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The deadlift is a fundamental exercise in resistance training, essential for the development of overall strength and power. This review synthesizes current research on kinematics and electromyographic (EMG) activity during deadlifts, highlighting the effects of different variations and techniques on performance and muscle activation. Kinematic studies have revealed significant differences in joint angles and movement patterns between conventional and sumo deadlifts, emphasizing the importance of technique and experience in optimizing performance and reducing injury risk. EMG analysis has also revealed distinct muscle activation profiles for key muscles, such as the vastus lateralis, gluteus maximus, and hamstrings, across different deadlift variations. These findings are critical for designing effective, individualized training programs in strength and conditioning, as well as developing targeted rehabilitation and injury prevention strategies in sports medicine. By understanding the biomechanical and neuromuscular dynamics of the deadlift, practitioners can improve performance, minimize injury risk, and tailor interventions to the specific needs of athletes. Thus, this review provides a comprehensive overview of the current understanding of deadlift kinematics and EMG activity, offering valuable insights for optimizing training and rehabilitation protocols.

Abstract Background Myocardial infarction (MI), a representative form of ischemic heart disease, remains a huge burden worldwide. This study aimed to explore whether extracellular vesicles (EVs) secreted from hyaluronic acid (HA)-primed induced mesenchymal stem cells (HA-iMSC-EVs) could enhance the cardiac repair after MI. Results HA-iMSC-EVs showed typical characteristics for EVs such as morphology, size, and marker proteins expression. Compared with iMSC-EVs, HA-iMSC-EVs showed enhanced tube formation and survival against oxidative stress in endothelial cells, while reduced reactive oxygen species (ROS) generation in cardiomyocytes. In THP-1 macrophages, both types of EVs markedly reduced the expression of pro-inflammatory signaling players, whereas HA-iMSC-EVs were more potent in augmenting anti-inflammatory markers. A significant decrease of inflammasome proteins was observed in HA-iMSC-EV-treated THP-1. Further, phospho-SMAD2 as well as fibrosis markers in TGF-β1-stimulated cardiomyocytes were reduced in HA-iMSC-EVs treatment. Proteomic data showed that HA-iMSC-EVs were enriched with multiple pathways including immunity, extracellular matrix organization, angiogenesis, and cell cycle. The localization of HA-iMSC-EVs in myocardium was confirmed after delivery by either intravenous or intramyocardial route, with the latter increased intensity. Echocardiography revealed that intramyocardial HA-iMSC-EVs injections improved cardiac function and reduced adverse cardiac remodeling and necrotic size in MI heart. Histologically, MI hearts receiving HA-iMSC-EVs had increased capillary density and viable myocardium, while showed reduced fibrosis. Conclusions Our results suggest that HA-iMSC-EVs improve cardiac function by augmenting vessel growth, while reducing ROS generation, inflammation, and fibrosis in MI heart. Graphical Abstract

We present a novel in situ liquid-cell transmission electron microscopy (TEM) approach to study the behavior of metal nanoparticles under high-energy electron irradiation. By utilizing a radically-inert liquid environment, we aim to minimize radiolysis effects and explore the influence of charge-induced transformations. We observed complex dynamics in nanoparticle behavior, including morphological changes and transitions between amorphous and crystalline states. These transformations are attributed to the delicate interplay between charge accumulation on the nanoparticles and enhanced radiolysis, suggesting a significant role for charge-assisted processes in nanoparticle evolution. Our findings provide valuable insights into the fundamental mechanisms driving nanoparticle behavior at the nanoscale and demonstrate the potential of liquid-cell TEM for studying complex physicochemical processes in controlled environments.

LiFePO4 emerges as a viable alternative to cobalt‐containing cathodes, such as Li[Ni1–x–yMnxCoy]O2 and Li[Ni1−x−yCoxAly]O2. As Fe is abundant in nature, LiFePO4 is a low‐cost material. Moreover, stable structure of LiFePO4 imparts long service life and thermal stability. However, the practical implementation of LiFePO4 cathode in energy storage devices is impeded by its low energy density and high ionic/electrical resistance. Herein, the LiFePO4 electrode with high active material loading and low ionic/electrical resistance through the dry process is reported for the first time. The dry process not only enables the uniform distribution of the polymeric binders and conductive additives within the thick electrode but also inhibits the formation of cracks. Furthermore, the bridge‐like connection of polytetrafluoroethylene facilitates the insertion and extraction of Li ions to the LiFePO4 crystal. Hence, the dry‐processed LiFePO4 electrode with high areal capacity (7.8 mAh cm−2) exhibits excellent cycle stability over 300 cycles in full‐cell operation. In addition, it is demonstrated that the estimated energy density of prismatic cell with the dry‐processed LiFePO4 electrode is competitive with state‐of‐the‐art Li[Ni1–x–yMnxCoy]O2‐based battery.

Structure-based drug design (SBDD) has gained popularity owing to its ability to develop more potent drugs compared to conventional drug-discovery methods. The success of SBDD relies heavily on obtaining the three-dimensional structures of drug targets. X-ray crystallography is the primary method used for solving structures and aiding the SBDD workflow; however, it is not suitable for all targets. With the resolution revolution, enabling routine high-resolution reconstruction of structures, cryogenic electron microscopy (cryo-EM) has emerged as a promising alternative and has attracted increasing attention in SBDD. Cryo-EM offers various advantages over X-ray crystallography and can potentially replace X-ray crystallography in SBDD. To fully utilize cryo-EM in drug discovery, understanding the strengths and weaknesses of this technique and noting the key advancements in the field are crucial. This review provides an overview of the general workflow of cryo-EM in SBDD and highlights technical innovations that enable its application in drug design. Furthermore, the most recent achievements in the cryo-EM methodology for drug discovery are discussed, demonstrating the potential of this technique for advancing drug development. By understanding the capabilities and advancements of cryo-EM, researchers can leverage the benefits of designing more effective drugs. This review concludes with a discussion of the future perspectives of cryo-EM-based SBDD, emphasizing the role of this technique in driving innovations in drug discovery and development. The integration of cryo-EM into the drug design process holds great promise for accelerating the discovery of new and improved therapeutic agents to combat various diseases.

Predictably, the upcoming six generation (6G) networks demand ultra-massive interconnectivity comprising densely congested sustainable small-to-tiny networks. The conventional radio access network (RAN) will be redesigned to provide the necessary intelligence in all areas to meet required network flexibility, full coverage, and massive access. In this respect, this paper focuses on intelligent massive RAN (mRAN) architecture and key technologies fulfilling the requirements. Particularly, we investigate potential artificial intelligence algorithms for network and resource management issues in 6G mRAN. Furthermore, we summarize the research issues in edge technologies and physical layer intelligence on 6G network architecture.

BackgroundAccurate and timely assessment of children’s developmental status is crucial for early diagnosis and intervention. More accurate and automated developmental assessments are essential due to the lack of trained health care providers and imprecise parental reporting. In various areas of development, gross motor development in toddlers is known to be predictive of subsequent childhood developments. ObjectiveThe purpose of this study was to develop a model to assess gross motor behavior and integrate the results to determine the overall gross motor status of toddlers. This study also aimed to identify behaviors that are important in the assessment of overall gross motor skills and detect critical moments and important body parts for the assessment of each behavior. MethodsWe used behavioral videos of toddlers aged 18-35 months. To assess gross motor development, we selected 4 behaviors (climb up the stairs, go down the stairs, throw the ball, and stand on 1 foot) that have been validated with the Korean Developmental Screening Test for Infants and Children. In the child behavior videos, we estimated each child’s position as a bounding box and extracted human keypoints within the box. In the first stage, the videos with the extracted human keypoints of each behavior were evaluated separately using a graph convolutional networks (GCN)–based algorithm. The probability values obtained for each label in the first-stage model were used as input for the second-stage model, the extreme gradient boosting (XGBoost) algorithm, to predict the overall gross motor status. For interpretability, we used gradient-weighted class activation mapping (Grad-CAM) to identify important moments and relevant body parts during the movements. The Shapley additive explanations method was used for the assessment of variable importance, to determine the movements that contributed the most to the overall developmental assessment. ResultsBehavioral videos of 4 gross motor skills were collected from 147 children, resulting in a total of 2395 videos. The stage-1 GCN model to evaluate each behavior had an area under the receiver operating characteristic curve (AUROC) of 0.79 to 0.90. Keypoint-mapping Grad-CAM visualization identified important moments in each behavior and differences in important body parts. The stage-2 XGBoost model to assess the overall gross motor status had an AUROC of 0.90. Among the 4 behaviors, “go down the stairs” contributed the most to the overall developmental assessment. ConclusionsUsing movement videos of toddlers aged 18-35 months, we developed objective and automated models to evaluate each behavior and assess each child’s overall gross motor performance. We identified the important behaviors for assessing gross motor performance and developed methods to recognize important moments and body parts while evaluating gross motor performance.

PurposeThe objective of this study was to analyze proposed Korean nursing legislation as depicted in newspaper articles, to highlight issues related to the legislative process for this potential law, and to better understand social awareness regarding this matter.MethodsThe study focused on articles from 11 leading newspapers in Korea, published between February 2020 and August 2023, that pertained to nursing legislation. The articles were retrieved from the BigKinds database. Following text preprocessing, analytical methods including term frequency-inverse document frequency were employed, along with latent Dirichlet allocation (LDA), for word and topic modeling analysis. Additionally, LDA was applied across time periods to examine temporal changes in topics.ResultsFollowing preprocessing, a total of 7,967 words were extracted from the 991 articles selected for analysis. The primary themes identified in newspaper articles concerning the nursing legislation were organized into three main topics: 1) the necessity and impact of enactment of the nursing law, 2) the political context surrounding enactment of the law, and 3) the conflicts between and actions of healthcare organizations related to enactment of the law.ConclusionsThe findings confirmed that media coverage regarding the proposed nursing legislation primarily concentrated on the political and social conflicts associated with the law's passage, rather than its necessity and substance. More compelling evidence must be presented concerning the influence of the nursing workforce and the work environment of nurses on patient safety and health outcomes. Additionally, strategies should be devised to improve public comprehension of the nursing law's provisions.

Histones are subjected to extensive covalent modifications that affect inter-nucleosomal interactions as well as alter chromatin structure and DNA accessibility. Through switching the corresponding histone modifications, the level of transcription and diverse downstream biological processes can be regulated. Although animal systems are widely used in studying histone modifications, the signalling processes that occur outside the nucleus prior to histone modifications have not been well understood due to the limitations including non viable mutants, partial lethality, and infertility of survivors. Here, we review the benefits of using Arabidopsis thaliana as the model organism to study histone modifications and their upstream regulations. Similarities among histones and key histone modifiers such as the Polycomb group (PcG) and Trithorax group (TrxG) in Drosophila, Human, and Arabidopsis are examined. Furthermore, prolonged cold-induced vernalization system has been well-studied and revealed the relationship between the controllable environment input (duration of vernalization), its chromatin modifications of FLOWERING LOCUS C (FLC), following gene expression, and the corresponding phenotypes. Such evidence suggests that research on Arabidopsis can bring insights into incomplete signalling pathways outside of the histone box, which can be achieved through viable reverse genetic screenings based on the phenotypes instead of direct monitoring of histone modifications among individual mutants. The potential upstream regulators in Arabidopsis can provide cues or directions for animal research based on the similarities between them.

Throughput prediction is crucial for reducing latency in time-critical services. We study the attention-based LSTM model for predicting future throughput. First, we collected the TCP logs and throughputs in LTE networks and transformed them using CUBIC and BBR trace log data. Then, we use the sliding window method to create input data for the prediction model. Finally, we trained the LSTM model with an attention mechanism. In the experiment, the proposed method shows lower normalized RMSEs than the other method.

A 61-year-old female patient with chronic kidney disease due to diabetes mellitus and hypertension–induced nephropathy received a deceased donor kidney transplant in March 2020. In July 2020, she was transferred from a local hospital due to the exacerbation of general weakness and diarrhea. Upon her arrival, we noticed a high level of serum creatinine (sCr) of 1.5 mg/dL and a decrease in urine output. Her laboratory results indicated significant hemolysis, with a hemoglobin level of 7.0 g/dL, platelet count of 20 ×103/µL, and a lactate dehydrogenase level of 3,207 IU/L. Kidney biopsy showed severe thrombotic microangiopathy without any evidence of acute rejection. Under the impression of atypical hemolytic uremic syndrome (aHUS), we immediately started plasmapheresis and hemodialysis for anuria. Eculizumab was considered as a kidney graft rescue therapy since her sCr level was not effectively decreased, and her anuria continued despite hemodialysis and plasmapheresis. Eculizumab (900 mg) was administered weekly for 4 weeks. An additional 600 mg of eculizumab was administered on the day of plasmapheresis. Since the patient’s laboratory data gradually improved, hemodialysis and plasmapheresis were ceased on admission day 37. After that, eculizumab was administered biweekly (1,200 mg) two more times. The patient’s sCr and platelet count normalized after 2 months of eculizumab treatment. Based on our experience, a shorter interval between the clinical diagnosis of aHUS and administration of eculizumab increases the likelihood of rescuing the kidney.

Dark-matter-deficient galaxies (DMDGs) discovered in the survey of ultra-diffuse galaxies (UDGs), in apparent conflict with standard cold dark matter, may be produced by high-velocity galaxy–galaxy collisions, the so-called Mini-Bullet scenario. Recent observations of an aligned trail of 7–11 UDGs near NGC 1052, including DMDGs DF2 and DF4, suggesting a common formation event, ∼8.9 ± 1.5 Gyr ago, provide a test.Hydro/ N -body simulations, supplemented by galaxy orbit integrations, demonstrate that satellite–satellite collisions outside the host-galaxy virial radius can reproduce the observed UDGs in the NGC 1052 group. A trail of ∼10 DMDGs is shown to form, including 2 massive ones that replicate the observed motions of DF2 and DF4. The linear relation, v = A x + v _0 , conjectured previously to relate positions ( x ) and velocities ( v ) of the aligned DMDGs as a signature of the collision event, is approximately obeyed, but individual DMDGs can deviate significantly from it. The progenitors whose collision spawned the trail of DMDGs survive the collision without themselves becoming DMDGs. We predict that one progenitor is located at the end of the trail, which can be tested by observing the difference between its stars, formed pre-collision, from those of the DMDGs, formed post-collision. By contrast, stellar ages and metallicities of the DMDGs are nearly identical. We further offer a hint that the tidal field of host NGC 1052 may contribute to making DMDGs diffuse. ΛCDM simulation in a 100 cMpc box finds our required initial conditions ∼10 times at z < 3. These results indicate current observations are consistent with the Mini-Bullet scenario.

In this study, crystallization in highly supersaturated aqueous urea solutions was investigated using in situ infrared thermography facilitated by an acoustic levitation apparatus. A notable contribution of this thermographic approach is the identification of a transient heat release signature, particularly pronounced beyond the solubility limit, indicating the enhanced formation of bonds between urea molecules in the supersaturated states. Surprisingly, the temporal evolution of the heat release measurements on an acoustically levitated droplet strongly suggests a two-stage process for urea crystallization. A comprehensive statistical analysis based on classical nucleation theory is used to further investigate the exceptionally high degree of supersaturation and the emergence of prominent heat signatures observed toward the onset of crystallization.

We investigate the coherence properties of a transmission electron microscope by analyzing nano-diffraction speckles originating from bulk metallic glass. The spatial correlation function of the coherent diffraction patterns, obtained in the transmission geometry, reveals the highly coherent nature of the electron probe beam and its spatial dimension incident on the sample. Quantitative agreement between the measured speckle contrast and an analytical model yields estimates for the transverse and longitudinal coherence lengths of the source. We also demonstrate that the coherence can be controlled by changing the beam convergence angle. Our findings underscore the preservation of electron beam coherence throughout the electron optics, as evidenced by the high-contrast speckles observed in the scattering patterns of the amorphous system. This study paves the way for the application of advanced coherent diffraction methodologies to investigate local structures and dynamics occurring at atomic-length scales across a diverse range of materials.

Abstract The prevalence of cardiocerebrovascular disease (CVD) is continuously increasing, and it is the leading cause of human death. Since it is difficult for physicians to screen thousands of people, high-accuracy and interpretable methods need to be presented. We developed four machine learning-based CVD classifiers (i.e., multi-layer perceptron, support vector machine, random forest, and light gradient boosting) based on the Korea National Health and Nutrition Examination Survey. We resampled and rebalanced KNHANES data using complex sampling weights such that the rebalanced dataset mimics a uniformly sampled dataset from overall population. For clear risk factor analysis, we removed multicollinearity and CVD-irrelevant variables using VIF-based filtering and the Boruta algorithm. We applied synthetic minority oversampling technique and random undersampling before ML training. We demonstrated that the proposed classifiers achieved excellent performance with AUCs over 0.853. Using Shapley value-based risk factor analysis, we identified that the most significant risk factors of CVD were age, sex, and the prevalence of hypertension. Additionally, we identified that age, hypertension, and BMI were positively correlated with CVD prevalence, while sex (female), alcohol consumption and, monthly income were negative. The results showed that the feature selection and the class balancing technique effectively improve the interpretability of models.

Mutations in breast cancer-associated 1 (BRCA1) increase the lifetime risk of developing breast cancer by up to 51% over the risk of the general population. Many aspects of this multifunctional protein have been revealed, including its essential role in homologous recombination repair, E3 ubiquitin ligase activity, transcriptional regulation, and apoptosis. Although most studies have focused on BRCA1 deficiency due to mutations, only a minority of patients carry BRCA1 mutations. A recent study has suggested an expanded definition of BRCA1 deficiency with reduced BRCA1 levels, which accounts for almost half of all triple-negative breast cancer (TNBC) patients. Reduced BRCA1 levels can result from epigenetic modifications or increased proteasomal degradation. In this review, we discuss how this knowledge of BRCA1 function and regulation of BRCA1 protein stability can help overcome the challenges encountered in the clinic and advance current treatment strategies for BRCA1-related breast cancer patients, especially focusing on TNBC.

Abstract Despite the many comorbidities and high mortality rate in preterm infants with patent ductus arteriosus (PDA), therapeutic strategies vary depending on the clinical setting, and most studies of the related risk factors are based on small sample populations. We aimed to compare the performance of artificial intelligence (AI) analysis with that of conventional analysis to identify risk factors associated with symptomatic PDA (sPDA) in very low birth weight infants. This nationwide cohort study included 8369 very low birth weight (VLBW) infants. The participants were divided into an sPDA group and an asymptomatic PDA or spontaneously close PDA (nPDA) group. The sPDA group was further divided into treated and untreated subgroups. A total of 47 perinatal risk factors were collected and analyzed. Multiple logistic regression was used as a standard analytic tool, and five AI algorithms were used to identify the factors associated with sPDA. Combining a large database of risk factors from nationwide registries and AI techniques achieved higher accuracy and better performance of the PDA prediction tasks, and the ensemble methods showed the best performances.

Plants utilize delicate mechanisms to effectively respond to changes in the availability of nutrients such as iron. The responses to iron status involve controlling gene expression at multiple levels. The regulation of iron deficiency response by a network of transcriptional regulators has been extensively studied and recent research has shed light on post-translational control of iron homeostasis. Although not as considerably investigated, an increasing number of studies suggest that histone modification and DNA methylation play critical roles during iron deficiency and contribute to fine-tuning iron homeostasis in plants. This review will focus on the current understanding of chromatin-based regulation on iron homeostasis in plants highlighting recent studies in Arabidopsis and rice. Understanding iron homeostasis in plants is vital, as it is not only relevant to fundamental biological questions, but also to agriculture, biofortification, and human health. A comprehensive overview of the effect and mechanism of chromatin-based regulation in response to iron status will ultimately provide critical insights in elucidating the complexities of iron homeostasis and contribute to improving iron nutrition in plants.

BackgroundPolicy makers and practitioners in low- and middle-income countries (LMICs) are increasingly focusing on the effectiveness of digital devices in the delivery of medical and educational services to children under resource constraints. It is widely known that digital literacy can be fostered through exposure to and education regarding digital devices, which can improve children’s academic performance as well as their search and communication skills in the digital era. However, the correlation between the cognitive function of children and exposure and intensity of the exposure to digital devices has rarely been studied, and the association between digital device exposure and the socioeconomic characteristics and cognitive development of children in LMICs is unknown. ObjectiveThis study examines the association among exposure to digital devices, socioeconomic status, and cognitive function in children aged 3 to 9 years in Cambodia. MethodsWe used a survey of 232 children that gathered data on familiarity with digital devices, demographic characteristics, and socioeconomic status, as well as a Cambridge Neuropsychological Test Automated Battery test for cognitive function, to examine the association between possible barriers and factors that may influence the cognitive function of children in 2 Cambodian schools from April 22, 2019, to May 4, 2019. A comparative analysis was performed with and without digital exposure, and an association analysis was performed among the variables from the survey and cognitive function. ResultsSignificant differences were observed in demographic and socioeconomic characteristics such as school location, family type, and family income according to digital device exposure. The results of the Cambridge Neuropsychological Test Automated Battery tests, except for 1 test related to executive function, indicated no significant differences (P>.05) between group A and group B or among the 4 subgroups. Pretest digital device experience and amount of time spent using digital devices during the test had no significant impacts on the cognitive development of the children. Conversely, the multivariate analyses showed that cognitive function was associated with educational expenses per child, school (location), family type, and family income. ConclusionsThese results provide evidence to policy makers and practitioners on the importance of improving socioeconomic conditions, leading to investment in education by implementing programs for children’s cognitive development through digital devices in LMICs.

BackgroundAutism spectrum disorder (ASD) is characterized by abnormalities in social communication and limited and repetitive behavioral patterns. Children with ASD who lack social communication skills will eventually not interact with others and will lack peer relationships when compared to ordinary people. Thus, it is necessary to develop a program to improve social communication abilities using digital technology in people with ASD. ObjectiveWe intend to develop and apply a metaverse-based child social skills training program aimed at improving the social interaction abilities of children with ASD aged 7-12 years. We plan to compare and analyze the biometric information collected through wearable devices when applying the metaverse-based social skills training program to evaluate emotional changes in children with ASD in stressful situations. MethodsThis parallel randomized controlled study will be conducted on children aged 7-12 years diagnosed with ASD. A metaverse-based social skills training program using digital technology will be administered to children who voluntarily wish to participate in the research with consent from their legal guardians. The treatment group will participate in the metaverse-based social skills training program developed by this research team once a week for 60 minutes per session for 4 weeks. The control group will not intervene during the experiment. The treatment group will use wearable devices during the experiment to collect real-time biometric information. ResultsThe study is expected to recruit and enroll participants in March 2022. After registering the participants, the study will be conducted from March 2022 to May 2022. This research will be jointly conducted by Yonsei University and Dobrain Co Ltd. Children participating in the program will use the internet-based platform. ConclusionsThe metaverse-based Program for the Education and Enrichment of Relational Skills (PEERS) will be effective in improving the social skills of children with ASD, similar to the offline PEERS program. The metaverse-based PEERS program offers excellent accessibility and is inexpensive because it can be administered at home; thus, it is expected to be effective in many children with ASD. If a method can be applied to detect children's emotional changes early using biometric information collected through wearable devices, then emotional changes such as anxiety and anger can be alleviated in advance, thus reducing issues in children with ASD. Trial RegistrationClinical Research Information Service KCT0006859; https://tinyurl.com/4r3k7cmj International Registered Report Identifier (IRRID)PRR1-10.2196/35960

Purpose The severity of a patient’s medical condition, changing pharmacodynamics and pharmacokinetics, and variability in medication highlight the importance of pharmacological intervention by intensive care unit (ICU) specialized pharmacists. Methods Retrospective observations of ICU interventions (omission, changes in medicine, side effects, changes in administration route and dosage, redundancy, and nutritional care) performed between April 2017 and March 2018, determined by an interdisciplinary team (including a specialized ICU pharmacist and a surgical intensivist) on their surgical ICU round, were analyzed. Medicinal prescriptions were screened weekly during the surgical ICU round, and interventions were made if any corrections were necessary. Two days later another team including a surgical intensivist, a pharmacist, and a nutritionist evaluated the patients’ nutritional status (performed weekly). Results In the 23-bed ICU, the average number of patients whose prescriptions were examined was 22.38 per surgical round. There were 382 interventions made over 1 year, which was 9.68 interventions per day. The interventions were for nutritional care (161 cases, 42.2%), followed by changes in administration route and dosage (94 cases, 24.6%), omission (59 cases, 15.5%), redundancy (40 cases, 10.4%), changes in medicine (15 cases, 3.9%), and side effects (13 cases, 3.4%). Conclusion The conditions of patients admitted to ICU are typically unstable. Pharmacological interventions suggested by a specialized pharmacist may help control the changing medical condition of patients in ICU. A higher participation of pharmacists specialized in working in an interdisciplinary ICU team-based system could lead to safer treatments.

Pre-harvest sprouting (PHS) of rice (Oryza sativa L.) causes severe economic problems due to reduced grain quality and yield. Fine mapping was carried out to identify genes associated with PHS; the detected quantitative trait locus (QTL) was narrowed down to 50 Kbp using F3:4 populations, four polymorphic insertion and deletion (InDel) markers, and two cleaved amplified polymorphic sequence (CAPS) markers. In one region, five candidate genes were detected, and the SNP and InDel in each gene (Os01g0111400 and Os01g0111600) were confirmed to show the differences and resulting amino acid changes between parent plants. Based on haplotype, expression, and co-segregation analysis, the InDel in Os01g0111600 was confirmed to be associated with the PHS trait. The results of this study could be applied to improve the PHS tolerance of Japonica rice varieties, and they also improved our understanding of the genetic basis underlying PHS tolerance.

Objective:Breast cancer is the most common type of cancer among women in the Philippines. Philippines has one of the highest breast cancer mortality rate and the lowest mortality-to-incidence ratio in Asia. This study has three objectives: 1) explore Filipino women's knowledge, attitudes toward, and practices of breast cancer and cancer screening, 2) examine if an educational program increases women’s intention to seek future breast cancer screening, and 3) examine associations between demographic variables and breast cancer screening practices.Materials and Methods:A total of 944 women from two urban areas (Calasciao and Tacloban City) and one rural area (Sogood) of the Philippines participated in this cross-sectional study. Study participants attended an educational program and completed study questionnaires regarding demographics, knowledge about, and practices of breast self-exams, clinical breast exams and mammography as well as reported barriers toward future screening.Results:The results showed a disparity between knowledge of routine breast cancer screening and actuals screening behaviors. Following breast health education and screening programs, participants reported greater intention to adhere to recommended breast cancer screening guidelines. The multivariate analyses showed that education level is a significant predictor for CBE and mammography uptake in current study.Conclusion:This study has implications for breast cancer control among women in low-resources settings. Designing and implementing effective educational programs that increase women’s awareness about breast cancer and promote screening uptake are important steps to reduce the burden affected by breast cancer among women in the Philippines and other South Asian low- to middle-income countries.

Despite the unprecedented success of deep learning in various fields, it has been recognized that clinical diagnosis requires extra caution when applying recent deep learning techniques because false prediction can result in severe consequences. In this study, we proposed a reliable deep learning framework that could minimize incorrect segmentation by quantifying and exploiting uncertainty measures. The proposed framework demonstrated the effectiveness of a public dataset: Multimodal Brain Tumor Segmentation Challenge 2018. By using this framework, segmentation performances, particularly for small lesions, were improved. Since the segmentation of small lesions is difficult but also clinically significant, this framework could be effectively applied to the medical imaging field.

Protein transduction domains (PTDs) have been shown to promote the delivery of therapeutic proteins or peptides into the living cells. In a previous study, we showed that the double mutant of TCTP-PTD 13, TCTP-PTD 13M2, was more effective in the delivery of insulin than the wild-type TCTP-PTD 13. In this study, we applied this approach to the nasal delivery of a different peptide, exendin-4, using as carriers, several modified TCTP-PTDs, such as TCTP-PTD 13M1, 13M2, and 13M3. Nasal co-administration of TCTP-PTD 13M2 with exendin-4 showed the highest exendin-4 uptake among the three analogs in normal rats, and also decreased blood glucose levels by 43.3% compared with that of exendin-4 alone and by 18.6% compared with that of exendin-4 plus TCTP-PTD 13 in diabetic mice. We also designed an additional covalently linked conjugate of TCTP-PTD 13M2 and exendin-4 and evaluated its hypoglycemic effect after subcutaneous or intranasal delivery. Subcutaneous administration of exendin-4 that its C-terminus is covalently linked to TCTP-PTD 13M2 showed hypoglycemic effect of 42.2% compared to that in untreated group, whereas intranasal delivery was not successful in diabetic mice. We conclude that a simple mixing TCTP-PTD 13M2 with peptide/protein drugs can be potentially a generally applicable approach for intranasal delivery into animals.

Carrier peptides, termed protein transduction domains (PTDs), serve as provide promising vehicles for intranasal delivery of macromolecular drugs. A mutant PTD derived from human translationally controlled tumor protein (TCTP-PTD 13, MIIFRALISHKK) was reported to provide enhanced intranasal delivery of insulin. In this study, we tested whether its efficiency could be further improved by replacing amino acids in TCTP-PTD 13 or changing the amino acids in the carrier peptides from the l- to the d-form. We assessed the pharmacokinetics of PTD-mediated transmucosal delivery of insulin in normal rats and the activity of insulin in alloxan-induced diabetic rats. The safety/toxicity profile of the carrier peptides was evaluated based on the release of lactate dehydrogenase (LDH) in nasal wash fluid, body weight changes, and several biochemical parameters. Pharmacokinetic and pharmacodynamic studies showed that the l-form of a double substitution A6L, I8A (MIIFRLLASHKK), designated as l-TCTP-PTD 13M2 was the most effective carrier for intranasal insulin delivery. The relative bioavailability of insulin co-administered intranasally with l-TCTP-PTD 13M2 was 37.1% of the value obtained by the subcutaneous route, which was 1.68-fold higher than for insulin co-administered with l-TCTP-PTD 13. Moreover, co-administration of insulin plus l-TCTP-PTD 13M2 reduced blood glucose levels compared to levels in diabetic rats treated with insulin plus l-TCTP-PTD 13. There was no evidence of toxicity. These results suggest that the newly designed PTD is a useful carrier peptide for the intranasal delivery of drugs or biomolecules.

Direct seeding is considered an efficient cultivation technology that reduces water use and labor costs. Mesocotyl length is one of the significant traits in cultivation; long mesocotyl is beneficial for the rate and uniformity of seedling emergence. In this study, we used a core collection of 137 rice accessions to identify quantitative trait loci (QTL) for mesocotyl elongation. A genome-wide association study (GWAS), combined with a principal component analysis (PCA) and a kinship matrix analysis, was conducted for the genotype analysis of 2 million, high-quality single nucleotide polymorphisms (SNPs). Through this GWAS analysis, 11 lead SNPs were confirmed to be associated with mesocotyl length, and a linkage disequilibrium (LD) decay analysis identified the 230 kb exploratory range for the detection of QTLs and candidate genes. Based on the gene expression database and haplotype analysis, five candidate genes (Os01g0269800, Os01g0731100, Os08g0136700, Os08g0137800, and Os08g0137900) were detected to be significantly associated with phenotypic variation. Five candidate gene expressions are reported to be associated with various plant hormone responses. Interestingly, two biotic stress response genes and two copper-containing redox proteins were detected as the candidate genes. The results of this study provide associated SNPs in candidate genes for mesocotyl length and strategies for developing direct seeding in breeding programs.

Salinity is one of the major constraints causing soil problems and is considered a limitation to increased rice production in rice-growing countries. This genome-wide association study (GWAS) experiment was conducted to understand the genetic basis of salt tolerance at the seedling stage in Korean rice. After 10 days of salt stress treatment, salt tolerance was evaluated with a standard evaluation system using a visual salt injury score. With 191 Korean landrace accessions and their genotypes, including 266,040 single-nucleotide polymorphisms (SNPs), using a KNU Axiom Oryza 580K Genotyping Array, GWAS was conducted to detect three QTLs with significant SNPs with a −log10(P) threshold of ≥3.66. The QTL of qSIS2, showed −log10(P) = 3.80 and the lead SNP explained 7.87% of total phenotypic variation. The QTL of qSIS4, showed −log10(P) = 4.05 and the lead SNP explained 10.53% of total phenotypic variation. The QTL of qSIS8 showed −log10(P) = 3.78 and the lead SNP explained 7.83% of total phenotypic variation. Among the annotated genes located in these three QTL regions, five genes were selected as candidates (Os04g0481600, Os04g0485300, Os04g0493000, Os04g0493300, and Os08g0390200) for salt tolerance in rice seedlings based on the gene expression database and their previously known functions.

Oxidative stress is a pathological condition occurring due to an imbalance between the oxidants and antioxidant defense systems in the body. Nuclear factor E2-related factor 2 (NRF2), encoded by the gene NFE2L2, is the master regulator of phase II antioxidant enzymes that protect against oxidative stress and inflammation. NRF2/ARE signaling has been considered as a promising target against oxidative stress-mediated diseases like diabetes, fibrosis, neurotoxicity, and cancer. The consumption of dietary phytochemicals acts as an effective modulator of NRF2/ARE in various acute and chronic diseases. In the present review, we discussed the role of NRF2 in diabetes, Alzheimer’s disease (AD), Parkinson’s disease (PD), cancer, and atherosclerosis. Additionally, we discussed the phytochemicals like curcumin, quercetin, resveratrol, epigallocatechin gallate, apigenin, sulforaphane, and ursolic acid that have effectively modified NRF2 signaling and prevented various diseases in both in vitro and in vivo models. Based on the literature, it is clear that dietary phytochemicals can prevent diseases by (1) blocking oxidative stress-inhibiting inflammatory mediators through inhibiting Keap1 or activating Nrf2 expression and its downstream targets in the nucleus, including HO-1, SOD, and CAT; (2) regulating NRF2 signaling by various kinases like GSK3beta, PI3/AKT, and MAPK; and (3) modifying epigenetic modulation, such as methylation, at the NRF2 promoter region; however, further investigation into other upstream signaling molecules like NRF2 and the effect of phytochemicals on them still need to be investigated in the near future.

A genome-wide association study (GWAS) was used to investigate the genetic basis of chilling tolerance in a collection of 117 rice accessions, including 26 Korean landraces and 29 weedy rices, at the reproductive stage. To assess chilling tolerance at the early young microspore stage, plants were treated at 12 °C for 5 days, and tolerance was evaluated using seed set fertility. GWAS, together with principal component analysis and kinship matrix analysis, revealed five quantitative trait loci (QTLs) associated with chilling tolerance on chromosomes 3, 6, and 7. The percentage of phenotypic variation explained by the QTLs was 11–19%. The genomic region underlying the QTL on chromosome 3 overlapped with a previously reported QTL associated with spikelet fertility. Subsequent bioinformatic and haplotype analyses suggested three candidate chilling-tolerance genes within the QTL linkage disequilibrium block: Os03g0305700, encoding a protein similar to peptide chain release factor 2; Os06g0495700, encoding a beta tubulin, autoregulation binding-site-domain-containing protein; and Os07g0137800, encoding a protein kinase, core-domain-containing protein. Further analysis of the detected QTLs and the candidate chilling-tolerance genes will facilitate strategies for developing chilling-tolerant rice cultivars in breeding programs.

Grain size affects the yield and quality of rice. The large grain line (LGL), showing a large grain size and japonica-like genome, was selected in the breeding field. The 94 F2 plants derived from a cross between LGL and Hanareum (a high-yielding tongil-type variety) were used for the quantitative trait loci (QTL) analysis of grain length (GL), grain width (GW), and grain thickness (GT). A linkage map of the F2 population, covering 1312 cM for all 12 chromosomes, was constructed using 123 Fluidigm SNP markers. A total of nine QTLs for the three traits were detected on chromosomes two, three, four, six, and seven. Two QTLs for GL on chromosomes two and six explained 17.3% and 16.2% of the phenotypic variation, respectively. Two QTLs were identified for GW on chromosomes two and three, and explained 24.3% and 23.5% of the phenotypic variation, respectively. The five QTLs for GT detected on chromosomes two, three, five, six and seven, explained 13.2%, 14.5%, 16.6%, 10.9%, and 10.2% of the phenotypic variation, respectively. A novel QTL for GT, qGT2, was validated on the same region of chromosome two in the selected F3 population. The QTLs identified in this study, and LGL, could be applied to the development of large-grain rice varieties.

Cellular networks are facing explosive growth of mobile data traffic due to the proliferation of smart devices and traffic-intensive applications. As a cost-effective solution, delayed Wi-Fi offloading was introduced to shift the delay-tolerant traffic from cellular to Wi-Fi networks by trading additional delays. Our paper studies a multi-flow rate control problem where each flow has different traffic load and a deadline. To maximize user satisfaction defined as offloading efficiency minus disutility caused by deadline violation, we propose a dynamic programming-based rate control algorithm. Moreover, to reduce the computation and memory, we propose a simple threshold-based rate control algorithm.

Nonhost resistance, a resistance of plant species against all nonadapted pathogens, is considered the most durable and efficient immune system of plants but yet remains elusive. The underlying mechanism of nonhost resistance has been investigated at multiple levels of plant defense for several decades. In this review, we have comprehensively surveyed the latest literature on nonhost resistance in terms of preinvasion, metabolic defense, pattern-triggered immunity, effector-triggered immunity, defense signaling, and possible application in crop protection. Overall, we summarize the current understanding of nonhost resistance mechanisms. Pre- and postinvasion is not much deviated from the knowledge on host resistance, except for a few specific cases. Further insights on the roles of the pattern recognition receptor gene family, multiple interactions between effectors from nonadapted pathogen and plant factors, and plant secondary metabolites in host range determination could expand our knowledge on nonhost resistance and provide efficient tools for future crop protection using combinational biotechnology approaches.[Graphic: see text] Copyright © 2017 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Iron is an essential micronutrient for nearly all organisms, but excessive iron can lead to the formation of cytotoxic reactive oxygen species. Therefore, iron acquisition and homeostasis must be tightly regulated. Plants have evolved complex mechanisms to optimize their use of iron, which is one of the most limiting nutrients in the soil. In particular, transcriptional regulation is vital for regulating iron in plants, and much work has revealed the role of transcription factors on this front. Our study adds novel insights to the transcriptional regulation of iron homeostasis in plants by showing that chromatin remodeling via histone 3 lysine 27 trimethylation (H3K27me3) modulates the expression of FIT-dependent genes under iron deficiency. We provide evidence that FIT-dependent iron acquisition genes, IRT1 and FRO2, as well as FIT itself are direct targets of PRC2-mediated H3K27me3. In the clf mutant, which lacks the predominant H3K27 tri-methyltransferase, induction of FIT, FRO2, IRT1, and other FIT-regulated genes in roots is significantly higher under iron deficient conditions than in wild type. Furthermore, we observe that clf mutants are more tolerant to iron deficiency than wild type, indicating that gene expression levels appear to be limiting the plants ability to access iron. We propose that H3K27me3 attenuates the induction of FIT-target genes under iron deficiency and hypothesize that this may serve as a mechanism to restrict the maximum level of induction of iron acquisition genes to prevent iron overload.

In this paper, we propose a prediction algorithm, the combination of Long Short-Term Memory (LSTM) and attention model, based on machine learning models to predict the vision coordinates when watching 360-degree videos in a Virtual Reality (VR) or Augmented Reality (AR) system. Predicting the vision coordinates while video streaming is important when the network condition is degraded. However, the traditional prediction models such as Moving Average (MA) and Autoregression Moving Average (ARMA) are linear so they cannot consider the nonlinear relationship. Therefore, machine learning models based on deep learning are recently used for nonlinear predictions. We use the Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) neural network methods, originated in Recurrent Neural Networks (RNN), and predict the head position in the 360-degree videos. Therefore, we adopt the attention model to LSTM to make more accurate results. We also compare the performance of the proposed model with the other machine learning models such as Multi-Layer Perceptron (MLP) and RNN using the root mean squared error (RMSE) of predicted and real coordinates. We demonstrate that our model can predict the vision coordinates more accurately than the other models in various videos.

We conducted a genome-wide association study (GWAS) of cold tolerance in a collection of 127 rice accessions, including 57 Korean landraces at the seedling stage. Cold tolerance of rice seedlings was evaluated in a growth chamber under controlled conditions and scored on a 0–9 scale, based on their low-temperature response and subsequent recovery. GWAS, together with principal component analysis (PCA) and kinship matrix analysis, revealed four quantitative trait loci (QTLs) on chromosomes 1, 4, and 5 that explained 16.5% to 18.5% of the variance in cold tolerance. The genomic region underlying the QTL on chromosome four overlapped with a previously reported QTL associated with cold tolerance in rice seedlings. Similarly, one of the QTLs identified on chromosome five overlapped with a previously reported QTL associated with seedling vigor. Subsequent bioinformatic and haplotype analyses revealed three candidate genes affecting cold tolerance within the linkage disequilibrium (LD) block of these QTLs: Os01g0357800, encoding a pentatricopeptide repeat (PPR) domain-containing protein; Os05g0171300, encoding a plastidial ADP-glucose transporter; and Os05g0400200, encoding a retrotransposon protein, Ty1-copia subclass. The detected QTLs and further evaluation of these candidate genes in the future will provide strategies for developing cold-tolerant rice in breeding programs.

A 307-m tall meteorological tower was used to evaluate meteorological observation data obtained using a rotary-wing unmanned aerial vehicle (UAV). A comparative study between the tower and UAV observations was conducted during the daytime (06:00 to 19:00 local time (LT)) in the summer of 2017 (16–18th August). Hourly vertical profiles of air temperature, relative humidity, black carbon (BC), and ozone (O3) concentrations were obtained for up to 300 m height. Statistical metrics for evaluating the accuracy of UAV observations against the tower observation showed positive (potential temperature) and negative (relative humidity) biases, which were within acceptable ranges. The daytime evolution of the lower atmospheric boundary layer (ABL) was successfully captured by the hourly UAV observations. During the early morning, a large vertical slope of potential temperature was observed between 100 and 140 m, corresponding to the stable ABL height. The large vertical slope coincided with the large differences in BC and O3 concentrations between altitudes below and above the height. The transition from stable to convective ABL was observed at 10–11 LT, indicated by the ABL height higher than 300 m in the convective ABL. Finally, we provide several recommendations to reduce uncertainties of UAV observation.

To increase coverage of protein identification of an Agaricus bisporus fruiting body, we analyzed the crude protein fraction of the fruiting body by using a shotgun proteomics approach where 7 MudPIT (Multi-Protein identification Technology) runs were conducted and the MS/MS spectra from the 7 MudPIT runs were merged. Overall, 3093 non-redundant proteins were identified to support the expression of those genes annotated in the genome database of Agaricus bisporus. The physicochemical properties of the identified proteins, i.e., wide pI value range and molecular mass range, were indicative of unbiased protein identification. The relative quantification of the identified proteins revealed that K5XI50 (Aldedh domain-containing protein) and K5XEW1 (Ubiquitin-like domain-containing protein) were highly abundant in the fruiting body. Based on the information in the Uniprot (Universal Protein Resource) database for A. bisporus, only approximately 53% of the 3093 identified proteins have been functionally described and approximately 47% of the proteins remain uncharacterized. Gene Ontology analysis revealed that the majority of proteins were annotated with a biological process, and proteins associated with coiled-coil (12.8%) and nucleotide binding (8.21%) categories were dominant. The Kyoto Encyclopedia of Genes and Genome analysis revealed that proteins involved in biosynthesis of secondary metabolites and tyrosine metabolism were enriched in a fruiting body of Agaricus bisporus, suggesting that the proteins are associated with antioxidant metabolites.

The Yeongdong region, located east of the Taebaek Mountains, South Korea, often experiences severe windstorms in spring, causing a lot of damages, especially when forest fires spread out rapidly by strong winds. Here, the characteristics and generation mechanisms of the windstorms in the Yeongdong region on 8 April 2012 are examined through a high-resolution Weather Research and Forecasting (WRF) model simulation. In the Yangyang area, the steep descent of the isentropes on the lee slope of the mountain and their recovery farther leeward are seen. Inversion layers and incoming flow in hydraulic jump regime suggest that the hydraulic jump is responsible for the downslope windstorm. In the Jangjeon area, the plume-shaped wind pattern extending seaward from the gap exit is seen when the sea-level pressure difference between the gap inside and the gap exit, being responsible for the gap winds, is large. In the Uljin area, downslope windstorms pass over the region with weak wind, low Richardson number, and deep planetary boundary layer (PBL), making banded pattern in the wind and PBL height fields. This study demonstrates that the characteristics of the windstorms in the lee of the Taebaek Mountains and their generation mechanisms differ depending on local topographic features.

Lesion mimic mutants (LMMs) commonly exhibit spontaneous cell death similar to the hypersensitive defense response that occurs in plants in response to pathogen infection. Several lesion mimic mutants have been isolated and characterized, but their molecular mechanisms remain largely unknown. Here, a spotted leaf sheath (sles) mutant derived from japonica cultivar Koshihikari is described. The sles phenotype differed from that of other LMMs in that lesion mimic spots were observed on the leaf sheath rather than on leaves. The sles mutant displayed early senescence, as shown, by color loss in the mesophyll cells, a decrease in chlorophyll content, and upregulation of chlorophyll degradation-related and senescence-associated genes. ROS content was also elevated, corresponding to increased expression of genes encoding ROS-generating enzymes. Pathogenesis-related genes were also activated and showed improved resistance to pathogen infection on the leaf sheath. Genetic analysis revealed that the mutant phenotype was controlled by a single recessive nuclear gene. Genetic mapping and sequence analysis showed that a single nucleotide substitution in the sixth exon of LOC_Os07g25680 was responsible for the sles mutant phenotype and this was confirmed by T-DNA insertion line. Taken together, our results revealed that SLES was associated with the formation of lesion mimic spots on the leaf sheath resulting early senescence and defense responses. Further examination of SLES will facilitate a better understanding of the molecular mechanisms involved in ROS homeostasis and may also provide opportunities to improve pathogen resistance in rice.

Purpose: The present survey was conducted to investigate the perceptions among nurses of neonatal pain and the associated use of pharmacologic measures (PMs) and nonpharmacologic comfort measures (CMs) in neonatal intensive care units (NICUs). Pain perception, the necessity and actual use of PMs and CMs, and their relationships were investigated and compared according to nurses' positions, educational levels, the existence of guidelines, and prior education on neonatal pain management. Methods: Participants were 141 nurses from five NICUs at university hospitals. A questionnaire was developed by researchers based on previous studies of neonatal pain management and current practices in surveyed NICUs. Five-point Likert scales were used to assess nurses' perceptions of pain, the necessity of PMs and CMs, and their actual use in 29 painful procedures. Results: The mean scores of perceived pain and the necessity of PMs and CMs were 3.68, 2.96, and 3.79 points, respectively. The actual use of PMs and CMs was 1.67 and 2.63 points, respectively. The perceived necessity of PMs correlated with the actual use of PMs (r = .316, p

Micro-emboli have been reported to occur commonly during arthroscopic surgery, which is frequently performed as an orthopedic surgical procedure. We here report a patient who experienced unilateral postoperative visual loss after a hip arthroscopy using irrigation fluid in the supine position without any evidence of external compression to either eye throughout the surgical procedure. Retinal fundoscopy suggested that the patient had central retinal artery occlusion, one of the causes of the postoperative visual loss. This case suggests that arthroscopic surgery may pose a substantial risk for paradoxical air embolism, such as central retinal artery occlusion, and suggests the need to prevent the entry of micro-air bubbles during such a type of surgery.

Preeclampsia and gestational diabetes (GDM) have several mechanisms in common. The aim of this study was to determine whether women with preeclampsia have an increased risk of GDM in a subsequent pregnancy. Study data were collected from the Korea National Health Insurance Claims Database of the Health Insurance Review and Assessment Service for 2007-2012. Patients who had their first delivery in 2007 and a subsequent delivery between 2008 and 2012 in Korea were enrolled. A model of multivariate logistic regression analysis was performed with GDM as the final outcome to evaluate the risk of GDM in the second pregnancy. Among the 252,276 women who had their first delivery in 2007, 150,794 women had their second delivery between 2008 and 2012. On the multivariate regression analysis, women with preeclampsia alone in the first pregnancy had an increased risk of GDM in the second pregnancy when compared with women who had neither of these conditions in their first pregnancy (OR 1.2, 95% CI, 1.1-1.3). Women with GDM alone in the first pregnancy were at an increased risk for GDM in the second pregnancy (OR 3.3, 95% CI 3.1-3.4). The co-presence of preeclampsia and GDM in the first pregnancy further increased the risk of GDM in the second pregnancy (OR 5.9, 95% CI, 4.0-8.6). Our study showed that a history of preeclampsia may serve as an additional risk factor for GDM in a subsequent pregnancy.

Plants have evolved developmental mechanisms to ensure reproduction when in sub-optimal local environments. The shade-avoidance syndrome is one such mechanism that causes plants to elongate and accelerate flowering. Plants sense shade via the decreased red:far-red (R:FR) ratio that occurs in shade. We explored natural variation in flowering behavior caused by a decrease in the R:FR ratio of Arabidopsis thaliana accessions. A survey of accessions revealed that most exhibit a vigorous rapid-flowering response in a FR-enriched environment. However, a subset of accessions appeared to be compromised in the accelerated-flowering component of the shade-avoidance response. The genetic basis of the muted response to FR enrichment was studied in three accessions (Fl-1, Hau-0, and Mir-0). For all three accessions, the reduced FR flowering-time effect mapped to the FLOWERING LOCUS T (FT) region, and the FT alleles from these accessions are expressed at a lower level in FR-enriched light compared to alleles from accessions that respond robustly to FR enrichment. In the Mir-0 accession, a second genomic region, which includes CONSTANTS (CO), also influenced flowering in FR-enriched conditions. We have demonstrated that variation in the degree of precocious flowering in shaded conditions (low R:FR ratio) results from allelic variation at FT.

Spring orchid (Cymbidium goeringii) is one of the most important species belonging to Orchidaceae owing to its aesthetic appeal, fragrant flowers and ideal characteristics for using as a houseplant. In this study, the complete chloroplast genome of Korean C. goeringii acc. smg222 was determined by Illumina sequencing. The circular double-stranded DNA of 148,441 bp consisted of two inverted repeat regions of 25,610 bp each, a large single copy region of 83,311 bp, and a small single copy region of 13,910 bp. The genome contained 122 genes, of which 104 were unique and 18 were duplicated within the IRs. The 104 unique genes included 70 protein-coding genes, 30 distinct tRNA genes, and four rRNA genes. Phylogenetic tree analysis revealed that C. goeringii acc. smg222 was clustered with Cymbidium kanran, a cymbidium species native to Korea.

Through a comparative shotgun quantitative proteomics analysis in Brassica rapa (inbred line Chiifu), total of 3,009 nonredundant proteins were identified with a false discovery rate of 0.01 in 3-week-old plants subjected to dehydration treatment for 0, 24, and 48 h, plants subjected to drought stress. Ribulose-bisphosphate carboxylases, chlorophyll a/b-binding protein, and light harvesting complex in photosystem II were highly abundant proteins in the leaves and accounted for 9%, 2%, and 4%, respectively, of the total identified proteins. Comparative analysis of the treatments enabled detection of 440 differentially expressed proteins during dehydration. The results of clustering analysis, gene ontology (GO) enrichment analysis, and analysis of composite expression profiles of functional categories for the differentially expressed proteins indicated that drought stress reduced the levels of proteins associated with photosynthesis and increased the levels of proteins involved in catabolic processes and stress responses. We observed enhanced expression of many proteins involved in osmotic stress responses and proteins with antioxidant activities. Based on previously reported molecular functions, we propose that the following five differentially expressed proteins could provide target genes for engineering drought resistance in plants: annexin, phospholipase D delta, sDNA-binding transcriptional regulator, auxin-responsive GH3 family protein, and TRAF-like family protein.