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Species extinction is increasing due to anthropogenic threats such as climate change and land-use change. Thus, there is increasing interest in predicting the future fate of species and implementing effective management strategies. In this study, we used spatially-explicit stochastic population models to simulate future projections of three Monkeyflower species, Erythranthe cardinalis, Erythranthe lewisii, and Erythranthe guttata, under climate and land-use change in their regional habitat range in the California Floristic Province. We compared future population projections of two of the three Monkeyflower species, sub-divided into lower and higher elevation ranges, to examine the role of elevational differences in life history parameters in the persistence of the species under projected habitat changes. Lastly, due to the appearance of oscillations and declines in population trajectories of one Monkeyflower species, we explored the role of small, colonized patches on population trajectories. The modeling framework linked species distribution models (SDMs) with population models and dispersal modes parametrized with a combination of multi-year population census data, information from the literature, and publicly available environmental data, including temperature and precipitation projections under two climate scenarios and two climate models. Due to high population growth rates, all three species were limited by changes in habitat due to climate and land-use change. However, subpopulations of E. cardinalis had a low population growth rate at lower elevational ranges leading to extirpation in that region. Conversely, E. lewisii had a high population growth rate but experienced substantial declines in suitable habitat. In the population trajectories of E. lewisii, damped oscillations were observed stemming from a combination of high growth rates and colonization of new small patches which paradoxically reduced the overall population size across the metapopulation. Th

To control net sodium (Na+) uptake, Arabidopsis plants utilize the plasma membrane (PM) Na+/H+ antiporter SOS1 to achieve Na+ efflux at the root and Na+ loading into the xylem, and the channel-like HKT1;1 protein that mediates the reverse flux of Na+ unloading off the xylem. Together, these opposing transport systems govern the partition of Na+ within the plant yet they must be finely co-regulated to prevent a futile cycle of xylem loading and unloading. Here, we show that the Arabidopsis SOS3 protein acts as the molecular switch governing these Na+ fluxes by favoring the recruitment of SOS1 to the PM and its subsequent activation by the SOS2/SOS3 kinase complex under salt stress, while commanding HKT1;1 protein degradation upon acute sodic stress. SOS3 achieves this role by direct and SOS2-independent binding to previously unrecognized functional domains of SOS1 and HKT1;1. These results indicate that roots first retain moderate amounts of salts to facilitate osmoregulation, yet when sodicity exceeds a set point, SOS3-dependent HKT1;1 degradation switches the balance toward Na+ export out of the root. Thus, SOS3 functionally links and co-regulates the two major Na+ transport systems operating in vascular plants controlling plant tolerance to salinity.

Previous research has emphasised the importance of examining institutional influences on FDI attractiveness. There is, however, relatively limited, conflicting, research exploring the relationship between informal institutional effects, such as level of corruption, and FDI motivation. Addressing this gap, we adopt a configurational fsQCA-based approach to link informal institutional influences to FDI motivation driving the presence or absence of FDI flows. Conceptualising corruption as bribery and unfair business practices, we extend our understanding of informal institutional quality impact on FDI inflows. Results reveal that informal institutional effects on FDI vary across regions, with several pathways explaining the presence or absence of FDI, according to the presence or absence of corruption. We add to previous studies by identifying the conditions that, when combined with corruption, are linked to the presence or absence of FDI. Results also indicate that whilst corruption appears unimportant in preventing FDI, and is of only secondary importance in driving FDI, it appears to have importance in determining the type of MNEs’ undertaking FDI. Overall, corruption is likely determining which companies invest in a country, rather than if, traditional reasons for FDI, particularly Resource and Market seeking, being key, with strategic and efficiency-seeking also being of secondary importance.

Juyoung Khwarg,1 Soyoung Lee,1,2 In-Jin Jang,1 Won-Ho Kang,3 Hye Jung Lee,4 Kyu Yeon Kim,4 Ki-Sun Jeong,4 Chongho Won,4 Youn Woong Choi,5 Dae Chul Ha,5 RaeHoon Jung,5 Min-Gu Han,5 Won Tae Jung,6 Kyu-Yeol Nam,6 YeSeul Kim,6 Kyung-Sang Yu,1 Jaeseong Oh1,7 1Department of Clinical Pharmacology and Therapeutics, Seoul National University College of Medicine and Hospital, Seoul, Republic of Korea; 2Integrated Major in Innovative Medical Science, Seoul National University Graduate School, Seoul, Republic of Korea; 3R&D Center, Korea United Pharm. Inc., Seoul, Republic of Korea; 4Caleb Multilab, Inc., Seoul, Republic of Korea; 5R&D Center, Korea United Pharm.Inc., Sejong, Republic of Korea; 6Global R&D, Korea United Pharm. Inc., Seoul, Republic of Korea; 7Department of Pharmacology, Jeju National University College of Medicine, Jeju, Republic of KoreaCorrespondence: Jaeseong Oh, Department of Pharmacology, Jeju National University College of Medicine, 15, Aran 13-gil, Jeju-si, Jeju-do, 63241, Republic of Korea, Email jaeseong5@jejunu.ac.krPurpose: Statins are widely used in combination with omega-3 fatty acids for the treatment of patients with dyslipidemia. The aim of this study was to compare the pharmacokinetic (PK) profiles of atorvastatin and omega-3-acid ethyl esters between fixed-dose combination (FDC) and loose combination in healthy subjects.Methods: A randomized, open-label, single-dose, 2-sequence, 2-treatment, 4-period replicated crossover study was performed. Subjects were randomly assigned to one of the 2 sequences and alternately received four FDC soft capsules of atorvastatin/omega-3-acid ethyl esters (10/1000 mg) or a loose combination of atorvastatin tablets (10 mg × 4) and omega-3-acid ethyl ester soft capsules (1000 mg× 4) for four periods, each period accompanied by a high-fat meal. Serial blood samples were collected for PK analysis of atorvastatin, eicosapentaenoic acid (EPA), and docosahexaenoic acid (DHA). PK parameters were calculated

ObjectivePrimary Sjögren's syndrome (pSS) is the second most common chronic autoimmune connective tissue disease. Autoantibodies, immunoglobulin (IgG) anti-SSA/Ro, in serum is a key diagnostic feature of pSS. Since pSS is a disease of the salivary gland, we investigated anti-SSA/Ro52 in saliva.MethodsUsing a novel electrochemical detection platform, Electric Field-Induced Release and Measurement, we measured IgG/M/A, IgG, IgA, IgA isotypes (IgA1 and IgA2) and IgA1 subclasses (polymeric and monomeric IgA1) to anti-SSA/Ro52 in saliva supernatant of 34 pSS, 35 dry eyes and dry mouth (patients with Sicca) and 41 health controls.ResultsSaliva IgG/M/A, IgG, IgA, IgA isotypes and IgA1 subclasses to anti-SSA/Ro52 differed significantly between pSS, non-pSS Sicca and healthy subjects. Elevated monomeric IgA1 was observed in patients with non-pSS Sicca while elevated polymeric IgA1 (pIgA1) was observed in patients with pSS. Salivary polymeric but not monomeric IgA1 (mIgA1) isoform correlated with focus score (r2=0.467, p=0.001) CONCLUSIONS: Salivary anti-Ro52 polymeric IgA1 isoform is associated with glandular inflammation in pSS, while salivary monomeric IgA1 is associated with Sicca. Whether IgA1 isotope switching plays a role in the progression of the Sicca to pSS warrants further investigation.

Sang Mi Park,1,2 Da Yeon Kim,3 Kyeong Hyeon Lee,1 Yong-Il Shin,1,4 Sang-Cheol Han,5 Sang-Mo Kwon1,2 1Department of Physiology, Laboratory of Vascular Medicine and Stem Cell Biology, School of Medicine, Pusan National University, Yangsan, Republic of Korea; 2BK21 GRAND Convergence Medical Science Education Research Center, Pusan National University, Yangsan, South Korea; 3Genetic & Epigenetic Toxicology Research Group, Korea Institute of Toxicology (KIT), Daejeon, Republic of Korea; 4Department of Rehabilitation Medicine, Pusan National University Yangsan Hospital, Yangsan, Republic of Korea; 5CEN Co., Ltd. Nanoconvergence Center, Muan-ro, Miryang, 761, Republic of KoreaCorrespondence: Sang-Mo Kwon, Department of Physiology, Laboratory of Vascular Medicine and Stem Cell Biology, School of Medicine, Pusan National University, Yangsan, Republic of Korea, Tel +82-51-510-8072, Fax +82-51-510-8076, Email smkwon323@pusan.ac.krPurpose: 5-fluorouracil (5-FU) is a first-line chemotherapeutic agent used to treat colorectal cancer (CRC). However, 5-FU induces drug resistance and activation of cancer stem cells (CSCs). In the present study, we designed a novel biocompatible nanomedicine system with high efficacy and biocompatibility by synthesizing mesoporous silica nanoparticle (MSN)-structured ZnO and gold ions. Oleuropein (OLP) is a phenolic compound derived from olive leaves that exerts anti-cancer effects. Therefore, we synthesized OLP-loaded ZnO/Au MSNs (ZnO/Au/OLP MSNs) and examined their anti-cancer effects on 5-FU-resistant CRC cells.Methods: ZnO/Au MSNs were synthesized and functionalized, and their physical and chemical compositions were characterized using UV-visible spectroscopy, dynamic light scattering, and transmission electron microscopy (TEM). Their effects were assessed in terms of cellular proliferation capacity, migration and invasion ability, colony-forming ability, spheroid-forming ability, reactive oxygen species (ROS) production, and mitochondrial me

Distributed Deep Learning (DDL), as a paradigm, dictates the use of GPU-based clusters as the optimal infrastructure for training large-scale Deep Neural Networks (DNNs). However, the high cost of such resources makes them inaccessible to many users. Public cloud services, particularly Spot Virtual Machines (VMs), offer a cost-effective alternative, but their unpredictable availability poses a significant challenge to the crucial checkpointing process in DDL. To address this, we introduce DeepVM, a novel solution that recommends cost-effective cluster configurations by intelligently balancing the use of Spot and On-Demand VMs. DeepVM leverages a four-stage process that analyzes instance performance using the FLOPP (FLoating-point Operations Per Price) metric, performs architecture-level analysis with linear programming, and identifies the optimal configuration for the user-specific needs. Extensive simulations and real-world deployments in the AWS environment demonstrate that DeepVM consistently outperforms other policies, reducing training costs and overall makespan. By enabling cost-effective checkpointing with Spot VMs, DeepVM opens up DDL to a wider range of users and facilitates a more efficient training of complex DNNs., Comment: 14 pages, 8 figures

Addressing the challenge of limited labeled data in clinical settings, particularly in the prediction of fatty liver disease, this study explores the potential of graph representation learning within a semi-supervised learning framework. Leveraging graph neural networks (GNNs), our approach constructs a subject similarity graph to identify risk patterns from health checkup data. The effectiveness of various GNN approaches in this context is demonstrated, even with minimal labeled samples. Central to our methodology is the inclusion of human-centric explanations through explainable GNNs, providing personalized feature importance scores for enhanced interpretability and clinical relevance, thereby underscoring the potential of our approach in advancing healthcare practices with a keen focus on graph representation learning and human-centric explanation., Comment: Paper accepted in Human-Centric Representation Learning workshop at AAAI 2024 (https://hcrl-workshop.github.io/2024/)

Mining of formulaic alpha factors refers to the process of discovering and developing specific factors or indicators (referred to as alpha factors) for quantitative trading in stock market. To efficiently discover alpha factors in vast search space, reinforcement learning (RL) is commonly employed. This paper proposes a method to enhance existing alpha factor mining approaches by expanding a search space and utilizing pretrained formulaic alpha set as initial seed values to generate synergistic formulaic alpha. We employ information coefficient (IC) and rank information coefficient (Rank IC) as performance evaluation metrics for the model. Using CSI300 market data, we conducted real investment simulations and observed significant performance improvement compared to existing techniques., Comment: Accepted by ICOIN 2024

A large and fast-growing number of studies across the social sciences use experiments to better understand the role of race in human interactions, particularly in the American context. Researchers often use names to signal the race of individuals portrayed in these experiments. However, those names might also signal other attributes, such as socioeconomic status (e.g., education and income) and citizenship. If they do, researchers would benefit greatly from pre-tested names with data on perceptions of these attributes; such data would permit researchers to draw correct inferences about the causal effect of race in their experiments. In this paper, we provide the largest dataset of validated name perceptions to date based on three different surveys conducted in the United States. In total, our data include over 44,170 name evaluations from 4,026 respondents for 600 names. In addition to respondent perceptions of race, income, education, and citizenship from names, our data also include respondent characteristics. Our data will be broadly helpful for researchers conducting experiments on the manifold ways in which race shapes American life.

Functional annotation of open reading frames in microbial genomes remains substantially incomplete. Enzymes constitute the most prevalent functional gene class in microbial genomes and can be described by their specific catalytic functions using the Enzyme Commission (EC) number. Consequently, the ability to predict EC numbers could substantially reduce the number of un-annotated genes. Here we present a deep learning model, DeepECtransformer, which utilizes transformer layers as a neural network architecture to predict EC numbers. Using the extensively studied Escherichia coli K-12 MG1655 genome, DeepECtransformer predicted EC numbers for 464 un-annotated genes. We experimentally validated the enzymatic activities predicted for three proteins (YgfF, YciO, and YjdM). Further examination of the neural network’s reasoning process revealed that the trained neural network relies on functional motifs of enzymes to predict EC numbers. Thus, DeepECtransformer is a method that facilitates the functional annotation of uncharacterized genes.

Wafer-scale monolayer two-dimensional (2D) materials have been realized by epitaxial chemical vapor deposition (CVD) in recent years. To scale up the synthesis of 2D materials, a systematic analysis of how the growth dynamics depend on the growth parameters is essential to unravel its mechanisms. However, the studies of CVD-grown 2D materials mostly adopted the control variate method and considered each parameter as an independent variable, which is not comprehensive for 2D materials growth optimization. Herein, we synthesized a representative 2D material, monolayer hexagonal boron nitride (hBN), on single-crystalline Cu (111) by epitaxial chemical vapor deposition and varied the growth parameters to regulate the hBN domain sizes. Furthermore, we explored the correlation between two growth parameters and provided the growth windows for large flake sizes by the Gaussian process. This new analysis approach based on machine learning provides a more comprehensive understanding of the growth mechanism for 2D materials. © 2023 American Chemical Society.

Muscle stem cells, the engine of muscle repair, are affected in myotonic dystrophy type 1 (DM1); however, the underlying molecular mechanism and the impact on the disease severity are still elusive. Here, we show using patients’ samples that muscle stem cells/myoblasts exhibit signs of cellular senescence in vitro and in situ. Single cell RNAseq uncovers a subset of senescent myoblasts expressing high levels of genes related to the senescence-associated secretory phenotype (SASP). We show that the levels of interleukin-6, a prominent SASP cytokine, in the serum of DM1 patients correlate with muscle weakness and functional capacity limitations. Drug screening revealed that the senolytic BCL-XL inhibitor (A1155463) can specifically remove senescent DM1 myoblasts by inducing their apoptosis. Clearance of senescent cells reduced the expression of SASP, which rescued the proliferation and differentiation capacity of DM1 myoblasts in vitro and enhanced their engraftment following transplantation in vivo. Altogether, this study identifies the pathogenic mechanism associated with muscle stem cell defects in DM1 and opens a therapeutic avenue that targets these defective cells to restore myogenesis.

Objective: To examine the prevalence of novel newborn types among 165 million live births in 23 countries from 2000 to 2021. Design: Population-based, multi-country analysis. Setting: National data systems in 23 middle- and high-income countries. Population: Liveborn infants. Methods: Country teams with high-quality data were invited to be part of the Vulnerable Newborn Measurement Collaboration. We classified live births by six newborn types based on gestational age information (preterm <37 weeks versus term ≥37 weeks) and size for gestational age defined as small (SGA, <10th centile), appropriate (10th–90th centiles), or large (LGA, >90th centile) for gestational age, according to INTERGROWTH-21st standards. We considered small newborn types of any combination of preterm or SGA, and term + LGA was considered large. Time trends were analysed using 3-year moving averages for small and large types. Main outcome measures: Prevalence of six newborn types. Results: We analysed 165 017 419 live births and the median prevalence of small types was 11.7% – highest in Malaysia (26%) and Qatar (15.7%). Overall, 18.1% of newborns were large (term + LGA) and was highest in Estonia 28.8% and Denmark 25.9%. Time trends of small and large infants were relatively stable in most countries. Conclusions: The distribution of newborn types varies across the 23 middle- and high-income countries. Small newborn types were highest in west Asian countries and large types were highest in Europe. To better understand the global patterns of these novel newborn types, more information is needed, especially from low- and middle-income countries.

Temporal interpolation often plays a crucial role to learn meaningful representations in dynamic scenes. In this paper, we propose a novel method to train spatiotemporal neural radiance fields of dynamic scenes based on temporal interpolation of feature vectors. Two feature interpolation methods are suggested depending on underlying representations, neural networks or grids. In the neural representation, we extract features from space-time inputs via multiple neural network modules and interpolate them based on time frames. The proposed multi-level feature interpolation network effectively captures features of both short-term and long-term time ranges. In the grid representation, space-time features are learned via four-dimensional hash grids, which remarkably reduces training time. The grid representation shows more than 100 times faster training speed than the previous neural-net-based methods while maintaining the rendering quality. Concatenating static and dynamic features and adding a simple smoothness term further improve the performance of our proposed models. Despite the simplicity of the model architectures, our method achieved state-of-the-art performance both in rendering quality for the neural representation and in training speed for the grid representation., Comment: CVPR 2023. Project page: https://sungheonpark.github.io/tempinterpnerf

Yun-Jeong Jeong,1,&ast; Kyoung-Hee Lee,2,&ast; Jisu Woo,2 Ji Yeon Kim,2 Chang-Hoon Lee,2,3 Chul-Gyu Yoo2,3 1Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Dongguk University Ilsan Hospital, Ilsan Dong-gu, Goyang-si, Gyeonggi-do, Korea; 2Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea; 3Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea&ast;These authors contributed equally to this workCorrespondence: Chul-Gyu Yoo, 101 Daehakno, Jongno-gu, Seoul, 03080, Korea, Tel +82-2-2072-3760, Fax +82-2-762-9662, Email cgyoo@snu.ac.krBackground: Macroautophagy plays an important role in the pathogenesis of chronic obstructive pulmonary disease (COPD), but the role of chaperone-mediated autophagy (CMA) has not been investigated. We investigated if and how CMA is involved in the pathogenesis of COPD.Methods: We measured the level of lysosome-associated membrane protein-2A (LAMP-2A), which is a critical component of CMA that functions as a receptor for cytosolic substrate proteins, in total lung tissues and primary human bronchial epithelial cells (HBECs) from healthy never smokers, smokers, and COPD patients. We assessed the effects of LAMP-2A knock-down on cigarette smoke extract (CSE)-induced aging, cell cycle arrest, and apoptosis in BEAS-2B cells and the expression levels of apoptosis hallmarks in primary HBECs and lung tissue sections.Results: We found that the protein levels of LAMP-2A in lung homogenates and primary HBECs from smokers and COPD patients were lower than those from never smokers. In addition, its level in primary HBECs was negatively correlated with years of smoking. CSE caused degradation of LAMP-2A protein via the lysosomal pathway by activating macroautophagy. Knock-down of LAMP-2A markedly enhanced CSE-induced expression of senescence markers such as p16, p21, p27, and p53. G

The COSINE-100 experiment has been operating with 106 kg of low-background NaI(Tl) detectors to test the results from the DAMA/LIBRA experiment, which claims to have observed dark matter. However, since the background of the NaI(Tl) crystals used in the COSINE-100 experiment is 2-3 times higher than that in the DAMA detectors, no conclusion regarding the claimed observation from the DAMA/LIBRA experiment could be reached. Therefore, we plan to upgrade the current COSINE-100 experiment to the next phase, COSINE-200, by using ultra-low background NaI(Tl) detectors. The basic principle was already proved with the commercially available Astro-grade NaI powder from Sigma-Aldrich company. However, we have developed a mass production process of ultra-pure NaI powder at the Center for Underground Physics (CUP) of the Institute for Basic Science (IBS), Korea, using the direct purification of the raw NaI powder. We plan to produce more than 1,000 kg of ultra-pure powder for the COSINE200 experiment. With our crystal grower installed at CUP, we have successfully grown a low-background crystal using our purification technique for the NaI powder. We have assembled a low-background NaI(Tl) detector. In this article, we report the performance of this ultra-pure NaI(Tl) crystal detector produced at IBS, Korea.

Civilian fusion demands structural materials that can withstand the harsh environments imposed inside fusion plasma reactors. The structural materials often transmute under 14.1 MeV fast neutrons, producing helium (He), which embrittles the grain boundary (GB) network. Here, it is shown that neutron-friendly and mechanically strong nano-phases with atomic-scale free volume can have low He-embedding energy E emb ${\mathcal{E}}_{\mathrm{emb}}$ and >10 at.% He-absorbing capacity, and can be especially advantageous for soaking up He on top of resisting radiation damage and creep, provided they have thermodynamic compatibility with the matrix phase, satisfactory equilibrium wetting angle, as well as a high enough melting point. The preliminary experimental demonstration proves that E emb ${\mathcal{E}}_{\mathrm{emb}}$ is a good ab initio predictor of He shielding potency in nano-heterophase materials, and thus, E emb ${\mathcal{E}}_{\mathrm{emb}}$ is used as a key feature for computational screening. In this context, a list of viable compounds expected to be good He-absorbing nano-phases is presented, taking into account E emb ${\mathcal{E}}_{\mathrm{emb}}$ , the neutron absorption and activation cross-sections, the elastic moduli, melting temperature, the thermodynamic compatibility, and the equilbrium wetting angle of the nano-phases with the Fe matrix as an example.

Dual-mode optical encryption based on holographic metasurfaces and color components is of great attraction because of their enhanced information security and storage; however, the realization of independently as well as reversibly encodable holographic metasurfaces and color components remains unreported. Herein, we present reconfigurable dual-mode encryptions of structural colors (SC) and holograms, achieved through stimuli-responsive block copolymer (BCP) photonic crystals (PCs) with micro-imprinted holographic metasurfaces. Holographic images appear when the micro-imprinted BCP PCs, consisting of self-assembled alternating lamellae of two dielectrics, are exposed to an incident laser. A characteristic SC develops in the visible range when the imprinted film is immersed in a liquid agent that can swell one of the dielectrics, allowing for dual-mode holographic and SC encodings in the solid and liquid states, respectively. The dual-mode optical encoding is reconfigured. The holographic image can be erased and replaced with another micropattern, while preserving the SC. Moreover, an SC, set by crosslinking of the swellable lamellae, is reset by chemical de-crosslinking and subsequent transient re-crosslinking, enabling the SC reconfigurability of the BCP PC film. A prototype of a high-security reconfigurable dual encryption has been developed, wherein true information is decrypted when holographic passwords are confirmed with full-color visible SC passwords., Funding Agencies|National Research Foundation of Korea [NRF-2021M3H4A1A04086553]; Open Resource Research Program of the Korea Institute of Science and Technology [2E31551]; National Research Foundation of Korea - Ministry of Science, ICT & Future Planning [NRF-2022M3C1A3081211]; National Research Foundation of Korea (NRF) - Ministry of Science and ICT [2018M3D1A1058536]; National Research Foundation of Korea (NRF) - Korean government (MEST) [RS-2023-00208577]; Technology Innovation Program Development Program-Development and demonstration of new market-creating display technologies - Ministry of Trade, Industry & Energy (MOTIE, Korea) [20023880]

The precise timing of flowering in adverse environments is critical for plants to secure reproductive success. We report a mechanism in Arabidopsis (Arabidopsis thaliana) controlling the time of flowering by which the S-acylation-dependent nuclear import of the protein SALT OVERLY SENSITIVE3/CALCINEURIN B-LIKE4 (SOS3/CBL4), a Ca2+-signaling intermediary in the plant response to salinity, results in the selective stabilization of the flowering time regulator GIGANTEA inside the nucleus under salt stress, while degradation of GIGANTEA in the cytosol releases the protein kinase SOS2 to achieve salt tolerance. S-acylation of SOS3 was critical for its nuclear localization and the promotion of flowering, but partly dispensable for salt tolerance. SOS3 interacted with the photoperiodic flowering components GIGANTEA and FLAVIN-BINDING, KELCH REPEAT, F-BOX1 and participated in the transcriptional complex that regulates CONSTANS to sustain the transcription of CO and FLOWERING LOCUS T under salinity. Thus, the SOS3 protein acts as a Ca2+- and S-acylation-dependent versatile regulator that fine-tunes flowering time in a saline environment through the shared spatial separation and selective stabilization of GIGANTEA, thereby connecting two signaling networks to co-regulate the stress response and the time of flowering.

Importance: International guidelines recommend avoiding intravenous thrombolysis (IVT) in patients with ischemic stroke who have a recent intake of a direct oral anticoagulant (DOAC).ObjectiveTo determine the risk of symptomatic intracranial hemorrhage (sICH) associated with use of IVT in patients with recent DOAC ingestion.Design, Setting, and ParticipantsThis international, multicenter, retrospective cohort study included 64 primary and comprehensive stroke centers across Europe, Asia, Australia, and New Zealand. Consecutive adult patients with ischemic stroke who received IVT (both with and without thrombectomy) were included. Patients whose last known DOAC ingestion was more than 48 hours before stroke onset were excluded. A total of 832 patients with recent DOAC use were compared with 32 375 controls without recent DOAC use. Data were collected from January 2008 to December 2021.ExposuresPrior DOAC therapy (confirmed last ingestion within 48 hours prior to IVT) compared with no prior oral anticoagulation. Main Outcomes and Measures: The main outcome was sICH within 36 hours after IVT, defined as worsening of at least 4 points on the National Institutes of Health Stroke Scale and attributed to radiologically evident intracranial hemorrhage. Outcomes were compared according to different selection strategies (DOAC-level measurements, DOAC reversal treatment, IVT with neither DOAC-level measurement nor idarucizumab). The association of sICH with DOAC plasma levels and very recent ingestions was explored in sensitivity analyses.ResultsOf 33 207 included patients, 14 458 (43.5%) were female, and the median (IQR) age was 73 (62-80) years. The median (IQR) National Institutes of Health Stroke Scale score was 9 (5-16). Of the 832 patients taking DOAC, 252 (30.3%) received DOAC reversal before IVT (all idarucizumab), 225 (27.0%) had DOAC-level measurements, and 355 (42.7%) received IVT without measuring DOAC plasma levels or reversal treatment. The unadjusted rate of sIC

Immersive technologies such as virtual reality (VR), augmented reality (AR), and holograms will change users' digital experience. These immersive technologies have a multitude of applications, including telesurgeries, teleconferencing, Internet shopping, computer games, etc. Holographic-type communication (HTC) is a type of augmented reality media that provides an immersive experience to Internet users. However, HTC has different characteristics and network requirements, and the existing network architecture and transport protocols may not be able to cope with the stringent network requirements of HTC. Therefore, in this paper, we provide an in-depth and critical study of the transport protocols for HTC. We also discuss the characteristics and the network requirements for HTC. Based on the performance evaluation of the existing transport protocols, we propose a roadmap to design new high-performance transport protocols for immersive applications., Comment: Accepted in The 14th International Conference on Ubiquitous and Future Networks (ICUFN 2023), Paris France, July 4-7 2023

Mouse molars resemble human teeth, as their roots develop and stop growing. In contrast, mouse incisors grow and erupt continuously due to the presence of a persistent stem cell niche identified as the labial cervical loop, which actively gives rise to dentin-forming odontoblasts to support tooth homeostasis and injury repair. Autophagy (ATG), a cellular degradation process whereby macromolecules and organelles are sequestered to be recycled, has been shown to play a role in mineralized tissue-forming cells including odontoblasts. However, the precise role of ATG in odontoblasts in vivo remains unclear. Beclin1 is an indispensable ATG-related protein involved in ATG initiation. Therefore, we conditionally deleted Beclin1 in odontoblast-specific manner and generated Becn1f/f;Dmp1Cre/+ (Becn1 cKO) mice. From these mice, molars and incisors were evaluated radiographically and histologically. MicroCT scanning was employed to observe dentin formation and measure pulp tissue volume, histological analysis to examine dentin formation and dental pulp cells, and RNAscope in situ hybridization to identify odontoblast differentiation in the incisor stem cell niche and mesenchymal tissue in molars. We further evaluated the mRNA expression of FGF signaling genes in human dental pulp stem cells in vitro using Becn1 knocked down dental pulp cells (DPCs). Becn1 cKO mice were born at the expected Mendalian ratio. However, Becn1 cKO mice at the 6th month mark exhibited increased obliteration of the pulp chamber in both molar and incisors. Interestingly, both Becn1 wildtype (WT) and Becn1 ckO mice a normal laCL histology. When Becn1 was knocked down in DPCs, Etv4, a downstream target gene of FGF signaling pathway, was significantly upregulated. Our study highlights the possible role of Beclin1 in pulp calcification of molars, as Beclin1 KO mice molars were characterized by a completely obliteration and calcification of the pulp space, and suggests that Beclin1 may play a role in develo

This dissertation investigates how government policies influenced U.S. minority coalition formation in the 1960s and 1970s. I argue that the key to explaining this puzzle lies in ethnic elites’ strategic calculations, as influenced by historical legacies, policy changes, and variations. Chapter 2 examines why American minority mobilization emphasized race so much in the 1960s and 1970s. In leveraging the Chinese immigrant communities along the U.S.–Canadian border on the West Coast, I found that what makes the U.S. unique is its immigration and segregation policies. Chapter 3 investigates why Asian and Latin American national origin groups joined forces as Asian Americans and Latinos in the 1960s and 1970s. I explain the welfare state as an underappreciated mechanism that mobilized these intra-racial coalitions. Chapter 4 examines why inter-racial coalitions were rare or short-lived in the 1960s and 1970s. I found that although racial minority groups are often described collectively as people of color, their issues varied because they faced different policy challenges. Additionally, the misalignment of political agendas made coordinating actions among them difficult. Taken together, these three chapters highlight how combining a historical perspective and strategic analysis offers new insights into the contingent nature of minority coalition formation in the U.S. and beyond. The rich archival, organizational, and text data I assembled provide an example of how to undertake historical research on marginalized groups in a data-intensive way.

Cirrhotic cardiomyopathy is a clinical syndrome in patients with liver cirrhosis characterized by blunted cardiac contractile responses to stress and/or heart rate-corrected QT (QTc) interval prolongation. Caveolin-3 (Cav-3) plays a critical role in cardiac protection and is an emerging therapeutic target for heart disease. We investigated the protective role of cardiac-specific overexpression (OE) of Cav-3 in cirrhotic cardiomyopathy. Biliary fibrosis was induced in male Cav-3 OE mice and transgene negative (TGneg) littermates by feeding a diet containing 3,5-diethoxycarbonyl-1,4-dihydrocollidine (DDC; 0.1%) for 3 wk. Liver pathology and blood chemistries were assessed, and stress echocardiography, telemetry, and isolated heart perfusion studies to assess adrenergic responsiveness were performed. Cav-3 OE mice showed a similar degree of hyperdynamic contractility, pulmonary hypertension, and QTc interval prolongation as TGneg mice after 3 wk of DDC diet. Blunted systolic responses were shown in both DDC-fed Cav-3 OE and TGneg hearts after in vivo isoproterenol challenge. However, QTc interval prolongation after in vivo isoproterenol challenge was significantly less in DDC-fed Cav-3 OE hearts compared with DDC-fed TGneg hearts. In ex vivo perfused hearts, where circulatory factors are absent, isoproterenol challenge showed hearts from DDC-fed Cav-3 OE mice had better cardiac contractility and relaxation compared with DDC-fed TGneg hearts. Although Cav-3 OE in the heart did not prevent cardiac alterations in DDC-induced biliary fibrosis, cardiac expression of Cav-3 reduced QTc interval prolongation after adrenergic stimulation in cirrhosis.NEW & NOTEWORTHY Prevalence of cirrhotic cardiomyopathy is up to 50% in cirrhotic patients, and liver transplantation is the only treatment. However, cirrhotic cardiomyopathy is associated with perioperative morbidity and mortality after liver transplantation; therefore, management of cirrhotic cardiomyopathy is crucial for suc

[EN] Translation, in English, is a term that defines, on the one hand, the act of translating from one language to another, and on the other, the act of moving from one place to another. Weaving a game with the double meaning of this expression, the synthesis of this audiovisual essay is based within an introspective dynamic, in defining the link between two cultures, and two places; Galicia and Korea, through an intimate look in which the subaltern subject is compensated. Starting from the East-West construct, as Edward Said explains, the East is seen as an amalgam in which the mystical and the exotic are observed with desire, always from a superior position. The term is in itself a way of reaffirming himself; the, white, European, Christian and endocentric man, in front of the rest. Taking these concepts as a way of understanding the subjective identity of a migrant woman, the structure of this experimentation is based on a series of interventions in the landscape, in different territories. In this way, a portable and removable structure is placed in a forest, a stream or a lake. These spaces hide places where people once settled, but today they remain forgotten. The color white and its meanings in the folklore of both cultures; purity, life, fragility or death, will ultimately serve as a backbone that gives meaning to the sequence of images and sounds, which are interrelated through this comparative analysis., [ES] Translation, en inglés, es un término que define, por una parte, el acto de traducir de un idioma a otro, y por otra, el de trasladar de un lugar a otro. Urdiendo un juego con el doble sentido de esta expresión, la síntesis de este ensayo audiovisual se basa dentro de una dinámica introspectiva, en definir el vínculo entre dos culturas, y dos lugares; Galicia y Corea, a través de una mirada íntima en la que se resarza al sujeto subalterno. Partiendo del constructo Oriente-Occidente, como explica Edward Saíd, el primero es visto como un amalgama en el que lo místico y lo exótico se observan con deseo, siempre desde una posición superior. El término se trata en sí mismo de una forma de reafirmarse a sí mismo; al hombre, blanco, europeo, cristiano y endocéntrico, frente al resto. En consecuencia, tomando estos conceptos como una forma de comprender la propia identidad subjetiva de una mujer migrante, la estructura de esta experimentación se basa en una serie de intervenciones en el paisaje, en distintos territorios. De este modo, una estructura portátil y desmontable es colocada en un bosque, un arroyo o un lago. Estos espacios, esconden lugares en los que las personas se asentaron antaño, pero hoy permanecen olvidados. El color blanco y sus significaciones en el folclore de ambas culturas; pureza, vida, fragilidad o muerte, servirán, en definitiva, de elemento vertebrador que da sentido a la secuencia de imágenes y sonidos, las cuales se interrelacionan a través de este análisis comparativo.

A fundamental challenge to providing edge-AI services is the need for a machine learning (ML) model that achieves personalization (i.e., to individual clients) and generalization (i.e., to unseen data) properties concurrently. Existing techniques in federated learning (FL) have encountered a steep tradeoff between these objectives and impose large computational requirements on edge devices during training and inference. In this paper, we propose SplitGP, a new split learning solution that can simultaneously capture generalization and personalization capabilities for efficient inference across resource-constrained clients (e.g., mobile/IoT devices). Our key idea is to split the full ML model into client-side and server-side components, and impose different roles to them: the client-side model is trained to have strong personalization capability optimized to each client's main task, while the server-side model is trained to have strong generalization capability for handling all clients' out-of-distribution tasks. We analytically characterize the convergence behavior of SplitGP, revealing that all client models approach stationary points asymptotically. Further, we analyze the inference time in SplitGP and provide bounds for determining model split ratios. Experimental results show that SplitGP outperforms existing baselines by wide margins in inference time and test accuracy for varying amounts of out-of-distribution samples., Comment: To appear in IEEE INFOCOM 2023

The method of neural radiance fields (NeRF) has been developed in recent years, and this technology has promising applications for synthesizing novel views of complex scenes. However, NeRF requires dense input views, typically numbering in the hundreds, for generating high-quality images. With a decrease in the number of input views, the rendering quality of NeRF for unseen viewpoints tends to degenerate drastically. To overcome this challenge, we propose pseudo-view augmentation of NeRF, a scheme that expands a sufficient amount of data by considering the geometry of few-shot inputs. We first initialized the NeRF network by leveraging the expanded pseudo-views, which efficiently minimizes uncertainty when rendering unseen views. Subsequently, we fine-tuned the network by utilizing sparse-view inputs containing precise geometry and color information. Through experiments under various settings, we verified that our model faithfully synthesizes novel-view images of superior quality and outperforms existing methods for multi-view datasets.

Most recent studies have shown several vulnerabilities to attacks with the potential to jeopardize the integrity of the model, opening in a few recent years a new window of opportunity in terms of cyber-security. The main interest of this paper is directed towards data poisoning attacks involving label-flipping, this kind of attacks occur during the training phase, being the aim of the attacker to compromise the integrity of the targeted machine learning model by drastically reducing the overall accuracy of the model and/or achieving the missclassification of determined samples. This paper is conducted with intention of proposing two new kinds of data poisoning attacks based on label-flipping, the targeted of the attack is represented by a variety of machine learning classifiers dedicated for malware detection using mobile exfiltration data. With that, the proposed attacks are proven to be model-agnostic, having successfully corrupted a wide variety of machine learning models; Logistic Regression, Decision Tree, Random Forest and KNN are some examples. The first attack is performs label-flipping actions randomly while the second attacks performs label flipping only one of the 2 classes in particular. The effects of each attack are analyzed in further detail with special emphasis on the accuracy drop and the misclassification rate. Finally, this paper pursuits further research direction by suggesting the development of a defense technique that could promise a feasible detection and/or mitigation mechanisms; such technique should be capable of conferring a certain level of robustness to a target model against potential attackers., Comment: arXiv admin note: substantial text overlap with arXiv:2202.10276

Hye Jung Park,1 Soyoung Jeon,2 Hye Sun Lee,2 Bo Yeon Kim,3 Yu Jin Chae,3 Gui Ok Kim,3 Jung-Won Park,4,5 Jae-Hyun Lee4,5 1Department of Internal Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea; 2Biostatistics Collaboration Unit, Yonsei University College of Medicine, Seoul, Republic of Korea; 3Healthcare Insurance Review & Assessment Service, Wonju, Republic of Korea; 4Division of Allergy and Immunology, Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea; 5Institute of Allergy, Yonsei University College of Medicine, Seoul, Republic of KoreaCorrespondence: Jae-Hyun Lee, Division of Allergy and Immunology, Department of Internal Medicine, Institute of Allergy, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea, Tel +82-2-2228-1977, Fax +82-2-393-6884, Email jhleemd@yuhs.acBackground: Although a wide variety of asthma medications have been developed and are used in clinical practice, there is limited evidence of their comparative effects on asthma exacerbations.Methods: We used claims data provided by the Health Insurance Review and Assessment Service. We selected subjects commencing asthma treatment between July 1, 2017 and June 30, 2018, with no change in drug regimen. The primary outcome was asthma exacerbation requiring systemic corticosteroids. Cox regression analysis was used to assess outcomes considering the exacerbation-free period.Results: Of the 254,951 asthma subjects, 107,694 subjects (42.2%) experienced asthma exacerbation. Inhaled corticosteroids (ICSs) (hazard ratio [HR], 0.378– 0.508), ICS-long-acting β2-agonist (LABAs) (HR, 0.284– 0.479), long-acting muscarine antagonists (LAMAs) (HR, 0.432– 0.572), leukotriene receptor antagonists (LTRAs) (HR, 0.371– 0.419), and xanthines (HR, 0.326– 0.482) significantly reduced the rate of first and second exacerbation of asthma (all P-values, < 0.001)

This paper presents several conditions to determine strong sign controllability for diffusively-coupled undirected networks. The strong sign controllability is determined by the sign patterns (positive, negative, zero) of the edges. We first provide the necessary and sufficient conditions for strong sign controllability of basic components, such as path, cycle, and tree. Next, we propose a merging process to extend the basic componenets to a larger graph based on the conditions of the strong sign controllability. Furthermore, we develop an algorithm of polynomial complexity to find the minimum number of external input nodes while maintaining the strong sign controllability of a network.

Machine learning models have been widely adopted in several fields. However, most recent studies have shown several vulnerabilities from attacks with a potential to jeopardize the integrity of the model, presenting a new window of research opportunity in terms of cyber-security. This survey is conducted with a main intention of highlighting the most relevant information related to security vulnerabilities in the context of machine learning (ML) classifiers; more specifically, directed towards training procedures against data poisoning attacks, representing a type of attack that consists of tampering the data samples fed to the model during the training phase, leading to a degradation in the models accuracy during the inference phase. This work compiles the most relevant insights and findings found in the latest existing literatures addressing this type of attacks. Moreover, this paper also covers several defense techniques that promise feasible detection and mitigation mechanisms, capable of conferring a certain level of robustness to a target model against an attacker. A thorough assessment is performed on the reviewed works, comparing the effects of data poisoning on a wide range of ML models in real-world conditions, performing quantitative and qualitative analyses. This paper analyzes the main characteristics for each approach including performance success metrics, required hyperparameters, and deployment complexity. Moreover, this paper emphasizes the underlying assumptions and limitations considered by both attackers and defenders along with their intrinsic properties such as: availability, reliability, privacy, accountability, interpretability, etc. Finally, this paper concludes by making references of some of main existing research trends that provide pathways towards future research directions in the field of cyber-security.

Proton conduction underlies many important electrochemical technologies. A family of new proton electrolytes is reported: acid-in-clay electrolyte (AiCE) prepared by integrating fast proton carriers in a natural phyllosilicate clay network, which can be made into thin-film (tens of micrometers) fluid-impervious membranes. The chosen example systems (sepiolite-phosphoric acid) rank top among the solid proton conductors in terms of proton conductivities (15 mS cm-1 at 25 °C, 0.023 mS cm-1 at -82 °C), electrochemical stability window (3.35 V), and reduced chemical reactivity. A proton battery is assembled using AiCE as the solid electrolyte membrane. Benefitting from the wider electrochemical stability window, reduced corrosivity, and excellent ionic selectivity of AiCE, the two main problems (gassing and cyclability) of proton batteries are successfully solved. This work draws attention to the element cross-over problem in proton batteries and the generic "acid-in-clay" solid electrolyte approach with superfast proton transport, outstanding selectivity, and improved stability for room- to cryogenic-temperature protonic applications.

Although robot-based automation in chemistry laboratories can accelerate the material development process, surveillance-free environments may lead to dangerous accidents primarily due to machine control errors. Object detection techniques can play vital roles in addressing these safety issues; however, state-of-the-art detectors, including single-shot detector (SSD) models, suffer from insufficient accuracy in environments involving complex and noisy scenes. With the aim of improving safety in a surveillance-free laboratory, we report a novel deep learning (DL)-based object detector, namely, DenseSSD. For the foremost and frequent problem of detecting vial positions, DenseSSD achieved a mean average precision (mAP) over 95% based on a complex dataset involving both empty and solution-filled vials, greatly exceeding those of conventional detectors; such high precision is critical to minimizing failure-induced accidents. Additionally, DenseSSD was observed to be highly insensitive to the environmental changes, maintaining its high precision under the variations of solution colors or testing view angles. The robustness of DenseSSD would allow the utilized equipment settings to be more flexible. This work demonstrates that DenseSSD is useful for enhancing safety in an automated material synthesis environment, and it can be extended to various applications where high detection accuracy and speed are both needed.

Song Yi Lee,1,&ast; Do Yeon Kim,1,&ast; Sang Bum Suh,1 Ji Youn Suh,1 Sung Bin Cho2 1BNV Biolab, Seoul, Korea; 2Yonsei Seran Dermatology and Laser Clinic, Seoul, Korea&ast;These authors contributed equally to this workCorrespondence: Sung Bin Cho, Yonsei Seran Dermatology and Laser Clinic, 224 Siheung-daero, Seoul, 08628, Korea, Tel +82 2-2135-1375, Fax +82 70-8250-1375, Email drsbcho@gmail.comBackground: Human fibroblast-derived multi-peptide factors (MPFs) promote wound repair by playing crucial roles in cell recruitment, adhesion, attachment, migration, and proliferation.Methods: Cultured human dermal fibroblasts (HDFs) were directly treated with non-contact low- and high-energy nitrogen plasma and further cultured in various conditioned media. Cell proliferation and wound-healing properties were evaluated.Results: In Opti-modified Eagle’s medium + GlutaMAX culture, reduced HDF viability was observed 24 h after 2-J/pulse plasma treatment and 12 and 24 h after 3-J/pulse treatment. Meanwhile, in dermal fibroblast-conditioned medium (DFCM) containing MPF culture, reduced HDF viability was observed only 24 h after 3-J/pulse treatment. Under DFCM-MPF culture, the wound area percentage was significantly decreased after 12 and 24 h in untreated HDFs; at 9, 12, and 24 h after 1-J/pulse plasma treatment; at 3, 6, 9, 12, and 24 h after 2-J/pulse plasma treatment; and at 9, 12, and 24 h after 3-J/pulse plasma treatment. Greater migration of HDFs with or without plasma treatment was found in DFCM-MPFs than in other conditioned media.Conclusion: Low-energy nitrogen plasma treatment promotes HDF proliferation and wound repair. DFCM-MPFs enhanced cell proliferation and improved the wound healing properties of HDFs treated with low- and high-energy plasma.Keywords: human dermal fibroblasts, multi-peptide factors, dermal fibroblast-conditioned media, plasma, nitrogen, cell proliferation, wound healing, cell migration

Jinhwa Jang,1 Myung-Jae Hwang,1 Yoo-Yeon Kim,1 Shin Young Park,1 Myeongsu Yoo,1 Seong-Sun Kim,1 Sangwon Lee,2 Donghyok Kwon1 1Division of Public Health Emergency Response Research, Korea Disease Control and Prevention Agency, Cheongju-si, Chungcheongbuk-do, Republic of Korea; 2Director General for Public Health Emergency Preparedness, Korea Disease Control and Prevention Agency, Cheongju-si, Chungcheongbuk-do, Republic of KoreaCorrespondence: Donghyok Kwon, Division of Public Health Emergency Response Research, Korea Disease Control and Prevention Agency, 187, OsongSaengmyeong 2-ro, Osong-eup, Heungdeok-gu, Cheongju-si, Chungcheongbuk-do, 28159, Republic of Korea, Tel +82-43-719-7730, Fax +82-43-719-7749, Email vethyok@korea.krBackground: In South Korea, the epidemiological characteristics of children and adolescents infected with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) have not been reported to date. The purpose of this study was to identify major epidemiological characteristics and transmission patterns of coronavirus disease 2019 (COVID-19) in children and adolescents.Methods: This study was conducted through a system integrated in an epidemiological investigation by the Korea Disease Control and Prevention Agency from January 20, 2020, to June 5, 2021. We analyzed the epidemiological characteristics of 14,967 children and adolescents with COVID-19 according to the age groups and transmission age patterns of 3721 infector-infectee pairs in South Korea.Results: Among the total confirmed COVID-19 cases, 14,967 patients were aged 0– 18 years. The most affected age group among children and adolescents were those aged 16– 18 years (3589, 24.0%). For all age groups, the infection route through friends and family members (31.9%) was the highest. For the contact age pattern analysis, infection from infectors aged 30– 49 years to infectees aged 0– 12 years showed a statistically significant relation (p < 0.001) compared to that in other age

Background The Liver Imaging Reporting and Data System (LI-RADS) assigns a risk category for hepatocellular carcinoma (HCC) to imaging observations. Establishing the contributions of major features can inform the diagnostic algorithm. Purpose To perform a systematic review and individual patient data meta-analysis to establish the probability of HCC for each LI-RADS major feature using CT/MRI and contrast-enhanced US (CEUS) LI-RADS in patients at high risk for HCC. Materials and Methods Multiple databases (MEDLINE, Embase, Cochrane Central Register of Controlled Trials, and Scopus) were searched for studies from January 2014 to September 2019 that evaluated the accuracy of CT, MRI, and CEUS for HCC detection using LI-RADS (CT/MRI LI-RADS, versions 2014, 2017, and 2018; CEUS LI-RADS, versions 2016 and 2017). Data were centralized. Clustering was addressed at the study and patient levels using mixed models. Adjusted odds ratios (ORs) with 95% CIs were determined for each major feature using multivariable stepwise logistic regression. Risk of bias was assessed using Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) (PROSPERO protocol: CRD42020164486). Results A total of 32 studies were included, with 1170 CT observations, 3341 MRI observations, and 853 CEUS observations. At multivariable analysis of CT/MRI LI-RADS, all major features were associated with HCC, except threshold growth (OR, 1.6; 95% CI: 0.7, 3.6; P = .07). Nonperipheral washout (OR, 13.2; 95% CI: 9.0, 19.2; P = .01) and nonrim arterial phase hyperenhancement (APHE) (OR, 10.3; 95% CI: 6.7, 15.6; P = .01) had stronger associations with HCC than enhancing capsule (OR, 2.4; 95% CI: 1.7, 3.5; P = .03). On CEUS images, APHE (OR, 7.3; 95% CI: 4.6, 11.5; P = .01), late and mild washout (OR, 4.1; 95% CI: 2.6, 6.6; P = .01), and size of at least 20 mm (OR, 1.6; 95% CI: 1.04, 2.5; P = .04) were associated with HCC. Twenty-five studies (78%) had high risk of bias due to reporting ambiguity or study desig

There is increasing evidence that cancer stem cells (CSC) are more radioresistant than differentiated cancer cells (DCC). Radiation treatment of solid tumors can induce long-term enrichment of CSC, which can lead to resistance and a loss of sensitivity to radiotherapy. At the same time, radiation-induced reprogramming of DCCs into CSCs has also been observed. Using a mathematical model, we study the dynamics of CSCs and DCCs with reprogramming induced by radiation therapy. We also investigate the effect of feedback on cell division rates together with reprogramming, and renewal probability. We observe that feedback on cell division rates results in long-term enrichment of CSC whereas the effect of feedback on self-renewal probabilities results only in short-term CSC enrichment even when there is reprogramming. In the context of glioblastoma, we find there is an optimal choice of dose fractionation to reduce CSC percentages and tumor sizes.

I designed the game so that the player can choose between various paths. Also, although this is a simple game, I considered the correlation so that players' choices could be added and lead to results. I agree with that it's a bit childish game, but the user will surely feel pleasure. My theme: Falling, Soulmate I made a game based on my experience of feeling the love from a close friend(soulmate).

The East Asian marginal seas are among the most productive fisheries grounds. However, in recent decades they experienced massive proliferations of jellyfish that pose vast challenges for the management of harvested fish stocks. In the Korean Peninsula, the common bloom-formers Scyphozoan species Aurelia coerulea and Nemopilema nomurai are of major concern due to their detrimental effects on coastal socio-ecological systems. Here, we used pluriannual field observations spanning over 14 years to test the extent of climate influence on the interannual variability and bloom dynamics of A. coerulea and N. nomurai. To depict climate-jellyfish interactions we assessed partitioning effects, direct/indirect links, and the relative importance of hydroclimate forces on the variability of these species. We show that jellyfish interannual patterns and bloom dynamics are shaped by forces playing out at disparate scales. While abundance changes and earlier blooms of A. coerulea were driven by local environmental conditions, N. nomurai interannual patterns and bloom dynamics were linked with regional climate processes. Our results provide a synoptic picture of cascading effects from large scale climate to jellyfish dynamics in the Korean Peninsula that may affect fisheries sustainability due to the prominent detrimental impact these species have in the region