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Highlights A LiDAR-guided automatic airflow control system for precision sprayers was developed. Three models were built to measure the amount of airflow required for apple trees. The study confirmed that adjusting the fan inlet could control airflow penetration into tree canopies. Results suggest that the system can reduce spray drift and off-target losses. Abstract. The airflow discharged from orchard airblast sprayers is a primary component for successfully carrying spray droplets to the target trees. Because of the variation in orchard tree canopies, control of the airflow to minimize off-target loss during spray application is essential. An automatic airflow control system for precision sprayers was developed to maximize spray droplet coverage on targets and minimize off-target loss while considering the tree canopy densities. The primary component of the system was an iris damper, which was designed as a retrofit attachment on the fan inlet of a three-point airblast intelligent sprayer. A 3D light detection and ranging (LiDAR) sensor was installed at the top of the sprayer to acquire the tree canopy data. A motor was employed to control the damper opening with a micro-controller. To develop the models required for automatic airflow control, field experiments were conducted at three canopy density orchards with different cultivars (GoldRush, Gala, and Fuji). A total of 15 trees (five trees from each cultivar) were randomly selected, and five different damper openings (openings 1, 2, 3, 4, and 5) were tested for each tree. Opening 1 represented the same air inlet as a traditional precision airblast sprayer, while openings 2, 3, 4, and 5 were the sequentially reduced air inlets of the sprayer. A canopy density measurement algorithm was scripted to measure the canopy point density of individual trees. Three models were built to show relationships between (1) tree canopy point densities and airflows; (2) canopy densities and damper openings; and (3) damper opening and motor steps. The combination of the two models (2 & 3) was used to assess the amount of airflow required for a specific canopy density. Field validations for medium and high-density trees showed that the system achieved adequate spray penetration at the top, middle, bottom, back-left, and back-right positions of the tree sections and reduced off-target loss at the ground and edge of next row sections using openings 4 and 2, respectively. However, the mechanical motion of the damper required 3 s to move from minimum to maximum opening, so the average canopy density was recommended to control the airflow. The overall results suggested that the automatic airflow control system could reduce spray drift and off-target losses and improve spray application efficiency in orchards. Keywords: Automation, Canopy sensing, Fan inlet, Precision spraying, Variable rate application.

Digital intervention tools against problematic smartphone usage help users control their consumption on smartphones, for example, by setting a time limit on an app. However, today's social media apps offer a mix of quasiessential and addictive features in an app (e.g., Instagram has following feeds, recommended feeds, stories, and direct messaging features), which makes it hard to apply a uniform logic for all uses of an app without a nuanced understanding of feature-level usage behaviors. We study when and why people regret using different features of social media apps on smartphones. We examine regretful feature uses in four smartphone social media apps (Facebook, Instagram, YouTube, and KakaoTalk) by utilizing feature usage logs, ESM surveys on regretful use collected for a week, and retrospective interviews from 29 Android users. In determining whether a feature use is regretful, users considered different types of rewards they obtained from using a certain feature (i.e., social, informational, personal interests, and entertainment) as well as alternative rewards they could have gained had they not used the smartphone (e.g., productivity). Depending on the types of rewards and the way rewards are presented to users, probabilities to regret vary across features of the same app. We highlight three patterns of features with different characteristics that lead to regretful use. First, "following"-based features (e.g., Facebook's News Feed and Instagram's Following Posts and Stories) induce habitual checking and quickly deplete rewards from app use. Second, recommendation-based features situated close to actively used features (e.g., Instagram's Suggested Posts adjacent to Search) cause habitual feature tour and sidetracking from the original intention of app use. Third, recommendation-based features with bite-sized contents (e.g., Facebook's Watch Videos) induce using "just a bit more," making people fall into prolonged use. We discuss implications of our findings for how social media apps and intervention tools can be designed to reduce regretful use and how feature-level usage information can strengthen self-reflection and behavior changes.

HighlightsA robotic mushroom picking mechanism was developed, including positioning, picking, and stipe trimming.The picking end-effector was designed based on a bending motion around the stipe-substrate joint.The overall success rate of the developed picking mechanism reached 91.4%.Acting time and air pressure for the suction cup were studied in mushroom bruise level tests.Abstract. Button mushroom (Agaricus bisporus) harvesting mainly relies on costly manpower, which is time-consuming and labor-intensive. Robotic harvesting is an alternative method to address this challenge. In this study, a robotic mushroom picking mechanism was designed, including a picking end-effector based on a bending motion, a four degree-of-freedom (DoF) positioning end-effector for moving the picking end-effector, a mushroom stipe trimming end-effector, and an electro-pneumatic control system. A laboratory-scale prototype was fabricated to validate the performance of the mechanism. Bruise tests on the mushroom caps were also conducted to analyze the influence of air pressure and acting time of the suction cup on bruise level. The test results showed that the picking end-effector was successfully positioned to the target locations. The success rate of the picking end-effector was 90% at first pick and increased to 94.2% after second pick. The main reason for the failures was inclined growing condition of those mushrooms, resulting in difficulties in engaging the mushroom cap with the suction cup facing straight downward. The trimming end-effector achieved a success rate of 97% overall. The bruise tests indicated that the air pressure was the main factor affecting the bruise level, compared to the suction cup acting time, and an optimized suction cup may help to alleviate the bruise damage. The laboratory test results indicated that the developed picking mechanism has potential to be implemented in automatic mushroom harvesting. Keywords: Bruise test, End-effector, Mushroom, Robotic harvesting.

HighlightsA branch accessibility simulation was performed for robotic pruning of apple trees.A virtual tree environment was established using a kinematic manipulator model and an obstacle model.Rapidly-exploring random tree (RRT) was combined with smoothing and optimization for improved path planning.Effects on RRT path planning of the approach angle of the end-effector and cutter orientation at the target were studied.Abstract. Robotic pruning is a potential solution to reduce orchard labor and associated costs. Collision-free path planning of the manipulator is essential for successful robotic pruning. This simulation study investigated the collision-free branch accessibility of a six rotational (6R) degrees of freedom (DoF) robotic manipulator with a shear cutter end-effector. A virtual environment with a simplified tall spindle tree canopy was established in MATLAB. An obstacle-avoidance algorithm, rapidly-exploring random tree (RRT), was implemented for establishing collision-free paths to reach the target pruning points. In addition, path smoothing and optimization algorithms were used to reduce the path length and calculate the optimized path. Two series of simulations were conducted: (1) performance and comparison of the RRT algorithm with and without smoothing and optimization, and (2) performance of collision-free path planning considering different approach poses of the end-effector relative to the target branch. The simulations showed that the RRT algorithm successfully avoided obstacles and allowed the manipulator to reach the target point with 23 s average path finding time. The RRT path length was reduced by about 28% with smoothing and by 25% with optimization. The RRT smoothing algorithm generated the shortest path lengths but required about 1 to 3 s of additional computation time. The lowest coefficient of variation and standard deviation values were found for the optimization method, which confirmed the repeatability of the method. Considering the different end-effector approach poses, the simulations suggested that successfully finding a collision-free path was possible for branches with no existing path using the ideal (perpendicular cutter) approach pose. This study provides a foundation for future work on the development of robotic pruning systems. Keywords: Agricultural robotics, Collision-free path, Manipulator, Path planning, Robotic pruning, Virtual tree environment.

HighlightsAn end-effector with two degrees of freedom (2R) was developed for pruning apple trees.A rational 2×2 relationship (R2 = 0.93) was found for ‘Fuji’ apple tree branch diameter and cutting force.Simulation showed that the cutter can be aligned in a wide range of orientations in a spherical workspace.The developed end-effector was able to cut branches up to 12 mm in diameter.Abstract. Robotics and automation technologies are now used extensively in agriculture, while production operations for tree fruit crops still largely depend on manual labor. Manual pruning is a labor-intensive and costly task in apple production. Robotic pruning is a potential solution, but it involves several challenges due to the unstructured work environment. This study focused on designing an end-effector prototype for pruning considering the maneuvering, spatial, mechanical, and horticultural requirements. Branch cutting force was measured with a thin force sensor to provide guidelines for the end-effector design. The test results indicated the relationship between the force required to cut different diameter branches with an R2 value of 0.93. The end-effector was developed using two rotary motors, a pneumatic cylinder, and a pair of bypass shear blades. A three-directional linear manipulator system and a control system were built for moving the end-effector to targeted locations. A mathematical model was developed for simulation of the workspace utilization and reachable points of the end-effector. The simulation results indicated that the end-effector can be aligned in a wide range of orientations of the cutter. Field tests were conducted for validation of the simulation results and performance assessment of the end-effector. The results indicated that the end-effector with the current parameter settings successfully cut branches up to 12 mm in diameter and was able to cut branches in a wide range of possible orientations in a given 3D space. The robotic end-effector developed in this study is a core component of an automated pruning system for fruit trees. In future work, an integrated manipulator system will be developed for branch accessibility with collision-free trajectories. Keywords: Malus × domestica (Borkh.), Pruning end-effector, Reachable-points simulation, Tree pruning.

HighlightsThermal conductivity significantly decreased (p < 0.05), particularly in the last two weeks of the growing season.Thermal conductivity values were significantly different (p < 0.05) between the measurement locations.Thermal conductivity had a moderate correlation (0.35 < |r| < 0.67) with maturity indices.Abstract. ±±W m·K-1±±2-1 Keywords: Apple maturity, DNHP, Harvest time, Malus × domestica (Borkh.), Thermal conductivity, Thermal properties.

Amphibian biodiversity is declining globally, with over 40% of species being considered threatened to become extinct. Crucial to the success of conservation initiatives are a comprehensive understanding of life history and reproductive ecology of target species. Here we provide an overview of the Pseudacris genus, including breeding behaviour, reproduction, development, survival and longevity. We present an updated distribution map of the 18 species found throughout North America. We also summarize the conservation status at the national and subnational (state, provincial, and territorial) levels, in Canada, USA, and Mexico, to evaluate the relationship between life history traits and extinction risk. Results show a high degree of consistency in the life history traits of Pseudacris species considering their relative diversity and wide distribution in North America. However, data are lacking for several species, particularly in the Fat Frog and West Coast clades, causing some uncertainties and discrepancies in the literature. We also found that the most threatened populations of chorus frog were located in the east coast of the USA, potentially as a result of increased levels of anthropogenic disturbance. We suggest that the similarities in life history traits among chorus frog species provides an opportunity for collaboration and united efforts for the conservation of the genus. Supplementary Information The online version contains supplementary material available at 10.1186/s12983-021-00425-w.

Monitoring of fruit size development has important implications for apple orchard management decision making such as scheduling for fruitlet chemical thinning and allocating resources for harvest. The current method for tracking fruit size development is by tagging a sample of fruits and using calipers or sizing rings to make measurements, which can be labor-intensive and time-consuming. In this study, a stereo vision system was developed which sized fruits on a tree and kept track of their growth during the season by matching fruit in images across time. Neural network models including Faster R-CNN and Mask R-CNN were used for fruit detection and on-tree fruit sizing. Camera pose estimation using feature matching of apples was used for tracking individual fruit growth. The best performance on fruit matching for the ‘Golden Delicious‘ variety during the growing season in an apple orchard was observed in September and October; 74% of all detected fruits which were fully visible were matched between the two months. Fruitlets averaging 25 mm in diameter also had a matching accuracy of 73% during two imaging trials performed on the same day for the month of June.

Precision irrigation with sensors has proven to be effective for water saving in crop production. Internet of things (IoT) system is necessary for monitoring real-time data from sensors and automating irrigation systems. Long-range wide-area network (LoRaWAN) is low-cost and easy to be implemented in IoT systems that can be used for precision crop irrigation. In this study, an IoT-based precision irrigation system with LoRaWAN technology was developed and evaluated as a precision management tool on fresh-market tomato production in an open field. Four irrigation scheduling treatments were designed and tested, including ET (ETc), MP60 (Watermark 200SS-5 soil matric potential sensors, -60 kPa), MP40 (-40 kPa), and GesCoN (decision support system). The treatments were arranged based on a randomized complete block design (RCBD) with four replications. System feasibility, yield, and irrigation water use efficiency (iWUE) were evaluated during the experiment. The results indicated that treatment MP60 and GesCoN had a marketable yield 15.2% and 22.1% higher than ET, respectively. MP40 had a marketable yield 12.5% lower than ET. GesCoN had a significantly higher yield than ET and MP40. However, MP60 did not produce significantly different results from GesCoN and ET but had higher yield than MP40. MP40 received relatively low water via irrigation because of unproper installation and positioning of the soil moisture sensors, which caused a higher incidence of blossom end-rot and thus lower marketable yield. Nevertheless, the LoRaWAN-based IoT system worked well in terms of power consumption, communication, sensors reading and valve control. It can be potentially implemented for precision and automatic irrigation operation in vegetable fields.

Various cucurbitacins have been isolated, and their structures have been elucidated. Owing to their economic potential and importance as active pharmacological compounds, their cytotoxicity in various cancer cells has been assessed. Here, we mined several candidate genes with potential involvement in cucurbitacin biosynthesis in watermelon (Citrullus lanatus) and performed in vitro enzymatic assays and instrumental analyses using various substrates to identify cucurbitacin functions and products. Enzymatic activities of two acetyltransferases (ACTs) and one UDP-glucosyltransferase (UGT) against cucurbitacins were confirmed, resulting in the synthesis of novel cucurbitacins in vivo and/or in vitro to our knowledge. As ACTs and UGT are involved in the dynamic conversion of cucurbitacins by catalyzing acetylation and glucosylation at moieties in the cucurbitacins skeleton, these findings improve our knowledge on how these genes contribute to the diversity of cucurbitacins., Kim et al. use RNAseq of two watermelons to select candidate genes coding for enzymes that catalyze modifications of cucurbitacins. They characterise four of the 16 candidate enzymes (3 different acetyltransferases and one UDP-glucosyltransferase) by HPLC, LC-MS, NMR, and in vitro enzymatic assay. They further show with in vivo assay in Drosophila, that acetylation of cucurbitacin increases neuronal activity in insects.

International audience; Anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis is an autoimmune disorder which affects small-and, to a lesser degree, medium-sized vessels. ANCA-associated vasculitis encompasses three disease phenotypes: granulomatosis with polyangiitis (GPA), microscopic polyangiitis (MPA), and eosinophilic granulomatosis with polyangiitis (EGPA). This classification is largely based on clinical presentations and has several limitations. Recent research provided evidence that genetic background, risk of relapse, prognosis, and co-morbidities are more closely related to the ANCA serotype, proteinase 3 (PR3)-ANCA and myeloperoxidase (MPO)-ANCA, compared to the disease phenotypes GPA or MPA. This finding has been extended to the investigation of biomarkers predicting disease activity, which again more closely relate to the ANCA serotype. Discoveries related to the immunopathogenesis translated into clinical practice as targeted therapies are on the rise. This review will summarize the current understanding of the immunopathogenesis of ANCA-associated vasculitis and the interplay between ANCA serotype and proposed disease biomarkers and illustrate how the extending knowledge of the immunopathogenesis will likely translate into development of a personalized medicine approach in the management of ANCA-associated vasculitis.

Mushrooms are picked manually one by one, which is time consuming and labor intensive. Robotic harvesting is an alternative method to address this issue. The purpose of this paper was to assess hand-picking methods as candidate techniques for implementation in a robotic end-effector designed to harvest Agaricus mushrooms. Conventional manual mushroom picking comprises a combination motion of twisting, bending, and lifting. To find an effective and simple picking method for robotic harvesting, a series of picking force and motion studies were conducted to compare among different picking methods. Four picking motions were considered, including conventional method, and three simplified methods, namely, bending, lifting, and twisting. The sensors used during picking included three force sensors and an inertial measurement unit. A damage test on the mushroom cap was also conducted to analyze the crop bruise level under different forces and acting duration. Experimental data were recorded for normal contact forces and mushroom rotation angles. The conventional picking method required the most orientation changes to detach a mushroom, which could generate complexity for designing a robotic end-effector with the equivalent dexterity. The test results indicated that bending was a simple and effective method for mushroom separation due to the least picking time and force needed compared to the other three patterns. Both lifting and twisting methods required a larger force on the index finger than on the thumb to detach mushrooms, which resulted in lower success pick rate and obvious bruise damage. The results also indicated that a bigger contacting force was the major reason for causing bruising, by comparing with the acting time. The outcomes could provide some guideline information for developing a robotic mushroom picking system for Agaricus mushroom harvesting.

Pruning of apple trees requires 80-120 working hours of labor per hectare accounting for 20% of the total production cost. Robotic pruning is a potential solution to decrease labor dependence and associated costs. Autonomous precise manipulation of a robotic manipulator in presence of obstacles is a challenge. The spatial requirements and collision-free path planning for the robotic manipulator is essential for automated systems. This simulation study focused on investigating the branch accessibility of a six-rotational (6R) degrees of freedom (DoF) robotic manipulator with a shear blade type end-effector. A virtual tree canopy environment was established in MATLAB for simulation. The Rapidly-exploring Random Tree (RRT) obstacle avoidance algorithm was used to establish a collision-free path to reach the target pruning points. The path smoothing and optimization algorithms were also used to reduce path length and calculate the optimize path. The simulation showed that the integrated robotic manipulator reached the pruning points avoiding obstacle untargeted branches. The path generation time, path length, target reaching time, and number of accessible branches (success) and collisions (failure) was recorded. The study provides the foundation information for future work on the development of a robotic pruning system

Accurate measurement of fruit size in apple orchards before harvest can have important implications on profits and management practices. Obtaining a distribution of fruit size can be labor intensive for a large orchard and therefore requires an automated system that can quickly and accurately size fruit on every tree. This study proposes an automated imaging system that uses stereo vision for finding the metric surface area of apples. Deep convolutional neural network models were utilized to classify apples as ideal candidates for sizing based on their orientation and visibility in an image. The results produced a correlation of apple size to apple weight of R2=0.69 making the system capable of capturing variability in fruit diameter distribution that ranges by 1cm (or equivalently 60 grams). There was also an improvement in correlation to yield when combining fruit size with fruit count than when utilizing fruit count alone.

Cucurbitacins are a group of tetracyclic triterpenes produced by members of the Cucurbitaceae family that are known for their bitter taste, and have both positive and negative attributes based on their use. The aim of the present study was to profile cucurbitacins through the quantitative analysis of diverse watermelon (Citrullus spp.) germplasms, including Citrullus colocynthis and Citrullus lanatus, using liquid chromatography–mass spectrometry (LC–MS) and high performance liquid chromatography. We isolated cucurbitacins B and E, and cucurbitacin E glycoside and evaluated the concentration of these compounds in watermelon leaves, fruits, and seedling extracts. High amounts of cucurbitacin E glycosides were found in most of the C. colocynthis leaves at concentrations between 1.3 and 0.9 mg/g of fresh weight, while relatively low concentrations of cucurbitacin B and E were detectable in these tissues. Interestingly, cucurbitacin E glycosides were only detected in most C. colocynthis fruits at concentrations between 0.21 and 3.2 mg/g fresh weight. We also confirmed the correlation between bitter taste and cucurbitacin E glycoside content. Cucurbitacin B and E and cucurbitacin E glycoside were found in most of the cultivars tested, while cucurbitacin agylcones were the primary cucurbitacins identified in seedlings. This study reveals the cucurbitacin composition in various watermelon germplasms and in different plant tissue.

The original version of this article unfortunately contained a mistake. The affiliation “China West Normal University” should be removed from the author Dr. Chenglin Wang. The correct affiliation details are given below.

Ethylene is an important regulator of developmental and stress responses in plants, and 1-aminocyclopropane-1-carboxylic acid synthase (ACS) proteins catalyze one of the rate-limiting steps in endogenous ethylene biosynthesis. Accordingly, the function of ACS family genes has been extensively studied in plants including Arabidopsis and tomato; however, little is known about the systemic function of ACS genes in cucumber (Cucumis sativus L.). Here, we investigated the expression patterns of eight cucumber ACS family genes (CsACSs) in a variety of tissues and sex types, as well as in response to exogenous ethylene application, and their ACS activities. Tissue-specific expression profiling in monoecious and gynoecious cucumber plants revealed that some CsACSs were differentially expressed. In particular, the five genes CsACS1, CsACS1-2, CsACS2, CsACS6, and CsACS11 were highly expressed in the shoot apex regions of gynoecious and hermaphroditic cucumber plants. The expression of most CsACSs was also induced by exogenous ethylene application. Furthermore, three CsACS isoforms (CsACS9, CsACS10, and CsACS12) showed no ACS enzymatic activity, which was associated with the amino acid variations in the conserved active residues of CsACS proteins. However, an in vitro pull-down assay revealed that two enzymatically inactive isoforms (CsACS9 and CsACS10) did not significantly interact with four active isoforms (CsACS1, CsACS1-2, CsACS2, and CsACS6). Taken together, our findings will be valuable for elucidating the relationship between RNA expression, ACS activity, protein–protein interactions between CsACSs and cucumber sex types.

Precision spraying is one of the most promising techniques to produce healthy and sustainably profitable crops. However, accurate canopy density measurements for precision spraying decisions are still a challenging endeavor, especially in orchards with uneven terrain conditions. A sensor fusion-based canopy point correction system was developed with a 3D light detection and ranging (LiDAR) sensor and an inertial navigation system-global navigation satellite system (INS-GNSS) for accurate tree canopy density measurement. The LiDAR sensor was used to acquire the tree canopy architectures, while the INS-GNSS sensor was to evaluate the terrain slopes and the tree georeferenced locations. A mathematical model was developed to perform the simulation for correction of canopy points based on given changes in the roll, pitch, and yaw angles. A sensor fusion algorithm was developed to process the canopy point corrections for the tree fruit orchards with three different sloping conditions, including longitudinal, lateral, and combination of both slopes. Simulation results reported that the developed model established the correction of tree canopy points with varying roll, pitch, and yaw angles. Field evaluation results suggested that the developed system could be used for correcting canopy points at any sloping conditions in various terrains. The measured tree canopy density from the corrected canopy points reported a possible of off-target chemical reduction up to 13.87%, 5.19%, and 15.45% in orchard sites 1, 2 and 3, respectively. With the accurate tree canopy density measurement, it is anticipated that the developed system could be used to reduce the off-target deposition for precision spraying applications in uneven tree fruit orchards.

Introduction: While intensive induction chemotherapy has been standard-or-care for patients with acute myeloid leukemia (AML), intensive regimens have often been limited in elderly patients with comorbidities. As an alternative option, less intensive hypomethylating agents (HMAs), decitabine (DAC) and azacitidine (AZA), are currently being used in these unfit patients. However, their low response rates and adverse events when administered alone suggest a need to develop novel HMAs that elicit enhanced efficacy and reduced mortality. A recent study demonstrated pharmacological improvements of a novel 4′-thio-modified analog, 5-aza-4′-thio-2′-deoxycytidine (hereafter NTX-301), including enhanced chemical stability and incorporation into DNA and improved preclinical efficacy (Thottassery, 2014). However, the mechanism of action (MoA) of NTX-301 has not yet been understood. Herein, we aim to thoroughly investigate the preclinical efficacy and MoAs of NTX-301 in AML through comparative analysis with DAC and AZA. To this end, we used in vitro and in vivo preclinical models of AML and performed multiomics-based analyses. Results: We comprehensively examined viability of 200 cancer cell lines (CCLs) upon treatment with NTX-301. Consistent with the current use of HMAs as therapeutics for hematologic malignancies, this sensitivity profiling displayed the most remarkable potency of NTX-301 toward blood CCLs (OR=3.97, p=0.0003). In addition, phenotypic assays revealed that the anti-leukemic activity of NTX-301 was superior to that of DAC, which is attributed to more effective actions in inducing apoptosis, cell cycle arrest, and differentiation. Supporting the in vitro results, orally administrated NTX-301 led to more potent tumor regression, better tolerability, and survival benefits over DAC and AZA in both systemic (1.5-2.0 mg/kg, qdx5 then 2 days off, 5 days on, and 9 days off, for 3 cycles) and subcutaneous (0.2-1.5 mg/kg) xenograft models. To assess the underlying MoAs, we interrogated global alterations at the transcriptome and methylome levels upon treatment with NTX-301 in three AML cell lines using RNA sequencing and methylation array. Methylome analyses revealed that NTX-301-induced demethylation patterns were distinguished from DAC; DAC triggered stronger global demethylation than NTX-301 did, whereas NTX-301 derived rather selective demethylation, preferentially in early-replicating regions, H3K27ac-marked regions, and non-CpG islands. In transcriptome analyses compared with DAC, NTX-301 more markedly elicited a transcriptional reversal toward a normal myeloid-like signature by increasing a differentiation signature and suppressing a leukemic stem cell signature. NTX-301 also mediated more pronounced activation of DNA damage response and the p53 pathway, which are characterized by marked induction of pH2AX and pChk1 and increased stability of p53, respectively. Given the synthetic lethality of p53 activation and BCL2 inhibition (Rongqing, 2017), stronger p53 stabilization by NTX-301 may confer more benefits in combination with venetoclax. Indeed, the combination of NTX-301 + venetoclax produced a more synergistic combination index compared with DAC + venetoclax. Strikingly, the combined NTX-301 (0.5-2.0 mg/kg) + venetoclax (50 mg/kg) achieved complete tumor remission, no notable toxicity, and prolonged survival benefits over AZA (2.5 mg/kg) + venetoclax (50 mg/kg) in preclinical models of AML. By integrating sensitivity profiles and multiomics data of 200 CCLs, we interrogated molecular determinants associated with sensitivity to NTX-301. Intriguingly, when comparing methylomes between sensitive and resistant CCLs, we found a significantly biased global hypermethylation trend toward sensitive CCLs. A combinatorial set of the most significantly biased 352 differentially methylated regions (FDR Conclusions: Our study demonstrated an improved therapeutic index of NTX-301 over traditional HMAs, providing a rationale for further clinical development of the agent as a single-agent or in combination with other agents. We also believe that our study for MoAs and biomarkers will improve our understanding of NTX-301. Disclosures Lim: Pinotbio: Research Funding. Yoo: Pinotbio: Research Funding. Cho: Pinotbio: Research Funding. Choi: Pinotbio: Research Funding. Jung: Pinotbio: Research Funding. Jung: Pinotbio: Current Employment. Lee: Pinotbio: Current Employment. Chun: Pinotbio: Current Employment. Go: Pinotbio: Current Employment. Lee: Pinotbio: Current Employment. Choi: Pinotbio: Research Funding.

Automation and robotics have been widely applied in many agricultural operations; however, the production operations of apple trees are usually performed manually. Pruning is one of the most labor-intensive operations, accounting for about 20% of the total labor costs. Robotic pruning is a potential long-term solution to deal with the issue of labor shortages and associated high costs. In recent years, researchers have advanced technologies that could lead to the development of a robotic pruning system. However, numerous challenges are involved for successful adoption of robotic pruning technologies. This review highlighted the technological progress in the core components of a robotic pruner including machine vision, manipulator, end-effector, path planning, and obstacle avoidance; the challenges associated with the existing technologies; and potential solutions to the development of an automated pruning system. The review covers both scientific/research and commercial technologies developed for robotic tree pruning. The available literature related to all technological components of a robotic pruning system was reviewed in detail, and useful information was synthesized for presenting in the paper. Finally, the paper scrutinizes the challenges and potential future opportunities for developing a robotic pruning system for a sustainable apple production system.

Machine vision systems are being utilized extensively in agriculture applications. Daytime imaging in outdoor field conditions presents challenges such as variable lighting and colour inconsistencies due to sunlight. Motion blur can occur due to vehicle movement and vibrations from ground terrain. A camera system with active lighting can be a solution to overcome these challenges. In this study, the usage of over-current driven LEDs to produce a powerful flash was investigated as a viable light source for daytime imaging. The current drawn by an LED was increased by a factor of six times its normal rating resulting in increased illuminance. A circuit was designed for storing and releasing energy to the LEDs for a strobe-like effect and a controller was used for synchronizing the strobe with a camera to acquire images. The system was deployed in an apple orchard on three days in summer of 2020. Images were taken throughout the day in both sunny and cloudy conditions of different canopy structures. There was substantial improvement in image brightness and colour consistency by using the LED flashes. Images captured by the prototype system during an 11-hour period showed an average decrease of 85% in standard deviation for the Hue-Saturation-Value (HSV) channels compared to that of the auto-exposure setting. Additionally, the prototype system was able to fix motion blur in images averaging 7 mm in error for a stereo vision application with the camera moving at 7 km/hr. These results show that the designed LED flash system can reduce the undesirable effects of lighting variability and motion blur in images stemming from outdoor field conditions.

Button mushrooms (Agaricus bisporus) are picked by hand individually, which is time consuming and labor intensive. Robotic harvesting is an alternative method to address this issue. Picking force and motion are critical for developing an effective robotic mushroom picking end-effector. Mushrooms are typically growing in a cluster. Conventional manual mushroom picking comprises a combination motion of twisting, bending, and lifting. To find an effective and simple picking method for robotic harvesting, a series of tests were conducted to compare the picking force and motion among the conventional method and three simplified methods, i.e., bending, twisting, and lifting. A sensor system was developed to measure the picking force and motion with three force sensors and an inertial measurement unit (IMU). The results showed that the conventional picking method required the most orientation changes to detach a mushroom, which could generate complexity for designing a robotic end-effector with the equivalent dexterity. The bending method was simple and effective with the least force compared to the other three methods, with the operation time, detachment angle, and peak force of 0.9 ± 0.5 s,13.6 ± 6.7°, and 3.3 ± 2.4 N respectively. A vacuum picking end-effector was then designed and evaluated with the three simplified methods. The results of picking end-effector evaluation also indicated that the bending motion achieved the best performance, with the picking rate of 100% for these target mushrooms, especially for the clustered ones. The developed picking end-effector can be further improved for an automatic mushroom picking system in the future.

An unmanned ground-based canopy density measurement system to support precision spraying in apple orchards was developed to precisely apply pesticides to orchard canopies. The automated measurement system was comprised of a light detection and ranging (LiDAR) sensor, an interface box for data transmission, and a laptop computer. A data processing and analysis algorithm was developed to measure point cloud indices from the LiDAR sensor to describe the distribution of tree canopy density within four sections according to the position of the trellis wires. Experiments were conducted in two orchard sites, one with GoldRush (larger trees) and the other one with Fuji (smaller trees) apple trees. Tree leaves were counted manually from each section separated by trellis wires. Field evaluation results showed a strong correlation of 0.95 (R2 = 89.30%) between point cloud data and number of leaves for the Fuji block and a correlation of 0.82 (R2 = 67.16%) was obtained for the GoldRush block. A strong correlation of 0.98 (R2 = 95.90%) was achieved in the relationship between canopy volume and number of leaves. Finally, a canopy density map was generated to provide a graphical view of the tree canopy density in different sections. Since accurate canopy density information was computed, it is anticipated that the developed prototype system can guide the sprayer unit for reducing excessive pesticide use in orchards.

BACKGROUND/OBJECTIVES This study analyzed the quality of lunches provided in senior leisure service (SLS) facilities and compared institutional foodservice (IF) and non-institutional foodservice (non-IF). SUBJECTS/METHODS Data of 390 adults aged 65 years or older who ate lunches in SLS facilities were analyzed using the information from the 2013–2017 Korea National Health and Nutrition Examination Survey. The participants were classified into IF (n = 129) and non-IF (n = 261) groups according to meal type provided. The intake of major food groups, energy and nutrients, and nutrient adequacy ratio (NAR) and mean adequacy ratio (MAR) were analyzed. The diversity of meals was evaluated by food group patterns, dietary diversity score (DDS) and dietary variety score (DVS). Energy intake was adjusted in model 1, while energy and sex were adjusted in model 2. All confounding variables were adjusted in model 3. RESULTS The intake of seafoods (P < 0.001 in models 1, 2, and 3), seaweeds (P < 0.01 in models 1 and 2), and dairy products (P < 0.05 in models 1, 2, and 3) was significantly higher in the IF group. No significant difference existed in energy intake; however, the intake of all nutrients except carbohydrate and vitamin C was significantly higher in the IF group. NAR of all nutrients, excluding vitamin C, was higher in the IF group, and MAR was also higher in the IF group (P < 0.001 in models 1, 2, and 3). The IF group had significantly higher DDS and DVS than the non-IF group (P < 0.001). CONCLUSIONS The lunches provided in SLS facilities were better in terms of quantity and quality when provided through IF than through non-IF. More systematic foodservice programs should be implemented in SLS facilities, especially in facilities wherein users prepare their own meals.

BACKGROUND The colitis-associated cancer exhibits different characteristics according to sex in the initiation and progression of the tumors. The aim of this study was to investigate the sex-associated difference in the azoxymethane/dextran sulfate sodium (AOM/DSS)-induced colitis-associated cancer model. METHODS The AOM/DSS ICR mouse model was established to compare male with female, and then the severity of colitis-associated carcinogenesis was examined macroscopically and histologically regarding the number, size, and location of tumors. Subsequently, levels of colonic mucosal cytokine, interleukin (IL)-1β and myeloperoxidase (MPO) were assessed. RESULTS At the 16th week, the tumor multiplicity and the pro-inflammatory factors differed according to sex. The total tumor number was significantly higher in male (P = 0.020) and the number of large tumors (diameter > 2 mm) was higher in male (P = 0.026). In male, the tumors located more in distal colon (P = 0.001). MPO was significantly higher in AOM/DSS-treated male mice compared to the control group (P = 0.003), whereas the corresponding female group showed no significant change (P = 0.086). Colonic IL-1β level significantly increased in AOM/DSS groups compared to control groups both in male and female (male, P = 0.014; female, P = 0.005). It was higher in male group; however, there was no statistical significance (P = 0.226). CONCLUSIONS In AOM/DSS murine model, colitis-associated colon tumorigenesis are induced more severely in male mice than female probably by way of inflammatory mediators such as IL-1β and MPO. The sex-related differences at the animal model of colon cancer suggest the importance of approach to disease with sex-specific medicine in human.

BACKGROUND The aim of this study was to investigate the effect of N-methyl-N-nitrosourea (MNU) treatment followed by chronic Helicobacter pylori SS1 and H. felis colonization on the stomachs of C57BL/6 mice. The role of MNU and Helicobacter species in gastric carcinogenesis was also elucidated. METHODS A total of 69 C57BL/6 mice at 4 weeks of age were divided into 6 groups according to MNU treatment and H. pylori SS1 or H. felis infection. The mice were sacrificed at 21 and 50 weeks. The degree of inflammation was determined by histopathology. The levels of gastric mucosal myeloperoxidase, TNF-α, and interleukin-1β (IL-1β) were measured by ELISA. RESULTS In the H. felis groups with or without MNU, the incidence of gastric tumors was 21.1% and 35.0% at 21 and 50 weeks, respectively. No gastric tumors were observed in all control mice. At 50 weeks, 37.5% of gastric adenoma cases were observed in the H. felis alone and MNU + H. felis groups. Furthermore, 12.5% of gastric adenocarcinoma cases were observed in the MNU alone and MNU + H. felis groups. The gastric mucosal IL-1β level was significantly higher in the MNU + H. felis group at 21 weeks and H. felis group at 50 weeks, respectively, than that for control mice (P < 0.05). However, the effect of MNU on H. pylori SS1-induced gastric carcinogenesis was low compared to that on H. felis. CONCLUSIONS Administration of MNU before H. felis infection provokes severe inflammation through IL-1β, and eventually induces gastric cancer. However, the role of MNU in H. pylori SS1-induced gastric carcinogenesis model is minor.

An image brightness enhancement algorithm for outdoor images was proposed.Images had constant brightness after enhancement regardless of the original brightness.Applied canny edge density was proposed to choose the best citrus-containing circle.The detection algorithm showed different performances depending on size of sub-image.Highest performance was 89.6% for correct identification and 5.0% for false positive. The devastating disease Huanglongbing (HLB) has greatly affected citrus in Florida and other growing regions. Detecting dropped fruit is one method of estimating the presence and severity of the disease. The purpose of this study was to develop a machine vision system that can detect dropped citrus on the ground in varying illumination conditions and identify decaying stages of the dropped fruit. In this paper, a novel method for image brightness correction using a contrast limited adaptive histogram equalization was developed to produce constant image brightness levels between and within images. Objectives of this study were to: (1) solve the varying illumination problem and create a consistent brightness level between and within the images, (2) develop an algorithm to eliminate multiple detections of a single fruit from the circular Hough transform, (3) design an algorithm to evaluate decaying stages of the dropped citrus, and (4) demonstrate ability to create a fruit drop map of citrus at each decaying stage in a commercial citrus grove. The result shows all processed images had desired brightness levels (152 out of 255) with a standard deviation of 1.0. Correct identification of fruit and false positives were measured as 89.6% and 5.0%, respectively. False classifications of decay stages of fruit were as low as 4.2% and 18.5% for recently dropped fruit and rotten fruit, respectively. The techniques developed in this work could be further developed into a commercial machine vision system for a real-time dropped fruit mapping system.