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Abstract Monocytes directly contribute to atherosclerosis development by their recruitment to plaques in which they differentiate into macrophages. In the present study, we ask how modulating monocyte glucose metabolism could affect their homeostasis and their impact on atherosclerosis. Here we investigate how circulating metabolites control monocyte behavior in blood, bone marrow and peripheral tissues of mice. We find that serum glucose concentrations correlate with monocyte numbers. In diet-restricted mice, monocytes fail to metabolically reprogram from glycolysis to fatty acid oxidation, leading to reduced monocyte numbers in the blood. Mechanistically, Glut1-dependent glucose metabolism helps maintain CD115 membrane expression on monocytes and their progenitors, and regulates monocyte migratory capacity by modulating CCR2 expression. Results from genetic models and pharmacological inhibitors further depict the relative contribution of different metabolic pathways to the regulation of CD115 and CCR2 expression. Meanwhile, Glut1 inhibition does not impact atherosclerotic plaque development in mouse models despite dramatically reducing blood monocyte numbers, potentially due to the remaining monocytes having increased migratory capacity. Together, these data emphasize the role of glucose uptake and intracellular glucose metabolism in controlling monocyte homeostasis and functions.

Background & Aims: Metabolic-dysfunction associated steatohepatitis (MASH) is associated with obesity and diabetes, and is linked to liver fibrosis and cardiovascular disease. Identification of patients who have MASH is challenging and the development of non-invasive strategies to diagnose and follow this condition is an important unmet need. Recent studies in mouse and humans have identified that significant changes occur in liver macrophage composition during MASH progression; namely, resident Kupffer cells decrease in number while recruited monocyte-derived macrophages increase. Methods: We developed peptide radiotracers targeted to C–C motif chemokine receptor 2 (CCR2) and CD163 to conduct positron emission tomography (PET) imaging of recruited vs. resident macrophages, respectively. Mice were placed on a MASH-inducing diet and non-invasive PET imaging of the liver was performed with tissue confirmation studies using flow cytometry and immunofluorescence. Statistical analyses were conducted using Student’s t tests, Pearson correlational analysis, and linear regression. Results: Using a mouse model of MASH, we found that the liver uptake of both CCR2 and CD163 radiotracers detected an increase in recruited cells and a decrease in resident macrophages. These findings correlated well with tissue macrophage content assessed by flow cytometry with an r value of 0.77 (p = 0.002) and 0.78 (p = 0.001) for CCR2 and CD163, respectively. Serial imaging with these radiotracers at several time points during MASH progression and regression revealed good correlation between liver macrophage composition and PET signal intensity. Conclusion: We demonstrate that novel PET radiotracers targeting CCR2 and CD163 can be used to image macrophage composition in MASH. Non-invasive molecular imaging of inflammation has the potential for diagnosis and monitoring of disease activity in humans with MASH. Impact and implications:: Macrophage-mediated inflammation contributes to MASH progression and fibrosis; however, liver biopsy is currently the only tool to assess this response. Thus, the development of non-invasive imaging modalities to identify and follow inflammatory activation is an area of need for patient care. In this study, we leverage molecular imaging using PET radiotracers to follow changes in macrophage composition that are related to MASH disease activity. The results in our preclinical model provide important proof of concept evidence that this approach can be used to diagnose MASH and to follow disease activity in response to intervention. Ongoing studies will evaluate the utility of this modality in humans with MASH.

Summary: Background: Pulmonary fibrosis is a challenging clinical problem with lung pathology featuring immune cell infiltrates, fibroblast expansion, and matrix deposition. Molecular analysis of diseased lungs and preclinical models have uncovered C–C chemokine receptor type 2 (CCR2)+ monocyte egress from the bone marrow into the lung, where they acquire profibrotic activities. Current drug treatment is focused on fibroblast activity. Alternatively, therapeutic targeting and monitoring CCR2+ cells may be an effective patient management strategy. Methods: Inhibition of CCR2+ cells and, as a benchmark, the clinical antifibrotic agent, nintedanib, were used in mouse lung fibrosis models. Lungs were evaluated directly for CCR2+ cell infiltration and by non-invasive CCR2+ positron emission tomography imaging (CCR2-PET). Findings: Lung CCR2+ cells were significantly elevated in the bleomycin model as determined by tissue evaluation and CCR2-PET imaging. A protective treatment protocol with an oral CCR2 inhibitor was compared to oral nintedanib. While we expected disparate effects on CCR2+ cells, each drug similarly decreased lung CCR2+ cells and fibrosis. Chemotaxis assays showed nintedanib indirectly inhibited C–C motif chemokine 2 (CCL2)-mediated migration of CCR2+ cells. Even delayed therapeutic administration of nintedanib in bleomycin and the silicosis progressive fibrosis models decreased the accumulation of CCR2+ lung cells. In these treatments early CCR2-PET imaging predicted the later development of fibrosis. Interpretation: The inhibition of CCR2+ cell egress is likely a critical controller for stabilising lung fibrosis, as provided by nintedanib. Imaging with CCR2-PET may be useful to monitor nintedanib treatment responses, guide decision-making in the treatment of patients with progressive pulmonary fibrosis, and as a biomarker for drug development. Funding: National Institutes of Health (NIH), R01HL131908 (SLB), R35HL145212 (YL), P41EB025815 (YL), K01DK133670 (DHK); Barnes Jewish Hospital Foundation (SLB).

This study was carried out to explore the significance of morphology-based selection for breeding, using a case study of indigenous buckwheat landrace from Korea. Although many studies have utilized molecular methods to investigate germplasm diversity, this research underscores the often-overlooked importance of morphology-based selection in breeding strategies. Furthermore, it highlights the necessity of considering geographical information only when it accurately reflects the actual environment. The study collected and analyzed five traits from 96 samples across 27 varieties. The hypothesis was that these 27 samples might have been grouped by region due to similar environmental conditions. This hypothesis was tested using a dendrogram, clustering, correlation analysis of each trait, and PCA analysis. The results showed that morphological traits are a crucial factor in germplasm or landrace selection and that they should be considered the basic information for breeding purposes. Morphological traits were found to be random regardless of the locations where they were collected, indicating that they should be used to determine breeding targets rather than geographic locations. The study suggested that understanding the physiological traits of specific germplasm groups can accelerate breeding efforts. Overall, this study provided important insights into the selection of germplasm or landrace for breeding purposes, highlighting the importance of morphology-based selection and the need to consider environmental factors.

Abstract A digital twin is a digital representation that closely resembles or replicates a real world object by combining interdisciplinary knowledge and advanced technologies. Digital twins have been applied to various fields, including to the agricultural field. Given big data and systematic data management, digital twins can be used for predicting future outcomes. In this study, we endeavor to create an agricultural digital twin using mandarins as a model crop. We employ an Open API to aggregate data from various sources across Jeju Island, covering an area of approximately 185,000 hectares. The collected data are visualized and analyzed at regional, inter-orchard, and intra-orchard scales. We observe that the intra-orchard analysis explains the variation of fruit quality substantially more than the inter-orchard analysis. Our data visualization and analysis, incorporating statistical models and machine learning algorithms, demonstrate the potential use of agricultural digital twins in the future, particularly in the context of micro-precision and individualized agriculture. This concept extends the current management practices based on data-driven decisions, and it offers a glimpse into the future of individualized agriculture by enabling customized treatment for plants, akin to personalized medicine for humans.

Abstract Background Managing and investigating all available genetic resources are challenging. As an alternative, breeders and researchers use core collection—a representative subset of the entire collection. A good core is characterized by high genetic diversity and low repetitiveness. Among the several available software, GenoCore uses a coverage criterion that does not require computationally expensive distance-based metrics. Results ShinyCore is a new method to select a core collection through two phases. The first phase uses the coverage criterion to quickly attain a fixed coverage, and the second phase uses a newly devised score (referred to as the rarity score) to further enhance diversity. It can attain a fixed coverage faster than a currently available algorithm devised for the coverage criterion, so it will benefit users who have big data. ShinyCore attains the minimum coverage specified by a user faster than GenoCore, and it then seeks to add entries with the rarest allele for each marker. Therefore, measures of genetic diversity and distance can be improved. Conclusion Although GenoCore is a fast algorithm, its implementation is difficult for those unfamiliar with R, ShinyCore can be easily implemented in Shiny with RStudio and an interactive web applet is available for those who are not familiar with programming languages.

This study investigated the potential of petal colorimetric data to classify vase life stages in cut lisianthus flowers (Eustoma grandiflorum). We analyzed the changes in the petal color space over time, focusing on the b* value as an indicator of senescence due to increasing yellowing caused by copigmentation. A comparative analysis was conducted between two cultivation methods: soil (S) and hydroponic (H) cultivation. The objective was to evaluate the performance of machine learning models trained to classify vase life stages based on petal color data. Automated machine learning models exhibited better performance in H-cultivated cut flowers, effectively distinguishing days within the vase life stages from Days 1 to 14 for H cultivation. Cut flowers cultivated under S conditions showed less variation in the color space from Days 1 to 9, maintaining a relatively uniform color range. This made it more difficult to distinguish the vase life stages compared to H cultivation. These findings demonstrate that petal color metrics can serve as reliable indicators of cut flower senescence and potentially facilitate nondestructive methods for classifying vase life stages. This technology holds promise for wider applications in the floriculture industry, improving quality control, and extending the vase life of various cut-flower crops.

Lisianthus, a globally popular ornamental plant, has a variable vase life (5–28 days). This study investigated biomass-related characteristics of four cultivars grown in soil or hydroponic cultivation with different treatment timings (vegetative and reproductive stage) and concentrations (0, 0.1, 0.3, and 0.5 mM) of salicylic acid (SA) in order to explain vase life. The results show that the SA treatment effects varied depending on cultivar, SA treatment timing, concentration, and cultivation method. Principle component analysis revealed that Blue Picote cultivar cultivated hydroponically with 0.5 mM SA at the reproductive stage had the longest vase life. Furthermore, vase life demonstrated a high positive correlation with dry weight, SPAD, Mg content, and flowering day. We developed a model using automated machine learning algorithms to estimate postharvest vase life, based on biomass-related characteristics measured during the pre-harvest period. Similar to the PCA results, this model also identified dry weight as the most influential predictor of vase life. This model proposes the possibility of estimating vase life by setting characteristics highly correlated with vase life as features for machine learning. It is anticipated that this model will be widely utilized in the floriculture industry for standardizing cut flower quality assessments in the future.

Bronchiolitis obliterans syndrome (BOS) is a major impediment to lung transplant survival and is generally resistant to medical therapy. Extracorporeal photophoresis (ECP) is an immunomodulatory therapy that shows promise in stabilizing BOS patients, but its mechanisms of action are unclear. In a mouse lung transplant model, we show that ECP blunts alloimmune responses and inhibits BOS through lowering airway TGF-β bioavailability without altering its expression. Surprisingly, ECP-treated leukocytes were primarily engulfed by alveolar macrophages (AMs), which were reprogrammed to become less responsive to TGF-β and reduce TGF-β bioavailability through secretion of the TGF-β antagonist decorin. In untreated recipients, high airway TGF-β activity stimulated AMs to express CCL2, leading to CCR2+ monocyte-driven BOS development. Moreover, we found TGF-β receptor 2–dependent differentiation of CCR2+ monocytes was required for the generation of monocyte-derived AMs, which in turn promoted BOS by expanding tissue-resident memory CD8+ T cells that inflicted airway injury through Blimp-1–mediated granzyme B expression. Thus, through studying the effects of ECP, we have identified an AM functional plasticity that controls a TGF-β–dependent network that couples CCR2+ monocyte recruitment and differentiation to alloimmunity and BOS.

Bunium persicum is a valuable medicinal plant with limited production but high market demand. It thrives predominantly in high-altitude regions. The main challenges hindering its widespread cultivation are seed dormancy and a lengthy seed-to-seed cycle, making its large-scale cultivation difficult. Six genotypes of Bunium persicum were collected from different altitudes to evaluate its germination behavior and seed dormancy. The study was conducted during 2020–23 and comprised three experiments (viz., seed germination under an open field, controlled conditions, and micro-tuberization). Under open field conditions, germination percent was genotype dependent, and the highest germination percentage, root length, and shoot length were recorded in Shalimar Kalazeera-1. Germination behavior assessment of the Bunium persicum revealed that treatment T9 (GA3 (25 ppm) + TDZ (9 µM/L)) is effective in breaking the dormancy of Bunium persicum as well as in obtaining a higher germination percent for early development of the tubers. Similarly, with regard to the effect of temperature and moisture conditions, stratification under moist chilling conditions showed effectiveness in breaking seed dormancy as the germination percentage in stratified seeds was at par with the most efficient growth hormone. With regard to the in vitro micro-propagation, direct regeneration showed multiple shoot primordia at the base of the tubers without intervening callus phase from the MS medium supplemented with BA (22.2 µM) and NAA (13.95 µM) 4 weeks after sub-culturing. Similarly, medium supplemented with JA (8.0 mg/L) and BA (22.2 µM) produced well-organized somatic embryos with shiny surfaces, which appeared at the swelled basal portion of apical stems. Further, the combination of JA (6.0 mg/L) and BA (22.2 M) was effective in developing the micro-tubers and also enhanced the weight and length of Bunium persicum micro-tubers.

Precision agriculture employs cutting-edge technologies to increase agricultural productivity while reducing adverse impacts on the environment. Precision agriculture is a farming approach that uses advanced technology and data analysis to maximize crop yields, cut waste, and increase productivity. It is a potential strategy for tackling some of the major issues confronting contemporary agriculture, such as feeding a growing world population while reducing environmental effects. This review article examines some of the latest recent advances in precision agriculture, including the Internet of Things (IoT) and how to make use of big data. This review article aims to provide an overview of the recent innovations, challenges, and future prospects of precision agriculture and smart farming. It presents an analysis of the current state of precision agriculture, including the most recent innovations in technology, such as drones, sensors, and machine learning. The article also discusses some of the main challenges faced by precision agriculture, including data management, technology adoption, and cost-effectiveness.

CD36 mediates the uptake of long-chain fatty acids (FAs), a major energy substrate for the myocardium. Under excessive FA supply, CD36 can cause cardiac lipid accumulation and inflammation while its deletion reduces heart FA uptake and lipid content and increases glucose utilization. As a result, CD36 was proposed as a therapeutic target for obesity-associated heart disease. However, more recent reports have shown that CD36 deficiency suppresses myocardial flexibility in fuel preference between glucose and FAs, impairing tissue energy balance, while CD36 absence in tissue macrophages reduces efferocytosis and myocardial repair after injury. In line with the latter homeostatic functions, we had previously reported that CD36–/– mice have chronic subclinical inflammation. Lipids are important for the maintenance of tissue homeostasis and there is limited information on heart lipid metabolism in CD36 deficiency. Here, we document in the hearts of unchallenged CD36–/– mice abnormalities in the metabolism of triglycerides, plasmalogens, cardiolipins, acylcarnitines, and arachidonic acid, and the altered remodeling of these lipids in response to an overnight fast. The hearts were examined for evidence of inflammation by monitoring the presence of neutrophils and pro-inflammatory monocytes/macrophages using the respective positron emission tomography (PET) tracers, 64Cu-AMD3100 and 68Ga-DOTA-ECL1i. We detected significant immune cell infiltration in unchallenged CD36–/– hearts as compared with controls and immune infiltration was also observed in hearts of mice with cardiomyocyte-specific CD36 deficiency. Together, the data show that the CD36–/– heart is in a non-homeostatic state that could compromise its stress response. Non-invasive immune cell monitoring in humans with partial or total CD36 deficiency could help evaluate the risk of impaired heart remodeling and disease.

The hemiparkinsonian nonhuman primate model induced by unilateral injection of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) into the carotid artery is used to study Parkinson’s disease. However, there have been no studies that the contralateral distribution of MPTP via the cerebral collateral circulation is provided by both the circle of Willis (CoW) and connections of the carotid artery. To investigate whether MPTP-induced unilaterally damaged regions were determined by asymmetrical cerebral blood flow, the differential asymmetric damage of striatal subregions, and examined structural asymmetries in a circle of Willis, and blood flow velocity of the common carotid artery were observed in three monkeys that were infused with MPTP through the left internal carotid artery. Lower flow velocity in the ipsilateral common carotid artery and a higher ratio of ipsilateral middle cerebral artery diameter to anterior cerebral artery diameter resulted in unilateral damage. Additionally, the unilateral damaged monkey observed the apomorphine-induced contralateral rotation behavior and the temporary increase of plasma RANTES. Contrastively, higher flow velocity in the ipsilateral common carotid artery was observed in the bilateral damaged monkey. It is suggested that asymmetry of blood flow velocity and structural asymmetry of the circle of Willis should be taken into consideration when establishing more efficient hemiparkinsonian nonhuman primate models.

Facility cultivation has been evolved from greenhouses to smart farms using artificial intelligence (AI) that simulates big data to maximize production. However, the big data for AI in smart farm is not studied well; the effect of differences among varieties within a crop remains unclear. Therefore, the response of two varieties of blueberry, 'Suziblue' and 'Star', to light was tested using SAPD meter in order to demonstrate the environmental responses could be different among varieties within the same species. The results showed that those two varieties had significant differences in SPAD values based on the leaf's position and time, whereas 'Star' did not. This indicates that the effect of light depends on the variety, which implies that other traits and other crops may show similar differences. These results are based on a simple experiment. However, it is enough to elucidate that it is extremely important to characterize responses to the environment not only for each crop but also for each variety to collect data for smart farming to increase accuracy for modeling; consequently, to maximize the efficiency of these facilities.

To date, 19 species of spiny lobsters from the genus Panulirus have been discovered, of which only P. japonicus, P. penicilatus, P. stimpsoni, and P. versicolor have been documented in South Korean waters. In this study, we aimed to identify and update the current list of spiny lobster species that inhabit South Korean waters based on the morphological features and the phylogenetic profile of cytochrome oxidase I (COI) of mitochondrial DNA (mtDNA). Spiny lobsters were collected from the southern and eastern coasts of Jeju Island, South Korea. Phylogenetic analyses were performed using neighbor-joining (NJ), maximum likelihood (ML), and Bayesian inference (BI) methods. The ML tree was used to determine the spiny lobster lineages, thereby clustering the 17 specimens collected in this study into clades A, B, C, and D, which were reciprocally monophyletic with P. japonicus, P. homarus homarus, P. longipes, and P. stimpsoni, respectively. These clades were also supported by morphological examinations. Interestingly, morphological variations, including the connected pleural and transverse groove at the third abdominal somite, were observed in four specimens that were genetically confirmed as P. japonicus. This finding is novel within the P. japonicus taxonomical reports. Additionally, this study updates the documentation of spiny lobsters inhabiting South Korean waters as P. longipes and P. homarus homarus were recorded for the first time in this region.

Objective According to reported spawning characteristics of Japanese eel, Anguilla japonica, which exhibit spawning and migration patterns that are synchronized with lunar cycles and photoperiod, we hypothesized that a close association exists between specific photic signals (daylight, daylength, and moonlight) and endocrinological regulation. Given the photic control in melatonin secretion, this hypothesis was tested by investigating whether melatonin signals act as mediators relaying photic signals during testis development in the eel. Methods We examined changes in melatonin-secretion patterns using time-resolved fluorescence immunoassays in sexually immature and mature male Japanese eels under the condition of a new moon (NM) and a full moon (FM). Results The eye and plasma melatonin levels exhibited a nocturnal pattern under a 12-h light: dark cycle (12L12D) or under constant darkness (DD), but not with constant light (LL). Eye melatonin levels were similar under the 12L12D and short-day (9L15D) conditions. In the long-day condition (15L9D), secreted plasma melatonin levels were stable, whereas short-day melatonin secretion began when darkness commenced. Sexual maturation began at 8 weeks following intraperitoneal injection of human chorionic gonadotropin (hCG), and NM exposure led to significantly higher eye and plasma melatonin levels compared with those detected under FM exposure.

Climate change may alter tree species’ distribution, which could impact on forest biodiversity. However, frequent and continuous surveys of forests need intense labor and are time-consuming. The current study utilized SENTINEL-2 images of Geomunoreum to solve this problem as a case study. Acquired images were converted into various indices, such as the normalized difference vegetation index (NDVI), which could be an efficient method to examine the diversity in forests over time. In the current study, the images were obtained in March and April from 2017 to 2021. As a result of analysis using NDVI images of the study area taken from the satellite, vegetation groups were classified into evergreen trees and deciduous trees. This implies that NDVI using extracted data from SENTINEL-2 images could be used for surveying large-scale examinations for tree classification in order to observe variations caused by climate change in an efficient and cost-effective manner.

Background Since the establishment of biological augmentation to improve the treatment of rotator cuff tears, it is imperative to explore newer techniques to reduce the retear rate and improve long-term shoulder function after rotator cuff repair. This study was undertaken to determine the consequences of a gel-type atelocollagen injection during arthroscopic rotator cuff repair on clinical outcomes, and evaluate its effect on structural integrity. Methods Between January 2014 and June 2015, 121 patients with full thickness rotator cuff tears underwent arthroscopic rotator cuff repair. Of these, 61 patients were subjected to arthroscopic rotator cuff repair in combination with an atelocollagen injection (group I), and 60 patients underwent arthroscopic rotator cuff repair alone (group II). The visual analogue scale (VAS) for pain and the Korean Shoulder Society (KSS) scores were evaluated preoperatively and postoperatively. Magnetic resonance imaging (MRI) was performed at 6 months postoperatively, to assess the integrity of the repair. Results VAS scores were significantly lower in group I than in group II at 3, 7, and 14 days after surgery. KSS scores showed no significant difference between groups in the 24 months period of follow-up. No significant difference was obtained in the healing rate of the rotator cuff tear at 6 months postoperatively (p=0.529). Conclusions Although a gel-type atelocollagen injection results in reduced pain in patients at 2 weeks after surgery, our study does not substantiate the administration of atelocollagen during rotator cuff repair to improve the clinical outcomes and healing of the rotator cuff.

An assay for detecting Apple scar skin viroid (ASSVd) was developed based on nucleic acid sequence based amplification (NASBA) in combination with real-time detection during the amplification process using molecular beacon. The ASSVd specific primers for amplification of the viroid RNA and molecular beacon for detecting the viroid were designed based on highly conserved regions of several ASSVd sequences including Korean isolate. The assay had a detection range of 1 × 104 to 1 × 1012 ASSVd RNA copies/μl with reproducibility and precision. Following the construction of standard curves based on time to positive (TTP) value for the serial dilutions ranging from 1 × 107 to 1 × 1012 copies of the recombinant plasmid, a standard regression line was constructed by plotting the TTP values versus the logarithm of the starting ASSVd RNA copy number of 10-fold dilutions each. Compared to the established RT-PCR methods, our method was more sensitive for detecting ASSVd. The real-time quantitative NASBA method will be fast, sensitive, and reliable for routine diagnosis and selection of viroid-free stock materials. Furthermore, real-time quantitative NASBA may be especially useful for detecting low levels in apple trees with early viroid-infection stage and for monitoring the influence on tree growth.

Tangor (Citrus unshiu × C. sinensis) cultivars obtained through interspecific hybridization have gained popularity in various countries, including South Korea. However, tangor has a relatively short history of cultivation and thus has been less well researched in terms of physiology and opping technology compared to mandarin. In addition, although tangor grows more vigorously than mandarin and thus has high nutrient demands and longer harvest time, it is more prone to various physiological disorders. Furthermore, the demand for nutrients could vary depending on the cultivars even within the same species. Thus, the current study examined the effects of nitrogen deficiency and resupply on the uptake of mineral nutrients using a specific cultivar ‘Shiranuhi’ as a case study. In this study, the tangor cultivar ‘Shiranuhi’ was cultivated in a hydroponics system, which allows the control of nutrient contents, and changes in mineral nutrient contents under nitrogen deficiency and nitrogen resupply were examined. Based on this, the results show the straightforward relationship between nitrogen and other mineral nutrients under a hydroponic system applying the cultivation of tangor. This implies that the hydroponics system can be applied to tangor cultivation and efficiently and widely expanded in Northeast Asia, and the income of growers will increase through the production of high-quality fruits.

Silicon promotes nodule formation in legume roots which is crucial for nitrogen fixation. However, it is very time-consuming and laborious to count the number of nodules and to measure nodule size manually, which led nodule characterization not to be study as much as other agronomical characters. Thus, the current study incorporated various techniques including machine learning to determine the number and size of root nodules and identify various root phenotypes from root images that may be associated with nodule formation with and without silicon treatment. Among those techniques, the machine learning for characterizing nodule is the first attempt, which enabled us to find high correlations among root phenotypes including root length, number of forks, and average link angles, and nodule characters such as number of nodules and nodule size with silicon treatments. The methods here could greatly accelerate further investigation such as delineating the optimal concentration of silicon for nodule formation.