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Plant architecture is an important determinant of the canopy light interception and photosynthesis. Therefore, effective and nondestructive methods for obtaining plant architecture can help us understand the relationships between plant physiological processes and morphogenesis. Digital camera technology has become relatively ubiquitous and inexpensive, leading to a recent surge in utilizing plant imaging to capture data. Therefore, a three-dimensional (3-D) reconstruction of plant architecture based on these photographed image sequences can be realized. However, the accuracy evaluation of reconstruction is always determined from visual effect and or from 1-D or 2-D measured data. In this study, image sequences were obtained around experimental plants (e.g. egg plant, sweet pepper and cucumber) by slightly moving a commercial camera for image generation so that each neighboring image pair shared short baseline. Structure from motion (SFM) method was applied to produce a set of sparse point cloud based on plant image sequences. As the sparse point cloud was inadequate for the reconstruction of complicated plant architecture, multiple-view stereo (MVS) method was further used to produce dense and accurate point cloud based on the output of SFM. Software Bundler and CMVS were applied to implement the SFM and MVS methods, respectively. Bundler takes a set of images as input, and produces a 3D reconstruction of sparse scene geometry and camera parameters as output. CMVS takes a set of images and camera parameters (the output of Bundler) as input, and outputs a set of dense points with geometry details. Once original point cloud has been obtained, point cloud processing procedures were conducted to refine point cloud, including deleting noise points and scaling to the actual size of experimental plants. In order to obtain point cloud of individual blade, segmentation of point cloud of plants was conducted based on region growing segmentation algorithm. Once point cloud of individual blade was obtained, Poisson surface reconstruction algorithm was used to reconstruct each leaf. Before accuracy evaluation, point cloud of individual leaf blade and corresponding laser scanning point cloud were aligned to the same 3-D coordinate system using the Iterative Closest Point algorithm. Then, comparison on 3-D scale based on Hausdorff distance was made between point cloud data obtained from plant image sequences and referenced point cloud data with laser scanning on individual leaf blade level. Furthermore, phenotypic attributes, such as leaf blade width, leaf blade length and blade area were extracted based on data from image sequences and from laser scanning methods. Besides, these attributes of each blade were manually measured. Finally, comparisons were made for blade area, blade length and blade maximum width between data from the image sequence-based model, laser scanning based model and manually measured data. The results showed that high accuracy of 3-D reconstruction was obtained based on plant image sequence method. Hausdorff distances of experimental plants were ranged from 0 to 10 mm, and most of the values were less than 4.0 mm. There was a good agreement between measured and calculated blade area, blade length and maximum width with R² > 0.95 for blade area, RMSE < 4.5 mm for blade width, and RMSE < 5.6 mm for blade length. There was no significant difference for each attribute between measured and calculated data (ANOVA, P > 0.05). A key advance of the current 3-D reconstruction of plant architecture is the capability to non-destructively capture plant traits with high accuracy. This advance permits time-series measurements that are necessary to follow the progression of growth and stress on individual plants, and will play an important role in related research fields, such as plant phenotyping, genetic breeding, interactions between plant phenotype and environment. [ABSTRACT FROM AUTHOR]

The spatial distribution of solar radiation casts important influences on eco-physiological functions of plant canopies. A simulation model of the three-dimensional (3D) effect of direct and indirect solar radiation in real maize canopies is developed from measured 3D canopy structure meshes. The model includes two procedures: parallel direct light pass and diffusive indirect radiation pass. The former one is based on the Monte Carlo ray tracing algorithm. After enough ray casting, the radiation is obtained. Then, the diffusive indirect radiation pass uses a modified Monte Carlo radiosity model to evaluate the diffusion distribution. Results indicate that simulated sun fleck ratio is significantly consistent with the measured dataset. [ABSTRACT FROM AUTHOR]

The measurement of organ-scale traits in large-scale fields remains a bottleneck in genotype-phenotype association studies for crop improvement. To address this issue, an advanced cross-circling oblique (CCO) route was proposed, consisting of multiple single-circle routes. Using multi-view images from lightweight UAVs with the CCO route, 3D crop canopies were reconstructed for maize, cotton, and sugar beet. Organ-scale traits were estimated from the CCO-derived and traditional five-directional oblique (FDO)-derived 3D canopy models and were compared to manual measurements. An algorithm was further proposed to compare the image utilisation efficiency between the CCO route and FDO route with three indicators, including the total utilisation (TU), effective utilisation (EU), and occlusion rate (OR). The results showed that the proposed CCO route can obtain complete canopy structures throughout the growth stages for crops with relatively wide-row planting, such as maize. For densely planted crops like cotton, the full canopy structure at early growth stages (47 d after sowing (DAS)) and the upper parts of the canopy architecture at later growth stages (71 and 90 DAS) could be obtained. The leaf length and width from different layers estimated from CCO-derived models were in good agreement with manual measurements for maize (R2 = 0.93, RMSE = 3.05 cm, nRMSE = 4.7% and R2 = 0.88, RMSE = 0.49 cm, nRMSE = 5.5% for leaf length and leaf width, respectively) and cotton (R2 = 0.81, RMSE = 1.16 cm, nRMSE = 8.6% and R2 = 0.93, RMSE = 0.99 cm, nRMSE = 7.2% for leaf length and leaf width, respectively). CCO-derived 3D canopy models also provided higher accuracy for organ-scale trait estimation than FDO-derived 3D canopy models (R2 of 0.80 versus 0.76 for both leaf length and width estimation, respectively). Regarding image utilisation, the CCO route outperformed the FDO route, with an average value of 124% higher in EU and 11.7% lower in OR, tested on sugar beet varieties with different canopy structures. The proposed CCO route adopts a non-linear mobile route to obtain canopy images from more perspectives, taking into account both the model accuracy and efficiency. Although the flight altitude of the CCO in this study was relatively low (4 m above the canopy), the same model accuracy can be achieved at higher flight altitudes using a higher-quality camera, thus significantly reducing image acquisition time. This study represents the first time that accurate crop structures in large-scale fields were characterised using a method featuring mobility, affordability, throughput, accuracy, and efficiency. The proposed method could provide novel opportunities for accelerating plant breeding and precision agriculture. [ABSTRACT FROM AUTHOR]

Accurate and real-time field wheat ear counting is of great significance for wheat yield prediction, genetic breeding and optimized planting management. In order to realize wheat ear detection and counting under the large-resolution Unmanned Aerial Vehicle (UAV) video, Space to depth (SPD) module was added to the deep learning model YOLOv7x. The Normalized Gaussian Wasserstein Distance (NWD) Loss function is designed to create a new detection model YOLOv7xSPD. The precision, recall, F1 score and AP of the model on the test set are 95.85%, 94.71%, 95.28%, and 94.99%, respectively. The AP value is 1.67% higher than that of YOLOv7x, and 10.41%, 39.32%, 2.96%, and 0.22% higher than that of Faster RCNN, SSD, YOLOv5s, and YOLOv7. YOLOv7xSPD is combined with the Kalman filter tracking and the Hungarian matching algorithm to establish a wheat ear counting model with the video flow, called YOLOv7xSPD Counter, which can realize real-time counting of wheat ears in the field. In the video with a resolution of 3840×2160, the detection frame rate of YOLOv7xSPD Counter is about 5.5FPS. The counting results are highly correlated with the ground truth number (R 2 =  0.99), and can provide model basis for wheat yield prediction, genetic breeding and optimized planting management., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The Reviewer LZ declared a shared affiliation with the authors GS, SF, YM to the handling editor at the time of review., (Copyright © 2024 Xu, Zhou, Yu, Sun, Fei, Zhu and Ma.)

Weeds can compete with crops for sunlight, water, space and various nutrients, which can affect the growth of crops.In recent years, people have started to use self-driving agricultural equipment, robots, etc. for weeding work and use of drones for weed identification and spraying of weeds with herbicides, and the effectiveness of these mobile weeding devices is largely limited by the superiority of weed detection capability. To improve the weed detection capability of mobile weed control devices, this paper proposes a lightweight weed segmentation network model DCSAnet that can be better applied to mobile weed control devices. The whole network model uses an encoder-decoder structure and the DCA module as the main feature extraction module. The main body of the DCA module is based on the reverse residual structure of MobileNetV3, effectively combines asymmetric convolution and depthwise separable convolution, and uses a channel shuffle strategy to increase the randomness of feature extraction. In the decoding stage, feature fusion utilizes the high-dimensional feature map to guide the aggregation of low-dimensional feature maps to reduce feature loss during fusion and increase the accuracy of the model. To validate the performance of this network model on the weed segmentation task, we collected a soybean field weed dataset containing a large number of weeds and crops and used this dataset to conduct an experimental study of DCSAnet. The results showed that our proposed DCSAnet achieves an MIoU of 85.95% with a model parameter number of 0.57 M and the highest segmentation accuracy in comparison with other lightweight networks, which demonstrates the effectiveness of the model for the weed segmentation task., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Yu, Che, Yu and Ma.)

The taxane class of microtubule stabilizers are some of the most effective and widely used chemotherapeutics. The anticancer activity of taxanes arises from their ability to induce tubulin assembly by selectively recognizing the curved (c-) conformation in unassembled tubulin as compared to the straight (s-) conformation in assembled tubulin. We first designed and synthesized a series of 3'N-modified taxanes bearing covalent groups. Instead of discovering covalent taxanes, we found a series of non-covalent taxanes 2, in which the 3'N side chain was found to be essential for cytotoxicity due to its role in locking tubulin in the s-conformation. A representative compound bearing an acrylamide moiety (2h) exhibited increased binding affinity to the unassembled tubulin c-conformation and less cytotoxicity than paclitaxel. Further exploration of chemical space around 2h afforded a new series 3, in which derivatives such as 3l bind more tightly to both the s- and c-conformations of tubulin compared to paclitaxel, leading to more efficient promotion of tubulin polymerization and a greater persistence of in vitro efficacy against breast cancer cells after drug washout. Although 3l also had improved in vivo potency as compared to paclitaxel, it was also associated with increased systemic toxicity that required localized, intratumoral injection to observe potent and prolonged antitumor efficacy., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Masson SAS. All rights reserved.)

Automated organ segmentation in anatomical sectional images of canines is crucial for clinical applications and the study of sectional anatomy. The manual delineation of organ boundaries by experts is a time-consuming and laborious task. However, semi-automatic segmentation methods have shown low segmentation accuracy. Deep learning-based CNN models lack the ability to establish long-range dependencies, leading to limited segmentation performance. Although Transformer-based models excel at establishing long-range dependencies, they face a limitation in capturing local detail information. To address these challenges, we propose a novel ECA-TFUnet model for organ segmentation in anatomical sectional images of canines. ECA-TFUnet model is a U-shaped CNN-Transformer network with Efficient Channel Attention, which fully combines the strengths of the Unet network and Transformer block. Specifically, The U-Net network is excellent at capturing detailed local information. The Transformer block is equipped in the first skip connection layer of the Unet network to effectively learn the global dependencies of different regions, which improves the representation ability of the model. Additionally, the Efficient Channel Attention Block is introduced to the Unet network to focus on more important channel information, further improving the robustness of the model. Furthermore, the mixed loss strategy is incorporated to alleviate the problem of class imbalance. Experimental results showed that the ECA-TFUnet model yielded 92.63% IoU, outperforming 11 state-of-the-art methods. To comprehensively evaluate the model performance, we also conducted experiments on a public dataset, which achieved 87.93% IoU, still superior to 11 state-of-the-art methods. Finally, we explored the use of a transfer learning strategy to provide good initialization parameters for the ECA-TFUnet model. We demonstrated that the ECA-TFUnet model exhibits superior segmentation performance on anatomical sectional images of canines, which has the potential for application in medical clinical diagnosis.

Objectives: This study aimed to perform a multicenter comparison between robotic pancreaticoduodenectomy (RPD) and open pancreaticoduodenectomy (OPD)., Background: Previous comparisons of RPD versus OPD have only been carried out in small, single-center studies of variable quality., Methods: Consecutive patients who underwent RPD (n = 1032) or OPD (n = 1154) at 7 centers in China between July 2012 and July 2020 were included. A 1:1 propensity score matching (PSM) was performed., Results: After PSM, 982 patients in each group were enrolled. The RPD group had significantly lower estimated blood loss (EBL) (190.0 vs 260.0 mL; P < 0.001), and a shorter postoperative 1length of hospital stay (LOS) (12.0 (9.0-16.0) days vs 14.5 (11.0-19.0) days; P < 0.001) than the OPD group. There were no significant differences in operative time, major morbidity including clinically relevant postoperative pancreatic fistula (CR-POPF), bile leakage, delayed gastric emptying, postoperative pancreatectomy hemorrhage (PPH), reoperation, readmission or 90-day mortality rates. Multivariable analysis showed R0 resection, CR-POPF, PPH and reoperation to be independent risk factors for 90-day mortality. Subgroup analysis on patients with pancreatic ductal adenocarcinoma (PDAC) (n = 326 in each subgroup) showed RPD had advantages over OPD in EBL and postoperative LOS. There were no significant differences in median disease-free survival (15.2 vs 14.3 months, P = 0.94) or median overall survival (24.2 vs 24.1 months, P = 0.88) between the 2 subgroups., Conclusions: RPD was comparable to OPD in feasibility and safety. For patients with PDAC, RPD resulted in similar oncologic and survival outcomes as OPD., Competing Interests: The authors report no conflicts of interest., (Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.)

Background: Crop breeding based on root system architecture (RSA) optimization is an essential factor for improving crop production in developing countries. Identification, evaluation, and selection of root traits of soil-grown crops require innovations that enable high-throughput and accurate quantification of three-dimensional (3D) RSA of crops over developmental time., Results: We proposed an automated imaging system and 3D imaging data processing pipeline to quantify the 3D RSA of soil-grown individual plants across seedlings to the mature stage. A multi-view automated imaging system composed of a rotary table and an imaging arm with 12 cameras mounted with a combination of fan-shaped and vertical distribution was developed to obtain 3D image data of roots grown on a customized root support mesh. A 3D imaging data processing pipeline was developed to quantify the 3D RSA based on the point cloud generated from multi-view images. The global architecture of root systems can be quantified automatically. Detailed analysis of the reconstructed 3D root model also allowed us to investigate the Spatio-temporal distribution of roots. A method combining horizontal slicing and iterative erosion and dilation was developed to automatically segment different root types, and identify local root traits (e.g., length, diameter of the main root, and length, diameter, initial angle, and the number of nodal roots or lateral roots). One maize (Zea mays L.) cultivar and two rapeseed (Brassica napus L.) cultivars at different growth stages were selected to test the performance of the automated imaging system and 3D imaging data processing pipeline., Conclusions: The results demonstrated the capabilities of the proposed imaging and analytical system for high-throughput phenotyping of root traits for both monocotyledons and dicotyledons across growth stages. The proposed system offers a potential tool to further explore the 3D RSA for improving root traits and agronomic qualities of crops., (© 2023. The Author(s).)

Early prediction of grain yield helps scientists to make better breeding decisions for wheat. Use of machine learning (ML) methods for fusion of unmanned aerial vehicle (UAV)-based multi-sensor data can improve the prediction accuracy of crop yield. For this, five ML algorithms including Cubist, support vector machine (SVM), deep neural network (DNN), ridge regression (RR) and random forest (RF) were used for multi-sensor data fusion and ensemble learning for grain yield prediction in wheat. A set of thirty wheat cultivars and breeding lines were grown under three irrigation treatments i.e., light, moderate and high irrigation treatments to evaluate the yield prediction capabilities of a low-cost multi-sensor (RGB, multi-spectral and thermal infrared) UAV platform. Multi-sensor data fusion-based yield prediction showed higher accuracy compared to individual-sensor data in each ML model. The coefficient of determination ( R 2 ) values for Cubist, SVM, DNN and RR models regarding grain yield prediction were observed from 0.527 to 0.670. Moreover, the results of ensemble learning through integrating the above models illustrated further increase in accuracy. The predictions of ensemble learning showed high R 2 values up to 0.692, which was higher as compared to individual ML models across the multi-sensor data. Root mean square error (RMSE), residual prediction deviation (RPD) and ratio of prediction performance to inter-quartile range (RPIQ) were calculated to be 0.916 t ha -1 , 1.771 and 2.602, respectively. The results proved that low altitude UAV-based multi-sensor data can be used for early grain yield prediction using data fusion and an ensemble learning framework with high accuracy. This high-throughput phenotyping approach is valuable for improving the efficiency of selection in large breeding activities., Supplementary Information: The online version contains supplementary material available at 10.1007/s11119-022-09938-8., Competing Interests: Conflict of interestThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022.)

Background: CENPK is a novel oncogene which is aberrantly expression in some malignant tumors. However, the role and mechanisms of CENPK in gastric cancer have not been explored., Methods: In this study, we use RT-PCR and IHC to study CENPK expression in gastric cancer cells and tissues. In addition, we constructed the two kinds of CENPK siRNA lentivirus to knock down CENPK. Then, we use High content living cell imaging System, Cell Counting Kit-8, colony formation, wound healing and Transwell assays to demonstrate the function of CENPK on gastric cancer cells AGS and MKN45. Meanwhile, we use flow cytometry assay to study CENPK function on gastric cancer cell apoptosis and cell cycle arrest. Subcutaneous tumorigenesis in nude mice was also performed to confirm CENPK function on gastric cancer. Finally, we use Co-IP, LC-MS and function rescue assay to study the downstream interaction molecular of CENPK., Results: We demonstrated that CENPK expression were up-regulated in GC cell lines. Poor differentiation and III-IV stage had more percentages of high CENPK expression. Knocking down CENPK could significantly suppress GC cells proliferation, migration and invasion, and induce GC cells apoptosis and G1/S phase transition arrest. Subcutaneous tumorigenesis confirmed the tumor-promoting effects of CENPK in vivo. Remarkably, we found for the first time that XRCC5 might be interacted with CENPK through Co-IP, LC-MS and rescue study., Conclusion: CENPK promotes GC cell proliferation and migration via interacting with XRCC5 and may be a novel prognostic factor or therapeutic target for CENPK., (© 2022. The Author(s) under exclusive licence to The International Gastric Cancer Association and The Japanese Gastric Cancer Association.)

Background: With the advances in surgical techniques and perioperative management, the surgical indications for pancreaticoduodenectomy have been extended to elderly patients. Whether robotic pancreaticoduodenectomy (RPD) is superior to open pancreaticoduodenectomy (OPD) in older patients remains uncertain. Thus, this study aimed to compare perioperative outcomes between RPD and OPD in elderly patients., Methods: The demographics and perioperative outcomes of a consecutive series of elderly patients (aged ≥75 years) who underwent RPD or OPD at seven pancreatic centers in China between July 2011 and July 2020 were retrospectively analyzed., Results: Of the 302 patients included in this study, 169 underwent RPD and 133 underwent OPD. The RPD group had a shorter operative time (OT) (264.3 vs. 278.2 min, P = 0.01) and less estimated blood loss (EBL) (100 (50 150) vs. 200 (150 300) mL, P < 0.001) than the OPD group. RPDs in 3 (1.8%) patients were converted to OPD. The postoperative length of stay (LOS) after RPD was significantly shorter than that after OPD (13.0 vs. 17.0 days, P < 0.001). No significant differences were found in the rates of clinically relevant postoperative pancreatic fistula, bile leakage, delayed gastric emptying, postoperative pancreatectomy hemorrhage, major morbidity, reoperation, 90-day readmission, or 90-day mortality between the two groups (P > 0.05). The multivariate logistic regression analysis revealed that type 2 diabetes, chronic obstructive pulmonary disease, postoperative hemorrhage, and cardiac events were independent risk factors for postoperative 90-day mortality., Conclusions: This study demonstrated that RPD was comparable to OPD in terms of safety and feasibility in elderly patients with shorter OT, lower EBL, and shorter postoperative LOS. Surgical approach was not an independent risk factor for 90-day mortality., (Copyright © 2022 IJS Publishing Group Ltd. Published by Elsevier Ltd. All rights reserved.)

Chemotherapy-induced intestinal mucositis (CIM) is a common adverse reaction to antineoplastic treatment with few appropriate, specific interventions. We aimed to identify the role of the G protein coupled estrogen receptor (GPER) in CIM and its mechanism. Adult male C57BL/6 mice were intraperitoneally injected with 5-fluorouracil to establish the CIM model. The selective GPER agonist G-1 significantly inhibited weight loss and histological damage in CIM mice and restored mucosal barrier dysfunction, including improving the expression of ZO-1, increasing the number of goblet cells, and decreasing mucosal permeability. Moreover, G-1 treatment did not alter the antitumor effect of 5-fluorouracil. In the CIM model, G-1 therapy reduced the expression of proapoptotic protein and cyclin D1 and cyclin B1, reversed the changes in the number of TUNEL + cells, Ki67 + and bromodeoxyuridine + cells in crypts. The selective GPER antagonist G15 eliminated all of the above effects caused by G-1 on CIM, and application of G15 alone increased the severity of CIM. GPER was predominantly expressed in ileal crypts, and G-1 inhibited the DNA damage induced by 5-fluorouracil in vivo and vitro, as confirmed by the decrease in the number of γH2AX + cells in the crypts and the comet assay results. Referring to the data from GEO dataset we verified GPER activation restored ERK1/2 activity in CIM and 5-fluorouracil-treated IEC-6 cells. Once the effects of G-1 on ERK1/2 activity were abolished with the ERK1/2 inhibitor PD0325901, the effects of G-1 on DNA damage both in vivo and in vitro were eliminated. Correspondingly, all of the manifestations of G-1 protection against CIM were inhibited by PD0325901, such as body weight and histological changes, the mucosal barrier, the apoptosis and proliferation of crypt cells. In conclusion, GPER activation prevents CIM by inhibiting crypt cell DNA damage in an ERK1/2-dependent manner, suggesting GPER might be a target preventing CIM., (© 2021. The Author(s).)

Purpose: To evaluate whether anti-vascular endothelial growth factor (VEGF) therapy combined with panretinal photocoagulation could reverse diabetic retinopathy (DR)., Method: Fifty-two patients (72 eyes) with high-risk proliferative DR who were diagnosed and treated from June 2018 to May 2019 were divided into the laser group (16 cases, 32 eyes) and combination group (36 cases, 40 eyes) according to a review of the medical records., Results: Within-group comparison: There were no significant differences in best-corrected visual acuity (BCVA), central foveal thickness (CFT), and microaneurysms in the laser group before and after treatment, but there were statistically significant improvements in the combination group. After the treatment, the BCVA of the patients in the combination group was 0.44 ± 0.17, which was significantly better than 0.70 ± 0.18 before treatment; the CFT after treatment was 266.51 ± 33.28 μm, which was significantly lower than 382.37 ± 54.03 μm at baseline; the MA after treatment was 56.12 ± 23.29, which was significantly lower than 121.44 ± 40.35. There was a statistically significant decrease in hard exudates area in both two groups before and after treatment. Comparison between groups: The difference in BCVA, CFT, MA and between the two groups was statistically significant (all P < 0.05), and the area of retinal neovascularization between the two groups was no significant difference, but decreased more rapidly in the combination group than that in the laser group., Conclusion: Using intravitreal injection of anti-VEGF drugs combined with panretinal photocoagulation to treat DR might morphologically and functionally reverse retinal changes caused by diabetes mellitus.

G protein-coupled estrogen receptor (GPER) might be involved in ulcerative colitis (UC), but the direct effect of GPER on UC is still unclear. We used male C57BL/6 mice to establish the acute colitis model with administration of dextran sulfate sodium and explored the effect of GPER on acute colitis and its possible mechanism. The selective GPER agonist G-1 inhibited weight loss and colon shortening and decreased the disease activity index for colitis and histologic damage in mice with colitis. All of these effects were prevented by a selective GPER blocker. G-1 administration prevented the dysfunction of tight junction protein expression and goblet cells in colitis model and thus inhibited the increase of mucosal permeability in colitis-suffering mice significantly. GPER activation reduced expression of glucose-regulating peptide-78 and anti-CCAAT/enhancer-binding protein homologous protein and attenuated the three arms of the unfolded protein response in colitis. G-1 therapy inhibited the increase of cleavage caspase-3- and TUNEL-positive cells in colonic crypts in the colitis model, increased the number of Ki67- and bromodeoxyuridine-positive cells in crypts, and reversed the decrease of cyclin D1 and cyclin B1 expression in colitis, indicating its protective effect on crypt cells. In cultured CCD841 cells, G-1 treatment fought against cell injury induced by endoplasmic reticulum stress. These findings demonstrate that GPER activation prevents colitis by protecting the colonic crypt cells, which are associated with inhibition of endoplasmic reticulum stress. SIGNIFICANCE STATEMENT: We demonstrate that G protein-coupled estrogen receptor (GPER) activation prevents dextran sulfate sodium-induced acute colitis by protecting the crypt cells, showing that it inhibited the crypt cell apoptosis and protected proliferation of crypt cells, which resulted in protection of the intestinal mucosal barrier. This protective effect was achieved (at least in part) by inhibiting endoplasmic reticulum stress. Mucosal healing is regarded as a key therapeutic target for colitis, and GPER is expected to become a new therapeutic target for colitis., (Copyright © 2021 by The Author(s).)

The aim of this study is to investigate the feasibility and advantages of the da Vinci robotic system with the "3 + 2" mode (3 robotic arms and 2 assistants) in radical gastrectomy for gastric cancer.The clinical data of 65 patients who underwent da Vinci robotic gastrectomy with the "3 + 2" mode from July 2016 to October 2019 were grouped into an observation group. An additional 65 patients who underwent robotic gastrectomy under the classic mode during the same period were grouped into a control group. The short-term surgical outcomes were compared between 2 different groups.Compared with the control group, the observation group had a significantly shorter operative time (176.18 ± 15.49 vs 203.85 ± 12.77 minutes, P < .001) and lower operation costs ($2761.19 ± $191.91 vs $3690.91 ± $162.82; P < .001). No statistical differences in other outcomes were observed (P > .05).We show that robotic gastrectomy with "3 + 2" mode is a safe and beneficial surgical procedure in new robotic surgery institutions.

Objective: To explore the treatment of superficial incision dehiscence after abdominal surgery by Z-plasty combined with negative-pressure wound therapy., Methods: A retrospective study was performed on seven patients with superficial abdominal incision dehiscence from October 2018 to February 2019. All patients were given systemic antibiotics and nutrition support. During the first stage, surgical debridement with negative-pressure wound therapy was performed. Local Z-plasty was performed in the second stage., Results: The incision healed well in all patients, and no infection or necrosis occurred in the flaps. During the follow-up of 7.3 months (range, 5-10 months), no incision rupture or redehiscence occurred., Conclusions: Surgical debridement, negative-pressure wound therapy, and Z-plasty can be used to treat superficial abdominal incision dehiscence and achieve good therapeutic effect and prognosis. Z-plasty can be used as an alternative to direct suture of incisions because of its simplicity and excellent results.

Objective: To test the causal effect of hip circumference adjusted for body mass index(HCadjBMI) and coronary heart disease(CHD) using a Mendelian randomization analysis., Methods: Based on genome-wide association study, the associations between the genetic instruments(IVs) and HCadjBMI were obtained from the GIANT consortium(n=211 114, European), the associations between IVs and CHD were derided from CARDIoGRAM consortium(n=86 995, European). The inverse-variance weighted method was used to estimate a pooled OR for the effect of a 1 cm higher HCadjBMI on CHD. Evidence of directional pleiotropy averaged across all variants was sought using MR-Egger regression., Results: A total of 70 genetic variants that reached genome-wide significance and independent of each other were identified as IVs. A combined genetic variants expected to confer a lifetime exposure of per SD higher HCadjBMI was associated with a lower risk of CHD(OR=0. 831, 95%CI 0. 730-0. 946). MR-Egger regression intercept suggested that directional pleiotropy was unlikely to be biasing the result(intercept-0. 0012, P=0. 875). There was no specific single nucleotide polymorphism(SNP) detected by "leave one out" analysis., Conclusion: A genetic predisposition to higher HCadjBMI was associated with lower risk of CHD.

Insulin resistance (IR) is a vital hallmark of type 2 diabetes mellitus, which is characterized by an impaired ability of insulin to promote glucose uptake and utilization. Lipid deposition is closely associated with impaired insulin sensitivity. PPAR γ plays an important role in glucose homeostasis, adipocyte differentiation, and insulin sensitivity. Likewise, DGAT2 also exerts a crucial role in integrating carbohydrate and lipid metabolism in the liver. The present study is aimed at evaluating a Chinese medicinal formula, Tangduqing granules (TDQ), with multifaceted actions against lipid and glucose metabolism disorder and IR of type 2 diabetes. An animal model of type 2 diabetes was developed by high-fat diet feeding plus low-dose streptozotocin injection. After oral administration of TDQ for 5 weeks, the effects on glucose and lipid metabolism and the underlying mechanism were evaluated by biochemical, histological, RT-PCR, and western blotting methods. The results showed that TDQ decreased fasting blood glucose, ameliorated glucose tolerance, and improved IR. Besides, TDQ regulated hyperlipidemia symptoms, decreased serum lipid levels and liver TG, and reduced hepatic steatosis in a type 2 diabetic rat model. Furthermore, TDQ reversed diabetes-induced decrease in the mRNA and protein expression of PPAR γ and elevation in the mRNA and protein levels of DGAT2 in the liver. In addition, we showed that interference of TDQ ameliorated palmitate-induced glucose and lipid metabolic abnormalities in HepG2 cells. TDQ are, therefore, a potential Chinese medicinal formula that relieves IR and lipid metabolism disorder might be through promotion of PPAR γ and decrease of DGAT2 expression.

Purpose: The main aim of the study was to evaluate in vitro and in vivo the anticancer and apoptotic effects of neochlorogenic acid in human gastric carcinoma cell death and the underlying mechanism of apoptosis induction, reactive oxygen species (ROS) production and loss of mitochondrial membrane potential (MMP), m-TOR/PI3K/AKT signalling pathway, cell migration and cell invasion suppression., Methods: Fluorescence microscopy using DAPI and annexin V/PI staining in combination with flow cytometry was used to study the apoptotic effects induced by neochlorogenic acid on gastric cancer cells. The effects on ROS and MMP were studied by flow cytometry. Western blot assay was used to evaluate the effects of neochlorogenic acid on m-TOR/PI3/Akt signaling pathway. To examine the anti-cancer activity of neochlorogenic acid in vivo, we used the nude mice xenograft model., Results: The results indicated that neochlorogenic acid exhibited an IC50 of 20 µM in these cells. The study also showed that apoptosis was due to loss of MMP and increased intracellular ROS production. Neochlorogenic acid downregulated the expression of key proteins of m-TOR/PI3/Akt signaling pathway. After 6 weeks of neochlorogenic acid administration to mice, the average tumor volumes and growth for the untreated control group were significantly higher than the treated groups., Conclusion: Based on these results, we propose that neochlorogenic acid can be a prospective anti-cancer therapeutic lead for the management of human gastric carcinoma.

Background and Aims: Failure to account for the variation of kernel growth in a cereal crop simulation model may cause serious deviations in the estimates of crop yield. The goal of this research was to revise the GREENLAB-Maize model to incorporate source- and sink-limited allocation approaches to simulate the dry matter accumulation of individual kernels of an ear (GREENLAB-Maize-Kernel)., Methods: The model used potential individual kernel growth rates to characterize the individual potential sink demand. The remobilization of non-structural carbohydrates from reserve organs to kernels was also incorporated. Two years of field experiments were conducted to determine the model parameter values and to evaluate the model using two maize hybrids with different plant densities and pollination treatments. Detailed observations were made on the dimensions and dry weights of individual kernels and other above-ground plant organs throughout the seasons., Key Results: Three basic traits characterizing an individual kernel were compared on simulated and measured individual kernels: (1) final kernel size; (2) kernel growth rate; and (3) duration of kernel filling. Simulations of individual kernel growth closely corresponded to experimental data. The model was able to reproduce the observed dry weight of plant organs well. Then, the source-sink dynamics and the remobilization of carbohydrates for kernel growth were quantified to show that remobilization processes accompanied source-sink dynamics during the kernel-filling process., Conclusions: We conclude that the model may be used to explore options for optimizing plant kernel yield by matching maize management to the environment, taking into account responses at the level of individual kernels.

Background and Aims: Global agriculture is facing the challenge of a phenotyping bottleneck due to large-scale screening/breeding experiments with improved breeds. Phenotypic analysis with high-throughput, high-accuracy and low-cost technologies has therefore become urgent. Recent advances in image-based 3D reconstruction offer the opportunity of high-throughput phenotyping. The main aim of this study was to quantify and evaluate the canopy structure of plant populations in two and three dimensions based on the multi-view stereo (MVS) approach, and to monitor plant growth and development from seedling stage to fruiting stage., Methods: Multi-view images of flat-leaf cucumber, small-leaf pepper and curly-leaf eggplant were obtained by moving a camera around the plant canopy. Three-dimensional point clouds were reconstructed from images based on the MVS approach and were then converted into surfaces with triangular facets. Phenotypic parameters, including leaf length, leaf width, leaf area, plant height and maximum canopy width, were calculated from reconstructed surfaces. Accurate evaluation in 2D and 3D for individual leaves was performed by comparing reconstructed phenotypic parameters with referenced values and by calculating the Hausdorff distance, i.e. the mean distance between two surfaces., Key Results: Our analysis demonstrates that there were good agreements in leaf parameters between referenced and estimated values. A high level of overlap was also found between surfaces of image-based reconstructions and laser scanning. Accuracy of 3D reconstruction of curly-leaf plants was relatively lower than that of flat-leaf plants. Plant height of three plants and maximum canopy width of cucumber and pepper showed an increasing trend during the 70 d after transplanting. Maximum canopy width of eggplants reached its peak at the 40th day after transplanting. The larger leaf phenotypic parameters of cucumber were mostly found at the middle-upper leaf position., Conclusions: High-accuracy 3D evaluation of reconstruction quality indicated that dynamic capture of the 3D canopy based on the MVS approach can be potentially used in 3D phenotyping for applications in breeding and field management.

In order to solve the heat transfer mechanism in radiofrequency treatment of atherosclerosis, we design two experimental structures to simulate the plaque, and use three frequencies and a variety of electrode arrangement, to study the heat transfer mechanism and heating capacity under the special structure. The results show that the temperature increment and heating area increase with increasing frequency. Under the structure in which the lipid particles are embedded in the fiber cap, using three electrodes with opposite polar arrangement between middle electrode and others, achieves effective heating to lipid pool in the plaque.

Objective: To investigate the effects of polyunsaturated fatty acids (PUFA) ω-3 and ω-6, and their middle metabolites PGE2 and PGE3 on angiogenesis formation of gastric cancer, and to explore associated mechanism., Methods: The effects of ω-3, ω-6, PGE2, PGE3 on the proliferation and migration of human umbilical vein endothelial cell (HUVEC) were measured by proliferation and migration assay respectively. The angiogenesis assay in vivo was used to measure the effects of ω-3, ω-6, PGE2 and PGE3 on neovascularization. In all the assays, groups without ω-3, ω-6, PGE2 and PGE3 were designed as the control., Results: With the increased concentration of ω-6 from 1 μmol/L to 10 μmol/L, the proliferation ability of HUVECs enhanced, and the number of migration cells also increased from 28.2±3.0 to 32.8±2.1, which was higher than control group (21.2±3.2) respectively (both P<0.05). With the increased concentration of ω-3 from 1 μmol/L to 10 μmol/L, the proliferation ability of HUVECs was inhibited, and the number of migration cells decreased from 15.8±2.0 to 11.0±2.1, which was lower than control group (22.1±3.0) respectively (both P<0.05). In the angiogenesis assay, compared with control group (standard number: 43 721±4 654), the angiogenesis ability of HUVECs was significantly enhanced by ω-6 in concentration-dependent manner (1 μmol/L group: 63 238±4 795, 10 μmol/L group: 78 166±6 123, all P<0.01). Meanwhile, with the increased concentration of ω-3 from 1 μmol/L to 10 μmol/L, the angiogenesis ability was significantly decreased from 30 129±3 102 to 20 012±1 541(all P<0.01). The proliferation and migration ability of HUVECs were significantly promoted by ω-6 metabolites PGE2 (P<0.05) in a concentration-dependent manner. In contrast, ω-3 metabolites PGE3 significantly inhibited the proliferation and migration ability of HUVECs in a concentration-dependent manner (all P<0.05). After rofecoxib (a COX-2 specific inhibitor) inhibited the expression of COX-2, the expression level of PGE2 was significantly decreased in a dose-dependent manner. In co-culture system, whose gastric cancer cells expressed positive COX-2, ω-6 could increase angiogenesis of gastric cancer cells(P<0.01), but ω-3 could inhibit such angiogenesis(P<0.01). In co-culture system, whose gastric cancer cells did not express COX-2, ω-3 could inhibit the angiogenesis of gastric cancer cells (P<0.05), but ω-6 had no effect on angiogenesis., Conclusions: The PUFA ω-6 can enhance the angiogenesis via the promotion of proliferation and migration of HUVECs, and COX-2 and PGE2 may play an important role in this process, whereas, the ω-3 can inhibit the angiogenesis through its middle metabolites PGE3 to inhibit the proliferation and migration of HUVECs. Results of this experiment may provide a new approach to inhibit and prevent the spread of gastric cancer.