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Abstract Chub mackerels (Scomber japonicus) are a migratory marine fish widely distributed in the Indo-Pacific Ocean. They are globally consumed for their high Omega-3 content, but their population is declining due to global warming. Here, we generated the first chromosome-level genome assembly of chub mackerel (fScoJap1) using the Vertebrate Genomes Project assembly pipeline with PacBio HiFi genomic sequencing and Arima Hi-C chromosome contact data. The final assembly is 828.68 Mb with 24 chromosomes, nearly all containing telomeric repeats at their ends. We annotated 31,656 genes and discovered that approximately 2.19% of the genome contained DNA transposon elements repressed within duplicated genes. Analyzing 5-methylcytosine (5mC) modifications using HiFi reads, we observed open/close chromatin patterns at gene promoters, including the FADS2 gene involved in Omega-3 production. This chromosome-level reference genome provides unprecedented opportunities for advancing our knowledge of chub mackerels in biology, industry, and conservation.

RGBW remosaicing is an interpolation technique that converts RGBW images captured using RGBW color filtering arrays into Bayer images. Although recent learning-based approaches using convolutional neural networks have shown substantial performance improvements, most algorithms require high computational and memory complexities, which limit their practical applicability. In this work, we propose an efficient and effective RGBW remosaicing algorithm based on learned kernel-based interpolation. First, the proposed algorithm extracts deep feature maps from input RGBW images. Then, we develop a learned kernel-based interpolation module composed of local and non-local interpolation blocks that generates two intermediate Bayer images. Specifically, the local interpolation block learns local filters to recover a Bayer image, whereas the non-local interpolation block recovers a Bayer image by estimating the non-local filters of dynamic shapes. Finally, a reconstructed Bayer image is obtained by combining the complementary information from the intermediate Bayer images using a spatially weighted fusion block. Experimental results demonstrate that the proposed algorithm achieves comparable or even better performance than state-of-the-art algorithms while providing the lowest computational and memory complexities.

Abstract Background False duplications in genome assemblies lead to false biological conclusions. We quantified false duplications in popularly used previous genome assemblies for platypus, zebra finch, and Anna’s Hummingbird, and their new counterparts of the same species generated by the Vertebrate Genomes Project, of which the Vertebrate Genomes Project pipeline attempted to eliminate false duplications through haplotype phasing and purging. These assemblies are among the first generated by the Vertebrate Genomes Project where there was a prior chromosomal level reference assembly to compare with. Results Whole genome alignments revealed that 4 to 16% of the sequences are falsely duplicated in the previous assemblies, impacting hundreds to thousands of genes. These lead to overestimated gene family expansions. The main source of the false duplications is heterotype duplications, where the haplotype sequences were relatively more divergent than other parts of the genome leading the assembly algorithms to classify them as separate genes or genomic regions. A minor source is sequencing errors. Ancient ATP nucleotide binding gene families have a higher prevalence of false duplications compared to other gene families. Although present in a smaller proportion, we observe false duplications remaining in the Vertebrate Genomes Project assemblies that can be identified and purged. Conclusions This study highlights the need for more advanced assembly methods that better separate haplotypes and sequence errors, and the need for cautious analyses on gene gains.

Abstract Background Many short-read genome assemblies have been found to be incomplete and contain mis-assemblies. The Vertebrate Genomes Project has been producing new reference genome assemblies with an emphasis on being as complete and error-free as possible, which requires utilizing long reads, long-range scaffolding data, new assembly algorithms, and manual curation. A more thorough evaluation of the recent references relative to prior assemblies can provide a detailed overview of the types and magnitude of improvements. Results Here we evaluate new vertebrate genome references relative to the previous assemblies for the same species and, in two cases, the same individuals, including a mammal (platypus), two birds (zebra finch, Anna’s hummingbird), and a fish (climbing perch). We find that up to 11% of genomic sequence is entirely missing in the previous assemblies. In the Vertebrate Genomes Project zebra finch assembly, we identify eight new GC- and repeat-rich micro-chromosomes with high gene density. The impact of missing sequences is biased towards GC-rich 5′-proximal promoters and 5′ exon regions of protein-coding genes and long non-coding RNAs. Between 26 and 60% of genes include structural or sequence errors that could lead to misunderstanding of their function when using the previous genome assemblies. Conclusions Our findings reveal novel regulatory landscapes and protein coding sequences that have been greatly underestimated in previous assemblies and are now present in the Vertebrate Genomes Project reference genomes.

Infrared and visible image fusion aims to generate more informative images of a given scene by combining multimodal images with complementary information. Although recent learning-based approaches have shown significant fusion performance, developing an effective fusion algorithm that can preserve complementary information while preventing bias toward either of the source images remains a significant challenge. In this work, we propose a multiscale progressive fusion (MPFusion) algorithm that extracts and progressively fuses multiscale features of infrared and visible images. The proposed algorithm consists of two networks, IRNet and FusionNet, which extract the intrinsic features of infrared and visible images, respectively. We transfer the multiscale information of the infrared image from IRNet to FusionNet to generate an informative fusion result. To this end, we develop the multi-dilated residual block (MDRB) and the progressive fusion block (PFB), which progressively combines the multiscale features from IRNet with those from FusionNet to fuse complementary features effectively and adaptively. Furthermore, we exploit edge-guided attention maps to preserve complementary edge information in the source images during fusion. Experimental results on several datasets demonstrate that the proposed algorithm outperforms state-of-the-art infrared and visible image fusion algorithms on both quantitative and qualitative comparisons.

We propose an orientation prediction algorithm based on Kalman-like error compensation for virtual reality (VR) and augmented reality (AR) devices using measurements of an inertial measurement unit (IMU), which includes a tri-axial gyroscope and a tri-axial accelerometer. First, the initial prediction of the orientation is estimated by assuming linear movement. Then, to improve the prediction accuracy, the accuracies of previous predictions are taken into account by computing the orientation difference between the current orientation and previous prediction. Finally, we define a weight matrix to determine the optimal adjustments for predictions corresponding to a given orientation, which is obtained by minimizing the estimation errors based on the minimum mean square error (MMSE) criterion using Kalman-like error compensation. Experimental results demonstrate that the proposed algorithm exhibits higher orientation prediction accuracy compared with conventional algorithms on several open datasets.

We propose an end-to-end unpaired learning approach to screen-shot image demoiréing based on cyclic moiré learning. The proposed cyclic moiré learning algorithm consists of the moiréing network and the demoiréing network. The moiréing network generates moiré images to construct a pseudo-paired set of moiré and clean images. Then, the demoiréing network is trained in a supervised manner using the generated pseudo-paired dataset to remove moiré artifacts. In the moiréing network, the moiré generation is separately learned as global pixel intensity degradation and moiré pattern generation for more realistic moiré artifact generation. Furthermore, the moiréing network and the demoiréing network are integrated together to be trained in an end-to-end manner. Experimental results on different datasets demonstrate that the proposed algorithm significantly outperforms state-of-the-art unsupervised demoiréing algorithms as well as image restoration algorithms.

Abstract At a time when the COVID-19 pandemic has been ongoing for more than a year, young people have been the subject of vigilant scrutiny and criticism regarding their active engagement in social activities. We posed the question of whether young people's response to COVID-19 was different from that of other generations and analyzed awareness and behavior to investigate this question. Specifically, we examined internet searches for information on COVID-19 and credit card consumption in South Korea among young people in their 20s and compared them to a reference group of people in their 50s. Our research has confirmed that there was no statistically significant difference between young people and the reference group in this regard. Furthermore, in the 25 sub-sectors of industry we examined, young people's consumption activities recovered significantly faster than the reference group in only three sub-sectors. This study demonstrated that young people showed stronger interest than the reference group in their response to COVID-19, and that they cooperated with the government’s social distancing policy by reducing their activities. Through this study, we presented a scientific approach for evaluating young people in regard to their response to COVID-19, offering useful implications for designing appropriate policies for public health.

Abstract Purpose/objective(s) To communicate our institutional experience with single isocenter radiosurgery treatments for multiple brain metastases, including challenges with determining planning target volume (PTV) margins and resulting consequences, image-guidance translational and rotational tolerances, intra-fraction patient motion, and prescription considerations with larger PTV margins. Materials/methods Eight patient treatments with 51 targets were planned with various margins using Elements Multiple Brain Mets SRS treatment planning software (Brainlab, Munich, Germany). Forty-eight plans with 0 mm, 1 mm and 2 mm margins were created, including plans with variable margins, where targets more than 6 cm away from the isocenter were planned with larger margins. The dosimetric impact of the margins were analyzed with V5Gy, V8Gy, V10Gy, V12Gy values. Additionally, 12 patient motion data were analyzed to determine both the impact of the repositioning threshold and the distributions of the patient translational and rotational movements. Results The V5Gy, V8Gy, V10Gy, V12Gy volumes approximately doubled when margins change from 0 to 1 mm and tripled when change from 0 to 2 mm. With variable margins, the aggregated results are similar to results from plans using the lower of two margins, since only 12.2% of the targets were more than 6 cm away from the isocenter. With 0.5 mm re-positioning threshold, 57.4% of the time the patients are repositioned. Reducing the threshold to 0.25 mm results in 91.7% repositioning rate, due to limitations of the fusion algorithm and actual patient motion. The 90th percentile of translational movements in all directions is 0.7 mm, while the 90th percentile of rotational movements in all directions is 0.6 degrees. Median translations and rotations are 0.2 mm and 0.2 degrees, respectively. Conclusions Based on the data presented, we have switched our modus operandi from 2 to 1 mm PTV margins, with an eventual goal of using 0.5 and 1.0 mm variable margins when an automated margin assignment method becomes available. The 0.5 mm and 0.5 degrees repositioning thresholds are clinically appropriate with small residual patient movements.

The little skate Leucoraja erinacea, a cartilaginous fish, displays pelvic fin driven walking-like behavior using genetic programs and neuronal subtypes similar to those of land vertebrates. However, mechanistic studies on little skate motor circuit development have been limited, due to a lack of high-quality reference genome. Here, we generated an assembly of the little skate genome, with precise gene annotation and structures, which allowed post-genome analysis of spinal motor neurons (MNs) essential for locomotion. Through interspecies comparison of mouse, skate and chicken MN transcriptomes, shared and divergent gene expression profiles were identified. Comparison of accessible chromatin regions between mouse and skate MNs predicted shared transcription factor (TF) motifs with divergent ones, which could be used for achieving differential regulation of MN-expressed genes. A greater number of TF motif predictions were observed in MN-expressed genes in mouse than in little skate. These findings suggest conserved and divergent molecular mechanisms controlling MN development of vertebrates during evolution, which might contribute to intricate gene regulatory networks in the emergence of a more sophisticated motor system in tetrapods.

We propose a single-shot high dynamic range (HDR) imaging algorithm with row-wise varying exposures in a single raw image based on a deep convolutional neural network (CNN). We first convert a raw Bayer input image into a radiance map by calibrating rows with different exposures, and then we design a new CNN model to restore missing information at the under- and over-exposed pixels and reconstruct color information from the raw radiance map. The proposed CNN model consists of three branch networks to obtain multiscale feature maps for an image. To effectively estimate the high-quality HDR images, we develop a robust loss function that considers the human visual system (HVS) model, color perception model, and multiscale contrast. Experimental results on both synthetic and captured real images demonstrate that the proposed algorithm can achieve synthesis results of significantly higher quality than conventional algorithms in terms of structure, color, and visual artifacts.

High dynamic range (HDR) image and video technology can provide significant picture quality improvement over the standard dynamic range (SDR). However, when HDR content is represented on an SDR display, dynamic range compression may result in image quality deterioration. To address this problem, we propose an optimized human visual system (HVS) response model-based tone-mapping algorithm to preserve the perceptual responses between the HDR image and its tone-mapped image. First, we measure the HVS response differences using a 2D histogram when an HDR image is displayed on an HDR device and when its tone-mapped image is displayed on an SDR device. Then, we formulate an optimization problem to minimize the differences. By efficiently solving the optimization problem, we obtain an optimal tone-mapping curve. Experimental results on actual displays demonstrate that the proposed algorithm provides superior image quality compared with conventional algorithms in terms of both subjective and objective evaluations.

We propose a novel monocular depth estimator, which improves the prediction accuracy on human regions by utilizing pose information. The proposed algorithm consists of two networks — PoseNet and DepthNet — to estimate keypoint heatmaps and a depth map, respectively. We incorporate the pose information from PoseNet to improve the depth estimation performance of DepthNet. Specifically, we develop the feature blending block, which fuses the features from PoseNet and DepthNet and feeds them into the next layer of DepthNet, to make the networks learn to predict the depths of human regions more accurately. Furthermore, we develop a novel joint training scheme using partially labeled datasets, which balances multiple loss functions effectively by adjusting weights. Experimental results demonstrate that the proposed algorithm can improve depth estimation performance significantly, especially around human regions. For example, the proposed algorithm improves the depth estimation performance on the human regions of ResNet-50 by 2.8% and 7.0% in terms of $\delta _{1}$ and RMSE, respectively, on the proposed HD + P dataset.

Removing fog components from maritime images is more challenging than removing them from land images because of the complicated scattering effects. In this paper, we propose a single maritime image defogging algorithm based on illumination decomposition. First, we decompose a foggy input image into glow and glow-free layers by formulating an optimization problem and then solving it effectively, where the optimization variables are updated by closed-form solutions. Then, the fog components in the glow-free layer are removed using a defogging algorithm. Finally, the natural illumination in the glow layer is recovered using a compensation scheme to obtain the final fog-free image. Experimental results on real test images demonstrate that the proposed algorithm outperforms state-of-the-art algorithms in terms of both subjective and objective evaluation criteria.

We propose a robust high dynamic range (HDR) video synthesis algorithm using the superpixel-based illuminance-invariant motion estimation technique. The proposed algorithm first selects an input frame in an alternating exposed input video as the reference. Then, the correspondences between two adjacent frames are estimated by employing a feature descriptor, which is robust against illuminance variation, and a superpixel segmentation technique. Next, the input frames are warped to the reference frame using the estimated motion maps. Finally, the final HDR frame is synthesized by constructing a weight map, which can handle complex motions and poor exposures by considering the underlying structures in the input frames. Experimental results on real test sequences show that the proposed algorithm can provide high-quality HDR videos compared with those obtained by state-of-the-art algorithms in terms of both subjective and objective evaluations.

We propose the property-specific aesthetic assessment (PSAA) algorithm with unsupervised aesthetic property discovery. The proposed PSAA algorithm uses an aesthetic feature extractor, an aesthetic property classifier, and multiple property-specific assessment networks. The aesthetic feature extractor analyzes aesthetics of images to generate features. Using such aesthetic features, we discover diverse aesthetic properties in an unsupervised manner and develop the aesthetic property classifier to predict the aesthetic property of each image. For each discovered aesthetic property, we train a property-specific assessment network. Thus, we can assess the aesthetic quality of an image using the property-specific network that corresponds to its property. Experimental results on a large dataset show that the proposed PSAA algorithm achieves state-of-the-art aesthetic assessment performance. Furthermore, we demonstrate that PSAA is useful for improving aesthetic qualities of images in two applications: contrast enhancement and image cropping.

In this paper, the problem of image speckle removal is addressed. To alleviate the pepper-salt remainder in the speckled image, we propose to utilize the nonlocal means filtering, where the weighting coefficients are derived based on the maximum a posteriori estimation with the total variation image prior. As a result, the objective function of the pixel fitting term plus the total variation regularizer is formulated, and it is solved with the majorization-minimization approach. To avoid the computationally intractable step size selection in the huge-scale gradient-based optimization, we split and solve the variables in the pixel fitting term and regularizer by means of the alternating direction method of multipliers. Performance analysis is performed for the Rayleigh and Gamma distributed signal models. The simulation and experimental results show the superior performance compared with other image despeckling methods in terms of various metrics and visual perception.

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.

Objective Holsteins are known as the world’s highest-milk producing dairy cattle. The purpose of this study was to identify genetic regions strongly associated with milk traits (milk production, fat, and protein) using Korean Holstein data. Methods This study was performed using single nucleotide polymorphism (SNP) chip data (Illumina BovineSNP50 Beadchip) of 911 Korean Holstein individuals. We inferred each genomic estimated breeding values based on best linear unbiased prediction (BLUP) and ridge regression using BLUPF90 and R. We then performed a genome-wide association study and identified genetic regions related to milk traits. Results We identified 9, 6, and 17 significant genetic regions related to milk production, fat and protein, respectively. These genes are newly reported in the genetic association with milk traits of Holstein. Conclusion This study complements a recent Holstein genome-wide association studies that identified other SNPs and genes as the most significant variants. These results will help to expand the knowledge of the polygenic nature of milk production in Holsteins.

Basal cell carcinoma (BCC) is the most common human cancer, characterized by aberrant activation of the hedgehog (HH) signaling pathway resulting from mutations in the patched 1 (PTCH1) or smoothened (SMO) genes. In the present study, to uncover the expression profile of HH signaling-related molecules, we thoroughly examined the mRNA and protein expression levels of six molecules including GLI1, GLI2, PTCH1, PTCH2, SHH, and SMO in BCC and various other cutaneous tumors. Real-time PCR analysis demonstrated that BCC showed remarkably enhanced mRNA expression of all HH molecules, except SMO compared to other skin tumors. However, immunohistochemical analysis revealed that only GLI1 protein was specifically upregulated in BCC, while the other HH-related proteins did not show any significant differences between the tumors. Notably, other skin malignancies such as squamous cell carcinoma, sebaceous carcinoma, and malignant melanoma showed no GLI1 expression and there was no difference in GLI1 expression between the BCC subtypes. In addition, GLI1 and GLI2 expression were strongly associated with the hair follicle stem cell markers, LGR4 and LGR5, which are known target genes of the Wnt pathway. Our results suggest that GLI1 has the potential to be a diagnostically useful marker for differentiating BCC from other skin malignancies and an interaction between the HH and Wnt signaling pathways may be involved in the development of BCCs.

Water-to-land transition has been independently evolved in multiple vertebrate lineages including the most recent common ancestor of tetrapod and multiple fish clades, and among them, mudskippers uniquely adapted to the mudflat. Even though physiological and morphological adaptation of mudskippers is thought to resemble that of the ancestral tetrapod, it is unclear if they share genome-wide evolutionary signatures. To detect potential signatures of positive selection in mudskipper and tetrapods, we analyzed 4118 singleton orthologues of terrestrial tetrapods, coelacanth, mudskipper, and fully aquatic fishes. Among positively selected genes identified in mudskipper and tetrapod lineages, genes involved in immune responses, mitochondrial oxidative phosphorylation, and kidney development were detected. On the other hand, tetrapod-specific and mudskipper-specific positively selected genes were functionally enriched for DNA repair processes, which could be associated with higher exposure to UV light. We also performed gene family analysis and discovered convergent contraction of eight gene families, including βγ-crystallin coding genes in both tetrapod and mudskipper lineages. Findings of this study suggest the similar genetic adaptation against environmental constraints between the ancient tetrapod and mudskippers for their land adaptation.

Abstract Delirium can result in undesirable outcomes including increased length of stays and mortality in patients admitted to the intensive care unit (ICU). Dexmedetomidine has emerged for delirium prevention in these patients; however, optimal dosing is challenging. A reinforcement learning-based Artificial Intelligence model for Delirium prevention (AID) is proposed to optimize dexmedetomidine dosing. The model was developed and internally validated using 2416 patients (2531 ICU admissions) and externally validated on 270 patients (274 ICU admissions). The estimated performance return of the AID policy was higher than that of the clinicians’ policy in both derivation (0.390 95% confidence interval [CI] 0.361 to 0.420 vs. −0.051 95% CI −0.077 to −0.025) and external validation (0.186 95% CI 0.139 to 0.236 vs. −0.436 95% CI −0.474 to −0.402) cohorts. Our finding indicates that AID might support clinicians’ decision-making regarding dexmedetomidine dosing to prevent delirium in ICU patients, but further off-policy evaluation is required.

Actigraphy is useful to assess sleep pattern of subjects for several days to several weeks, and collected sleep data is usually averaged out to know the general sleep pattern of each individual. However, intra-individual variability should be considered when assessing sleep patterns, with regard to the phenomenon of daily fluctuation. The aim of this study was to explore whether the mean sleep indices reflect intra-individual variability with regard to environmental noise. Indoor noise and sleep pattern were collected over 5 days, among 22 citizens of Ulsan Metropolitan city. We observed an association between environmental noise indices and various sleep indices such as sleep efficiency, number of awakenings, or fragmentation indices when we analyzed the data of 108 nights from 22 subjects. However, the significances were weakened when we analyzed noise and sleep/wake pattern after averaging out. In conclusion, we observed that the sleep/wake pattern over several days to weeks should not be averaged out when studied in relation with variable physiological phenomena, such as night-to-night variability.

In regenerative medicine, extracellular vesicles (EVs) possess the potential to repair injured cells by delivering modulatory factors. However, the therapeutic effect of EVs in large-scale tissue defects, which are subject to prolonged timelines for tissue architecture and functional restoration, remains poorly understood. In this study, we introduce EVs and cell-tethering hybrid hydrogels composed of tyramine-conjugated gelatin (GelTA) that can be in-situ crosslinked with EVs derived from human induced pluripotent stem cell-derived myofibers (hiPSC-myofibers) and hiPSC-muscle precursor cells. This hybrid hydrogel sustains the release of EVs and provides a beneficial nano-topography and mechanical properties for creating a favorable extracellular matrix. Secreted EVs from the hiPSC-myofibers contain specific microRNAs, potentially improving myogenesis and angiogenesis. Herein, we demonstrate increased myogenic markers and fusion/differentiation indexes through the combinatory effects of EVs and integrin-mediated adhesions in the 3D matrix. Furthermore, we observe a unique impact of EVs, which aid in maintaining the viability and phenotype of myofibers under harsh environments. The hybrid hydrogel in-situ crosslinked with hiPSCs and EVs is facilely used to fabricate large-scale muscle constructs by the stacking of micro-patterned hydrogel domains. Later, we confirmed a combinational effect, whereby muscle tissue regeneration and functional restoration were improved, via an in vivo murine volumetric muscle loss model.

Rotator cuff tears are common among physically active individuals and often require surgical intervention owing to their limited self-healing capacity. This study proposes a new bioprinting approach using bone- and tendon tissue-specific bioinks derived from decellularized extracellular matrix, supplemented with hydroxyapatite and TGF-β/poly(vinyl alcohol) to fabricate engineered tendon-to-bone complex tissue. To achieve this goal, a core-shell nozzle system attached to a bioprinter enables the effective and simultaneous fabrication of aligned tendon tissue, a gradient tendon-bone interface (TBI), and a mechanically improved bone region, mimicking the native tendon-to-bone structure. In vitro evaluation demonstrated the well-directed differentiation of human adipose stem cells towards osteogenic and tenogenic lineages in the bone and tendon constructs. In the graded TBI structure, further facilitated fibrocartilage formation and enhanced the integration of tendon-to-bone tissues compared to non-graded structures in vitro. Furthermore, using a rabbit rotator cuff tear model, implantation of the biologically graded constructs significantly promoted the rapid regeneration of full-thickness tendon-to-bone tissue, including the formation of a high-quality TBI in vivo. This bioprinting approach not only improved mechanical properties and tissue integration but also enhanced angiogenesis and extracellular matrix (ECM) formation, demonstrating its potential as a promising platform for the regeneration of tendon-to-bone complex tissues.

A reproducible analytical method using reverse-phase high liquid performance chromatography combined with UV detecting was developed for the quantitative determination of four compounds isolated from the ethanol extract of Phaseolus angularis seeds (PASE): oleanolic acid (1), oleanolic acid acetate (2), stigmasterol (3) and β-sitosterol (4). This method was fully validated in terms of linearity (r2 > 0.999), accuracy (98.5%–100.8%), precision (

PurposeUreaplasma colonization is related with perinatal complications in preterm infants. Little is known about the difference in virulence among various Ureaplasma urealyticum serovars. The aim of this study was to determine U. urealyticum serovars of preterm infants in order to assess whether any of the serovars were associated with bronchopulmonary dysplasia (BPD).MethodsThree hundred forty-four preterm infants with a gestational age less than 34 weeks admitted to Gangnam Severance Hospital neonatal intensive care unit from July 2011 to December 2012 were included in this study. Tracheal and gastric aspirations were conducted on infants to confirm Ureaplasma colonization. Ureaplasma colonization was confirmed in 9% of infants, of these, serovars were determined by real-time polymerase chain reaction.ResultsA total of 31 infants (gestational age, 29.3±3.1 weeks; birth weight, 1,170±790 g) were U. urealyticum positive. The Ureaplasma positive group treated for more days with oxygen and ventilation than the negative group (P

African swine fever (ASF), a contagious and lethal haemorrhagic disease of domestic pigs and wild boars, poses a significant threat to the global pig industry. Although experimental vaccine candidates derived from naturally attenuated, genetically engineered, or cell culture-adapted ASF virus have been tested, no commercial vaccine is accepted globally. We developed a safe and effective cell-adapted live attenuated vaccine candidate (ASFV-MEC-01) by serial passage of a field isolate in CA-CAS-01-A cells. ASFV-MEC-01, isolated via repeated plaque purification using next-generation sequencing analysis, was obtained at passage 18 and showed significant attenuation in 4- and 6-week-old pigs. ASFV-MEC-01 conferred 100% protection against challenge with lethal parental ASFV, which correlated with high ASFV-specific humoral and cellular immune responses. Additionally, ASFV-MEC-01 was not detected in blood until 28 days post-inoculation. Global transcriptome analysis showed that ASFV-MEC-01 lacking 12 genes triggered stronger innate antiviral responses than the parental virus, as exemplified by high levels of mRNA encoding interferon regulatory and inflammatory genes in PAM cells. Ectopic expression of most deleted genes increased replication of DNA viruses by suppressing production of interferons and pro-inflammatory cytokines. Among the genes deleted from ASFV-MEC-01, MGF100-1R interacted specifically with the scaffold dimerization domain of TBK1, thereby preventing TBK1 dimerization and impairing TBK1-mediated type I IFN and NF-κB signalling. These results suggest that attenuation of ASFV-MEC-01 may be mediated by induction of stronger type I IFN and NF-κB signalling within the host innate immune system. Thus, ASFV-MEC-01 could be a safe and effective live attenuated ASFV vaccine candidate with commercial potential.

Abstract The effectiveness of dual‐doping as a method of improving the conductivity of sulfide solid electrolytes (SEs) is not in doubt; however, the atomic‐level mechanisms underpinning these enhancements remain elusive. In this study, we investigate the atomic mechanisms associated with the high ionic conductivity of the Li7P3S11 (LPS) SE and its response to Ag/Cl dual dopants. Synthesis and electrochemical characterizations show that the 0.2 M AgCl‐doped LPS (Li6.8P3Ag0.1S10.9Cl0.1) exhibited an over 80% improvement in ionic conductivity compared with the undoped LPS. The atomic‐level structures responsible for the enhanced conductivity were generated by a set of experiment and simulation techniques: synchrotron X‐ray diffractometry, Rietveld refinement, density functional theory, and artificial neural network‐based molecular dynamics simulations. This thorough characterization highlights the role of dual dopants in altering the structure and ionic conductivity. We found that the PS4 and P2S7 structural motifs of LPS undergo transformation into various PSx substructures. These changes in the substructures, in conjunction with the paddle‐wheel effect, enable rapid Li migration. The dopant atoms serve to enhance the flexibility of PS4–P2S7 polyhedral frameworks, consequently enhancing the ionic conductivity. Our study elucidates a clear structure–conductivity relationship for the dual‐doped LPS, providing a fundamental guideline for the development of sulfide SEs with superior conductivity.

OK-432 (picibanil) is an inactivated preparation of Streptococcus pyogenes that causes pleurodesis by inducing a strong inflammatory response. Intrapleural instillation of OK-432 has recently been used to successfully treat neonatal and fetal chylothorax. Here we report a trial of intrapleural instillation of OK-432 in two preterm infants who were born with hydrops fetalis and massive bilateral pleural effusion. Both cases showed persistent pleural effusion, refractory to conservative treatment, up to postnatal days 26 and 46, respectively. An average of 80 to 140 mL of pleural fluid was drained daily. In case 1, the infant was treated with OK-432 during the fetal period at gestation 28 weeks and 4 days of gestation, but showed recurrence of pleural effusion and progressed into hydrops. Within two to three days after OK-432 injection, the amount of pleural fluid drainage was dramatically decreased and there was no reaccumulation. We did not observe any side effects related to OK-432 injection. We suggest that OK-432 should be considered as a therapeutic option in infants who have persistent pleural effusion for more than four weeks, with the expectation of the early removal of the chest tube and a good outcome.

PurposeThe life expectancy of patients with spinal muscular atrophy (SMA) type I is generally considered to be less than 2 years. Recently, with the introduction of proactive treatments, a longer survival and an improved survival rate have been reported. In this study, we analyzed the natural courses and survival statistics of SMA type I patients and compared the clinical characteristics of the patients based on their survival periods.MethodsWe reviewed the medical records of 14 pediatric patients diagnosed with SMA type I during a 9-year period. We examined the demographic and clinical characteristics of these patients, calculated their survival probabilities, and plotted survival curves as on the censoring date, January 1, 2010. We also compared the characteristics of the patients who died before the age of 24 months (early-death, ED group) and those who survived for 24 months or longer (long-survival, LS group).ResultsThe mean survival time was 22.8±2.0 months. The survival probabilities at 6 months, 12 months, 18 months, 24 months, and 30 months were 92.9%, 92.9%, 76.0%, 76.0%, and 65.1%, respectively. Birth weight was the only factor that showed a statistically significant difference between the ED and LS groups (P=0.048).ConclusionIn this study, the survival probabilities at 2 years were far greater than expected. Because of the limited number of patients and information in this study, the contribution of improved supportive care on longer survival could not be clarified; this may be elucidated in larger cohort studies.

This study demonstrates the feasibility of a novel casting process called tailored additive casting (TAC). The TAC process involves injecting the melt several times to fabricate a single component, with a few seconds of holding between successive injections. Using TAC, we can successfully produce commercial-grade automotive steering knuckles with a tensile strength of 383 ± 3 MPa and an elongation percentage of 10.7 ± 1.1%, from Al 6061 alloys. To produce steering knuckles with sufficient mechanical strength, the composition of an Al 6061 alloy is optimized with the addition of Zr, Zn, and Cu as minor elements. These minor elements influence the thermal properties of the melt and alloy, such as their thermal stress, strain rate, shrinkage volume, and porosity. Optimal conditions for heat treatment before and after forging further improve the mechanical strength of the steering knuckles produced by TAC followed by forging.

PurposeTo assess the validity of individual and combined prognostic effects of severe bronchopulmonary dysplasia (BPD), brain injury, retinopathy of prematurity (ROP), and parenteral nutrition associated cholestasis (PNAC).MethodsWe retrospectively analyzed the medical records of 80 extremely low birthweight (ELBW) infants admitted to the neonatal intensive care unit (NICU) of the Severance Children's Hospital, and who survived to a postmenstrual age of 36 weeks. We analyzed the relationship between 4 neonatal morbidities (severe BPD, severe brain injury, severe ROP, and severe PNAC) and poor outcome. Poor outcome indicated death after a postmenstrual age of 36 weeks or survival with neurosensory impairment (cerebral palsy, delayed development, hearing loss, or blindness) between 18 and 24 months of corrected age.ResultsEach neonatal morbidity correlated with poor outcome on univariate analysis. Multiple logistic regression analysis revealed that the odds ratios (OR) were 4.9 (95% confidence interval [CI], 1.0-22.6; P=0.044) for severe BPD, 13.2 (3.0-57.3; P

Lymphangioma is a rare benign congenital tumor of the lymphatic system, which is commonly diagnosed before 2 years of age. In the natronal report, cystic lymphangioma was usually reported as a huge translucent mass located in the head and neck area. It's occurrence in retropharyngeal space with respiratory obstruction and swallowing difficulty in neonate is extremely rare and postoperative nasopharyngeal reflux has rarely been reported. Complete resection is the standard therapy. However, involvement of the upper airway may be determining prognosis in the extensive lymphangiomas because of the difficulty of complete excision. We present a case of cystic lymphangioma in neonate which was initially asymptomatic but gradually progressed to cause respiratory obstruction due to enlargement. After resection, nasopharyngeal reflux developed with dysfunction of the soft palate and gradually improved with conservative care over 5 months.

Background Perioperative stroke is a severe complication following surgery. To identify patients at risk for perioperative stroke, several prediction models based on the preoperative factors were suggested. Prediction models often focus on preoperative patient characteristics to assess stroke risk. However, most existing models primarily base their predictions on the patient's baseline characteristics before surgery. We aimed to develop a machine‐learning model incorporating both pre‐ and intraoperative variables to predict perioperative stroke. Methods and Results This study included patients who underwent noncardiac surgery at 2 hospitals with the data of 15 752 patients from Seoul National University Hospital used for development and temporal internal validation, and the data of 449 patients from Boramae Medical Center used for external validation. Perioperative stroke was defined as a newly developed ischemic lesion on diffusion‐weighted imaging within 30 days of surgery. We developed a prediction model composed of pre‐ and intraoperative factors (integrated model) and compared it with a model consisting of preoperative features alone (preoperative model). Perioperative stroke developed in 109 (0.69%) patients in the Seoul National University Hospital group and 11 patients (2.45%) in the Boramae Medical Center group. The integrated model demonstrated superior predictive performance with area under the curve values of 0.824 (95% CI, 0.762–0.880) versus 0.584 (95% CI, 0.499–0.667; P

In bone tissue engineering, various approaches have been investigated to enhance osteogenic regeneration. Previous studies have predominantly employed scaffolds with aligned structures or reduced graphene oxide (RGO) to facilitate bone regeneration. However, current scaffold designs face limitations in combining structural guidance with effective electromagnetic stimulation. Additionally, delivering localized stimulation within scaffolds remains a challenge in maximizing the potential of these materials for bone regeneration. To address these limitations and strengthen previous approaches, this study presents a novel strategy in tissue engineering for enhanced osteogenic differentiation. RGO-incorporated nanofibers (RGO-NFs) were fabricated via electrospinning a 10% polycaprolactone (PCL) solution with RGO concentrations varying. The random fibers were deposited on a planar surface, while the aligned fibers were deposited on a rotating drum. The morphology and orientation of the fibers were confirmed through electron microscopy. X-ray diffraction spectrometry was employed to confirm the integration of RGO and PCL. All groups demonstrated optimal cell adhesion and viability. RGO-NFs exhibited higher osteogenesis-related protein expression than PCL-only scaffolds, further enhanced by pulsed electromagnetic field (PEMF) application. The application of PEMF stimulation within aligned RGO-NFs presents a potentially more efficient alternative to existing methods, offering a novel, non-invasive therapeutic strategy for bone defect regeneration.