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BackgroundElectronic medical records (EMRs) contain vast amounts of data that is of great interest to physicians, clinical researchers, and medial policy makers. As the size, complexity, and accessibility of EMRs grow, the ability to extract meaningful information from them has become an increasingly important problem to solve.MethodsWe develop a standardized data analysis process to support cohort study with a focus on a particular disease. We use an interactive divide-and-conquer approach to classify patients into relatively uniform within each group. It is a repetitive process enabling the user to divide the data into homogeneous subsets that can be visually examined, compared, and refined. The final visualization was driven by the transformed data, and user feedback direct to the corresponding operators which completed the repetitive process. The output results are shown in a Sankey diagram-style timeline, which is a particular kind of flow diagram for showing factors' states and transitions over time.ResultsThis paper presented a visually rich, interactive web-based application, which could enable researchers to study any cohorts over time by using EMR data. The resulting visualizations help uncover hidden information in the data, compare differences between patient groups, determine critical factors that influence a particular disease, and help direct further analyses. We introduced and demonstrated this tool by using EMRs of 14,567 Chronic Kidney Disease (CKD) patients.ConclusionsWe developed a visual mining system to support exploratory data analysis of multi-dimensional categorical EMR data. By using CKD as a model of disease, it was assembled by automated correlational analysis and human-curated visual evaluation. The visualization methods such as Sankey diagram can reveal useful knowledge about the particular disease cohort and the trajectories of the disease over time.

Grain number is crucial for analysis of yield components and assessment of effects of cultivation measures. The grain number per spike and thousand-grain weight can be measured by counting grains manually, but it is time-consuming, tedious and error-prone. Previous image processing algorithms cannot work well with different backgrounds and different sizes. This study used deep learning methods to resolve the limitations of traditional image processing algorithms. Wheat grain image datasets were collected in the scenarios of three varieties, six background and two image acquisition devices with different heights, angles and grain numbers, 1 748 images in total. All images were processed through color space conversion, image flipping and rotation. The grain was manually annotated, and the datasets were divided into training set, validation set and test set. We used the TensorFlow framework to construct the Faster Region-based Convolutional Neural Network Model. Using the transfer learning method, we optimized the wheat grain detection and enumeration model. The total loss of the model was less than 0.5 and the mean average precision was 0.91. Compared with previous grain counting algorithms, the grain counting error rate of this model was less than 3% and the running time was less than 2 s. The model can be effectively applied under a variety of backgrounds, image sizes, grain sizes, shooting angles, and shooting heights, as well as different levels of grain crowding. It constitutes an effective detection and enumeration tool for wheat grain. This study provides a reference for further grain testing and enumeration applications.

AIM: To evaluate the differences between the estimated and measured corneal ablation thickness in myopic eyes with different refractive errors in small incision lenticule extraction(SMILE)and investigate the precision of corneal ablation thickness in SMILE. METHODS: This prospective study included 234 eyes(143 myopic patients), who had undergone SMILE in our hospital from January 2017 to August 2019. The patients were divided into three groups according to a manifest refraction spherical equivalent(MRSE): low myopia(-0.50 to -3.00D, 78 eyes), moderate myopia(>-3.00 to -6.00D, 78 eyes), and high myopia(>-6.00D, 78 eyes). Observe the uncorrected distance visual acuity(UDVA)and MRSE before and after operation. The central corneal thickness(CCT)was measured by Pentacam preoperatively and postoperatively at 1mo. Compare the discrepancy between estimated corneal ablation thickness and measured corneal ablation thickness of three groups to discuss the precision of corneal ablation thickness in different refractive errors in SMILE. RESULTS: The UDVA was 0.8 or better in all eyes and 1.0 or better in 98.3% eyes postoperatively. The average measured corneal ablation thickness was significantly lower than average estimated corneal ablation thickness(84.92±23.15μm vs 100.07±26.83μm, PPY= -2.2495X+3.9287, R2=0.1589). The cutting error increased with MRSE(t=-6.620, PCONCLUSION: The measured corneal ablation thickness was lower than estimated corneal ablation thickness,the higher the refractive power was, the larger the cutting error would be in SMILE. Although there was significant discrepancy between measured corneal ablation thickness and estimated corneal ablation thickness, the effect of this surgery was ideal, the mismatch did not influence the precision of different refractive errors.

Abstract Remote sensing has been used as an important means of estimating crop production, especially for the estimation of crop yield in the middle and late growth period. In order to further improve the accuracy of estimating winter wheat yield through remote sensing, this study analyzed the quantitative relationship between satellite remote sensing variables obtained from HJ-CCD images and the winter wheat yield, and used the partial least square (PLS) algorithm to construct and validate the multivariate remote sensing models of estimating the yield. The research showed a close relationship between yield and most remote sensing variables. Significant multiple correlations were also recorded between most remote sensing variables. The optimal principal components numbers of PLS models used to estimate yield were 4. Green normalized difference vegetation index (GNDVI), optimized soil-adjusted vegetation index (OSAVI), normalized difference vegetation index (NDVI) and plant senescence reflectance index (PSRI) were sensitive variables for yield remote sensing estimation. Through model development and model validation evaluation, the yield estimation model’s coefficients of determination (R2) were 0.81 and 0.74 respectively. The root mean square error (RMSE) were 693.9 kg ha−1 and 786.5 kg ha−1. It showed that the PLS algorithm model estimates the yield better than the linear regression (LR) and principal components analysis (PCA) algorithms. The estimation accuracy was improved by more than 20% than the LR algorithm, and was 13% higher than the PCA algorithm. The results could provide an effective way to improve the estimation accuracy of winter wheat yield by remote sensing, and was conducive to large-area application and promotion.

Background: The increasing rates of Caesarean section (CS) beyond the WHO standards (10–15%) pose a significant global health concern.Objective: Systematic review and meta-analysis to identify an association between CS history and maternal adverse outcomes for the subsequent pregnancy and delivery among women classified in Robson classification (RC).Search Strategy: PubMed/Medline, EbscoHost, ProQuest, Embase, Web of Science, BIOSIS, MEDLINE, and Russian Science Citation Index databases were searched from 2008 to 2018.Selection Criteria: Based on Robson classification, studies reporting one or more of the 14 adverse maternal outcomes were considered eligible for this review.Data Collection: Study design data, interventions used, CS history, and adverse maternal outcomes were extracted.Main Results: From 4,084 studies, 28 (n = 1,524,695 women) met the inclusion criteria. RC group 5 showed the highest proportion among deliveries followed by RC10, RC7, and RC8 (67.71, 32.27, 0.02, and 0.001%). Among adverse maternal outcomes, hysterectomy had the highest association after preterm delivery OR = 3.39 (95% CI 1.56–7.36), followed by Severe Maternal Outcomes OR = 2.95 (95% CI 1.00–8.67). We identified over one and a half million pregnant women, of whom the majority were found to belong to RC group 5.Conclusions: Previous CS was observed to be associated with adverse maternal outcomes for the subsequent pregnancies. CS rates need to be monitored given the prospective risks which may occur for maternal and child health in subsequent births.

We report enzymes from the berberine bridge enzyme (BBE) superfamily that catalyze the oxidative cyclization of the monoterpene moiety in cannabigerolic acid (CBGA) to form cannabielsoin (CBE). The enzymes are from a variety of organisms and are previously uncharacterized. Out of 232 homologues chosen from the enzyme superfamily, four orthologues were shown to accept CBGA as a substrate and catalyze the biosynthesis of CBE. The four enzymes discovered in this study were recombinantly expressed and purified in Pichia pastoris. These enzymes are the first report of heterologous expression of BBEs that did not originate from the Cannabis plant that catalyze the production of cannabinoids using CBGA as substrate. This study details a new avenue for discovering and producing natural and unnatural cannabinoids.

ObjectiveThe aim of this study is to analyze and visualize the polymorbidity associated with chronic kidney disease (CKD). The study shows diseases associated with CKD before and after CKD diagnosis in a time-evolutionary type visualization.Materials and methodsOur sample data came from a population of one million individuals randomly selected from the Taiwan National Health Insurance Database, 1998 to 2011. From this group, those patients diagnosed with CKD were included in the analysis. We selected 11 of the most common diseases associated with CKD before its diagnosis and followed them until their death or up to 2011. We used a Sankey-style diagram, which quantifies and visualizes the transition between pre- and post-CKD states with various lines and widths. The line represents groups and the width of a line represents the number of patients transferred from one state to another.ResultsThe patients were grouped according to their states: that is, diagnoses, hemodialysis/transplantation procedures, and events such as death. A Sankey diagram with basic zooming and planning functions was developed that temporally and qualitatively depicts they had amid change of comorbidities occurred in pre- and post-CKD states.DiscussionThis represents a novel visualization approach for temporal patterns of polymorbidities associated with any complex disease and its outcomes. The Sankey diagram is a promising method for visualizing complex diseases and exploring the effect of comorbidities on outcomes in a time-evolution style.ConclusionsThis type of visualization may help clinicians foresee possible outcomes of complex diseases by considering comorbidities that the patients have developed.

Candidatus Liberibacter asiaticus (CLas) is the causative agent of Huanglongbing (HLB), which has caused great economic losses to the citrus industry. The molecular mechanism of the host response to CLas in wild citrus germplasm has been reported less. Eighteen weeks after inoculation via grafting, all the CLas-inoculated Chongyi wild mandarin (Citrus reticulata) were positive and showed severe anatomical aberrations, suggesting its susceptibility to HLB. Transcriptomics and metabolomics analyses of leaves, barks, and roots from mock-inoculated (control) and CLas-inoculated seedlings were performed. Comparative transcriptomics identified 3,628, 3,770, and 1,716 differentially expressed genes (DEGs) between CLas-infected and healthy tissues in the leaves, barks, and roots, respectively. The CLas-infected tissues had higher transcripts per kilobase per million values and more genes that reached their maximal expression, suggesting that HLB might cause an overall increase in transcript accumulation. However, HLB-triggered transcriptional alteration showed tissue specificity. In the CLas-infected leaves, many DEGs encoding immune receptors were downregulated. In the CLas-infected barks, nearly all the DEGs involved in signaling and plant-pathogen interaction were upregulated. In the CLas-infected roots, DEGs encoding enzymes or transporters involved in carotenoid biosynthesis and nitrogen metabolism were downregulated. Metabolomics identified 71, 62, and 50 differentially accumulated metabolites (DAMs) in the CLas-infected leaves, barks and roots, respectively. By associating DEGs with DAMs, nitrogen metabolism was the only pathway shared by the three infected tissues and was depressed in the CLas-infected roots. In addition, 26 genes were determined as putative markers of CLas infection, and a hypothesized model for the HLB susceptibility mechanism in Chongyi was proposed. Our study may shed light on investigating the molecular mechanism of the host response to CLas infection in wild citrus germplasm.

Transition metal-doped Sb2Se3 has become a heated topic caused by the strong nonlinear optical response and the ultrafast response time at high laser excitation. In this paper, the Co-doped Sb2Se3 with different doping amount (0.5, 1.0, and 1.5 W) nanofilms were prepared by magnetron sputtering technology, and the nonlinear behavior of Co-doped Sb2Se3 nanofilms at near infrared were systematically studied. The results of the femtosecond Z-Scan experiment indicate that the Co-doped Sb2Se3 nanofilms exhibit broadband nonlinear response properties owing to the free carrier absorption, the Kerr refraction, the two-photon absorption, and the free carrier refraction. The nonlinear absorption coefficients of Co-doped Sb2Se3 nanofilms are from 3.0 × 10−9 to 2.03 × 10−8 m/ W under excitation at 800, 980, and 1,030 nm, and the nonlinear refractive index of the Co-doped Sb2Se3 nanofilms is from 4.0 × 10−16 to -3.89 × 10−15 m2/ W at 800, 980, and 1,030 nm. More importantly, Co-doped Sb2Se3 (1.5 W) nanofilm exhibits ultrafast carrier absorption ( 6.3. The Co-doping content can controllably tune the crystalline degree, the ultrafast carrier absorption, the intensity of the reverse saturation absorption, the broadband nonlinear optical response, and the carrier relaxation time of Co-doped Sb2Se3 nanofilms. These results are sufficient to support their applications in broadband nonlinear photonic devices.

Graphene/MoS2/Ag thin films were successfully prepared by the magnetron sputtering technique and liquid phase exfoliation. Structure, morphology, optical properties, and nonlinear optical characteristics of the graphene/MoS2/Ag and graphene/MoS2 thin films were studied by X-ray diffractometer, spectrophotometer, field-scanning electron microscope, and femtosecond (fs) Z-scan technique. The results of the fs Z-scan experiment indicate that the graphene/MoS2/Ag thin films exhibit reverse saturable absorption properties due to the free carrier absorption and two-photon absorption. More importantly, with the increase of DC magnetron sputtering power (from 5 to 15 W), the local surface plasmon resonance effect of the Ag thin films increases, which leads to the enhancement of nonlinear optical properties of the graphene/MoS2/Ag thin films. The nonlinear absorption coefficients of the graphene/MoS2/Ag thin films are increased from 1.14 × 10–10 to 1.8 × 10–10 m/W at 800 nm and from 4.79 × 10–11 to 6.79 × 10–11 m/W at 1,030 nm, and the nonlinear refraction index of the graphene/MoS2/Ag thin films is -4.37 × 10–17∼−4.18 × 10–16 m2/W under the excitation of 800 and 1,030 nm, respectively. Moreover, when the graphene/MoS2/Ag thin films were excited at 800 and 1,030 nm, respectively, the nonlinear figure of merit values of the graphene/MoS2/Ag thin films are increased from 1.23 to 2.91 and from 1.30 to 1.47, which are enough to support the application of the graphene/MoS2/Ag thin films in the field of all-optical switching applications.

Background:. Facial thread lifting technology has been applied for more than 30 years, with relatively few complications. In 2014, China approved polydioxanone thread (an absorbable barbed thread) for large-scale nonsurgical facial lifting. However, due to surgeons’ lack of overall experience, the complications of polydioxanone thread facelift have been relatively high. Methods:. From April 2014 to January 2020, a total of 190 patients with postoperative complications of facelifts were treated after they underwent thread lifting in other hospitals. Of these, 189 patients were women and one was a man; the age of patients ranged from 28 to 62 years, with an average age of 37.4 years. Results:. Patients were mainly treated in our outpatient clinic for the following complications: skin dimpling (77 cases, 40.5%); contour irregularity (32 cases, 16.8%); visible threads (31 cases, 16.3%); thread extrusion (10 cases, 5.3%); infection (17 cases, 8.9%); swelling (nine cases, 4.7%); incomplete facial paralysis (five cases, 2.6%); hyperpigmentation (four cases, 2.1%); hematoma (four cases, 2.1%); allergy (one case, 0.05%). Follow-up was scheduled 1–24 weeks after treatment. Conclusions:. The most common complications of facial thread lifting are, in the following order, skin dimpling, contour irregularity, visible threads, and thread extrusion. The reasons for complications are mainly unfamiliarity with facial anatomy, unskilled surgical operation, and misunderstanding of the facial aesthetics of Asian women.

Robotic manipulators can reduce the cost of production and improve productivity; however, controlling a manipulator to follow a desired trajectory is a thorny problem. In this study, we introduced various forms of interference to facilitate the modeling of a dual-axis manipulator. The interference associated with the payload is handled by an adaptive radial basis neural network (ARBNN) controller, while other interference is estimated by a time delay estimator (TDE). The control signal is output by a non-singular fast terminal sliding mode controller (NFTSMC) to minimize further interference. Since the proposed controller can deal with the payload, system uncertainties, external disturbances, friction, and backlash, compared with conventional control methods, it has better tracking accuracy and stability.

In recent research, supervised image clustering based on Graph Neural Networks (GNN) connectivity prediction has demonstrated considerable improvements over traditional clustering algorithms. However, existing supervised image clustering algorithms are usually time-consuming and limit their applications. In order to infer the connectivity between image instances, they usually created a subgraph for each image instance. Due to the creation and process of a large number of subgraphs as the input of GNN, the computation overheads are enormous. To address the high computation overhead problem in the GNN connectivity prediction, we present a time-efficient and effective GNN-based supervised clustering framework based on density division namely DDC-GNN. DDC-GNN divides all image instances into high-density parts and low-density parts, and only performs GNN subgraph connectivity prediction on the low-density parts, resulting in a significant reduction in redundant calculations. We test two typical models in the GNN connectivity prediction module in the DDC-GNN framework, which are the graph convolutional networks (GCN)-based model and the graph auto-encoder (GAE)-based model. Meanwhile, adaptive subgraphs are generated to ensure sufficient contextual information extraction for low-density parts instead of the fixed-size subgraphs. According to the experiments on different datasets, DDC-GNN achieves higher accuracy and is almost five times quicker than those without the density division strategy.

Alcoholic liver disease (ALD) is one of the main causes of death in chronic liver disease. Oxidative stress and pyroptosis are important factors leading to ALD. Bromodomain-containing protein 4 (BRD4) is a factor that we have confirmed to regulate ALD. As a phenolic acid compound, sinapic acid (SA) has significant effects in antioxidant, anti-inflammatory and liver protection. In this study, we explored whether SA regulates oxidative stress and pyroptosis through BRD4 to play a protective effect in ALD. Male C57BL/6 mice and AML-12 cells were used for experiments. We found that SA treatment largely abolished the up-regulation of BRD4 and key proteins of the canonical pyroptosis signalling in the liver of mice fed with alcohol, while conversely enhanced the antioxidant response. Consistantly, both SA pretreatment and BRD4 knockdown inhibited oxidative stress, pyroptosis, and liver cell damage in vitro. More importantly, the expression levels of BRD4 and pyroptosis indicators increased significantly in ALD patients. Molecule docking analysis revealed a potent binding of SA with BRD4. In conclusion, this study demonstrates that SA reduces ALD through BRD4, which is a valuable lead compound that prevents the ALD process.