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KEY MESSAGE: Hyperspectral features enable accurate classification of soybean seeds using linear discriminant analysis and GWAS for novel seed trait genes. Evaluating crop seed traits such as size, shape, and color is crucial for assessing seed quality and improving agricultural productivity. The introduction of the SUnSet toolbox, which employs hyperspectral sensor-derived image analysis, addresses this necessity. In a validation test involving 420 seed accessions from the Korean Soybean Core Collections, the pixel purity index algorithm identified seed- specific hyperspectral endmembers to facilitate segmentation. Various metrics extracted from ventral and lateral side images facilitated the categorization of seeds into three size groups and four shape groups. Additionally, quantitative RGB triplets representing seven seed coat colors, averaged reflectance spectra, and pigment indices were acquired. Machine learning models, trained on a dataset comprising 420 accession seeds and 199 predictors encompassing seed size, shape, and reflectance spectra, achieved accuracy rates of 95.8% for linear discriminant analysis model. Furthermore, a genome-wide association study utilizing hyperspectral features uncovered associations between seed traits and genes governing seed pigmentation and shapes. This comprehensive approach underscores the effectiveness of SUnSet in advancing precision agriculture through meticulous seed trait analysis.
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Glycine max , Fenótipo , Sementes , Glycine max/genética , Sementes/genética , Sementes/anatomia & histologia , Estudo de Associação Genômica Ampla/métodos , Imageamento Hiperespectral/métodos , Pigmentação/genética , Processamento de Imagem Assistida por Computador/métodos , Algoritmos , Aprendizado de MáquinaRESUMO
Bakanae disease (BD), caused by the fungal pathogen Fusarium fujikuroi, is a serious threat to rice production worldwide. Breeding elite rice varieties resistant to BD requires the identification of resistance genes. Previously, we discovered a resistant quantitative trait locus (QTL), qFfR1, in a Korean japonica rice variety, Nampyeong. In this study, we fine-mapped qFfR1 with a Junam*4/Nampyeong BC3F3 population and delimited its location to a 37.1 kb region on chromosome 1. Complementation experiments with seven candidate genes in this region revealed that OsI_02728 is the gene for qFfR1. This gene encodes a protein with a typical leucine-rich repeat (LRR) receptor-like protein structure. RNA-sequencing-based transcriptomic analysis revealed that FfR1 induces the transcription of defense genes, including lignin and terpenoid biosynthesis genes, pathogenesis-related genes, and thionin genes. These results may facilitate investigations into the molecular mechanisms underlying BD resistance, including molecular patterns of Fusarium fujikuroi interacting with FfR1 and players working in signal transduction pathways downstream of FfR1, and the breeding of new BD-resistant varieties by providing a BD resistance gene with its precise selection marker. This will contribute to efficient control of BD, which is becoming more prevalent according to temperature rises due to climate change.
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Mapeamento Cromossômico , Resistência à Doença , Fusarium , Oryza , Doenças das Plantas , Locos de Características Quantitativas , Oryza/genética , Oryza/microbiologia , Resistência à Doença/genética , Doenças das Plantas/microbiologia , Doenças das Plantas/genética , Fusarium/patogenicidade , Clonagem Molecular , Proteínas de Plantas/genética , Proteínas de Plantas/metabolismo , Regulação da Expressão Gênica de Plantas , Cromossomos de Plantas/genéticaRESUMO
The gut microbiota plays a pivotal role in metabolic disorders, notably type 2 diabetes mellitus (T2DM). In this study, we investigated the synergistic potential of combining the effects of Bifidobacterium longum NBM7-1 (CKD1) with anti-diabetic medicines, Lobeglitazoneâ (LO), Sitagliptinâ (SI), and Metforminâ (Met), to alleviate hyperglycemia in a diabetic mouse model. CKD1 effectively mitigated insulin resistance, hepatic steatosis, and enhanced pancreatic ß-cell function, as well as fortifying gut-tight junction integrity. In the same way, SI-CKD1 and Met- CKD1 synergistically improved insulin sensitivity and prevented hepatic steatosis, as evidenced by the modulation of key genes associated with insulin signaling, ß-oxidation, gluconeogenesis, adipogenesis, and inflammation by qRT-PCR. The comprehensive impact on modulating gut microbiota composition was observed, particularly when combined with Metforminâ. This combination induced an increase in the abundance of Rikenellaceae and Alistipes related negatively to the T2DM incidence while reducing the causative species of Cryptosporangium, Staphylococcaceae, and Muribaculaceae. These alterations intervene in gut microbiota metabolites to modulate the level of butyrate, indole-3-acetic acid, propionate, and inflammatory cytokines and to activate the IL-22 pathway. However, it is meaningful that the combination of B. longum NBM7-1(CKD1) reduced the medicines' dose to the level of the maximal inhibitory concentrations (IC50). This study advances our understanding of the intricate relationship between gut microbiota and metabolic disorders. We expect this study to contribute to developing a prospective therapeutic strategy modulating the gut microbiota.
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Diabetes Mellitus Experimental , Diabetes Mellitus Tipo 2 , Microbioma Gastrointestinal , Resistência à Insulina , Metformina , Camundongos , Animais , Diabetes Mellitus Tipo 2/tratamento farmacológico , Regulação para Cima , Diabetes Mellitus Experimental/tratamento farmacológico , Metformina/farmacologia , Metformina/uso terapêuticoRESUMO
Osteoporosis is a serious health concern in patients with rheumatoid arthritis (RA). Machine learning (ML) models have been increasingly incorporated into various clinical practices, including disease classification, risk prediction, and treatment response. However, only a few studies have focused on predicting osteoporosis using ML in patients with RA. We aimed to develop an ML model to predict osteoporosis using a representative Korean RA cohort database. The KORean Observational study Network for Arthritis (KORONA) database, established by the Clinical Research Center for RA in Korea, was used in this study. Among the 5077 patients registered in KORONA, 2374 patients were included in this study. Four representative ML algorithms were used for the prediction: logistic regression (LR), random forest, XGBoost (XGB), and LightGBM. The accuracy, F1 score, and area under the curve (AUC) of each model were measured. The LR model achieved the highest AUC value at 0.750, while the XGB model achieved the highest accuracy at 0.682. Body mass index, age, menopause, waist and hip circumferences, RA surgery, and monthly income were risk factors of osteoporosis. In conclusion, ML algorithms are a useful option for screening for osteoporosis in patients with RA.
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Artrite Reumatoide , Osteoporose , Feminino , Humanos , Artrite Reumatoide/tratamento farmacológico , Aprendizado de Máquina , Menopausa , Osteoporose/diagnóstico , Osteoporose/epidemiologia , Osteoporose/etiologia , Fatores de Risco , Estudos Observacionais como AssuntoRESUMO
In the development of new organic crystals for nonlinear optical and terahertz (THz) applications, it is very challenging to achieve the essentially required non-centrosymmetric molecular arrangement. Moreover, the resulting crystal structure is mostly unpredictable due to highly dipolar molecular components with complex functional substituents. In this work, new organic salt crystals with top-level macroscopic optical nonlinearity by controlling the van der Waals volume (VvdW ), rather than by trial and error, are logically designed. When the VvdW of molecular ionic components varies, the corresponding crystal symmetry shows an observable trend: change from centrosymmetric to non-centrosymmetric and back to centrosymmetric. All non-centrosymmetric crystals exhibit an isomorphic P1 crystal structure with an excellent macroscopic second-order nonlinear optical response. Apart from the top-level macroscopic optical nonlinearity, new organic crystals introducing highly electronegative fluorinated substituents with strong secondary bonding ability show excellent performance in efficient and broadband THz wave generation, high crystal density, high thermal stability, and good bulk crystal growth ability.
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The gut microbiome is critical in human health, and various dietary factors influence its composition and function. Among these factors, animal products, such as meat, dairy, and eggs, represent crucial sources of essential nutrients for the gut microbiome. However, the correlation and characteristics of livestock consumption with the gut microbiome remain poorly understood. This review aimed to delineate the distinct effects of meat, dairy, and egg products on gut microbiome composition and function. Based on the previous reports, the impact of red meat, white meat, and processed meat consumption on the gut microbiome differs from that of milk, yogurt, cheese, or egg products. In particular, we have focused on animal-originated proteins, a significant nutrient in each livestock product, and revealed that the major proteins in each food elicit diverse effects on the gut microbiome. Collectively, this review highlights the need for further insights into the interactions and mechanisms underlying the impact of animal products on the gut microbiome. A deeper understanding of these interactions would be beneficial in elucidating the development of dietary interventions to prevent and treat diseases linked to the gut microbiome.
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Tiller number is an important trait associated with yield in rice. Tiller number in Korean japonica rice was analyzed under greenhouse conditions in 160 recombinant inbred lines (RILs) derived from a cross between the temperate japonica varieties Odae and Unbong40 to identify quantitative trait loci (QTLs). A genetic map comprising 239 kompetitive allele-specific PCR (KASP) and 57 cleaved amplified polymorphic sequence markers was constructed. qTN3, a major QTL for tiller number, was identified at 132.4 cm on chromosome 3. This QTL was also detected under field conditions in a backcross population; thus, qTN3 was stable across generations and environments. qTN3 co-located with QTLs associated with panicle number per plant and culm diameter, indicating it had pleiotropic effects. The qTN3 regions of Odae and Unbong40 differed in a known functional variant (4 bp TGTG insertion/deletion) in the 5' UTR of OsTB1, a gene underlying variation in tiller number and culm strength. Investigation of variation in genotype and tiller number revealed that varieties with the insertion genotype had lower tiller numbers than those with the reference genotype. A high-resolution melting marker was developed to enable efficient marker-assisted selection. The QTL qTN3 will therefore be useful in breeding programs developing japonica varieties with optimal tiller numbers for increased yield.
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Oryza , Humanos , Oryza/genética , Melhoramento Vegetal , Mapeamento Cromossômico , Locos de Características Quantitativas/genética , Regiões 5' não Traduzidas , República da CoreiaRESUMO
BACKGRUOUND: Height loss is a simple clinical measure associated with increased fracture risk. However, limited data exists on the association between height loss and fracture risk in postmenopausal Korean women. It is unknown whether this association varies with age. METHODS: Data on height loss over a 6-year period were collected from a community-based longitudinal follow-up cohort (Ansung cohort of the Korean Genome and Epidemiology Study). Incident fractures were defined based on self-reported fractures after excluding those due to severe trauma or toes/fingers. The association between incident fractures and height loss was investigated using a Cox proportional hazards model. RESULTS: During a median follow-up of 10 years after the second visit, 259/1,806 participants (median age, 64 years) experienced incident fractures. Overall, a 1 standard deviation (SD) decrease in height (1.6 cm/median 5.8 years) was associated with 9% increased risk of fracture (hazard ratio [HR], 1.09; P=0.037), which lost statistical significance after adjustment for covariates. When stratified into age groups (50-59, 60-69, 70 years or older), a 1 SD decrease in height remained a robust predictor of fracture in the 50 to 59 years age group after adjusting for covariates (adjusted hazard ratio [aHR], 1.52; P=0.003), whereas height loss was not an independent predictor of fracture in the 60 to 69 (aHR, 1.06; P=0.333) or the 70 years or older age groups (aHR, 1.05; P=0.700; P for interaction <0.05, for all). CONCLUSION: Height loss during the previous 6 years was associated with an increased 10-year fracture risk in postmenopausal women in their 50s.
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Fraturas Ósseas , Pós-Menopausa , Humanos , Feminino , Idoso , Pessoa de Meia-Idade , Fraturas Ósseas/epidemiologia , Fraturas Ósseas/etiologia , República da Coreia/epidemiologiaRESUMO
Drought is being annually exacerbated by recent global warming, leading to crucial damage of crop growth and final yields. Soybean, one of the most consumed crops worldwide, has also been affected in the process. The development of a resistant cultivar is required to solve this problem, which is considered the most efficient method for crop producers. To accelerate breeding cycles, genetic engineering and high-throughput phenotyping technologies have replaced conventional breeding methods. However, the current novel phenotyping method still needs to be optimized by species and varieties. Therefore, we aimed to assess the most appropriate and effective phenotypes for evaluating drought stress by applying a high-throughput image-based method on the nested association mapping (NAM) population of soybeans. The acquired image-based traits from the phenotyping platform were divided into three large categories-area, boundary, and color-and demonstrated an aspect for each characteristic. Analysis on categorized traits interpreted stress responses in morphological and physiological changes. The evaluation of drought stress regardless of varieties was possible by combining various image-based traits. We might suggest that a combination of image-based traits obtained using computer vision can be more efficient than using only one trait for the precision agriculture.
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The mainstream of high-energy cathode development is focused on increasing the Ni-ratio in layered structured cathode materials. The increment of the Ni portion in the layered cathode material escalates not only the deliverable capacity but also the structural degradation. High-Ni layered cathodes are highly vulnerable to exposure to air that contains CO2 and H2 O, forming problematic residual lithium compounds at the surface. In this work, a novel air- and moisture robust surface modification is reported for LiNi0.8 Co0.1 Mn0.1 O2 (NCM811) via the sol-gel coating method that selectively coats the internal surface area of the polycrystalline morphology secondary particles. Bare-, Li2 SnO3 -coated and LiCoO2 -coated NCM811 are exposed to different ambient environments (air, hot-air, and moisture-air) to systematically investigate the correlation between the internal/external coating morphology and performance degradations. The LiCoO2 -coated NCM811s exhibit high-capacity retention after exposure to all environments, due to the internal surface coating that prevents the penetration of harmful compounds into the polycrystalline NCM811. On the other hand, the Li2 SnO3 -coated NCM811s exposed to the ambient environments show gradual capacity fading, implying the occurrence of internal degradation. This paper highlights the impact of the internal degradation of polycrystalline NCM811 after environmental exposure and the correct coating mechanisms required to successfully prevent it.
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BACKGROUND & AIMS: The impact of the severity of sarcopenic obesity (SO) in nonalcoholic fatty liver disease (NAFLD) on the risk of significant liver fibrosis or cardiovascular disease (CVD) remains unclear. We aimed to identify high-risk subjects with SO for significant liver fibrosis or CVD among subjects with SO and NAFLD. METHODS: This multicenter, retrospective study involved 23,889 subjects with NAFLD who underwent a health screening program (2014-2020). Sarcopenia was defined based on gender-specific sarcopenia index cutoff using multi-frequency bioelectric impedance analysis. High-risk subjects with SO were defined as those with significant liver fibrosis by fibrosis-4 index >2.67 or atherosclerotic CVD risk score >20%. Multivariable logistic regression analysis for identifying high-risk subjects with SO was performed in a cross-sectional cohort with SO, and further validation was performed in a longitudinal cohort. RESULTS: SO prevalence was 5.4% (n = 1297 of 23,889). Older age (unstandardized beta [ß] = 3.23; P < .001), male (ß = 1.66; P = .027), sarcopenia index (ß = -6.25; P = .019), and metabolic syndrome (ß = 1.75; P < .001) were significant risk factors for high-risk SO. Based on a high-risk SO screening model, high-risk subjects with SO had significantly higher odds of significant liver fibrosis (training: adjusted odds ratio [aOR], 3.72; validation: aOR, 2.38) or CVD (training: aOR, 5.20; validation: aOR, 3.71) than subjects without SO (all P < .001). In subgroup analyses, the cumulative incidence of significant liver fibrosis or CVD development was significantly higher in high-risk subjects with SO than in low-risk subjects with SO in a longitudinal cohort considering all-cause mortality and liver transplantation as competing risks (sub-distribution hazard ratio, 5.37; P < .001). CONCLUSION: The high-risk screening model may enable the identification of high-risk subjects with SO with NAFLD.
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Doenças Cardiovasculares , Hepatopatia Gordurosa não Alcoólica , Sarcopenia , Humanos , Masculino , Hepatopatia Gordurosa não Alcoólica/complicações , Hepatopatia Gordurosa não Alcoólica/epidemiologia , Hepatopatia Gordurosa não Alcoólica/diagnóstico , Sarcopenia/complicações , Sarcopenia/epidemiologia , Estudos Retrospectivos , Estudos Transversais , Fatores de Risco , Cirrose Hepática/complicações , Cirrose Hepática/epidemiologia , Cirrose Hepática/diagnóstico , Obesidade/complicações , Obesidade/epidemiologia , Doenças Cardiovasculares/epidemiologia , Medição de RiscoRESUMO
Lithium-ion batteries (LIBs) continue to dominate the battery market with their efficient energy storage abilities and their ongoing development. However, at high charge/discharge C-rates their electrochemical performance decreases significantly. To improve the power density properties of LIBs, it is important to form a uniform electron transfer network in the cathode electrode via the addition of conductive additives. Carbon nanotubes (CNTs) with high crystallinity, high electrical conductivity, and high aspect ratio properties have gathered significant interest as cathode electrode conductive additives. However, due to the high aggregational properties of CNTs, it is difficult to form a uniform network for electron transfer within the electrode. In this study, to help fabricate electrodes with well-dispersed CNTs, various electrodes were prepared by controlling (i) the mixing order of the conductive material, binder, and active material, and (ii) the sonication process of the CNTs/NMP solution before the electrode slurry preparation. When the binder was mixed with a well sonicated CNTs/NMP solution, the CNTs uniformly adsorbed to the then added cathode material of LiNi0.6Co0.2Mn0.2O2 and were well-dispersed to form a flowing uniform network. This electrode fabrication process achieved > 98.74% capacity retention after 50 cycles at 5C via suppressed polarization at high current densities and a more reversible H1-M phase transition of the active material. Our study presents a novel design benchmark for the fabricating of electrodes applying well-dispersed CNTs, which can facilitate the application of LIBs in high current density applications.
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The objective of this study was to establish an automated system for the recognition of banknote serial numbers by developing a deep learning (DL)-based optical character recognition framework. An integrated serial number recognition model for the banknotes of four countries (South Korea (KRW), the United States (USD), India (INR), and Japan (JPY)) was developed. One-channel image data obtained from banknote counters were used in this study. The dataset used for the multi-currency integrated serial number recognition contains about 150,000 images. The class imbalance problem and model accuracy were improved through data augmentation based on geometric transforms that consider the range of errors that occur when a bill is inserted into the counter. In addition, by fine-tuning the recognition network, it was confirmed that the performance was improved when the serial numbers of the banknotes of four countries were recognized instead of the serial number of a banknote from each country from a single-currency dataset, and the generalization performance was improved by training the model to recognize the diverse serial numbers of multiple currencies. Therefore, the proposed method shows that real-time processing of less than 30 ms per image and character recognition with 99.99% accuracy are possible, even though there is a tradeoff between inference speed and serial number recognition accuracy when data augmentation based on the characteristics of banknote counters and a 1-stage object detector for banknote serial number recognition is used.
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Redes Neurais de Computação , Índia , Japão , República da CoreiaRESUMO
Photothermally triggered actuation enables the remote and local control of a material. The complex actuation can be achieved by controlling the photothermal efficiency of the material, which is crucial for the development of soft actuators. In this study, the photothermal efficiency of a hydrogel bilayer actuator consisting of a passive agarose/alginate double-network hydrogel layer and an active poly(N-isopropylacrylamide) (PNIPAm) layer was controlled via in situ oxidative polymerization of polydopamine nanoparticles (PDA NPs). Highly concentrated PDA NPs were successfully incorporated into the hydrogel bilayer without interrupting or weakening the polymer network during polymerization. The photothermal efficiency of the actuator was controlled using the number of polymerization cycles. Upon light irradiation, the heat generated by the photothermal effect of PDA NPs caused the shrinkage of the PNIPAm layer, resulting in the shape-morphing of the bilayer. The broad light absorption properties of PDA NPs allowed the bilayer to actuate under sunlight or visible light. Finally, we demonstrated controlled photothermal actuation using a pinwheel-shaped actuator consisting of four panels with different photothermal efficiencies.
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The development of efficient, robust, and high-throughput SNP genotyping platforms is pivotal for crop genetics and breeding. Recently, SNP genotyping platforms based on target capture sequencing, which is very flexible in terms of the number of SNP markers, have been developed for maize, cassava, and fava bean. We aimed to develop a target capture sequencing SNP genotyping platform for rice. A target capture sequencing panel containing 2565 SNPs, including 1225 SNPs informative for japonica and 1339 SNPs informative for indica, was developed. This platform was used in diversity analysis of 50 rice varieties. Of the 2565 SNP markers, 2341 (91.3%) produced useful polymorphic genotype data, enabling the production of a phylogenetic tree of the 50 varieties. The mean number of markers polymorphic between any two varieties was 854. The platform was used for QTL mapping of preharvest sprouting (PHS) resistance in an F8 recombinant inbred line population derived from the cross Odae × Joun. A genetic map comprising 475 markers was constructed, and two QTLs for PHS resistance were identified on chromosomes 4 and 11. This system is a powerful tool for rice genetics and breeding and will facilitate QTL studies and gene mapping, germplasm diversity analysis, and marker-assisted selection.
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Oryza , Genótipo , Oryza/genética , Filogenia , Melhoramento Vegetal , Locos de Características Quantitativas/genéticaRESUMO
Uniquely among mammalian organs, skin is capable of marked size change in adults, yet the mechanisms underlying this notable capacity are unclear. Here, we use a system of controlled tissue expansion in mice to uncover cellular and molecular determinants of skin growth. Through machine learning-guided three-dimensional tissue reconstruction, we capture morphometric changes in growing skin. We find that most growth is driven by the proliferation of the epidermis in response to mechanical tension, with more limited changes in dermal and subdermal compartments. Epidermal growth is achieved through preferential activation and differentiation of Lgr6+ stem cells of the epidermis, driven in part by the Hippo pathway. By single-cell RNA sequencing, we uncover further changes in mechanosensitive and metabolic pathways underlying growth control in the skin. These studies point to therapeutic strategies to enhance skin growth and establish a platform for understanding organ size dynamics in adult mammals.
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Células Epidérmicas , Receptores Acoplados a Proteínas G , Pele , Células-Tronco , Animais , Células Epidérmicas/citologia , Células Epidérmicas/metabolismo , Epiderme/crescimento & desenvolvimento , Epiderme/metabolismo , Camundongos , Receptores Acoplados a Proteínas G/metabolismo , Pele/crescimento & desenvolvimento , Pele/metabolismo , Células-Tronco/citologia , Células-Tronco/metabolismoRESUMO
All-solid-state Li batteries (ASSBs) promise better performance and higher safety than the current liquid-based Li-ion batteries (LIBs). Sulfide ASSBs have been extensively studied and considerably advanced in recent decades. Research on identifying suitable cathode materials for sulfide ASSBs is currently well established, with great progress being made in the commercialization of layered cathodes in the liquid-based LIBs. Research on anode materials for sulfide ASSBs is of great importance for enhancing the battery energy density. However, it seems that little has been published that summarizes studies of anode materials for sulfide ASSBs and suggests future research directions. Thus, within this Minireview, we aim to provide an overview of previous and current research focused on anode materials for sulfide ASSBs and to suggest a future research direction for developing suitable anode systems for sulfide ASSBs.
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Next-generation sequencing technologies have enabled the discovery of numerous sequence variations among closely related crop varieties. We analyzed genome resequencing data from 24 Korean temperate japonica rice varieties and discovered 954,233 sequence variations, including 791,121 single nucleotide polymorphisms (SNPs) and 163,112 insertions/deletions (InDels). On average, there was one variant per 391 base-pairs (bp), a variant density of 2.6 per 1 kbp. Of the InDels, 10,860 were longer than 20 bp, which enabled conversion to markers resolvable on an agarose gel. The effect of each variant on gene function was predicted using the SnpEff program. The variants were categorized into four groups according to their impact: high, moderate, low, and modifier. These groups contained 3524 (0.4%), 27,656 (2.9%), 24,875 (2.6%), and 898,178 (94.1%) variants, respectively. To test the accuracy of these data, eight InDels from a pre-harvest sprouting resistance QTL (qPHS11) target region, four highly polymorphic InDels, and four functional sequence variations in known agronomically important genes were selected and successfully developed into markers. These results will be useful to develop markers for marker-assisted selection, to select candidate genes in map-based cloning, and to produce efficient high-throughput genome-wide genotyping systems for Korean temperate japonica rice varieties.
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Mutação INDEL , Oryza/crescimento & desenvolvimento , Polimorfismo de Nucleotídeo Único , Sequenciamento Completo do Genoma/métodos , Genoma de Planta , Sequenciamento de Nucleotídeos em Larga Escala , Oryza/genética , Locos de Características Quantitativas , República da CoreiaRESUMO
Drought is a main factor limiting crop yields. Modern agricultural technologies such as irrigation systems, ground mulching, and rainwater storage can prevent drought, but these are only temporary solutions. Understanding the physiological, biochemical, and molecular reactions of plants to drought stress is therefore urgent. The recent rapid development of genomics tools has led to an increasing interest in phenomics, i.e., the study of phenotypic plant traits. Among phenomic strategies, high-throughput phenotyping (HTP) is attracting increasing attention as a way to address the bottlenecks of genomic and phenomic studies. HTP provides researchers a non-destructive and non-invasive method yet accurate in analyzing large-scale phenotypic data. This review describes plant responses to drought stress and introduces HTP methods that can detect changes in plant phenotypes in response to drought.
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Produtos Agrícolas/genética , Secas , Fenômica/métodos , Melhoramento Vegetal/métodos , Produtos Agrícolas/fisiologia , Ensaios de Triagem em Larga Escala/métodos , Estresse FisiológicoRESUMO
OBJECTIVE: VVZ-149 is a small molecule that both inhibits the glycine transporter type 2 and the serotonin receptor 5 hydroxytryptamine 2 A. In a randomized, parallel-group, and double-blind trial (NCT02844725), we investigated the analgesic efficacy and safety of VVZ-149 Injections, which is under clinical development as a single-use injectable product for treating moderate to severe postoperative pain. METHODS: Sixty patients undergoing laparoscopic and robotic-laparoscopic gastrectomy were randomly assigned to receive a 10-hour intravenous infusion of VVZ-149 Injections or placebo, initiated approximately 1 hour before completion of surgical suturing. Major outcomes included pain intensity and opioid consumption via patient-controlled analgesia and rescue analgesia provided "as needed." The treatment efficacy of VVZ-149 was further examined in a subpopulation requiring early rescue medication, previously associated with the presence of high levels of preoperative negative affect in a prior Phase 2 study (NCT02489526). RESULTS: Pain intensity was lower in the VVZ-149 (n = 30) than the placebo group (n = 29), reaching statistical significance at 4 hours post-emergence (P < .05), with a 29.5% reduction in opioid consumption for 24 hours and fewer demands for patient-controlled analgesia. In the rescued subgroup, VVZ-149 further reduced pain intensity (P < .05) with 32.6% less opioid consumption for 24 hours compared to placebo patients. CONCLUSIONS: VVZ-149 demonstrated effective analgesia with reduced postoperative pain and opioid requirements. Consistent with the results from the previous Phase 2 study, patients with early rescue requirement had greater benefit from VVZ-149, supporting the hypothesis that VVZ-149 may alleviate the affective component of pain and mitigate excessive use of opioids postoperatively.