Facilitating interaction between partial differential equation-based dynamics and unknown dynamics for regional wind speed prediction.

Regional wind speed prediction is an important spatiotemporal prediction problem which is crucial for optimizing wind power utilization. Nevertheless, the complex dynamics of wind speed pose a formidable challenge to prediction tasks. The evolving dynamics of wind could be governed by underlying physical principles that can be described by partial differential equations (PDE). This study proposes a novel approach called PDE-assisted network (PaNet) for regional wind speed prediction. In PaNet, a new architecture is devised, incorporating both PDE-based dynamics (PDE dynamics) and unknown dynamics. Specifically, this architecture establishes interactions between the two dynamics, regulated by an inter-dynamics communication unit that controls interactions through attention gates. Additionally, recognizing the significance of the initial state for PDE dynamics, an adaptive frequency-gated unit is introduced to generate a suitable initial state for the PDE dynamics by selecting essential frequency components. To evaluate the predictive performance of PaNet, this study conducts comprehensive experiments on two real-world wind speed datasets. The experimental results indicated that the proposed method is superior to other baseline methods.

Effects of hypertensive disorders of pregnancy on the complications in very low birth weight neonates.

OBJECTIVE: This study was designed to investigate the effects of hypertensive disorders of pregnancy (HDP) on the complications in very low birth weight (VLBW) neonates. METHODS: We retrospectively included VLBW neonates (<37 weeks) who were delivered by HDP pregnant women with a body weight of < 1,500 g (HDP group) hospitalized in our hospital between January 2016 and July 2021. Gestational age matched VLBW neonates delivered by pregnant women with a normal blood pressure, with a proportion of 1:1 to the HDP group in number, served as normal control. RESULTS: Then we compared the peripartum data and major complications between HDP group and control. The body weight, prelabor rupture of membrane (PROM), maternal age, cesarean section rate, fetal distress, small for gestational age (SGA), mechanical ventilation, RDS, necrotizing enterocolitis (NEC) (≥2 stage), Apgar score at 1 min, and mortality in HDP group showed statistical differences compared with those of the control (all p < 0.05). To compare the major complications among HDP subgroups, we classified the VLBW neonates of the HDP group into three subgroups including gestational hypertension group (n = 72), pre-eclampsia (PE) group (n = 222), and eclampsia group (n = 14), which showed significant differences in the fetal distress, Apgar score at 1 min, SGA, ventilation, RDS and NEC (≥2 stage) among these subgroups (all p < 0.05). Multivariate regression analysis showed that eclampsia and PE were the independent risk factors for SGA and NEC, respectively. CONCLUSION: HDP was associated with increased incidence of neonatal asphyxia, fatal distress, SGA, mechanical ventilation, RDS, NEC and mortality. Besides, eclampsia and PE were independent risk factors for SGA and NEC.

Research on the control rate of hypertension under family physician-contracted service.

BACKGROUND: Hypertension is one of the global public health problems. Family physician-contracted service (FPCS) is widely used in the health management of hypertension patients in China. The purpose of this study was to assess the effect of FPCS on hypertension control. METHODS: PubMed, Web of Science, the Cochrane Library, China National Knowledge Network, Chinese Scientific and Technological Journal Database (CQVIP), and Wanfang Database were searched for randomized controlled trials related to family physician-contracted service and hypertension control effect, and meta-analysis was performed on the literature meeting the inclusion criteria. The source of heterogeneity was discovered by meta-regression, and it was further investigated by subgroup analysis. The risk difference (RD) and 95% confidence interval (CI) were utilized as effect values. Evaluations of publication bias and sensitivity analysis were also conducted. RESULTS: A total of 46 studies were included, and the pooled RD suggested that FPCS could effectively improve the control rate by 19% (RD = 0.19; 95%CI: 0.16-0.21; P < 0.001; I2 = 59.3%). The average age (ß = 0.28; P = 0.05) and the intervention mode (ß = 0.36; P < 0.001) were found to be heterogeneous sources by the meta-regression. According to subgroup analysis, the hypertension control rates of the elderly and working-age population in the experimental group were 93.6% and 90.1%, respectively; the control rates of the "family physician" mode (FP), "family physician + patient" mode (FPP) and "family physician + patient + family member" mode (FPPF) in the experimental group were 90.1%, 94.4%, and 92.6%, respectively. The sensitivity analysis revealed steady results, with no discernible publication bias. CONCLUSIONS: The FPCS is beneficial to the control of hypertension. The control effect is influenced by average age and intervention mode. The control effect of hypertension in the elderly is better than that in the working-age population, and FPP and FPPF are more beneficial to the management of hypertension than FP. The quality and continuity of FPCS should receive more focus in the future, patient self-management and family support are also essential for managing hypertension.

An analysis of differences in Carbapenem-resistant Enterobacterales in different regions: a multicenter cross-sectional study.

OBJECTIVE: This study aimed to explore the characteristics of carbapenem-resistant Enterobacterales (CRE) patients in the intensive care unit (ICU) in different regions of Henan Province to provide evidence for the targeted prevention and treatment of CRE. METHODS: This was a cross-sectional study. CRE screening was conducted in the ICUs of 78 hospitals in Henan Province, China, on March 10, 2021. The patients were divided into provincial capital hospitals and nonprovincial capital hospitals for comparative analysis. RESULTS: This study involved 1009 patients in total, of whom 241 were CRE-positive patients, 92 were in the provincial capital hospital and 149 were in the nonprovincial capital hospital. Provincial capital hospitals had a higher rate of CRE positivity, and there was a significant difference in the rate of CRE positivity between the two groups. The body temperature; immunosuppressed state; transfer from the ICU to other hospitals; and use of enemas, arterial catheters, carbapenems, or tigecycline at the provincial capital hospital were greater than those at the nonprovincial capital hospital (P < 0.05). However, there was no significant difference in the distribution of carbapenemase strains or enzymes between the two groups. CONCLUSIONS: The detection rate of CRE was significantly greater in provincial capital hospitals than in nonprovincial capital hospitals. The source of the patients, invasive procedures, and use of advanced antibiotics may account for the differences. Carbapenem-resistant Klebsiella pneumoniae (CR-KPN) was the most prevalent strain. Klebsiella pneumoniae carbapenemase (KPC) was the predominant carbapenemase enzyme. The distributions of carbapenemase strains and enzymes were similar in different regions.

Research on multi-target data association of the infrared fish-eye warning system.

The multi-target data association method is studied in order to realize multi-target tracking in infrared fish-eye warning system. The Neural Joint Probabilistic Data Association (NJPDA) algorithm is analyzed. It is found that the NJPDA algorithm only considers the distance information between the measurement and the target in the data association process, and its tracking accuracy needs to be further improved. Therefore, a new method fused with direction information is proposed based on the NJPDA algorithm. The proposed algorithm defines the concept of direction difference, introduces the direction information of target motion, and modifies the likelihood function by Gaussian weighting method, so as to fuse the direction information of target motion into the calculation of data interconnection probability. Experimental results demonstrate that the tracking success rate of the proposed algorithm is nearly 10 % higher than that of JPDA and NJPDA algorithms and its consuming time meets the real-time requirement of the infrared fish-eye warning system.

The role of life satisfaction and living arrangements in the association between chronic disease and depression: a national cross-sectional survey.

Introduction: For middle-aged and older people, depression is a frequent and prevalent illness. The purpose of this study was to examine the moderating function of living arrangements in the mediating model as well as the mediating role of life satisfaction in the association between chronic diseases and depressive symptoms. Methods: The China Health and Retirement Longitudinal Study (CHARLS) provided the data for this investigation (2018). Respondents were grouped according to depression status to compare the differences between middle-aged and older people with different depression statuses. The moderating effect of living arrangements and the mediating effect of life satisfaction were tested using the Bootstrap program and the simple slope approach. Results: The population's total prevalence of depressive symptoms was 30.3%. According to the mediating effect research, middle-aged and older people with chronic diseases experienced substantial direct effects on depressive symptoms (ß = 1.011, p < 0.001). It has been established that life satisfaction has an 18.6% mediation effect between depressive symptoms and chronic diseases. Regarding the further moderating influence, it was discovered that chronic diseases had a more significant impact on the life satisfaction of middle-aged and older people who are in live alone than those who are living with others (ß = 0.037, p < 0.05). Conclusion: In middle-aged and older people, chronic diseases have a major influence on depressive symptoms. Life satisfaction mediated the relationship between chronic diseases and depressive symptoms, and living arrangements moderated the first part of the route in the mediation model. Therefore, life satisfaction and living arrangements should be important considerations to decrease the prevalence of depressive symptoms in middle-aged and older people.

Adaptive Transfer of Graph Neural Networks for Few-Shot Molecular Property Prediction.

Few-Shot Molecular Property Prediction (FSMPP) is an improtant task on drug discovery, which aims to learn transferable knowledge from base property prediction tasks with sufficient data for predicting novel properties with few labeled molecules. Its key challenge is how to alleviate the data scarcity issue of novel properties. Pretrained Graph Neural Network (GNN) based FSMPP methods effectively address the challenge by pre-training a GNN from large-scale self-supervised tasks and then finetuning it on base property prediction tasks to perform novel property prediction. However, in this paper, we find that the GNN finetuning step is not always effective, which even degrades the performance of pretrained GNN on some novel properties. This is because these molecule-property relationships among molecules change across different properties, which results in the finetuned GNN overfits to base properties and harms the transferability performance of pretrained GNN on novel properties. To address this issue, in this paper, we propose a novel Adaptive Transfer framework of GNN for FSMPP, called ATGNN, which transfers the knowledge of pretrained and finetuned GNNs in a task-adaptive manner to adapt novel properties. Specifically, we first regard the pretrained and finetuned GNNs as model priors of target-property GNN. Then, a task-adaptive weight prediction network is designed to leverage these priors to predict target GNN weights for novel properties. Finally, we combine our ATGNN framework with existing FSMPP methods for FSMPP. Extensive experiments on four real-world datasets, i.e., Tox21, SIDER, MUV, and ToxCast, show the effectiveness of our ATGNN framework.

PEPNet: A barotropic primitive equations-based network for wind speed prediction.

In wind speed prediction technologies, deep learning-based methods have achieved promising advantages. However, most existing methods focus on learning implicit knowledge in a data-driven manner but neglect some explicit knowledge from the physical theory of meteorological dynamics, failing to make stable and long-term predictions. In this paper, we explore introducing explicit physical knowledge into neural networks and propose Physical Equations Predictive Network (PEPNet) for multi-step wind speed predictions. In PEPNet, a new neural block called the Augmented Neural Barotropic Equations (ANBE) block is designed as its key component, which aims to capture the wind dynamics by combining barotropic primitive equations and deep neural networks. Specifically, the ANBE block adopts a two-branch structure to model wind dynamics, where one branch is physic-based and the other is data-driven-based. The physic-based branch constructs temporal partial derivatives of meteorological elements (including u-component wind, v-component wind, and geopotential height) in a new Neural Barotropic Equations Unit (NBEU). The NBEU is developed based on the barotropic primitive equations mode in numerical weather prediction (NWP). Besides, considering that the barotropic primitive mode is a crude assumption of atmospheric motion, another data-driven-based branch is developed in the ANBE block, which aims at capturing meteorological dynamics beyond barotropic primitive equations. Finally, the PEPNet follows a time-variant structure to enhance the model's capability to capture wind dynamics over time. To evaluate the predictive performance of PEPNet, we have conducted several experiments on two real-world datasets. Experimental results show that the proposed method outperforms the state-of-the-art techniques and achieve optimal performance.

Silver Ions Drive Ordered Self-Assembly Mechanisms and Inherent Properties of Lignin Nanoflowers.

Designing anisotropic lignin-based particles and promoting the high-value utilization of lignin have nowadays drawn much attention from scientists. However, systematic studies addressing the self-assembly mechanisms of anisotropic lignin-based particles are scarce. In this work, an interaction including the electrostatic forces and chelating forces between lignin and Ag+ was regulated via carboxymethylation modification. Subsequently, the aggregation morphology of carboxymethylated lignin in a Ag+ solution was observed via SEM. The result showed that a large number of Ag+ intercalated into the lignin molecules when the grafting degree of the carboxyl groups increased from 0.17 mmol/g to 0.53 mmol/g, which caused the lignin molecules to gradually transform from disordered blocks to ordered layers. Dynamics research indicated that the adsorption process of Ag+ in carboxymethylated lignin conforms to the Pseudo-first-order kinetic model. The saturated adsorption amount of Ag+ in the carboxymethylated lignin reached 1981.7 mg/g when the grafting rate of carboxyl groups increased to 0.53 mmol/g, which then fully intercalated into lignin molecules and formed a layered structure. The thermodynamic parameters showed that the thermal adsorption process conforms to the Langmuir model, which indicates that Ag+ is monolayer-adsorbed and intercalated into lignin molecules. Meanwhile, the ΔH values are more than 0, which suggests that this adsorption process is a endothermic reaction and that a higher temperature is conducive to an adsorption reaction. Therefore, self-assembly of lignin in a Ag+ solution under 70 °C is more conducive to the formation of a nanoflower structure, which is consistent with our experimental result. Finally, pH-responsive Pickering emulsions were successfully prepared using a lignin-based nanoflowers, which demonstrated their potential as a catalytic platform in the interface catalysis field. This work offers a deeper understanding into the formation mechanism of anisotropic lignin-based nanoflowers and hopes to be helpful for designing and preparing anisotropic lignin-based particles.

Prototype Completion for Few-Shot Learning.

Few-shot learning (FSL) aims to recognize novel classes with few examples. Pre-training based methods effectively tackle the problem by pre-training a feature extractor and then fine-tuning it through the nearest centroid based meta-learning. However, results show that the fine-tuning step makes marginal improvements. In this paper, 1) we figure out the reason, i.e., in the pre-trained feature space, the base classes already form compact clusters while novel classes spread as groups with large variances, which implies that fine-tuning feature extractor is less meaningful; 2) instead of fine-tuning feature extractor, we focus on estimating more representative prototypes. Consequently, we propose a novel prototype completion based meta-learning framework. This framework first introduces primitive knowledge (i.e., class-level part or attribute annotations) and extracts representative features for seen attributes as priors. Second, a part/attribute transfer network is designed to learn to infer the representative features for unseen attributes as supplementary priors. Finally, a prototype completion network is devised to learn to complete prototypes with these priors. Moreover, to avoid the prototype completion error, we further develop a Gaussian based prototype fusion strategy that fuses the mean-based and completed prototypes by exploiting the unlabeled samples. At last, we also develop an economic prototype completion version for FSL, which does not need to collect primitive knowledge, for a fair comparison with existing FSL methods without external knowledge. Extensive experiments show that our method: i) obtains more accurate prototypes; ii) achieves superior performance on both inductive and transductive FSL settings.

Enhancement of Li2ZrO3 Modification of the Cycle Life of N/S-Doped LiMn0.5Fe0.5PO4/C Composite Cathodes for Lithium Ion Batteries.

LiMn0.5Fe0.5PO4 cathodes have a high energy density but a poor rate and poor cycling performance. To this end, a series of N/S-doped LiMn0.5Fe0.5PO4/C composite cathodes modified with different contents of Li2ZrO3 were prepared by a solvothermal synthesis combined with calcination. The microstructure, chemical composition, and electrochemical properties are analyzed. Li2ZrO3 adsorbed on the LiMn0.5Fe0.5PO4 primary particles' surface in an amorphous state and on spherical particles (5-10 nm). The cycling life and rate performance of the cathodes are improved by the modification of a moderate amount of Li2ZrO3. The LMFP/NS-C/LZO1 shows available capacities of 166.8 and 118.9 mAh·g-1 at 0.1 and 5 C, respectively. The LMFP/NS-C/LZO1 shows no capacity loss after 100 cycles of charging/discharging (1 C), and still has a high capacity retention of 92.0% after 1000 cycles of charging/discharging (5 C). The excellent cycling performance of the LMFP/NS-C/LZO1 can be attributed to the improvement of the cathode microstructure and the electrochemical kinetics and the inhibition of Mn2+ dissolution by the moderate Li2ZrO3 modification.

Association of lymphopenia and RDW elevation with risk of mortality in acute aortic dissection.

OBJECTIVE: The study aimed to investigate whether lymphopenia and red blood cell distribution width (RDW) elevation are associated with an increased risk of mortality in acute aortic dissection (AAD). METHODS: This multicenter retrospective cohort study enrolled patients diagnosed with AAD by aortic computed tomographic angiography (CTA) from 2010 to 2021 in five teaching hospitals in central-western China. Cox proportional hazards regression and Kaplan-Meier curves were used in univariable and multivariable models. Clinical outcomes were defined as all-cause in-hospital mortality, while associations were evaluated between lymphopenia, accompanied by an elevated RDW, and risk of mortality. RESULTS: Of 1903 participants, the median age was 53 (interquartile range [IQR], 46-62) years, and females accounted for 21.9%. Adjusted increased risk of mortality was linearly related to the decreasing lymphocyte percentage (P-non-linearity = 0.942) and increasing RDW (P-non-linearity = 0.612), and per standard deviation (SD) of increment lymphocyte percentage and RDW was associated with the 26% (0.74, 0.64-0.84) decrement and 5% (1.05, 0.95-1.15) increment in hazard ratios (HRs) and 95% confidence intervals (CIs) of mortality, respectively. Importantly, lymphopenia and elevation of RDW exhibited a significant interaction with increasing the risk of AAD mortality (P-value for interaction = 0.037). CONCLUSIONS: Lymphopenia accompanied by the elevation of RDW, which may reflect the immune dysregulation of AAD patients, is associated with an increased risk of mortality. Assessment of immunological biomarkers derived from routine tests may provide novel perspectives for identifying the risk of mortality.

WDMNet: Modeling diverse variations of regional wind speed for multi-step predictions.

Regional wind speed prediction plays an important role in the development of wind power, which is usually recorded in the form of two orthogonal components, namely U-wind and V-wind. The regional wind speed has the characteristics of diverse variations, which are reflected in three aspects: (1) The spatially diverse variations of regional wind speed indicate that wind speed has different dynamic patterns at different positions; (2) The distinct variations between U-wind and V-wind denote that U-wind and V-wind at the same position exhibit different dynamic patterns; (3) The non-stationary variations of wind speed represent that the intermittent and chaotic nature of wind speed. In this paper, we propose a novel framework named Wind Dynamics Modeling Network (WDMNet) to model the diverse variations of regional wind speed and make accurate multi-step predictions. To jointly capture the spatially diverse variations and the distinct variations between U-wind and V-wind, WDMNet leverages a new neural block called Involution Gated Recurrent Unit Partial Differential Equation (Inv-GRU-PDE) as its key component. The block adopts involution to model spatially diverse variations and separately constructs hidden driven PDEs of U-wind and V-wind. The construction of PDEs in this block is achieved by a new Involution PDE (InvPDE) layers. Besides, a deep data-driven model is also introduced in Inv-GRU-PDE block as the complement to the constructed hidden PDEs for sufficiently modeling regional wind dynamics. Finally, to effectively capture the non-stationary variations of wind speed, WDMNet follows a time-variant structure for multi-step predictions. Comprehensive experiments have been conducted on two real-world datasets. Experimental results demonstrate the effectiveness and superiority of the proposed method over state-of-the-art techniques.

Discharge against medical advice among infants with 24-31 weeks' gestation admitted to Chinese neonatal intensive care units: A multicenter cohort study.

Background: Previous studies demonstrated high rates of discharge against medical advice (DAMA) among very preterm infants (VPIs) in China. Objectives: The aim of this study was to investigate the concurrent incidence, variation, and predictors of DAMA, along with the effect of DAMA on mortality of VPIs in China using data from the Chinese Neonatal Network (CHNN). Methods: All infants born at 24-31 completed weeks' gestation and admitted to 57 CHNN neonatal intensive care units (NICUs) in 2019 were included for this cohort study, excluding infants with major congenital anomalies. Patient information was prospectively collected using the CHNN database. Multivariable log-linear regression analysis was used to assess the association of perinatal factors and DAMA. Results: A total of 9,442 infants born at 24-31 completed weeks' gestation and admitted to 57 CHNN participating sites in 2019 were included in the study. Overall, 1,341 infants (14.2%) were discharged against medical advice. Rates of DAMA decreased with increasing gestational age (GA), and infants with lower GA were discharged earlier. DAMA infants had significantly higher rates of necrotizing enterocolitis, severe brain impairment, and bronchopulmonary dysplasia than non-DAMA infants. A total of 58.2% DAMA infants were predicted to die after discharge. The attributable risk percentage of mortality among DAMA infants was 92.4%. Younger maternal age, lower gestational age, small for gestational age, and Apgar score ≤3 at 5 min were independently associated with an increased risk of DAMA, while infants with antenatal steroids were less likely to be DAMA. Conclusion: The rate of DAMA in preterm infants between 24 and 31 weeks' gestation remained high in China with a significant impact on the mortality rates. Continuous efforts to reduce DAMA would result in substantial improvement of outcomes for VPIs in China.

One-Pot Synthesis of LiFePO4/N-Doped C Composite Cathodes for Li-ion Batteries.

LiFePO4/N-doped C composites with core-shell structures were synthesized by a convenient solvothermal method. Cetyltrimethylammonium bromide (CTAB) and glucose were used as nitrogen and carbon sources, respectively. The growth of LiFePO4 nanocrystals was regulated by CTAB, resulting in an average particle size of 143 nm for the LiFePO4/N-doped C. The N atoms existed in the carbon of LiFePO4/N-doped C in the form of pyridinic N and graphitic N. The LiFePO4/N-doped C composites delivered discharge specific capacities of 160.7 mAh·g-1 (0.1 C), 128.4 mAh·g-1 (5 C), and 115.8 mAh·g-1 (10 C). Meanwhile, no capacity attenuation was found after 100 electrochemical cycles at 1 C. N-doping enhanced the capacity performance of the LiFePO4/C cathode, while the core-shell structure enhanced the cycle performance of the cathode. The electrochemical test data showed a synergistic effect between N-doping and core-shell structure on the enhancement of the electrochemical performance of the LiFePO4/C cathode.

Smart Hierarchical Zeolitic Imidazolate Framework-Coated Stainless Steel Meshes with Switchable Wettability for Oil/Water Separation.

Selective filtration based on superwetting materials has brought about widespread attention in the field of oil/water separation. In this study, a ZIF-L@8-coated stainless steel mesh (ZIF-L@8-coated SSM) was prepared via in situ growth of two-dimensional leaf-shaped ZIF-L nanosheets on SSM, followed by heterogeneous epitaxial growth of ZIF-8 on a ZIF-L coating. The synthesized ZIF-L@8-coated SSM with a hierarchical micro/nanoscale structure exhibited outstanding switchable wettability between underwater superoleophobicity and underoil superhydrophobicity upon respective prewetting using water and oil without additional external stimuli. It possessed excellent separation performances and stabilities with respect to various types of oil/water mixtures. The switchable wettability mechanism was analyzed and elucidated in detail. The synthesized ZIF-L@8-coated SSM with switchable wettability in this study would have great potential in on-demand oil/water separation.

Facile synthesis of S-doped LiFePO4@N/S-doped carbon core-shell structured composites for lithium-ion batteries.

Heteroatom-doped carbon can significantly improve the electrochemical performance of LiFePO4cathodes, but it is limited by the complex preparation process and expensive dopants. A self-assembled S-doped LiFePO4@N/S-doped C core-shell structured composites were synthesized by a convenient solvothermal method are reported. The structure and the electrochemical performance of the composites were characterized. In the S-doped LiFePO4@N/S-doped C composites, the glucose-derived carbon microspheres were attached by LiFePO4/C particles to form secondary particles in the core-shell structure. The thioacetamide regulated the morphology of LiFePO4/C particles and provided N and S atoms to dope the composites. The S-doped LiFePO4@N/S-doped C composites delivered specific discharge capacities of 157.81 mAh g-1at 0.1 C and 121.26 mAh g-1at 5 C, and capacity retention of 99.88% after 100 charge/discharge cycles. The excellent electrochemical performance of the S-doped LiFePO4@N/S-doped C composites can be attributed to the synergism of thioacetamide and glucose.

DynamicNet: A time-variant ODE network for multi-step wind speed prediction.

Wind power is a new type of green energy. Though it is economical to access and gather such energy, effectively matching the energy with consumers' demand is difficult, because of the fluctuate, intermittent and chaotic nature of wind speed. Hence, multi-step wind speed prediction becomes an important research topic. In this paper, we propose a novel deep learning method, DyanmicNet, for the problem. DynamicNet follows an encoder-decoder framework. To capture the fluctuate, intermittent and chaotic nature of wind speed, it leverages a time-variant structure to build the decoder, which is different from conventional encoder-decoder methods. In addition, a new neural block (ST-GRU-ODE) is developed, which can model the wind speed in a continuous manner by using the neural ordinary differential equation (ODE). To enhance the prediction performance, a multi-step training procedure is also put forward. Comprehensive experiments have been conducted on two real-world datasets, where wind speed is recorded in the form of two orthogonal components namely U-Wind and V-Wind. Each component can be illustrated as wind speed images. Experimental results demonstrate the effectiveness and superiority of the proposed method over state-of-the-art techniques.

Identification of potential candidate proteins for reprogramming spinal cord-derived astrocytes into neurons: a proteomic analysis.

Our previous study has confirmed that astrocytes overexpressing neurogenic differentiation factor 1 (NEUROD1) in the spinal cord can be reprogrammed into neurons under in vivo conditions. However, whether they can also be reprogrammed into neurons under in vitro conditions remains unclear, and the mechanisms of programmed conversion from astrocytes to neurons have not yet been clarified. In the present study, we prepared reactive astrocytes from newborn rat spinal cord astrocytes using the scratch method and infected them with lentivirus carrying NEUROD1. The results showed that NEUROD1 overexpression reprogrammed the cultured reactive astrocytes into neurons in vitro with an efficiency of 13.4%. Using proteomic and bioinformatic analyses, 1952 proteins were identified, of which 92 were differentially expressed. Among these proteins, 11 were identified as candidate proteins in the process of reprogramming based on their biological functions and fold-changes in the bioinformatic analysis. Furthermore, western blot assay revealed that casein kinase II subunit alpha (CSNK2A2) and pinin (PNN) expression in NEUROD1-overexpressing reactive astrocytes was significantly increased, suggesting that NEUROD1 can directly reprogram spinal cord-derived reactive astrocytes into neurons in vitro, and that the NEUROD1-CSNK2A2-PNN pathway is involved in this process. This study was approved by the Animal Ethics Committee of Fujian Medical University, China (approval No. 2016-05) on April 18, 2016.

The Effect of Atrial Septal Defect in the Treatment of ARDS with Left Ventricular Dysfunction Simulating Severe COVID-19.

OBJECTIVE: To explore the effect of atrial septal defect (ASD) and venoarterial extracorporeal membrane oxygenation (VA-ECMO) in the treatment of ARDS combined with left ventricular dysfunction (LVD) to find a new effective method for treating severe COVID-19 patients. MATERIALS AND METHODS: Five large animal ARDS models of sheep were established by intravenous injection of Lipopolysaccharide. ASD was made under general anesthesia and VA-ECMO was simulated by extracorporeal circulation machine. The oxygenation of peripheral blood, systemic circulation, and cardiac function were observed under conditions of closed and opened ASD, and the significance of ASD shunt in improving cardiopulmonary function was evaluated. RESULTS: With ASD closed, the atrial shunts disappeared, the peripheral artery pressure of oxygen(PaO2): 141.2±21.4mmHg, the oxygenation index (PaO2/FiO2): 353.0±53.5, the mean blood pressure (MAP): 49.3±13.5 mmHg, the heart was full; with ASD opened, the left-to-right shunt was observed, PaO2: 169.3±18.9mmHg, PaO2/FiO2: 423.3±47.3, MAP: 68.2±16.1 mmHg, the range of cardiac motion significantly increased, heart beat was powerful, and systemic circulation significantly improved. Statistical analysis showed that there were significant differences between opened and closed ASD (P < .01). CONCLUSION: ASD plus VA-ECMO is an effective method for the treatment of ARDS combined with LVD, which is the main cause of death in severe COVID-19 patients. However, further clinical validation is needed.