Our method is able to detect human legs using a LiDAR sensor attached at a low position without additional sensors. This study proposes a 3D laser-based human leg detection and tracking framework to improve the robustness of human-following for autonomous mobile robots. With a deep learning-based human leg detector, using the Point-Voxel-RCNN model, the proposed 3D human leg tracking system can help robots robustly follow humans in cluttered and crowded environments. Additionally, we demonstrate the robustness of our method in a practical cluttered environment by comparing the performance of a conventional human leg detection and following system.

AbstractThe complete mitochondrial genome of Chrysemys dorsalis in Korea was sequenced and characterized. The mitochondrial genome is 17,258 bp in length and the GC content is 39%. It is constituted of 37 genes, 13 protein-coding genes, 22 transfer RNA genes, 2 ribosomal RNA genes, and a noncoding region. Phylogenetic analysis reveals that C. dorsalis forms a monophyletic group with C. picta turtles but is distinctly separated from them, aligning with previous findings. In Korea, C. dorsalis forms a discrete clade, separate from both native and invasive turtle species. No evidence of genetic disturbance or intermingling is observed. This is the first case of a complete mitochondrial genome from C. dorsalis and provides crucial data for understanding C. dorsalis and managing invasive species effectively, emphasizing the need for continued mitochondrial genome data accumulation.

AbstractSternotherus carinatus has been considered as a potential invasive species in Korea. However, the mitochondrial genome information of S. carinatus which can be used to control its effect on ecosystem is lacking. In this study, the complete mitochondrial genome of S. carinatus in Korea was sequenced and characterized. The mitochondrial genome consists of 37 genes (13 protein-coding genes, 22 transfer RNA genes, and 2 ribosomal RNA genes) and a noncoding region. Phylogenetic analysis based on the mitochondrial genome sequences showed that S. carinatus from Korea is separated from other turtles which are the invasive species in Korea. Sequence divergence calculations indicated near-zero divergence between S. carinatus populations in Korea, the USA, and China, suggesting limited genetic differentiation. In the context of the broader issue of invasive species disrupting ecosystems, this research contributes to the identification of mitochondrial genomes for various freshwater turtle species, emphasizing the need for extended data collection to discern genetic mixing trends between native and non-native species. This study is a significant step toward managing S. carinatus as a potential invasive species in Korea.

AbstractThe complete mitochondrial genome of Chrysemys picta bellii in Korea was sequenced and characterized. The mitochondrial genome consists of 37 genes (13 protein-coding genes, 22 transfer RNA genes, and 2 ribosomal RNA genes) and a noncoding region. Phylogenetic analysis based on the mitochondrial genome sequences revealed that C. p. bellii from Korea formed a cluster with C. p. bellii from China and C. picta from the USA, while showing clear separation from other turtle species within the C. picta cluster. This study presented the first complete mitochondrial genome from C. p. bellii in Korea, offering crucial information for managing invasive species and protecting the local ecosystem.

To guarantee the right to move for residents in areas where public transportation is insufficient, research is needed to identify vulnerable areas and prepare measures. This paper defines the vulnerable regions of public transportation within various city types in Korea. In order to identify appropriate areas to apply the Demand Responsive Transit (DRT), the regions with vulnerability were compared with a specific city (Yangsan-si) which already the DRT system was successfully adopted. To collect monthly bus data, web-data crawling method was performed and processed with coordinating program by matching GPS coordinate. The public transportation demand was predicted for each grid cell size (100 m, 250 m, and 500 m) by different methodologies. Various data mining models based on regression were analyzed to predict bus demand of vulnerable areas. Among models, a modified model was suggested to combine Automated machine learning models for high prediction performance. The modified model outperformed other methods as 0.685 and prediction performance was appropriate at 100 m rectangle grid. Regional characters of DRT bus allocation areas were extracted by K-means clustering method and differentiate urban and suburban types. The findings of this study provide valuable insights into conditions that DRT bus stop can be installed. The urban bus stop areas located in metropolitan cities and the suburban bus stop allocation areas located in countryside. The study results can be used as policy data for the successful introduction to prevent social exclusion and improve resident welfare in the future.

Abstract Global climate change has compelled many to rely on photovoltaic (PV) technology to meet the highly demanding energy needs of urban areas. In particular, transparent photovoltaic (TPV) devices can be utilized for building windows, not only supplying electric energy but also improving the overall thermal efficiency of a building. In this work, NiO/ZnO wide‐bandgap oxide TPV heterojunctions are fabricated with Ag nanowire (NW) top electrodes and their PV characteristics are investigated. Special attention is paid to the contributions of surface plasmon (SP) excitation in AgNWs to the PV performance of the TPV device. Light polarized perpendicular to the AgNW axis induces a localized SP resonance in AgNWs at a wavelength of 400 nm, as shown by optical measurements and calculations. The investigation on how the plasmonic AgNWs affect real‐space electric potential distributions and local current‐voltage characteristics of the TPV devices uses Kelvin probe force microscopy and current‐sensing atomic force microscopy, respectively. The spatial redistribution and transport of photogenerated charge carriers strongly depend on the polarization as well as the wavelength of incident light. The results demonstrate that the AgNW‐based top electrodes boost the wavelength‐selective absorption and the effective collection of photocarriers in TPV devices.

Abstract We report the electronic absorption spectroscopy of 7,7,8,8-tetracyanoquinodimethane (TCNQ) and its fluorinated derivatives (F2TCNQ and F4TCNQ), well-known electron-accepting molecules in common organic solvents (toluene, chlorobenzene, acetonitrile, and ethanol) under controlled exposure to air (O2) and UV light. All compounds (FxTCNQ (x = 0, 2, 4)) were stable in a neutral state (FxTCNQ0) in toluene and chlorobenzene, even under both O2 and UV light. On the other hand, in EtOH, the formation of FxTCNQ·− was monitored upon controlled exposure to O2 or UV light. Especially in air-equilibrated ethanol upon the UV-illumination, efficient α,α-dicyano-p-toluoylcyanide anion (DCTC−) and its fluorinated derivatives were generated evinced by the absorption peak near 480 nm, whereas the reaction was shut off by removing O2 or blocking UV light, thereby keeping FxTCNQ·− stable. However, even in deaerated ethanol, upon the UV-illumination, the anion formation of TCNQ and its fluorinated derivatives (FxTCNQ·−, x = 0, 2, 4) was inevitable, showing the stability of FxTCNQ0 depends on the choice of solvent.

The advent of autonomous vehicles (AVs) in the traffic stream is expected to innovatively prevent crashes resulting from human errors in manually driven vehicles (MVs). However, substantial safety benefits due to AVs are not achievable quickly because the mixed-traffic conditions in which AVs and MVs coexist in the current road infrastructure will continue for a considerably long period of time. The purpose of this study is to develop a methodology to evaluate the driving safety of mixed car-following situations between AVs and MVs on freeways based on a multi-agent driving-simulation (MADS) technique. Evaluation results were used to answer the question ‘What road condition would make the mixed car-following situations hazardous?’ Three safety indicators, including the acceleration noise, the standard deviation of the lane position, and the headway, were used to characterize the maneuvering behavior of the mixed car-following pairs in terms of driving safety. It was found that the inter-vehicle safety of mixed pairs was poor when they drove on a road section with a horizontal curve length of 1000 m and downhill slope of 1% or 3%. A set of road sections were identified, using the proposed evaluation method, as hazardous conditions for mixed car-following pairs consisting of AVs and MVs. The outcome of this study will be useful for supporting the establishment of safer road environments and developing novel V2X-based trafficsafetyinformation content that enables the enhancement of mixed-traffic safety.

We test whether Lyα emitters (LAEs) and Lyman-break galaxies (LBGs) can be good tracers of high- z large-scale structures, using the Horizon Run 5 cosmological hydrodynamical simulation. We identify LAEs using the Ly α emission line luminosity and its equivalent width, and LBGs using the broadband magnitudes at z ∼ 2.4, 3.1, and 4.5. We first compare the spatial distributions of LAEs, LBGs, all galaxies, and dark matter around the filamentary structures defined by dark matter. The comparison shows that both LAEs and LBGs are more concentrated toward the dark matter filaments than dark matter. We also find an empirical fitting formula for the vertical density profile of filaments as a binomial power-law relation of the distance to the filaments. We then compare the spatial distributions of the samples around the filaments defined by themselves. LAEs and LBGs are again more concentrated toward their filaments than dark matter. We also find the overall consistency between filamentary structures defined by LAEs, LBGs, and dark matter, with the median spatial offsets that are smaller than the mean separation of the sample. These results support the idea that the LAEs and LBGs could be good tracers of large-scale structures of dark matter at high redshifts.

We describe the survey design and science goals for One-hundred-deg ^2 DECam Imaging in Narrowbands (ODIN), a NOIRLab survey using the Dark Energy Camera (DECam) to obtain deep (AB ∼ 25.7) narrowband images over an unprecedented area of sky. The three custom-built narrowband filters, N 419, N 501, and N 673, have central wavelengths of 419, 501, and 673 nm and respective FWHM of 7.5, 7.6, and 10.0 nm, corresponding to Ly α at z = 2.4, 3.1, and 4.5 and cosmic times of 2.8, 2.1, and 1.4 Gyr, respectively. When combined with even deeper, public broadband data from the Hyper Suprime-Cam, DECam, and in the future, the Legacy Survey of Space and Time, the ODIN narrowband images will enable the selection of over 100,000 Ly α -emitting (LAE) galaxies at these epochs. ODIN-selected LAEs will identify protoclusters as galaxy overdensities, and the deep narrowband images enable detection of highly extended Ly α blobs (LABs). Primary science goals include measuring the clustering strength and dark matter halo connection of LAEs, LABs, and protoclusters, and their respective relationship to filaments in the cosmic web. The three epochs allow for the redshift evolution of these properties to be determined during the period known as Cosmic Noon, where star formation was at its peak. The narrowband filter wavelengths are designed to enable interloper rejection and further scientific studies by revealing [O ii ] and [O iii ] at z = 0.34, Ly α and He ii 1640 at z = 3.1, and Lyman continuum plus Ly α at z = 4.5. Ancillary science includes similar studies of the lower-redshift emission-line galaxy samples and investigations of nearby star-forming galaxies resolved into numerous [O iii ] and [S ii ] emitting regions.

Introduction: Autologous chondrocytes (ACs) are Human cell/tissue-based products used for the treatment of joint cartilage defects. Regulatory agencies have established regulations related to ACs to ensure their safety and efficacy. This study investigated the status and characteristics of ACs approved worldwide. Furthermore, the AC-related regulations were compared by country to provide reference materials for the development of product approval procedures. Methods: This study reviewed the current status of global AC products over the past 20 years by referring to the AC approval list provided on the International Society for Cell & Gene Therapy (ISCT) website. Based on the review report provided by the regulatory agencies that approved the products, major nonclinical/clinical data and product characteristics were reviewed; and the classification and definition of ACs and the approval review procedures were compared through the regulatory agencies’ websites. The development status of ACs was also analyzed using a clinical trial registration site. Results: Eight ACs were approved during the study period in Europe, the US, Japan, Australia, and Korea. Two products were withdrawn owing to marketability problems. Human cell/tissue-based products in each country are classified and defined distinguished from biopharmaceuticals, but the approval process for both products is the same. The approval period differs by country, with an average of 282.4 days and the shortest being in Korea (115 days). On Clinical Trials.gov, we screened 46 clinical trials related to ACs, which were conducted in Europe (41%), Korea (20%), and the US (17%). The knee accounted for the largest portion of the indication (37/46, 80%), followed by the ankle or hip joints. Measurements of improvements in function and pain were the main endpoints used to evaluate the efficacy of ACs. Observational studies were conducted to confirm the long-term safety of these products. Conclusions: This is the first study comparing the current status and characteristics of globally approved AC products, as well as their classification and definition by country. In the past two decades, clinical trials have been conducted on the application of ACs in tissue engineering to treat joint cartilage defects. ACs are expected to be used for the treatment of cartilage defect diseases.

The complete mitochondrial genome of Pseudemys concinna in Korea was sequenced and characterized. The mitochondrial genome is constituted of 37 genes (13 protein-coding genes, 22 transfer RNA (tRNA) genes, and two ribosomal RNA (rRNA) genes) and a noncoding region. Phylogenetic analysis based on the complete mitochondrial genome showed that P. concinna has closer relationship with Chrysemys picta than Trachemys scripta elegans. This is the first case for complete mitochondrial genome from P. concinna in Korea, which will provide information for biogeographical studies and management plan for invasive species.

Internet of Things (IoT) is revolutionizing and enhancing the quality of human lives in every aspect. With a disruption of IoT devices and applications, attackers are leveraging weak authentication and access control mechanisms on these IoT devices and applications to gain unauthorized access on user devices and data and cause them harm. Access control is a critical security mechanism to secure the IoT ecosystem which comprises cloud computing and edge computing services along with smart devices. Today major cloud and IoT service providers including Amazon Web Services (AWS), Google Cloud Platform (GCP), and Azure utilize some customized forms of Role-Based Access Control (RBAC) model along with specific authorization policies enabled by policy-based access control models. To enable fine-grained access control and overcome limitations of existing access control models, there is an imminent need to develop a flexible and dynamic access control model for securing smart devices, data and resources in the cloud-enabled IoT architecture. In this paper, we develop a formal attribute-based access control (ABAC) model for AWS IoT by building upon and extending previously developed access control model for AWS IoT, known as AWS-IoTAC model. We demonstrate the applicability of our proposed model through an industrial IoT use case and its implementation in the AWS IoT platform. Our proposed fine grained model for AWS IoT incorporates its existing capabilities and introduces new attributes for IoT entities and attribute-based policies for enabling expressive access control in AWS IoT. We also evaluate the performance of our model on the AWS cloud and IoT platform with the future smart industries use-case to depict the feasibility of our model in a real-world platform.

Traditionally, access control solutions have focused on how to utilize a specific type of decision parameter for access control decisions. While these “decision parameter”-focused approaches have been well accepted, they typically consider access control with centralized administration. Smart and collaborative computing systems (SCSs) such as online social networks, the Internet of Things (IoT) and connected cyber-physical systems (CPSs) require a disparate approach to meet their unique and complex access control requirements primarily because there are multiple participants who create, share, manage and protect resources (e.g., files, smart devices) individually, collaboratively or even competitively. A distinct feature of SCSs is the diffuse nature of control activities and their complex influence on other activities. Activity control (ACON) extends the scope of traditional access control models and considers how multiple administrative authorities (including users) can manage complex and interacting usage, service and control activities. In this paper, we articulate key characteristics and limitations of various existing access control models and highlight the significance and necessity of activity control in smart collaborative ecosystems. We then propose an extended ACON framework for catering to the needs of dynamic SCSs. Furthermore, we compare existing access control design principles and propose a set of activity control design principles for smart and collaborative computing systems. The proposed ACON framework and design principles will provide a solid foundation for secure SCS design and development.

In order to quickly and effectively respond to a newly received criminal case, information regarding the type and severity of the case is crucial for authorities. This paper designs and develops a crime type and risk level prediction technique based on machine learning technology and verifies its performance. The designed technology can predict crime type and crime risk level using a text-based criminal case summary, which is criminal case receipt data. For the text-based criminal case summary data, the KICS data format is considered, which is actual policing data that contains information about criminal cases. For the crime type, 21 representative types of crimes are considered; therefore, the system can predict one of 21 types of crime for each criminal case. Furthermore, to predict the crime risk level, we developed a crime risk calculation formula. The developed formula calculates the crime risk level and outputs the risk score in numerical terms considering the severity and damage level of the criminal case. To predict the crime type and crime risk score, both DNN and CNN-based prediction models were designed and developed. The performance evaluation section shows that, in the case of crime type prediction, the proposed prediction models can achieve better performance than traditional classification algorithms such as naïve Bayes and SVM. The performance of the CNN-based crime type prediction model is about 7% and 8% better than those of the SVM algorithm and the naïve Bayes algorithm, respectively. The performance of the designed technology was comprehensively analyzed and verified through various performance measurement parameters. It is also developed in the form of a software platform with a GUI, allowing field personnel (e.g. police officers) to intuitively identify the type of criminal case and the level of risk from a text-based criminal case summary upon receipt of a new criminal case.

The recent outbreak of blight in pome fruit plants has been a major concern as there are two indistinguishable Erwinia species, Erwinia amylovora and E. pyrifoliae, which cause blight in South Korea. Although there is a strict management protocol consisting of antibiotic-based prevention, the area and the number of cases of outbreaks have increased. In this study, we isolated four bacteriophages, pEp_SNUABM_03, 04, 11, and 12, that infect both E. amylovora and E. pyrifoliae and evaluated their potential as antimicrobial agents for administration against Erwinia-originated blight in South Korea. Morphological analysis revealed that all phages had podovirus-like capsids. The phage cocktail showed a broad spectrum of infectivity, infecting 98.91% of E. amylovora and 100% of E. pyrifoliae strains. The antibacterial effect was observed after long-term cocktail treatment against E. amylovora, whereas it was observed for both short- and long-term treatments against E. pyrifoliae. Genomic analysis verified that the phages did not encode harmful genes such as antibiotic resistance or virulence genes. All phages were stable under general orchard conditions. Collectively, we provided basic data on the potential of phages as biocontrol agents that target both E. amylovora and E. pyrifoliae.

The complete mitochondrial genome of Pseudemys peninsularis in Korea was sequenced and characterized. The mitochondrial genome is constituted of 37 genes (13 protein-coding genes, 22 transfer RNA genes, and two ribosomal RNA genes) and a noncoding region. Phylogenetic analysis based on the 13 protein-coding gene sequences showed that P. peninsularis has closer relationship with Chrysemys picta than Trachemys scripta elegans. This is the first case for a complete mitochondrial genome from P. peninsularis, which will provide information for biogeographical studies and management plans for invasive species.

The complete mitochondrial (mt) genome of Trachemys scripta ssp. in Korea was sequenced and characterized. The mt genome is constituted of 37 genes (13 protein-coding genes, 22 transfer RNA genes and 2 ribosomal RNA genes) and a control region. Phylogenetic analysis based on the complete mt genome showed that the unidentified turtle had the mt genome closely related to that of T. s. elegans, though it had distinct morphology compared to T. s. elegans. This study can provide information for biogeographical studies and management plan for invasive species.

The complete mitochondrial (mt) genome of Trachemys scripta troostii was sequenced and was characterized, which comprised 37 genes (13 protein-coding genes, 22 transfer RNAs, and 2 ribosomal RNAs) and a non-coding control region. Phylogenetic analysis based on the full mt genome indicated that T. s. troostii was more closely related to T. scripta from Canada than to T. s. elegans from China or T. s. scripta fom China. This is the first complete mt genome from T. s. troostii, which provides data for further study of phylogeny in Emydidae.

Although, both neurological examination and neuroimaging represent the main methods for the anatomical localization of lesions in stroke patients, atypical anatomical-functional representation of cortical lateralized syndromes can occur. Herein, we introduce three cases of atypical representation of left hemispheric syndromes with right hemispheric lesions and we explore the possible mechanisms underlying such disorders and their clinical implications.

Cardiac amyloidosis is characterized by the extracellular fibril deposition of amyloid protein in the myocardium. Cerebral embolism caused by cardiac amyloidosis is rare. We report a case of 59-year-old woman with multiple myeloma who developed cerebral infarction probably related to cardiac involvement of amyloidosis, and discuss the pathophysiological mechanisms based on kidney biopsy and characteristic echocardiographic and cardiac magnetic resonance imaging features.

With the recent success of deep learning, the amount of data and computation continues to grow daily. Hence a distributed deep learning system that shares the training workload has been researched extensively. Although a scale-out distributed environment using commodity servers is widely used, not only is there a limit due to synchronous operation and communication traffic but also combining deep neural network (DNN) training with existing clusters often demands additional hardware and migration between different cluster frameworks or libraries, which is highly inefficient. Therefore, we propose TensorLightning which integrates the widely used data pipeline of Apache Spark with powerful deep learning libraries, Caffe and TensorFlow. TensorLightning embraces a brand-new parameter aggregation algorithm and parallel asynchronous parameter managing schemes to relieve communication discrepancies and overhead. We redesign the elastic averaging stochastic gradient descent algorithm with pruned and sparse form parameters. Our approach provides the fast and flexible DNN training with high accessibility. We evaluated our proposed framework with convolutional neural network and recurrent neural network models; the framework reduces network traffic by 67% with faster convergence.

The complete mitochondrial (mt) genome of Trachemys scripta elegans in Korea was sequenced and characterized. The mt genome is constituted of 37 genes (13 protein-coding genes, 22 transfer RNA genes and 2 ribosomal RNA genes) and a noncoding control region. Phylogenetic analysis based on the complete mt genome showed that T. s. elegans Korea has closer relationship with T. scripta Canada than T. s. elegans China. This is the first complete mt genome from T. s. elegans in Korea, which provides information for biogeographical studies and management plan for invasive species.

Polyamides are often used for their superior thermal, mechanical, and chemical properties. They form a diverse set of materials that have a large variation in properties between linear to aromatic compounds, which renders the traditional quantitative structure–property relationship (QSPR) challenging. We use extended connectivity fingerprints (ECFP) and traditional QSPR fingerprints to develop machine learning models to perform high fidelity prediction of glass transition temperature (Tg), melting temperature (Tm), density (ρ), and tensile modulus (E). The non-linear model using random forest is in general found to be more accurate than linear regression; however, using feature selection or regularization, the accuracy of linear models is shown to be improved significantly to become comparable to the more complex nonlinear algorithm. We find that none of the models or fingerprints were able to accurately predict the tensile modulus E, which we hypothesize is due to heterogeneity in data and data sources, as well as inherent challenges in measuring it. Finally, QSPR models revealed that the fraction of rotatable bonds, and the rotational degree of freedom affects polyamide properties most profoundly and can be used for back of the envelope calculations for a quick estimate of the polymer attributes (glass transition temperature, melting temperature, and density). These QSPR models, although having slightly lower prediction accuracy, show the most promise for the polymer chemist seeking to develop an intuition of ways to modify the chemistry to enhance specific attributes.

The rapidly developing technology and lack of standards in the transportation industry for the proposed Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I), and Vehicle-to-Everything (V2X) networks, which all vehicles will operate under, drives concern about information validity and authenticity due to the risk of erroneous or malicious information being injected into a vehicular network (VN). In this paper, we apply a risk management process to a vehicular network that will identify hazards and possible controls that can lower their risk. After researching and reviewing various technologies along with several risk models, we have developed a basic framework for assessing and assigning risk through a phased method that leads to input for our developed model.

In today’s scenario, image watermarking has been an integral part in various multimedia applications. Watermarking is the approach for adding additional information to the existing image to protect the data from modification and to provide data integrity. Frequency transform domain techniques are complex and costly and degrade the quality of the image due to less embedding of bits. The proposed work utilize the original DCT method with some modifications and applies this method on frequency bands of DWT. Furthermore, the output is used in combination with a pixel modification method for embedding and extraction. The proposed outcome is the improvement of performance achieved in terms of time, imperceptibility, and robustness.

Sensorineural hearing loss (SNHL) is a multifactorial disease that more frequently affects preterm newborns. Although a number of maternal conditions have been reported to be associated with preterm birth, little information is available concerning maternal risk factors for the development of SNHL. We aimed to identify maternal and placental risk factors associated with a “refer” result on the newborn hearing screening (NHS) test and subsequently confirmed SNHL in very preterm neonates. Methods: This retrospective cohort study included 267 singleton neonates who were born alive after ≤ 32 weeks. Histopathologic examination of the placenta was performed, and clinical data were retrieved from a computerized perinatal database. Cases with two abnormal findings, “refer” on the NHS test, and presence of SNHL on the confirmation test were retrospectively reviewed based on electronic medical records. Results: Forty-two neonates (15.7%) showed a “refer” result, and, on the confirmation test, permanent SNHL was identified in 1.87% (5/267) of all neonates. Multivariate regression analysis revealed that the presence of funisitis was independently associated with a “refer” on the NHS test, whereas use of antenatal corticosteroids was statistically significantly associated with a reduced incidence of “refer” on the screening test. Neither histologic chorioamnionitis nor prematurity (as defined by low gestational age and birth weight) was associated with a “refer” on the NHS test. By contrast, multivariate analysis with occurrence of SNHL as a dependent variable identified no significant associations with the parameters studied, probably owing to the small total number of neonates with permanent SNHL. Conclusion: Presence of funisitis was significantly and independently associated with increased risk of abnormal NHS results, while administration of antenatal corticosteroids was related to a normal NHS result. These findings support the hypothesis that a systemic fetal inflammatory response, manifested as funisitis, might play a role in the pathogenesis of SNHL in preterm neonates.

In this work, highly osmotic oxidized sucrose-crosslinked polyethylenimine (SP2K) polymers were developed for gene delivery systems, and the transfection mechanism is examined. First, periodate-oxidized sucrose and polyethylenimine 2K (PEI2K) were crosslinked with various feed ratios via reductive amination. The synthesis was confirmed by 1H NMR and FTIR. The synthesized SP2K polymers could form positively charged (~40 mV zeta-potential) and nano-sized (150–200 nm) spherical polyplexes with plasmid DNA (pDNA). They showed lower cytotoxicity than PEI25K but concentration-dependent cytotoxicity. Among them, SP2K7 and SP2K10 showed higher transfection efficiency than PEI25K in both serum and serum-free conditions, revealing the good serum stability. It was found that SP2K polymers possessed high osmolality and endosome buffering capacity. The transfection experiments with cellular uptake inhibitors suggest that the transfection of SP2K polymers would progress by multiple pathways, including caveolae-mediated endocytosis. It was also thought that caveolae-mediated endocytosis of SP2K polyplexes would be facilitated through cyclooxygenase-2 (COX-2) expression induced by high osmotic pressure of SP2K polymers. Confocal microscopy results also supported that SP2K polyplexes would be internalized into cells via multiple pathways and escape endosomes efficiently via high osmolality and endosome buffering capacity. These results demonstrate the potential of SP2K polymers for gene delivery systems.

Human fibroblast growth factor 19 (hFGF19) is a difficult-to-express protein that is frequently fused with another protein for soluble expression. However, residual amino acids after cleavage with protease represent one of the major problems in therapeutic protein development. Here, we introduced synonymous codon substitutions in the N-terminal region encoding sequence of hFGF19 and co-expressed disulfide bond isomerase (ΔssDsbC) to functionally express hFGF19 without any fusion protein. Synonymous codon substitution significantly increased hFGF19 expression. Subsequent co-expression of ΔssDsbC with a selected variant of hFGF19 (scvhFGF19) further increased the proportion of soluble hFGF19 expression in Escherichia coli XL1-Blue. Both total and soluble scvhFGF19 expression increased remarkably in the alternative host, E. coli Origami 2 with mutated thioredoxin reductase and glutathione reductase. scvhFGF19 purification by anion exchange and heparin affinity chromatography resulted in a yield of 6.5 mg/L under normal induction conditions in flask culture. As such, a high cell density culture is expected to achieve an even higher yield. The biological activities of purified scvhFGF19 were assessed based on its ability to activate ERK1/2 signaling pathway in HepG2 hepatocarcinoma cells. In conclusion, the strategy described here may represent an efficient alternative process for the production of hFGF19 and/or related proteins.

With the growth of social network services, users have been able to freely create and share music in ways that were once thought unimaginable. Sharing a music video through such platforms can now be done simply by anyone with access to a computer or smart phone. Online music content can be divided into two major categories—user-generated content (UGC) and company-generated content (CGC). While previous studies on the content of online music videos have examined the impact of this content on, for example, a company's marketing effectiveness and brand image, they have given little attention to the different effects of user engagement of UGC and user engagement of CGC. This study attempts to address this lack by examining how these two kinds of user engagement differently influence user music choices. We will also examine the differing levels of impact on users across the initial, middle, and final periods after a song is released. In order to examine the different impacts of user engagement, we apply an estimation of generalized least squares (GLS) with a panel dataset of 1,035 songs found on Gaon, the official South Korean music ranking chart. We use the number of music video shares generated by users and firms as proxy variables of user engagement in UGC and CGC, respectively. We find that user engagement of UGC and CGC positively influence music sales. We also find that the effects are not static, but rather change in the initial, middle, and final periods after a song is released. In particular, this study finds that the effect of user engagement of UGC on sales is greater than the effect of user engagement of CGC in the initial period but that the effect of the latter becomes similar to that of former at the end of this period. This finding suggests that managers of digital music providers should encourage consumers to create their own content in the initial period, as potential consumers are more likely to buy songs with more UGC content and shares in the initial period.

Partial least squares (PLS) path modeling is a component-based structural equation modeling that has been adopted in social and psychological research due to its data-analytic capability and flexibility. A recent methodological advance is consistent PLS (PLSc), designed to produce consistent estimates of path coefficients in structural models involving common factors. In practice, however, PLSc may frequently encounter multicollinearity in part because it takes a strategy of estimating path coefficients based on consistent correlations among independent latent variables. PLSc has yet no remedy for this multicollinearity problem, which can cause loss of statistical power and accuracy in parameter estimation. Thus, a ridge type of regularization is incorporated into PLSc, creating a new technique called regularized PLSc. A comprehensive simulation study is conducted to evaluate the performance of regularized PLSc as compared to its non-regularized counterpart in terms of power and accuracy. The results show that our regularized PLSc is recommended for use when serious multicollinearity is present.

Tumor tissue represents a slightly acidic pH condition compared to normal tissue due to the accumulation of lactic acids via anaerobic metabolism. In this work, pH-responsive charge-conversional polymer (poly(ethylene imine)-poly(l-lysine)-poly(l-glutamic acid), PKE polymer) was employed for endowing charge-conversional property and serum stability to poly(ethylene imine) conjugated reduced graphene oxide-based drug delivery system (PEI-rGO). Zeta-potential value of PEI-rGO coated with PK5E7 polymer (PK5E7(PEI-rGO)) was −10.9 mV at pH 7.4 and converted to 29.2 mV at pH 6.0, showing pH-responsive charge-conversional property. Sharp-edged plate morphology of PEI-rGO was transformed to spherical nanostructures with vague edges by PK5E7 coating. Size of PK5E7(PEI-rGO) was found to be smaller than that of PEI-rGO in the serum condition, showing its increased serum stability. Loaded doxorubicin (DOX) in PK5E7(PEI-rGO) could be released rapidly in lysosomal condition (pH 5.0, 5 mM glutathione). Furthermore, DOX-loaded PK5E7(PEI-rGO) showed enhanced anticancer activity in HeLa and A549 cells in the tumor microenvironment-mimicking condition (pH 6.0, serum), which would be mediated by non-specific cellular interaction with decorated serum proteins. These results indicate that the pH-responsive charge-conversional PKE polymer coating strategy of cationic rGO nanostructures possesses a potential for acidic tumor microenvironment-targeted drug delivery systems.

Cholic acid-conjugated methylcellulose-polyethylenimines (MCPEI-CAs) were synthesized and characterized for drug delivery systems. Their synthesis was confirmed by 1H NMR and FT-IR analysis. Induced circular dichroism result with Congo red showed that methylcellulose (MC) and polyethylenimine-grafted cationic derivative (MC-PEI) would have helical conformation and random coil structure, respectively. It was found that MCPEI-CAs could form positively charged (>30 mV Zeta-potential) and spherical nano-aggregates (~250 nm Z-average size) by hydrophobic interaction of CA moieties. Critical aggregation concentration of MCPEI-CA10 was measured as 7.2 × 10−3 mg/mL. MCPEI-CA10 could encapsulate the anticancer drug doxorubicin (Dox) with 58.0% of drug loading content and 23.2% of drug loading efficiency and its release was facilitated in acidic condition. Cytotoxicity of MCPEI-CAs was increased with the increase of cholic acid (CA) graft degrees, probably due to the cellular membrane disruption by interaction with specific molecular structure of amphiphilic MCPEI-CA nano-aggregates. MCPEI-CA10/Dox nano-aggregates showed concentration-dependent anticancer activity, which could overcome the multidrug resistance of cancer cells. In this work, molecular conformation change of MC derivatives by chemical modification and a potential of MCPEI-CA10/Dox nano-aggregates for drug delivery systems were revealed.

The MUC1 protein is aberrantly expressed on many solid tumor cancers. In contrast to its apical clustering on healthy epithelial cells, it is uniformly distributed over cancer cells. However, a mechanistic link between aberrant expression and cancer has remained elusive. Herein, we report that a membrane-bound MUC1 cleavage product, that we call MUC1*, is the predominant form of the protein on cultured cancer cells and on cancerous tissues. Further, we demonstrate that transfection of a minimal fragment of MUC1, MUC1*(1110), containing a mere forty-five (45) amino acids of the extracellular domain, is sufficient to confer the oncogenic activities that were previously attributed to the full-length protein. By comparison of molecular weight and function, it appears that MUC1* and MUC1*(1110) are approximately equivalent. Evidence is presented that strongly supports a mechanism whereby dimerization of the extracellular domain of MUC1* activates the MAP kinase signaling cascade and stimulates cell growth. These findings suggest methods to manipulate this growth mechanism for therapeutic interventions in cancer treatments.