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Abstract Deep learning models have been developed for various predictions in glioma; yet, they were constrained by manual segmentation, task-specific design, or a lack of biological interpretation. Herein, we aimed to develop an end-to-end multi-task deep learning (MDL) pipeline that can simultaneously predict molecular alterations and histological grade (auxiliary tasks), as well as prognosis (primary task) in gliomas. Further, we aimed to provide the biological mechanisms underlying the model’s predictions. We collected multiscale data including baseline MRI images from 2776 glioma patients across two private (FAHZU and HPPH, n = 1931) and three public datasets (TCGA, n = 213; UCSF, n = 410; and EGD, n = 222). We trained and internally validated the MDL model using our private datasets, and externally validated it using the three public datasets. We used the model-predicted deep prognosis score (DPS) to stratify patients into low-DPS and high-DPS subtypes. Additionally, a radio-multiomics analysis was conducted to elucidate the biological basis of the DPS. In the external validation cohorts, the MDL model achieved average areas under the curve of 0.892–0.903, 0.710–0.894, and 0.850–0.879 for predicting IDH mutation status, 1p/19q co-deletion status, and tumor grade, respectively. Moreover, the MDL model yielded a C-index of 0.723 in the TCGA and 0.671 in the UCSF for the prediction of overall survival. The DPS exhibits significant correlations with activated oncogenic pathways, immune infiltration patterns, specific protein expression, DNA methylation, tumor mutation burden, and tumor-stroma ratio. Accordingly, our work presents an accurate and biologically meaningful tool for predicting molecular subtypes, tumor grade, and survival outcomes in gliomas, which provides personalized clinical decision-making in a global and non-invasive manner.

Abstract Background This study aimed to apply the backpropagation neural network (BPNN) to develop a model for predicting multidrug-resistant organism (MDRO) infection in critically ill patients. Methods This study collected patient information admitted to the intensive care unit (ICU) of the Affiliated Hospital of Qingdao University from August 2021 to January 2022. All patients enrolled were divided randomly into a training set (80%) and a test set (20%). The least absolute shrinkage and selection operator and stepwise regression analysis were used to determine the independent risk factors for MDRO infection. A BPNN model was constructed based on these factors. Then, we externally validated this model in patients from May 2022 to July 2022 over the same center. The model performance was evaluated by the calibration curve, the area under the curve (AUC), sensitivity, specificity, and accuracy. Results In the primary cohort, 688 patients were enrolled, including 109 (15.84%) MDRO infection patients. Risk factors for MDRO infection, as determined by the primary cohort, included length of hospitalization, length of ICU stay, long-term bed rest, antibiotics use before ICU, acute physiology and chronic health evaluation II, invasive operation before ICU, quantity of antibiotics, chronic lung disease, and hypoproteinemia. There were 238 patients in the validation set, including 31 (13.03%) MDRO infection patients. This BPNN model yielded good calibration. The AUC of the training set, the test set and the validation set were 0.889 (95% CI 0.852–0.925), 0.919 (95% CI 0.856–0.983), and 0.811 (95% CI 0.731–0.891), respectively. Conclusions This study confirmed nine independent risk factors for MDRO infection. The BPNN model performed well and was potentially used to predict MDRO infection in ICU patients.

Summary: Background: Previous deep learning models have been proposed to predict the pathological complete response (pCR) and axillary lymph node metastasis (ALNM) in breast cancer. Yet, the models often leveraged multiple frameworks, required manual annotation, and discarded low-quality images. We aimed to develop an automated and reusable deep learning (AutoRDL) framework for tumor detection and prediction of pCR and ALNM using ultrasound images with diverse qualities. Methods: The AutoRDL framework includes a You Only Look Once version 5 (YOLOv5) network for tumor detection and a progressive multi-granularity (PMG) network for pCR and ALNM prediction. The training cohort and the internal validation cohort were recruited from Guangdong Provincial People’s Hospital (GPPH) between November 2012 and May 2021. The two external validation cohorts were recruited from the First Affiliated Hospital of Kunming Medical University (KMUH), between January 2016 and December 2019, and Shunde Hospital of Southern Medical University (SHSMU) between January 2014 and July 2015. Prior to model training, super-resolution via iterative refinement (SR3) was employed to improve the spatial resolution of low-quality images from the KMUH. We developed three models for predicting pCR and ALNM: a clinical model using multivariable logistic regression analysis, an image model utilizing the PMG network, and a combined model that integrates both clinical and image data using the PMG network. Findings: The YOLOv5 network demonstrated excellent accuracy in tumor detection, achieving average precisions of 0.880–0.921 during validation. In terms of pCR prediction, the combined modelpost-SR3 outperformed the combined modelpre-SR3, image modelpost-SR3, image modelpre-SR3, and clinical model (AUC: 0.833 vs 0.822 vs 0.806 vs 0.790 vs 0.712, all p

The Baiyun gold deposit is a medium-sized deposit in northeastern Hubei around the southern margin of the Tongbai-Dabie metallogenic belt. However, its genesis has not been determined. The metallogenic process of the Baiyun gold deposit can be divided into three stages: quartz + feldspar, quartz + native gold + electrum + polymetallic sulfides, and quartz + pyrite + calcite + iron dolomite + illite. In this study, LA-ICP-MS was used for in situ trace element and isotope analyses in the main and late ore stage hydrothermal sulfides to evaluate the genesis and evolution of ore-forming fluids. Gold is positively correlated with Ag, Cu, Pb, Zn, and Te and the Co/Ni ratio is greater than 1. The S isotope values of Py1 and Py2 are −0.23–3.04‰ and 1.27–6.09‰, respectively. As mineralization progressed, S isotope values increased. In situ S isotope values of the two types of galena symbiotic with pyrite in the main metallogenic stage are 2.97–3.47‰. In situ Fe isotopic values of pyrite are −0.05–0.82‰; values in the two stages are similar without significant fractionation. We inferred that the Baiyun gold deposit formed via magmatic mineralization related to the subduction of the Pacific Plate during the Yanshanian.

Key points 1. Texture analysis based on coronal T2-weighted MR images could evaluate the renal function in patients with diabetes. 2. The All-K and LC-K outperformed other segmentation methods in the evaluation of renal function impairment. 3. The segmentation methods could affect the results of renal function evaluation and the integrity of the coronal slices was crucial for renal imaging texture analysis.

Background: Multi-center research has demonstrated that adopting Silva's pattern-based classification system (SPBC) enhances the clinical prognosis and facilitates hierarchical management of patients with endocervical adenocarcinomas (EAC). However, inconsistencies in SPBC can arise due to variations in pathologists' experience levels. Thus, the implementation of standardized decision-making tools becomes crucial to enhance the practicality of SPBC in clinical diagnosis and treatment. Methods: We enrolled a total of 90 patients with EAC in this study, of which 63 were assigned to the training group, and the remaining 27 were allocated to the validation group. To create and validate the prediction models for SPBC, we utilized a deep learning system (DLS) and calculated the area under the receiver operating characteristic curve (AUC). Results: In Silva pattern classification, ResNet50 achieved an average accuracy of 74.36% (63.64% for pattern A, 55.56% for pattern B, and 89.47% for pattern C respectively). Moreover, in test set, ResNet50 achieved an AUC of 0.69 for pattern A, 0.58 for pattern B, and 0.91 for pattern C. Conclusions: We successfully established a DLS for SPBC, which holds the potential to aid pathologists in accurately classifying patients with EAC.

Abstract Salt stress is a major challenge for plant growth and yield achievement in canola (Brassica napus L.). Nitrogen (N) is considered as an essential nutrient involved in many physiological processes, and carbon (C) is the most component of plant biomass. N and C assimilations of canola plants are always inhibited by salt stress. However, the knowledge of how salt stress affects biomass and seed yield through changing N and C characters is limited. A field experiment was conducted to investigate the growth process, N and C characters, photosynthetic performance, biomass accumulation and seed yield under the low and high soil salt-ion concentration conditions (LSSC and HSSC). The results indicated that HSSC postponed the time of early flowering stage and maturity stage by 4 ~ 5 days and 6 ~ 8 days, respectively, as compared with LSSC. Besides, HSSC decreased the N and C accumulation and C/N at both growing stages, suggesting that salt stress break the balance between C assimilation and N assimilation, with stronger effect on C assimilation. Although the plant N content under HSSC was increased, the photosynthesis rate at early flowering stage was decreased. The leaf area index at early flowering stage was also reduced. In addition, HSSC decreased N translocation efficiency especially in stem, and N utilization efficiency. These adverse effects of HSSC together resulted in reduced biomass accumulation and seed yield. In conclusion, the high soil salt-ion concentration reduced biomass accumulation and seed yield in canola through changing N and C characters.

Abstract For the development of a parallel mechanism (PM), it is necessary to establish a dynamic model which can accurately meet the requirements of real-time control. Compared with the general dynamic analysis model based on the inverse kinematics, the dynamic analysis model based on the forward kinematics has the advantage of low-complexity. In this paper, a new type of 3-DOF PM with analytical forward displacement analysis is proposed. Different from the general dynamic analysis based on the inverse kinematics, the displacement, velocity and acceleration equations of the PM are established and solved by forward kinematics. The inverse dynamic equation of the PM is constructed and solved by analyzing the forces on each link and based on Newton-Euler method. Then the theoretical results of an example are compared with the simulation results, which shows that the simulation results are basically consistent with the theoretical results. And the maximum error of the driving force of each pair is 1.32%, 5.8% and 5.2%, respectively, which verifies the correctness of the dynamic model. The PM has a potential application prospect in the grasping, spraying and picking of workpieces. The research results of this paper provide a theoretical basis for the design, manufacture and application of the PM.

Abstract Background Transcatheter arterial chemoembolization (TACE) is the mainstay of therapy for intermediate-stage hepatocellular carcinoma (HCC); yet its efficacy varies between patients with the same tumor stage. Accurate prediction of TACE response remains a major concern to avoid overtreatment. Thus, we aimed to develop and validate an artificial intelligence system for real-time automatic prediction of TACE response in HCC patients based on digital subtraction angiography (DSA) videos via a deep learning approach. Methods This retrospective cohort study included a total of 605 patients with intermediate-stage HCC who received TACE as their initial therapy. A fully automated framework (i.e., DSA-Net) contained a U-net model for automatic tumor segmentation (Model 1) and a ResNet model for the prediction of treatment response to the first TACE (Model 2). The two models were trained in 360 patients, internally validated in 124 patients, and externally validated in 121 patients. Dice coefficient and receiver operating characteristic curves were used to evaluate the performance of Models 1 and 2, respectively. Results Model 1 yielded a Dice coefficient of 0.75 (95% confidence interval [CI]: 0.73–0.78) and 0.73 (95% CI: 0.71–0.75) for the internal validation and external validation cohorts, respectively. Integrating the DSA videos, segmentation results, and clinical variables (mainly demographics and liver function parameters), Model 2 predicted treatment response to first TACE with an accuracy of 78.2% (95%CI: 74.2–82.3), sensitivity of 77.6% (95%CI: 70.7–84.0), and specificity of 78.7% (95%CI: 72.9–84.1) for the internal validation cohort, and accuracy of 75.1% (95% CI: 73.1–81.7), sensitivity of 50.5% (95%CI: 40.0–61.5), and specificity of 83.5% (95%CI: 79.2–87.7) for the external validation cohort. Kaplan-Meier curves showed a significant difference in progression-free survival between the responders and non-responders divided by Model 2 (p = 0.002). Conclusions Our multi-task deep learning framework provided a real-time effective approach for decoding DSA videos and can offer clinical-decision support for TACE treatment in intermediate-stage HCC patients in real-world settings.

Tsinghua University is currently developing a very-high-frequency electron gun that operates in continuous-wave (cw) mode at 216.667 MHz. This gun will serve as the beam source for the Shanghai high repetition rate XFEL and extreme light facility. The cavity profile has been optimized to minimize input power, peak surface electric field, and peak wall power density. The profile optimization also takes into account the suppression of multipacting effect. Additionally, thermal analysis has been performed to guide the design of water cooling channels in coordination with gun mechanical design. The fabrication of the gun has been completed, and the frequency and quality factor measured in cold test are in good agreement with simulation expectations. During high power conditioning, 75 kW cw radio frequency power was successfully fed into the gun, corresponding to a cathode gradient of 27 MV/m and a gun voltage of 780 keV. This operating gradient is currently the highest in the world for room-temperature VHF guns. Under this condition, the maximum dark current collected by the Faraday cup at the gun exit was 376 nA when the strength of the gun solenoid was scanned. To measure and optimize the beam quality, a test beamline was constructed. After preliminary optimization, the 95% projected transverse emittance was 0.161 mm mrad for 10 pC bunches with a bunch length of 0.49 mm rms, 0.429 mm mrad for 50 pC bunches with a bunch length of 1.15 mm rms, and 0.853 mm mrad for 100 pC bunches with a bunch length of 1.44 mm rms.

In this paper, the general-decay synchronization issue of a class of quaternion-valued neural networks with mixed time delays is investigated. Firstly, unlike some previous works where the quaternion-valued model is separated into four real-valued networks or two complex-valued networks, we consider the mixed-delayed quaternion-valued neural network model as a whole and introduce a novel nonlinear feedback controller for the corresponding response system. Then, by introducing a suitable Lyapunov–Krasovskii functional and employing a novel inequality technique, some easily verifiable sufficient conditions are obtained to ensure the general-decay synchronization for the considered drive-response networks. Finally, the feasibility of the established theoretical results is verified by carrying out Matlab numerical simulations.

At present, the fastener installation in a wingbox facing a narrow space must be performed manually. Using a robot is an appropriate solution for automatic assembly. However, the existing robots cannot meet the internal fastening requirements. A new robot with a prismatic joint and four revolute joints (1P4R) was developed to perform the positioning and operation in the wingbox. A compact arm link was designed, and mechanical frame structures were set up. The control system was also set up for the robot’s motion. Then, the forward kinematic model was carried out with the matrix transformation method, and in the analysis the workspace entirely covered the wingbox. The inverse kinematic model was established using the geometric method, and through calculation and simulation, the inverse kinematic equations were verified and refined.

Mechanized transplanting of rapeseed (Brassica napus L.) blanket seedling is an innovative cultivation technology. Cultivating high quality blanket seedling to ensure high survival rate of seedling after transplanting is the key of the technology. The effects of different uniconazole rates of 0, 0.5, 1.0, 1.5 and 2.0 mg/tray, spraying at one leaf and one heart stage, on selected agronomic traits, physiological indexes and survival rate of two rapeseed cultivars (‘Qinyou 10′ and ’Yangyou 9′) were investigated in 2018 and 2019. Our results showed that the plant height decreased significantly with the increase of uniconazole rate. However, the collar diameter increased significantly with the increase of uniconazole rate up to 1.5 mg/tray, and the leaf area, dry weights of root and shoot increased with increased uniconazole rate up to 1.0 mg/tray. The root to shoot ratios, N concentrations of root and shoot with the uniconazole rates of 1.0 and 1.5 mg/tray were higher than those with other treatments. As uniconazole rate increasing, gibberellin (GA) and auxin (IAA) concentrations of root and shoot decreased, while abscisic acid (ABA) concentrations increased, and cytokinin (CTK) concentrations topped at uniconazole rate of 1.0 mg/tray and decreased thereafter. The seedling survival rates with 1.0 and 1.5 mg/tray were greatly higher than those in other treatments. Regression analysis suggested plant survival rate was positively related to CTK concentrations and negatively to GA concentrations of root and shoot. To achieve high survival rate after mechanized transplanting, our study revealed that the uniconazole applied at a rate of 1.0 mg/tray was recommended as the best, followed by 1.5 mg/tray. The findings would help to enhance qualities of rapeseed blanket seedling and to promote popularization of mechanized transplanting of rapeseed production.

Ocean wave parameters, including wave height, direction and period, are necessary to improve forecasts of ocean wave conditions. Their accurate observation contributes to safety of both offshore operations and military operations. However, conventional wave observation methods that combine the three-axis accelerometer-based wave sensor with the gyroscope may show problems such as inner arm error, transverse sensitivity effect, and gyroscope drift. The first two are due to non-coincidence of centroids inside the accelerometer. Such problems will reduce reliability of data. To solve the problems, a new type of parallel six-dimensional accelerometer is developed to reduce principle errors and improve stability of wave buoys. The solution features a single mass and 12-chain redundancy. When compared with the performance of high-precision sensors in the wave pool, the wave buoy based on six-dimensional accelerometer is proved to be more accurate in wave height measurement than 3.75 % × measurement value, with wave direction accuracy of ± 1°, and the wave period measurement accuracy of ± 0.1s.

Both genetic predisposition and life events, particularly life stress, are thought to increase the risk for depression. Reward sensitivity appears to be attenuated in major depressive disorder (MDD), suggesting deficits in reward processing in these patients. We identified the VTA-BLA-NAc circuit as being activated by sex reward, and the VTA neurons that respond to sex reward are mostly dopaminergic. Acute or chronic reactivation of this circuit ameliorates the reward insensitivity induced by chronic restraint stress. Our histological and electrophysiological results show that the VTA neuron subpopulation responding to restraint stress, predominantly GABAergic neurons, inhibits the responsiveness of VTA dopaminergic neurons to reward stimuli, which is probably the mechanism by which stress modulates the reward processing neural circuits and subsequently disrupts reward-related behaviours. Furthermore, we found that the VTA-BLA-NAc circuit is a positive feedback loop. Blocking the projections from the BLA to the NAc associated with sex reward increases the excitability of VTA GABAergic neurons and decreases the excitability of VTA dopaminergic neurons, while activating this pathway decreases the excitability of VTA GABAergic neurons and increases the excitability of VTA dopaminergic neurons, which may be the cellular mechanism by which the VTA-BLA-NAc circuit associated with sex reward ameliorates the attenuated reward sensitivity induced by chronic stress.

This article is mainly concerned with the fixed-time and predefined-time synchronization problem for a type of complex-valued BAM neural networks with stochastic perturbations and impulse effect. First, some previous fixed-time stability results on nonlinear impulsive systems in which stabilizing and destabilizing impulses were separately analyzed are extended to a general case in which the stabilizing and destabilizing impulses can be handled simultaneously. Additionally, using the same logic, a new predefined-time stability lemma for stochastic nonlinear systems with a general impulsive effect is obtained by using the inequality technique. Then, based on these novel results, two novel controllers are implemented to derive some simple fixed/predefined-time synchronization criteria for the considered complex-valued impulsive BAM neural networks with stochastic perturbations using the non-separation method. Finally, two numerical examples are given to demonstrate the feasibility of the obtained results.

Collagens represent a major group of structural proteins expressed in different tissues and display distinct and variable properties. Whilst collagens are non-transparent in the skin, they confer transparency in the cornea and crystalline lens of the eye. There are 28 types of collagen that all share a common triple helix structure yet differ in the composition of their α-chains leading to their different properties. The different organization of collagen fibers also contributes to the variable tissue morphology. The important ability of collagen to form different tissues has led to the exploration and application of collagen as a biomaterial. Collagen type I (Col-I) and collagen type IV (Col-IV) are the two primary collagens found in corneal and lens tissues. Both collagens provide structure and transparency, essential for a clear vision. This review explores the application of these two collagen types as novel biomaterials in bioengineering unique tissue that could be used to treat a variety of ocular diseases leading to blindness.

Mechanized transplanting of rapeseed (Brassica napus L.) blanket seedling is an effective strategy to cope with the seasonal conflict and large labor cost in rapeseed production. The sowing density is a key factor to cultivate high-quality seedlings suitable for mechanized transplanting. An experiment was conducted to investigate the effects of different sowing density levels of 638, 696, 754, 812, 870 and 928 seeds per tray (referred as D1, D2, D3, D4, D5 and D6, respectively) on agronomic traits and survival rate after mechanized transplanting of two rapeseed cultivars (Zheyouza108 and Heza17) in 2020 and 2021. The results showed that high sowing density increased plant height but decreased leaf area, collar diameter, biomass accumulation, the ratio of root to shoot and seedling fullness. These negative effects jointly decreased the seedling rate and survival rate after mechanized transplanting. However, the seedlings under D1 and D2 posed a great plant survival rate of more than 95% after mechanized transplanting, suggesting that the seedlings under the two densities were perfect for mechanized transplanting. In addition, hierarchical analysis grouped D1 and D2 into the same class, indicating that their seedling qualities were not significantly different, though the blanket seedlings under D1 outperformed those under D2 in some traits. A sowing density of 696 seeds per tray (D2) is then recommended in this study, altogether considering its high-quality seedlings suitable for mechanized transplanting, and economically, fewer seedling trays required.

Purpose: This study aimed to compare the clinical characteristics, laboratory findings, and chest computed tomography (CT) findings of familial cluster (FC) and non-familial (NF) patients with coronavirus disease 2019 (COVID-19) pneumonia.Methods: This retrospective study included 178 symptomatic adult patients with laboratory-confirmed COVID-19. The 178 patients were divided into FC (n = 108) and NF (n = 70) groups. Patients with at least two confirmed COVID-19 cases in their household were classified into the FC group. The clinical and laboratory features between the two groups were compared and so were the chest CT findings on-admission and end-hospitalization.Results: Compared with the NF group, the FC group had a longer period of exposure (13.1 vs. 8.9 days, p < 0.001), viral shedding (21.5 vs. 15.9 days, p < 0.001), and hospital stay (39.2 vs. 22.2 days, p < 0.001). The FC group showed a higher number of involved lung lobes on admission (3.0 vs. 2.3, p = 0.017) and at end-hospitalization (3.6 vs. 1.7, p < 0.001) as well as higher sum severity CT scores at end-hospitalization (4.6 vs. 2.7, p = 0.005) than did the NF group. Conversely, the FC group had a lower lymphocyte count level (p < 0.001) and a significantly lower difference in the number of involved lung lobes (Δnumber) between admission and discharge (p < 0.001). Notably, more cases of severe or critical illness were observed in the FC group than in the NF group (p = 0.036).Conclusions: Patients in the FC group had a worse clinical course and outcome than those in the NF group; thus, close monitoring during treatment and follow-ups after discharge would be beneficial for patients with familial infections.

Objectives: Visual chest CT is subjective with interobserver variability. We aimed to quantify the dynamic changes of lung and pneumonia on three-dimensional CT (3D-CT) images in coronavirus disease 2019 (COVID-19) patients during hospitalization.Methods: A total of 110 laboratory-confirmed COVID-19 patients who underwent chest CT from January 3 to February 29, 2020 were retrospectively reviewed. Pneumonia lesions were classified as four stages: early, progressive, peak, and absorption stages on chest CT. A computer-aided diagnostic (CAD) system calculated the total lung volume (TLV), the percentage of low attenuation areas (LAA%), the volume of pneumonia, the volume of ground-glass opacities (GGO), the volume of consolidation plus the GGO/consolidation ratio. The CT score was visually assessed by radiologists. Comparisons of lung and pneumonia parameters among the four stages were performed by one-way ANOVA with post-hoc tests. The relationship between the CT score and the volume of pneumonia, and between LAA% and the volume of pneumonia in four stages was assessed by Spearman's rank correlation analysis.Results: A total of 534 chest CT scans were performed with a median interval of 4 days. TLV, LAA%, and the GGO/consolidation ratio were significantly decreased, while the volume of pneumonia, GGO, and consolidation were significantly increased in the progressive and peak stages (for all, P < 0.05). The CT score was significantly correlated with the pneumonia volume in the four stages (r = 0.731, 0.761, 0.715, and 0.669, respectively, P < 0.001).Conclusion: 3D-CT could be used as a useful quantification method in monitoring the dynamic changes of COVID-19 pneumonia.

Background: Hyperprogressive disease (HPD) is a new progressive pattern in patients with advanced hepatocellular carcinoma (HCC) treated with programmed cell death 1 (PD-1) inhibitors. We aimed to investigate risk factors associated with HPD in advanced HCC patients undergoing anti-PD-1 therapy. Methods: A total of 69 patients treated with anti-PD-1 therapy between March 2017 and January 2020 were included. HPD was determined according to the time to treatment failure, tumour growth rate, and tumour growth rate ratio. Univariate and multivariate analyses were performed to identify clinical variables significantly associated with HPD. A risk model was constructed based on clinical variables with prognostic significance for HPD. Findings: Overall, 10 (14·49%) had HPD. Haemoglobin level, portal vein tumour thrombus, and Child-Pugh score were significantly associated with HPD. The risk model had an area under the curve of 0·931 (95% confidence interval, 0·844–1·000). Patients with HPD had a significantly shorter overall survival (OS) than that of the patients with non-HPD (p

Aim: Early detection of coronavirus disease 2019 (COVID-19) patients who are likely to develop worse outcomes is of great importance, which may help select patients at risk of rapid deterioration who should require high-level monitoring and more aggressive treatment. We aimed to develop and validate a nomogram for predicting 30-days poor outcome of patients with COVID-19.Methods: The prediction model was developed in a primary cohort consisting of 233 patients with laboratory-confirmed COVID-19, and data were collected from January 3 to March 20, 2020. We identified and integrated significant prognostic factors for 30-days poor outcome to construct a nomogram. The model was subjected to internal validation and to external validation with two separate cohorts of 110 and 118 cases, respectively. The performance of the nomogram was assessed with respect to its predictive accuracy, discriminative ability, and clinical usefulness.Results: In the primary cohort, the mean age of patients was 55.4 years and 129 (55.4%) were male. Prognostic factors contained in the clinical nomogram were age, lactic dehydrogenase, aspartate aminotransferase, prothrombin time, serum creatinine, serum sodium, fasting blood glucose, and D-dimer. The model was externally validated in two cohorts achieving an AUC of 0.946 and 0.878, sensitivity of 100 and 79%, and specificity of 76.5 and 83.8%, respectively. Although adding CT score to the clinical nomogram (clinical-CT nomogram) did not yield better predictive performance, decision curve analysis showed that the clinical-CT nomogram provided better clinical utility than the clinical nomogram.Conclusions: We established and validated a nomogram that can provide an individual prediction of 30-days poor outcome for COVID-19 patients. This practical prognostic model may help clinicians in decision making and reduce mortality.

Salt stress is a major negative factor affecting the sustainable development of agriculture. Phosphorus (P) deficiency often occurs in saline soil, and their interaction inhibits plant growth and seed yield for canola (Brassica napus L.). P supply is considered an effective way to alleviate the damage of salt stress. However, the knowledge of how P supply can promote plant growth in saline environment was limited. A field experiment was conducted to explore the effects of P rate on accumulation, and partitioning, of biomass and P, leaf photosynthesis traits, and yield performance in saline soil in the coastal area of Yancheng City, Jiangsu Province, China, during the 2018–2019 and 2019–2020 growing seasons. P supply increased biomass and P accumulation in all organs, and root had the most increments among different organs. At flowering stage, P supply increased the biomass and P partitioning in root and leaf, but it decreased the partitioning in stem. At maturity stage, P supply facilitated the biomass and P partitioning in seed, but it decreased the partitioning in stem and shell, and it increased the reproductive-vegetative ratio, suggesting that P supply can improve the nutrients transporting from vegetative organs to reproductive organs. Besides, P supply improved the leaf area index and photosynthetic rate at the flowering stage. As a result, the seed yield and oil yield were increased. In conclusion, P supply can improve the canola plant growth and seed yield in a saline environment. P fertilizer at the rate of 120 kg P2O5 ha−1 was recommended in this saline soil.

The solution of the dynamic equations of the six-axis accelerometer is a prerequisite for sensor calibration, structural optimization, and practical application. However, the forward dynamic equations (FDEs) and inverse dynamic equations (IDEs) of this type of system have not been completely solved due to the strongly nonlinear coupling relationship between the inputs and outputs. This article presents a comprehensive study of the FDEs and IDEs of the six-axis accelerometer based on a parallel mechanism. Firstly, two sets of dynamic equations of the sensor are constructed based on the Newton–Euler method in the configuration space. Secondly, based on the analytical solution of the sensor branch chain length, the coordination equation between the output signals of the branch chain is constructed. The FDEs of the sensor are established by combining the coordination equations and two sets of dynamic equations. Furthermore, by introducing generalized momentum and Hamiltonian function and using Legendre transformation, the vibration differential equations (VDEs) of the sensor are derived. The VDEs and Newton–Euler equations constitute the IDEs of the system. Finally, the explicit recursive algorithm for solving the quaternion in the equation is given in the phase space. Then the IDEs are solved by substituting the quaternion into the dynamic equations in the configuration space. The predicted numerical results of the established FDEs and IDEs are verified by comparing with virtual and actual experimental data. The actual experiment shows that the relative errors of the FDEs and the IDEs constructed in this article are 2.21% and 7.65%, respectively. This research provides a new strategy for further improving the practicability of the six-axis accelerometer.

Keratoconus (KC) is a progressive degenerative inflammatory-related disease of the human cornea leading to decreased visual function. The pathogenesis of KC remains to be understood. Recent genetic studies indicate that gene variants of an inflammation-related molecule, hepatocyte growth factor (HGF), are associated with an increased susceptibility for developing KC. However HGF protein expression in KC has not been explored. In this initial study, we investigated late-stage KC and control corneas for the expression of HGF and its receptor mesenchymal-epithelial transition factor (c-Met/Met). KC buttons (~8 mm diameter) (n=10) and whole control corneas (n=6) were fixed in 10% formalin or 2% paraformaldehyde, paraffin embedded and sectioned. Sections were immunolabelled with HGF and c-Met antibodies, visualised using immunofluorescence, and examined with scanning laser confocal microscopy. Semiquantitative grading was used to compare HGF and c-Met immunostaining in KC and control corneas. Overall, KC corneas showed increased HGF and c-Met immunostaining compared to controls. KC corneal epithelium displayed heterogeneous moderate-to-strong immunoreactivity for HGF and c-Met, particularly in the basal epithelium adjacent to the cone area. Taken together with the recent genetic studies, our results further support a possible role for HGF/c-Met in the pathogenesis of KC.

PURPOSE: To investigate the modulatory effect of rat bone marrow mesenchymal stem cells (MSC) on human corneal epithelial cells (HCE-T) stimulated with pro-inflammatory cytokines interferon gamma (IFN-γ) and tumor necrosis factor alpha (TNF-α) in an in vitro co-cultured model. METHODS: HCE-T alone and co-cultured with MSC were stimulated with IFN-γ/TNF for 24 and 48 hours or left untreated. The expression of intracellular adhesion molecule (ICAM)-1, human leukocyte antigen ABC, DR and G (HLA-ABC, HLA-DR, HLA-G) were investigated by flow cytometry. Subcellular localization of nuclear factor-kappa B (NF-κB) and expression of indoleamine 2,3-dioxygenase (IDO) were assessed by immunofluorescence staining and western blot. The concentration of transforming growth factor beta 1 (TGF-β1) in the conditioned media from different cultures was evaluated by enzyme-linked immunosorbent assay. NF-κB and TGF-β1 signaling pathway blocking experiments were performed to analyze associations between the expression of cell surface molecules and the NF-κB transcription pathway, and the expression of IDO and TGF-β1 signaling pathway. RESULTS: IFN-γ/TNF treatment significantly up-regulated expression of ICAM-1, HLA-ABC, and induced de novo expression of HLA-DR and IDO on HCE-T cultured alone, while HLA-G expression remained unaffected. Up-regulation was significantly inhibited by co-culture with MSC. Increased TGF-β1 secretion was detected in 48 h IFN-γ/TNF-stimulated MSC monocultures and HCE-T/MSC co-cultures. MSC attenuated the activation of cytokine-induced NF-κB and IDO induction. Blockade of NF-κB transcription pathway by BMS-345541 significantly reduced the up-regulation of ICAM-1, HLA-ABC, HLA-DR and IDO expression, while blockade of TGF-β1 signaling pathways reversed the modulatory effect of MSC on IDO expression. CONCLUSIONS: MSC reduced the expression of adhesion and immunoregulatory molecules on pro-inflammatory cytokine-stimulated HCE-T via the NF-κB transcription pathway. MSC attenuated expression of IDO through both NF-κB transcription and TGF-β1 signaling pathways. Co-culture of HCEC with MSC therefore provides a useful in vitro model to study the anti-inflammatory properties of MSC on corneal epithelium.

We investigated the expression of the secreted frizzled-related proteins (SFRPs) in keratoconus (KC) and control corneas. KC buttons (∼8 mm diameter) (n = 15) and whole control corneas (n = 7) were fixed in 10% formalin or 2% paraformaldehyde and subsequently paraffin embedded and sectioned. Sections for histopathology were stained with hematoxylin and eosin, or Periodic Acid Schiff's reagent. A series of sections was also immunolabelled with SFRP 1 to 5 antibodies, visualised using immunofluorescence, and examined with a Zeiss LSM700 scanning laser confocal microscope. Semi-quantitative grading was used to compare SFRP immunostaining in KC and control corneas. Overall, KC corneas showed increased immunostaining for SFRP1 to 5, compared to controls. Corneal epithelium in all KC corneas displayed heterogeneous moderate to strong immunoreactivity for SFRP1 to 4, particularly in the basal epithelium adjacent to cone area. SFRP3 and 5 were localised to epithelial cell membranes in KC and control corneas, with increased SFRP3 cytoplasmic expression observed in KC. Strong stromal expression of SFRP5, including extracellular matrix, was seen in both KC and control corneas. In control corneas we observed differential expression of SFRP family proteins in the limbus compared to more central cornea. Taken together, our results support a role for SFRPs in maintaining a healthy cornea and in the pathogenesis of epithelial and anterior stromal disruption observed in KC.