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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.

Robotic pruning is a potential solution to address the issues of labor shortages and high associated costs, but it has challenges due to the unstructured working environment. For successful robotic pruning, target branches have to be reached with fewer spatial requirements for the end-effector cutter and the manipulator. A three-rotational (3R) degrees of freedom (DoF) end-effector was designed considering maneuvering, spatial, mechanical, and horticultural requirements. Simulations were conducted with the end-effector to investigate the reachable workspace, the cutter frame orientation, and the manipulability index. The simulation results suggested that the proposed design has a spherical reachable workspace with a void due to the presence of a physical constraint of the linear arm. The manipulability index was determined to be independent of the rotation of the first and last joint of the end-effector. The prototype of the proposed end-effector was integrated with a cartesian manipulator. An Arduino-based control system was developed along utilizing a Matlab graphical user interface (GUI). A series of field tests were conducted on ‘Fuji’/Bud. 9 apple trees with trellis-trained architecture. The field tests validated the simulation results, and the end-effector successfully cut branches up to ~25 mm diameter at wide range of orientations. This study provides the foundation for future investigations of branch accessibility for pruning with an integrated 3R end-effector and a cartesian manipulator system following a collision free trajectory.

The overall goal of this study was to develop a machine vision system to quantify dropped citrus fruits on the ground. Specific objectives were: (1) to build a machine vision system suitable for citrus grove field conditions, (2) to develop an image enhancement algorithm for varying illumination conditions, and (3) to develop an image processing algorithm to estimate citrus fruit drop count and mass. The image processing algorithm consisted of (1) illumination enhancement using a retinex algorithm, (2) classification, (3) segmentation using a watershed algorithm with h-minima transform, and (4) ellipse fitting for mass estimation. Performances of the algorithms were evaluated in terms of correct identification and false positive errors. The average correct identification rate was 88.1%, 83.6%, and 82.9% for logistic regression, k-nearest neighbor (kNN), and Bayesian classifiers, respectively. False positive errors were 13.7%, 40.9%, and 17.9% for logistic regression, kNN, Bayesian classifiers, respectively. The results demonstrate the system‘s ability to quantify dropped fruits with specific geo-referenced location information. Spatially varied fruit drop maps plotted from the results can assist growers in finding problematic areas in their citrus groves more efficiently while reducing inspection and treatment costs. Such maps can also facilitate treatment of citrus Huanglongbing (HLB) disease in combination with HLB intensity data, psyllid counts, fertilization programs, and other block-specific management practices.

The colonic response to stress is greater in female rats than in male rats. The aim of this study was to evaluate the effect of probiotics in the repeated water avoidance stress (rWAS)-induced colonic microinflammation model of Wistar rats in a sex-specific manner. The three groups (no-stress, WAS, and WAS with probiotics) were exposed to r-WAS for 1 h daily for 10 days, and Lactobacillus farciminis was administered by oral gavage for 10 days to animals in the probiotics group. The visceromotor response (VMR) to colorectal distension (CRD) was assessed using a barostat and noninvasive manometry before and after WAS exposure. Immunohistochemistry for mast cells and real-time polymerase chain reaction (RT-PCR) for detection of mucosal cytokines were performed using distal colon tissue after the animals were sacrificed. Significant reduction of VMR to CRD (visceral analgesia) was observed at 60 mmHg in the female WAS group (P = 0.045), but not in males. In addition, the female WAS with probiotics group showed a significantly lower colonic mucosal mast cell count in comparison to the female WAS group (P = 0.013), but this phenomenon was not observed in the male group. The colonic mucosal mRNA levels of interferon-γ (IFNR), tumor necrosis factor-α (TNFA), interleukin (IL) 6, and IL17 were higher in the female WAS group than in the male WAS group. The mRNA levels of IFNR, TNFA, and IL6 were significantly decreased in WAS females who received probiotics (all P < 0.050). In conclusion, rWAS is induced in a sex-specific manner. A 10-day-long treatment with L. farciminis is an effective therapy for rWAS-induced colonic microinflammation in female rates, but not in male rats.

Yield forecasting is important for farm management. In this study, red, green, and blue (RGB), near-infrared (NIR), and depth sensors were implemented in an outdoor machine vision system to determine the number of immature citrus in tree canopies in a citrus grove. The main objective was to compare the performances of three image data types for citrus yield forecasting. The performance comparison was conducted with two machine vision algorithm steps: 1) circular object detection for potential fruit areas and 2) classification of citrus fruit from the background. For circular object detection, circular Hough transform was used in the RGB and NIR images. For the depth images, CHOI‘s Circle Estimation (‘CHOICE‘) algorithm was developed using depth divergence and vorticity to find circular objects in the depth images. The classification process was conducted using AlexNet, a deep learning algorithm for all three image types. The implementation of a convolutional neural network allowed the machine vision algorithms to remain bias-free process during feature generation and selection. NIR images performed best with 96% true positive rate for both the circular object detection and classification. A machine vision system using this image type will produce a more objective yield prediction with a higher accuracy than other types.

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.

본 연구는 경기도 소재 초등돌봄교실의 돌봄전담사를 대상으로 집단면담조사 및 설문조사를 실시하여 도시와 농촌의 급 · 간식관리 현황을 비교 분석하였으며, 그 결과를 요약하면 다음과 같다. 첫째, 돌봄전담사 7명을 대상으로 한 집단면담조사 결과, 관련 지침이나 전문가의 도움 없이 돌봄전담사가 급 · 간식 운영을 전담하고 있었으며, 예산 부족으로 인한 질적 저하가 문제점으로 나타났다. 또한 초등돌봄교실의 급 · 간식을 공동관리할 수 있는 전문기관의 필요성이 도출되었다. 둘째, 돌봄전담사 101명을 대상으로 한 설문조사 결과, 학기 중 간식비는 평균 1,463원, 방학 중 급식비는 평균 4,062원이었으며, 학기 중 간식비 (p = 0.015)와 방학 중 급식비 (p = 0.039)는 농촌이 도시보다 유의적으로 적었다. 학기 중, 방학 중 급 · 간식 모두 완제품을 구매해서 제공하는 학교가 가장 많았으며 도시와 농촌 간 차이는 없었다. 셋째, 급식 영양관리기준이 있는 학교는 10% 미만에 불과하였다. 급식식단을 별도로 작성하고 있는 학교는 101개교 중 47개교였으며, 이 중 30개교 (63.8%)는 도시락공급업체로부터 식단을 제공받고 있었고, 17개 (19.3%)에서는 돌봄전담사가 식단을 작성하고 있었다. 간식식단을 작성하는 학교는 80개교로, 이 중 45개교 (44.6%)에서는 돌봄전담사가 식단을 작성하고 있었다. 농촌은 도시에 비해 돌봄전담사가 급식식단을 작성하는 비율이 높은 경향이 있었다 (p = 0.054). 넷째, 위생관리 기준이 있는 학교는 101개교 중 34개교(33.7%)에 불과하였으며, 31개교는 급 · 간식 제공 전 검식을 하지 않고 있었고 정기적인 건강검진을 하지 않는 돌봄전담사도 56.4%에 달했다. 급 · 간식 위생관리 현황은 지역에 따른 차이가 나타나지 않았다. 다섯째, 돌봄전담사가 응답한 적정 1회 간식비는 1,924원으로 실제 간식비보다 높아 적정 간식비에 대한 검토가 필요해 보였다. 바람직한 급 · 간식의 운영형태에 대한 의견에서는 초등돌봄교실 전문 급 · 간식지원센터 설치가 바람직하다는 응답이 48개교로 가장 많았다. 본 연구결과, 초등돌봄교실의 급 · 간식 운영에서는 지역구분과 관계없이 식단관리 및 위생관리 등에서 문제점이 나타났다. 초등돌봄교실에 참여하는 어린이들에게 위생적이며 영양이 풍부한 급 · 간식을 제공하기 위해서는 돌봄전담사가 식단작성 등 관련 업무를 담당하고 있는 현실을 고려하여 현장에서 효율적으로 활용할 수 있는 구체적인 급 · 간식 운영지침 마련이 시급하며, 돌봄전담사를 대상으로 한 영양 · 위생 교육 프로그램 개발이 필요하다. 또한 초등돌봄교실 급 · 간식 권장패턴 및 참고식단 개발이 필요하며, 정부 차원의 효율적인 제도 마련과 지원이 요구된다. 특히 농촌은 도시에 비해 급 · 간식의 단가가 낮고 돌봄전담사가 식단을 작성하는 경우가 많아 급 · 간식 단가의 상승을 우선적으로 고려할 필요가 있으며, 체계적인 급 · 간식 관리를 위한 제도 도입이 선행되어야 할 것이다.

A machine vision system for estimating number of citrus fruit drop was developed in this study. The objectives of this study were to design rugged hardware, to develop an image processing algorithm for accurate estimation of fruit count and to conduct field experiments. Image acquisition hardware was developed to be used in a commercial citrus grove specifically for unfavorable imaging conditions. The image processing algorithm included normalization of intensity, citrus fruit detection by a logistic classifier, and least square circle fitting. Accuracy of the algorithm was analyzed using two different methods. Firstly, the ability of detecting citrus fruit by the algorithm without any missed fruit was analyzed. The accuracy varied within three trials, and the highest was 89.5 percent. The second analysis was for the ability to avoid false positives which represent incorrect detection of the background object as a citrus. The percentage of false positive detection also varied between the trials. The highest error was 16.2 percent and the lowest error was 9.8 percent. Result of the experiments showed that each trial had different number and mass of citrus fruit drop. This was because each area in the images had different site-specific variable factors such as nutrient level, soil pH, disease, canopy size etc. The machine vision algorithm can be modified for more advanced application such as immature citrus fruit drop detection and counting during mechanical harvesting and early yield estimation.