First report of leaf spot caused by Colletotrichum camelliae in mung beans (Vigna radiata (L.) R. Wilczek) in South Korea.

Mung bean (Vigna radiata (L.) R. Wilczek) is a legume with high nutritional and economic value that is cultivated widely across Asia (Kang et al. 2014). In March 2022, a leaf spot disease in mung bean was observed at the Gangneung-Wonju National University Experimental farm (Gangneung, South Korea, 37.77°N, 128.86°E). The affected plants had irregular brown-gray leaf spots, and the bottom of the leaves showed concentric brown-gray rings that eventually progressed to necrotic lesions. Regardless of the cultivar, approximately 30% of the plants in the field were infected. To isolate the pathogen, the affected leaves were surface-sterilized by washing with 70% ethanol for 1 min, followed by washing with 2% NaClO for 2 min, then rinsing with sterile distilled water. We placed 3-mm sized diseased lesions on potato-dextrose agar (PDA), then incubated them at 27 ± 1 °C in the dark for 7 days and we obtained 1 isolate (CC1). The fungus on PDA had white aerial mycelia that became gray toward the center. Single spore cultures were obtained from fungal isolate. Isolated conidia were single celled, hyaline, cylindrical, and measured between 20.75 to 22.07 µm × 5.85 to 6.92 µm (n = 20), similar to other reports of C. camelliae(Wang et al. 2016). Mycelium from the single spore isolate was used for DNA extraction using Exgene™ Plant SV / (GeneAll®, Cat.No. 117-152), and we amplified the ITS region with primers ITS1 + ITS2 and ITS3 + ITS4, a portion of the actin gene with primers ACT-512F + 738R, and a portion of the beta-tubulin gene with primers BT2aF + BT2bR (Carbone et al. 1999; Glass et al. 1995; White et al. 1990). The amplified regions were sequenced by by Macrogen® (Seoul, South Korea). Sequences were deposited under GenBank accession numbers OR523262 (ITS), OR582483 (Actin), and OR566953 (beta-tubulin). MegaBLAST analysis of the ITS1, ITS2, ACT, and TUB regions showed 99% (216/217 bp) similarity with C. camelliae strain HNCS-26 (MK041440.1), 99% (303/305 bp) similarity with C. camelliae strain G3 (ON025203.1), 99% (242/244 bp) similarity with C. camelliae strain FWT41 (MN525820.1), and 99% (456/460 bp) with C. camelliae strain LF152 (KJ955239.1), respectively. To fulfill Koch's postulates, we conducted a pathogenicity teston the mung bean cultivar VC1973A (Seonhwanokdu) grown for four weeks at 25 °C with a 16-h day/8-h night cycle, simulating the field conditions when the symptoms were observed. We tested the pathogenicity on six plants , three control and three infected plants. Using three leaf replicates per plant resulting in total of nine leaves per group. Leaves were first injured using a sterile needle then either sterile 5 mm PDA plugs or plugs with C. camelliae were placed on the leaf for control and infected conditions, respectively. Irregular gray leaf spots were observed on the abaxial and adaxial of the infected leaf after 2 weeks, like the symptoms observed in the field. This was observed only on infected leaves and nowhere else on the plant and the control plants had no infection. We re-isolated the pathogen from diseased leaves and identified it as C. camelliae using the same molecular markers described previously, completing Koch's postulate. To the best of our knowledge, this is the first report of leaf spot caused by C. camelliae in mung bean plants in Korea, previously the fungi was reported to infect tea plants in Korea (Hassan et al. 2023). More studies are required to investigate potentially resistant mung bean varieties to minimize future damage caused by this fungus.

Assessment of Automated Identification of Phases in Videos of Total Hip Arthroplasty Using Deep Learning Techniques.

Background: As the population ages, the rates of hip diseases and fragility fractures are increasing, making total hip arthroplasty (THA) one of the best methods for treating elderly patients. With the increasing number of THA surgeries and diverse surgical methods, there is a need for standard evaluation protocols. This study aimed to use deep learning algorithms to classify THA videos and evaluate the accuracy of the labelling of these videos. Methods: In our study, we manually annotated 7 phases in THA, including skin incision, broaching, exposure of acetabulum, acetabular reaming, acetabular cup positioning, femoral stem insertion, and skin closure. Within each phase, a second trained annotator marked the beginning and end of instrument usages, such as the skin blade, forceps, Bovie, suction device, suture material, retractor, rasp, femoral stem, acetabular reamer, head trial, and real head. Results: In our study, we utilized YOLOv3 to collect 540 operating images of THA procedures and create a scene annotation model. The results of our study showed relatively high accuracy in the clear classification of surgical techniques such as skin incision and closure, broaching, acetabular reaming, and femoral stem insertion, with a mean average precision (mAP) of 0.75 or higher. Most of the equipment showed good accuracy of mAP 0.7 or higher, except for the suction device, suture material, and retractor. Conclusions: Scene annotation for the instrument and phases in THA using deep learning techniques may provide potentially useful tools for subsequent documentation, assessment of skills, and feedback.

Characterization of the complete chloroplast genome of Wolffia arrhiza and comparative genomic analysis with relative Wolffia species.

Lemnoideae, commonly referred to as the duckweed, are aquatic plants found worldwide. Wolffia species are known for their extreme reduction in size and complexity, lacking both roots and leaves, and they hold the distinction of being the smallest plants among angiosperms. Interestingly, it belongs to the Araceae family, despite its apparent morphological differences from land plants in the same family. Traditional morphological methods have limitations in classifying these plants, making molecular-level information essential. The chloroplast genome of Wolffia arrhiza is revealed that a total length of 169,602 bp and a total GC content of 35.78%. It follows the typical quadripartite structure, which includes a large single copy (LSC, 92,172 bp) region, a small single copy (SSC, 13,686 bp) region, and a pair of inverted repeat (IR, 31,872 bp each) regions. There are 131 genes characterized, comprising 86 Protein-Coding Genes, 37 Transfer RNA (tRNA) genes, and 8 ribosomal RNA (rRNA) genes. Moreover, 48 simple sequence repeats and 32 long repeat sequences were detected. Comparative analysis between W. arrhiza and six other Lemnoideae species identified 12 hotspots of high nucleotide diversity. In addition, a phylogenetic analysis was performed using 14 species belonging to the Araceae family and one external species as an outgroup. This analysis unveiled W. arrhiza and Wolffia globosa as closely related sister species. Therefore, this research has revealed the complete chloroplast genome data of W. arrhiza, offering a more detailed understanding of its evolutionary position and phylogenetic categorization within the Lemnoideae subfamily.

RiceProteomeDB (RPDB): a user-friendly database for proteomics data storage, retrieval, and analysis.

Rice, feeding a significant portion of the world, poses unique proteomic challenges critical to agricultural research and global food security. The complexity of the rice proteome, influenced by various genetic and environmental factors, demands specialized analytical approaches for effective study. The central challenges in rice proteomics lie in developing custom methods suited to the unique aspects of rice biology. These include data preprocessing, method selection, and result validation, all of which are essential for advancing rice research. Our aim is to decode these proteomic intricacies to facilitate breakthroughs in strain improvement, disease resistance, and yield optimization, all vital for combating global food insecurity. To achieve this, we have created the RiceProteomeDB (RPDB), a React + Django database, offering a streamlined and comprehensive platform for the analysis of rice proteomics data. RiceProteomeDB (RPDB) simplifies proteomics data management and analysis. It offers features for data organization, preprocessing, method selection, result validation, and data sharing. Researchers can access processed rice proteomics data, conduct analyses, and explore experimental conditions. The user-friendly web interface enhances navigation and interaction. RPDB fosters collaboration by enabling data sharing and proper acknowledgment of sources, contributing to proteomics research and knowledge dissemination. Availability and implementation: Web application: http://riceproteome.plantprofile.net/ . The web application's source code, user's manual, and sample data: https://github.com/dongu7610/Riceproteome .

Analysis of Changes in Sleep Quality and Patterns after Hip Fracture Using Real Evidence of Artificial Intelligence Linked (REAL) Hip Cohort Data.

Background and Objectives: Hip fractures are commonly found in elderly patients, and often result in chronic pain and decreased physical function, as well as worsening of overall health. It is known that early surgical intervention during the acute phase and rehabilitation are important for improving clinical outcomes for these patients. However, the importance of management for improving the quality of life of these patients is becoming more emphasized. Studies on changes in sleep patterns after hip fractures are rare overseas. Therefore, the aim of this study is to investigate the prevalence of sleep disturbance in patients with hip fractures and to analyze the changes in sleep disturbance after surgery by comparing the preoperative and postoperative results. Materials and Methods: During the period from August 2022 to January 2023, patients who underwent surgical treatment for hip fractures and were recruited into the REAL Hip Cohort were selected as research subjects. The sleep survey was conducted using the Pittsburgh Sleep Quality Index (PSQI). The PSQI is composed of 18 questions, each divided into areas of sleep quality, sleep latency, duration, efficiency, disturbance, use of medication, and daytime dysfunction. Each area is scored 0-3 points and the total is 0-21. A score greater than five indicates sleep disorder. The PSQI was surveyed during hospitalization and three months after surgery for post-fracture sleep status. To analyze changes before and after the fracture, paired T-tests and chi-square tests were performed. Results: From August 2022 to January 2023, a total of 40 patients who were recruited into the REAL Hip Cohort responded to the PSQI survey. The average age was 77.4 years and 36 were female. Sleep quality worsened from 0.75 ± 1.0 before surgery to 1.4 ± 1.0 three months after surgery (p = 0.019), and sleep efficiency also worsened from 0.4 ± 0.6 to 1.4 ± 1.0 (p < 0.001). The PSQI increased from an average of 5.2 ± 2.8 before surgery to 8.2 ± 4.2 three months after surgery (p = 0.007), and the number of patients who could be diagnosed with sleep disorders also increased from 12 (40%) to 24 (60%) (p = 0.030). Conclusions: A decline in overall sleep status was observed in patients in a survey on sleep patterns three months after hip fracture. Additional management is needed to improve their sleep patterns.

Unraveling the maternal and paternal origins of allotetraploid Vigna reflexo-pilosa.

The genomic structures of Vigna hirtella Ridl. and Vigna trinervia (B.Heyne ex Wight & Arn.) Tateishi & Maxted, key ancestral species of the allotetraploid Vigna reflexo-pilosa var. glabra (Roxb.) N.Tomooka & Maxted, remain poorly understood. This study presents a comprehensive genomic comparison of these species to deepen our knowledge of their evolutionary trajectories. By comparing the genomic profiles of V. hirtella and V. trinervia with those of V. reflexo-pilosa, we investigate the complex genomic mechanisms underlying allopolyploid evolution within the genus Vigna. Comparison of the chloroplast genome revealed that V. trinervia is closely related to V. reflexo-pilosa. De novo assembly of the whole genome, followed by synteny analysis and Ks value calculations, confirms that V. trinervia is closely related to the A genome of V. reflexo-pilosa, and V. hirtella to its B genome. Furthermore, the comparative analyses reveal that V. reflexo-pilosa retains residual signatures of a previous polyploidization event, particularly evident in higher gene family copy numbers. Our research provides genomic evidence for polyploidization within the genus Vigna and identifies potential donor species of allotetraploid species using de novo assembly techniques. Given the Southeast Asian distribution of both V. hirtella and V. trinervia, natural hybridization between these species, with V. trinervia as the maternal ancestor and V. hirtella as the paternal donor, seems plausible.

SoyDBean: a database for SNPs reconciliation by multiple versions of soybean reference genomes.

Due to the development of sequence technology and decreased cost, many whole genome sequences have been obtained. As a result, extensive genetic variations have been discovered from many populations and germplasms to understand the genetic diversity of soybean (Glycine max [L.] Merr.). However, assessing the quality of variation is essential because the published variants were collected using different bioinformatic methods and parameters. Furthermore, despite the enhanced genome contiguity and more efficient filling of "N" stretches in the new reference genome, there remains a dearth of endeavors to verify the caliber of variations present in it. The primary goal of this research was to discern a dependable set of SNPs that can withstand reconciliation across multiple reference genomes. Additionally, the investigation aimed to reconfirm the variations through the utilization of numerous whole genome sequencing data obtained from publicly available databases. Based on the result, we created datasets that comprised the thoroughly verified SNP coordinates between the reference assemblies. The resulting "SoyDBean" database is now publicly accessible through the following URL: http://soydbean.plantprofile.net/ .

Sophora genomes provide insight into the evolution of alkaloid metabolites along with small-scale gene duplication.

The genus Sophora (Fabaceae) includes medicinal plants that have been used in East Asian countries since antiquity. Sophora flavescens is a perennial herb indigenous to China, India, Japan, Korea, and Russia. Its dried roots have antioxidant, anti-inflammatory, antibacterial, apoptosis-modulating, and antitumor efficacy. The congeneric S. koreensis is endemic to Korea and its genome is less than half the size of that of S. flavescens. Nevertheless, this discrepancy can be used to assemble and validate the S. flavescens genome. A comparative genomic study of the two genomes can disclose the recent evolutionary divergence of the polymorphic phenotypic profiles of these species. Here, we used the PacBio sequencing platform to sequence and assemble the S. koreensis and S. flavescens genomes. We inferred that it was mainly small-scale duplication that occurred in S. flavescens. A KEGG analysis revealed pathways that might regulate the pharmacologically important secondary metabolites in S. flavescens and S. koreensis. The genome assemblies of Sophora spp. could be used in comparative genomics and data mining for various plant natural products.

Prevalence of Sarcopenia in Africa: A Systematic Review.

Objective: The world population gradually getting older, age-related sarcopenia is becoming more frequent. Known to be highly prevalent in high income countries, relative data in Africa are still scarce. This review aims to estimate the prevalence of sarcopenia in Africa and its characteristics. Study Design and Setting: A literature search in PubMed, Web of Science, Google Scholar, and Scopus was conducted in October 2022. All studies reporting the prevalence of sarcopenia in Africa within 15 years were included, and we did an assessment of bias with Hoy et al's risk bias assessment tool. The estimated prevalence of sarcopenia was the outcome and we performed secondary analyses by age, gender, and diagnostic criteria. The random effect model was used for the prevalence estimation. The prevalence of sarcopenia and 95% confidence interval (95% CI) were calculated using the inverse-variance method. Results: A total of 17 studies met our eligibility criteria, for a study population of 12,690 participants with 44.3% males and 55.7% females. The overall prevalence of sarcopenia was 25% (95% CI: 19-30%). The prevalence of sarcopenia among 50 years old and older was 23% (95% CI: 17-29%). We had a higher prevalence of sarcopenia among males (30%, %95 IC: 20-39%) than females (29%, %95 IC: 21-36%). The prevalence of sarcopenia was different depending on the diagnosis criteria used. Conclusion: The prevalence of sarcopenia in Africa was relatively high. However, the fact that the majority of included studies were hospital-based studies shows the necessity of further community-based studies in order to have a more accurate representation of the situation in the general population.

Correlation between Harris hip score and gait analysis through artificial intelligence pose estimation in patients after total hip arthroplasty.

BACKGROUND: Recently, open pose estimation using artificial intelligence (AI) has enabled the analysis of time series of human movements through digital video inputs. Analyzing a person's actual movement as a digitized image would give objectivity in evaluating a person's physical function. In the present study, we investigated the relationship of AI camera-based open pose estimation with Harris Hip Score (HHS) developed for patient-reported outcome (PRO) of hip joint function. METHOD: HHS evaluation and pose estimation using AI camera were performed for a total of 56 patients after total hip arthroplasty in Gyeongsang National University Hospital. Joint angles and gait parameters were analyzed by extracting joint points from time-series data of the patient's movements. A total of 65 parameters were from raw data of the lower extremity. Principal component analysis (PCA) was used to find main parameters. K-means cluster, X-squared test, Random forest, and mean decrease Gini (MDG) graph were also applied. RESULTS: The train model showed 75% prediction accuracy and the test model showed 81.8% reality prediction accuracy in Random forest. "Anklerang_max", "kneeankle_diff", and "anklerang_rl" showed the top 3 Gini importance score in the Mean Decrease Gini (MDG) graph. CONCLUSION: The present study shows that pose estimation data using AI camera is related to HHS by presenting associated gait parameters. In addition, our results suggest that ankle angle associated parameters could be key factors of gait analysis in patients who undergo total hip arthroplasty.

Integrative analyses of genes related to femoral head osteonecrosis: an umbrella review of systematic reviews and meta-analyses of observational studies.

BACKGROUND: Femoral head osteonecrosis (FHON) is a worldwide challenging clinical topic. Steroid use is one of the main etiologies of FHON. There are several genetic variants associated with FHON. Therefore, the purpose of this umbrella review was to provide a comprehensive summary of a meta-analysis and systematic review of genetic variations associated with nonsteroidal and steroid-induced FHON. METHODS: The eligible studies were selected from the PubMed and MEDLINE databases for the collection of diverse systematic meta-analyses and reviews. The genetic main effect score was assigned using the Human Genome Epidemiology Network's Venice criteria to assess the cumulative evidence on the effects of a single nucleotide polymorphism (SNP) on FHON. RESULTS: Eight articles reported the meta-analysis of candidate SNP-based studies covering eight genes and 13 genetic variants. In the nonsteroid-induced FHON genetic variants including rs2012390 and rs11225394 in MMP8, rs1800629 and rs361525 in tumor necrosis factor (TNF)-α, VNTR in intron 4, rs1799983 and rs2070744 in endothelial nitric oxide synthase (eNOS), rs2010963 in vascular endothelial growth factor (VEGF), and rs6025 in factor V showed significance in each reference. The steroid-induced FHON genetic variants including rs693 and rs1042031 in apolipoprotein (Apo)B, rs1045642 in ABCB1, and rs1799889 in PAI-1 showed significance in each reference. CONCLUSION: Based on the systematic review conducted in this study, we organized the genomes associated with FHON and looked at each contribution. Our results could give an integrative approach for understanding the mechanism of FHON etiology. It is expected that these results could contribute to the strategy of prediagnosis, evaluating the individual risk of nonsteroid-induced and steroid-induced FHON. LEVEL OF EVIDENCE: Level I.

Optimizing the Experimental Method for Stomata-Profiling Automation of Soybean Leaves Based on Deep Learning.

Stomatal observation and automatic stomatal detection are useful analyses of stomata for taxonomic, biological, physiological, and eco-physiological studies. We present a new clearing method for improved microscopic imaging of stomata in soybean followed by automated stomatal detection by deep learning. We tested eight clearing agent formulations based upon different ethanol and sodium hypochlorite (NaOCl) concentrations in order to improve the transparency in leaves. An optimal formulation-a 1:1 (v/v) mixture of 95% ethanol and NaOCl (6-14%)-produced better quality images of soybean stomata. Additionally, we evaluated fixatives and dehydrating agents and selected absolute ethanol for both fixation and dehydration. This is a good substitute for formaldehyde, which is more toxic to handle. Using imaging data from this clearing method, we developed an automatic stomatal detector using deep learning and improved a deep-learning algorithm that automatically analyzes stomata through an object detection model using YOLO. The YOLO deep-learning model successfully recognized stomata with high mAP (~0.99). A web-based interface is provided to apply the model of stomatal detection for any soybean data that makes use of the new clearing protocol.

N-acetylglucosaminyltransferase II Is Involved in Plant Growth and Development Under Stress Conditions.

Alpha-1,6-mannosyl-glycoprotein 2-ß-N-acetylglucosaminyltransferase [EC 2.4.1.143, N-acetylglucosaminyltransferase II (GnTII)] catalyzes the transfer of N-acetylglucosamine (GlcNAc) residue from the nucleotide sugar donor UDP-GlcNAc to the α1,6-mannose residue of the di-antennary N-glycan acceptor GlcNAc(Xyl)Man3(Fuc)GlcNAc2 in the Golgi apparatus. Although the formation of the GlcNAc2(Xyl)Man3(Fuc)GlcNAc2 N-glycan is known to be associated with GnTII activity in Arabidopsis thaliana, its physiological significance is still not fully understood in plants. To address the physiological importance of the GlcNAc2(Xyl)Man3(Fuc)GlcNAc2 N-glycan, we examined the phenotypic effects of loss-of-function mutations in GnTII in the presence and absence of stress, and responsiveness to phytohormones. Prolonged stress induced by tunicamycin (TM) or sodium chloride (NaCl) treatment increased GnTII expression in wild-type Arabidopsis (ecotype Col-0) but caused severe developmental damage in GnTII loss-of-function mutants (gnt2-1 and gnt2-2). The absence of the 6-arm GlcNAc residue in the N-glycans in gnt2-1 facilitated the TM-induced unfolded protein response, accelerated dark-induced leaf senescence, and reduced cytokinin signaling, as well as susceptibility to cytokinin-induced root growth inhibition. Furthermore, gnt2-1 and gnt2-2 seedlings exhibited enhanced N-1-naphthylphthalamic acid-induced inhibition of tropic growth and development. Thus, GnTII's promotion of the 6-arm GlcNAc addition to N-glycans is important for plant growth and development under stress conditions, possibly via affecting glycoprotein folding and/or distribution.

The Semi-Supervised Strategy of Machine Learning on the Gene Family Diversity to Unravel Resveratrol Synthesis.

Resveratrol is a phytochemical with medicinal benefits, being well-known for its presence in wine. Plants develop resveratrol in response to stresses such as pathogen infection, UV radiation, and other mechanical stress. The recent publications of genomic sequences of resveratrol-producing plants such as grape, peanut, and eucalyptus can expand our molecular understanding of resveratrol synthesis. Based on a gene family count matrix of Viridiplantae members, we uncovered important gene families that are common in resveratrol-producing plants. These gene families could be prospective candidates for improving the efficiency of synthetic biotechnology-based artificial resveratrol manufacturing.

Genome of the world's smallest flowering plant, Wolffia australiana, helps explain its specialized physiology and unique morphology.

Watermeal, Wolffia australiana, is the smallest known flowering monocot and is rich in protein. Despite its great potential as a biotech crop, basic research on Wolffia is in its infancy. Here, we generated the reference genome of a species of watermeal, W. australiana, and identified the genome-wide features that may contribute to its atypical anatomy and physiology, including the absence of roots, adaxial stomata development, and anaerobic life as a turion. In addition, we found evidence of extensive genome rearrangements that may underpin the specialized aquatic lifestyle of watermeal. Analysis of the gene inventory of this intriguing species helps explain the distinct characteristics of W. australiana and its unique evolutionary trajectory.

Differential gene expression profile by RNA sequencing study of elderly osteoporotic hip fracture patients with sarcopenia.

BACKGROUND: The purpose of this study was to report the RNA sequencing profile according to the presence or absence of sarcopenia in elderly patients with osteoporotic hip fracture. Therefore, an important genetic factor candidate for sarcopenia causing hip fracture in elderly with osteoporosis has been identified. METHODS: The patient group involved subjects over 65 years who had undergone hip fracture surgery. Among 323 hip fracture (HF) patients identified from May 2017 to December 2019, 162 HF patients (90 non-sarcopenia and 72 sarcopenia groups), excluding subjects with high energy trauma and non-osteoporosis, were finally included in the analysis. For RNA sequencing, each patient with hand grip strength (HGS) values in the top 10% were enrolled in the control group and with the bottom 10% in the patient group. After excluding patients with poor tissue quality, 6 patients and 5 patients were selected for sarcopenia and non-sarcopenia groups, respectively. For qPCR validation, each patient with HGS values in the top 20% and bottom 20% was enrolled in the control and patient groups, respectively. After excluding patients with poor tissue quality, 12 patients and 12 patients were enrolled in the sarcopenia and non-sarcopenia groups, respectively. Sarcopenia was defined according to the Asia Working Group for Sarcopenia (AWGS) criteria for low muscle strength (hand grip strength below 18 â€‹kg in women and 28 â€‹kg in men) and low muscle mass (SMI below 5.4 â€‹kg/m2 in women and 7.0 â€‹kg/m2 in men). The libraries were prepared for 100 bp paired-end sequencing using TruSeq Stranded mRNA Sample Preparation Kit (Illumina, CA, USA). The gene expression counts were supplied to Deseq2 to extract possible gene sets as differentially expressed genes (DEG) that discriminate between sarcopenia and non-sarcopenia groups that were carefully assigned by clinical observation. For the classification of the candidate genes from DEG analysis, we used the public databases; gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Quantitative real-time PCR was performed for validation. RESULTS: Samples collected were subjected to RNAseq using the Illumina platform. A total of 11 samples from both sarcopenia and non-sarcopenia groups were sequenced. Fifteen genes (RUNX 1, NGFR, CH3L1, BCL3, PLA2G2A, MYBPH, TEP1, SEMA6B, CSPG4, ACSL5, SLC25A3, NDUFB5, CYC1, ACAT1, and TCAP) were identified as differentially expressed genes (DEG) in both the groups.In the qPCR results, the expression levels of SLC25A3 and TCAP gene in the OS group were significantly lower than in the non-OS groups whereas an increase in RUNX1 mRNA level was observed in the OS samples (p â€‹< â€‹0.05). CONCLUSIONS: In summary, this study detected gene expression difference according to the presence or absence of sarcopenia in elderly osteoporosis female patients with hip fracture. We have also identified 15 important genes (RUNX 1, NGFR, CH3L1, BCL3, PLA2G2A, MYBPH, TEP1, SEMA6B, CSPG4, ACSL5, SLC25A3, NDUFB5, CYC1, ACAT1, TCAP), a few GO categories and biological pathways that may be associated with the osteosarcopenia. Our study may provide effective means for the prevention, diagnosis and treatment sarcopenia in elderly osteoporosis female patients. THE TRANSLATIONAL POTENTIAL OF THIS ARTICLE: These findings provide a novel insight into the effects of aging on the response in women with postmenopausal osteoporosis. Further studies are underway to identify the specific signalling pathways involved. These results reveal potential therapeutic targets that could aid the regenerative capacity of aging skeletal muscle.

Biofilm and Spore Formation of Clostridium perfringens and Its Resistance to Disinfectant and Oxidative Stress.

Clostridium perfringens is a major human pathogen that causes gastroenteritis via enterotoxin production and has the ability to form spores and biofilms for environmental persistence and disease transmission. This study aimed to compare the disinfectant and environmental resistance properties of C. perfringens vegetative cells and spores in planktonic and sessile conditions, and to examine the nucleotide polymorphisms and transcription under sessile conditions in C. perfringens strains isolated from meat. The sporulation rate of sessile C. perfringens TYJAM-D-66 (cpe+) was approximately 19% at day 5, while those of CMM-C-80 (cpe-) and SDE-B-202 (cpe+) were only 0.26% and 0.67%, respectively, at day 7. When exposed to aerobic conditions for 36 h, TYJAM-D-66, CMM-C-80, and SDE-B-202 vegetative cells showed 1.70 log, 5.36 log, and 5.67 log reductions, respectively. After treatment with sodium hypochlorite, the survival rates of TYJAM-D-66 vegetative cells (53.6%) and spores (82.3%) in biofilms were higher than those of planktonic cells (9.23%). Biofilm- and spore-related genes showed different expression within TYJAM-D-66 (-4.66~113.5), CMM-C-80 (-3.02~2.49), and SDE-B-202 (-5.07~2.73). Our results indicate the resistance of sessile cells and spores of C. perfringens upon exposure to stress conditions after biofilm formation.

Database: web application for visualization of the cumulated RNAseq data against the salicylic acid (SA) and methyl jasmonate (MeJA) treatment of Arabidopsis thaliana.

BACKGROUND: Plants have adapted to survive under adverse conditions or exploit favorable conditions in response to their environment as sessile creatures. In a way of plant adaptation, plant hormones have been evolved to efficiently use limited resources. Plant hormones including auxin, jasmonic acid, salicylic acid, and ethylene have been studied to reveal their role in plant adaptation against their environment by phenotypic observation with experimental design such as mutation on hormone receptors and treatment / non-treatment of plant hormones along with other environmental conditions. With the development of Next Generation Sequencing (NGS) technology, it became possible to score the total gene expression of the sampled plants and estimate the degree of effect of plant hormones in gene expression. This allowed us to infer the signaling pathway through plant hormones, which greatly stimulated the study of functional genomics using mutants. Due to the continued development of NGS technology and analytical techniques, many plant hormone-related studies have produced and accumulated NGS-based data, especially RNAseq data have been stored in the sequence read archive represented by NCBI, EBI, and DDBJ. DESCRIPTION: Here, hormone treatment RNAseq data of Arabidopsis (Col0), wild-type genotype, were collected with mock, SA, and MeJA treatments. The genes affected by hormones were identified through a machine learning approach. The degree of expression of the affected gene was quantified, visualized in boxplot using d3 (data-driven-document), and the database was built by Django. CONCLUSION: Using this database, we created a web application ( http://pgl.gnu.ac.kr/hormoneDB/ ) that lists hormone-related or hormone-affected genes and visualizes the boxplot of the gene expression of selected genes. This web application eventually aids the functional genomics researchers who want to gather the cases of the gene responses by the hormones.

Identification of plastid genomic regions inferring species identity from de novo plastid genome assembly of 14 Korean-native Iris species (Iridaceae).

Iris is one of the largest genera in the family Iridaceae, comprising hundreds of species, including numerous economically important horticultural plants used in landscape gardening and herbal medicine. Improved taxonomic classification of Iris species, particularly the endangered Korean-native Iris, is needed for correct species delineation. To this end, identification of diverse genetic markers from Iris genomes would facilitate molecular identification and resolve ambiguous classifications from molecular analyses; however, only two Iris plastid genomes, from Iris gatesii and Iris sanguinea, have been sequenced. Here, we used high-throughput next-generation sequencing, combined with Sanger sequencing, to construct the plastid genomes of 14 Korean-native Iris species with one outgroup and predict their gene content. Using these data, combined with previously published plastid genomes from Iris and one outgroup (Sisyrinchium angustifolium), we constructed a Bayesian phylogenetic tree showing clear speciation among the samples. We further identified sub-genomic regions that have undergone neutral evolution and accurately recapitulate Bayesian-inferred speciation. These contain key markers that could be used to identify and classify Iris samples into taxonomic clades. Our results confirm previously reported speciation patterns and resolve questionable relationships within the Iris genus. These data also provide a valuable resource for studying genetic diversity and refining phylogenetic relationships between Iris species.

Mapping and Validation of QTLs for the Amino Acid and Total Protein Content in Brown Rice.

Highly nutritious rice production will be benefited with the improvement of amino acid content (AAC) and protein content (PC). The identification of quantitative trait loci (QTLs) associated with the PC and AAC of rice grains could provide a basis for improving the nutritional value of rice grains. Here, we conducted QTL analyses using recombinant inbred lines from the cross between indica (Milyang 23 or M23) and japonica (Tong 88-7 or T887) rice varieties, afterward employing genotyping-by-sequencing to obtain a high-density genetic map. A total of 17 and 3 QTLs were detected for AAC and PC, respectively. Among them, two QTLs associated with more than 10 AACs, qAAC6.1 and qAAC7.1, were identified for the first time in this study. Each favorable allele that increased the AAC of the two QTLs was derived from M23 and T887, respectively. Allelic combination of qAAC6.1 M23 and qAAC7.1T887 showed significantly higher content of associated amino acids (AAs) than other allelic combinations. Near-isogenic line (NIL) possessing qAAC7.1T887 with M23 genetic background had significantly higher AACs than both parents. These results indicate that the pyramiding of QTLs would be useful in developing brown rice with a high AA and protein content.