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The key technology in enzymatic extraction of oil in the aqueous system is the enzymatic hydrolysis and demulsification performance. The process of extracting rice bran oil by enzymatic method under aqueous system is studied in this research. The results show that more than 84.10% rice bran oil extraction yield could be obtained under the following procedure and conditions. The extruded rice bran is screened through a 40-mesh sieve and mixed with ultrapure water at a ratio of 1∶7.5 (w/v), after which 2% (w/w) Alcalase 2.4 L is added to the mixture and the system is continuously incubated for 150 minutes at 57 ℃ and pH 9.0. After centrifugation, the pH of the emulsion to 7.0 reacting is adjusted further at 60 ℃ for 60 minutes to obtain the oil by breaking the emulsion. The quality of rice bran oil extracted, especially the content of bioactive substances, is obviously better than that extracted by the traditional solvent method. In addition, carbohydrase could not improve the oil extraction yield, while alkaline conditions are more favorable for rice bran oil extraction. Alkaline conditions and CaCl2 treatment are not conducive to demulsification, while 20%～30%ethanol treatment could improve the demulsification rate of the emulsion. The technology can promote the applications of aqueous enzymatic method in the vegetable oil manufacture industry, as well as the utilization of rice bran.

Summary: As the limited carrier densities in atomic thin materials can be well controlled by electrostatic gates, p-n junctions based on two-dimensional materials in the coplanar split-gate configuration can work as photodetectors or light-emitting diodes. These coplanar gates can be fabricated in a simple one-step lithography process and are frequently used in hybrid integration with on-chip optical structures. However, the polarization-dependent responsivity of such a configuration is less explored in the near-infrared band, and a clear understanding is still missing. Here we fabricate near-infrared tunable multiple modes twisted bilayer graphene photodetector enabled by the coplanar split-gate control and confirm that the photothermoelectric effect governs the photovoltage mechanism of the p-n junction mode. Our study also elucidates that the discrepancy of the responsivities under different linear polarizations is owing to the different cavity modes and provides a valuable example for designing chip-integrated optoelectronic devices.

The environmental impact of the chiral fungicide epoxiconazole and its chiral transformation products (TPs) on non-target organisms and the environment has become a significant concern due to its widespread use in agricultural practice. Enantioselectivity studies of parent contaminants cannot adequately assess the complexity of its chiral TPs in the environment. This study aimed to investigate the environmental behavior of epoxiconazole in an earthworm-soil system. 2S,3R-(–)-epoxiconazole was preferentially enriched in earthworms during the accumulation phase (p 0.8 was observed for the TPs in different matrices. The CYP450 monooxygenase of earthworm was significant activated. In vitro enzyme metabolism experiments (earthworm microsomes and recombinant CYP450 enzymes CYP2A6, CYP 2C9, and CYP 3A4) were carried out to further explain the biotransformation mechanism of epoxiconazole in earthworm. This study provides new evidence of enantiomeric biotransformation of chiral fungicide epoxiconazole in the earthworm-soil system and could provide valuable insights into their environmental risk assessment.

The emergency response is crucial in preventing and mitigating urban floods. Both remote sensing and social media data offer distinct advantages in large-scale flood monitoring and near-real-time flood monitoring. However, current research lacks a thorough exploration of the application of social media data and remote sensing imagery in the urban flood emergency response. To address this issue, this paper, while extracting disaster information based on social media data, deeply mines the spatiotemporal distribution characteristics and dynamic spatial accessibility of rescue points. Furthermore, SAR imagery and social media data for monitoring urban flooding are compared. This study took the Zhengzhou 7.20 urban flood as a case study and created a methodological framework to quickly extract flood disaster information (flood, landslide, and rescue points) using these two types of data; spatiotemporal analysis and random forest classification were also conducted to mine valuable information. Temporally, the study revealed that disaster information did not increase proportionally with the amount of rainfall during the rainfall process. Spatially, specific regions with higher susceptibility to flooding, landslides, and rescue points were identified, such as the central region characterized by low drainage standards and high-density urban areas, as well as the eastern region with low-lying terrain. Moreover, this study examined the spatial accessibility of rescue resources in real flood scenarios and found that their service coverage varied throughout the day during and after the disaster. In addition, social media excelled in high-density urban areas’ flood point extraction, while SAR performed better in monitoring floods at the edges of low-density urban areas and large water bodies, allowing them to complement each other, to a certain extent. The findings of this study provide scientific reference value for the optimal selection of rescue paths and the allocation of resources in the emergency response to urban floods caused by extreme rainstorms.

Three new dimeric sorbicillinoids (1–3) and one new 3,4,6-trisubstituted α-pyrone (5), along with seven analogues (4 and 6–11), were isolated from the mangrove endophytic fungus Trichoderma reesei SCNU-F0042 under the guidance of molecular networking approach. Their chemical structures were established by 1D and 2D NMR HR-ESI-MS and ECD analysis. In a bioassay, compound 2 exhibited moderate SARS-CoV-2 inhibitory activity with an EC50 value of 29.0 μM.

We investigate the MEMS resonant cantilevers for high-performance thermogravimetric analysis (TGA) of chemical decomposition, featuring high accuracy and minimized thermal lag. Each resonant cantilever is integrated with a microheater for sample heating near the free end, which is thermally isolated from the resonance excitation and readout elements at the fixed end. Combining finite element modeling and experiments, we demonstrate that the sample loading region can stabilize within ~11.2 milliseconds in response to a step heating of 500 °C, suggesting a very fast thermal response of the MEMS resonant cantilevers of more than 104 °C/s. Benefiting from such a fast thermal response, we perform high-performance TG measurements on basic copper carbonate (Cu2(OH)2CO3) and calcium oxalate monohydrate (CaC2O4·H2O). The measured weight losses better agree with the theoretical values with 5–10 times smaller thermal lags at the same heating rate, compared with those measured by using conventional TGA. The MEMS resonant cantilevers hold promise for highly accurate and efficient TG characterization of materials in various fields.

Abstract The incidence of bicuspid aortic valves (BAV) is high in the whole population, BAV-related thoracic aortic aneurysm (TAA) is accompanied by many adverse vascular events. So far, there are two key points in dealing with BAV-related TAA. First is fully understanding on its pathogenesis. Second is optimizing surgical intervention time. This review aims to illustrate the potential role of miRNAs in both aspects, that is, how miRNAs are involved in the occurrence and progression of BAV-related TAA, and the feasibilities of miRNAs as biomarkers.

Abstract Background Gout is initiated by the precipitation of monosodium urate (MSU) crystals within the joints and soft tissues, and it can eventually cause acute or chronic arthritis. MSU crystals trigger, amplify, and maintain a strong inflammatory response through promoting proinflammatory activity. In this study, the therapeutic effects of Stephania hainanensis (S. hainanensis) total alkaloid (SHA) were tested and evaluated on MSU-induced acute gouty arthritis in a mouse model. Methods After oral administration of SHA (10 or 20 mg/kg) or the antigout medicine colchicine (0.5 mg/kg) once daily for 3 consecutive days, MSU crystals suspended in saline (2.5 mg/50 μl) were intradermally injected into the right paw of the mice. Then, SHA and colchicine were administered for another 2 days. During this period, swelling of the ankle and clinical scores were measured at 12, 24, and 48 h postinjection. After the mice were euthanized, inflammatory cytokine expression and paw tissue inflammation-related gene and protein expression, and a histopathological analysis was performed. Results SHA had obvious therapeutic effects on MSU-induced acute gouty arthritis in mice. SHA alleviated ankle swelling and inhibited the production of cytokines, such as IL-1β and TNF-α. In addition, NLRP3, Caspase-1 and IL-1β, which are activated by MSU were also suppressed by SHA. The histological evaluation showed that SHA relieved the infiltration of inflammation around the ankle. Conclusions These results suggest that SHA is capable of anti-inflammatory activities and may be useful for treating gouty arthritis.

Abstract Background Understanding the functional effects of non-coding variants is important as they are often associated with gene-expression alteration and disease development. Over the past few years, many computational tools have been developed to predict their functional impact. However, the intrinsic difficulty in dealing with the scarcity of data leads to the necessity to further improve the algorithms. In this work, we propose a novel method, employing a semi-supervised deep-learning model with pseudo labels, which takes advantage of learning from both experimentally annotated and unannotated data. Results We prepared known functional non-coding variants with histone marks, DNA accessibility, and sequence context in GM12878, HepG2, and K562 cell lines. Applying our method to the dataset demonstrated its outstanding performance, compared with that of existing tools. Our results also indicated that the semi-supervised model with pseudo labels achieves higher predictive performance than the supervised model without pseudo labels. Interestingly, a model trained with the data in a certain cell line is unlikely to succeed in other cell lines, which implies the cell-type-specific nature of the non-coding variants. Remarkably, we found that DNA accessibility significantly contributes to the functional consequence of variants, which suggests the importance of open chromatin conformation prior to establishing the interaction of non-coding variants with gene regulation. Conclusions The semi-supervised deep learning model coupled with pseudo labeling has advantages in studying with limited datasets, which is not unusual in biology. Our study provides an effective approach in finding non-coding mutations potentially associated with various biological phenomena, including human diseases.

Abstract Background The more selective second-generation BTK inhibitors (BTKi) Acalabrutinib and Zanubrutinib and the first-generation BTKi Ibrutinib are highlighted by their clinical effectiveness in mantle cell lymphoma (MCL), however, similarities and differences of their biological and molecular effects on anti-survival of MCL cells induced by these BTKi with distinct binding selectivity against BTK remain largely unknown. Methods AlamarBlue assays were performed to define cytotoxicity of BTKi against MCL cells, Jeko-1 and Mino. Cleaved PARP and caspase-3 levels were examined by immunoblot analysis to study BTKi-induced apoptotic effects. Biological effects of BTKi on MCL-cell chemotaxis and lipid droplet (LD) accumulation were examined in Jeko-1, Mino and primary MCL cells via Transwell and Stimulated Raman scattering imaging analysis respectively. Enzyme-linked immunoassays were used to determine CCL3 and CCL4 levels in MCL-cell culture supernatants. RNA-seq analyses identified BTKi targets which were validated by quantitative RT-PCR (qRT-PCR) and immunoblot analysis. Results Acalabrutinib and Zanubrutinib induced moderate apoptosis in Ibrutinib high-sensitive JeKo-1 cells and Ibrutinib low-sensitive Mino cells, which was accompanied by cleaved PARP and caspase-3. Such effects might be caused by the stronger ability of Ibrutinib to upregulate the expression of pro-apoptotic genes, such as HRK, GADD45A, and ATM, in JeKo-1 cells than in Mino cells, and the expression of such apoptotic genes was slightly changed by Acalabrutinib and Zanubrutinib in both JeKo-1 and Mino cells. Further, Acalabrutinib, Zanubrutinib and Ibrutinib reduced MCL-cell chemotaxis with similar efficiency, due to their similar abilities to downmodulate chemokines, such as CCL3 and CCL4. Also, these three BTKi similarly suppressed MCL-cell LD accumulation via downregulating lipogenic factors, DGAT2, SCD, ENPP2 and ACACA without significant differences. Conclusion BTKi demonstrated differential capacities to induce MCL-cell apoptosis due to their distinct capabilities to regulate the expression of apoptosis-related genes, and similar biological and molecular inhibitory effects on MCL-cell chemotaxis and LD accumulation.

Posaconazole (POS) has been reported to present potential antitumor activity for glioblastoma (GBM). However, its molecular mechanisms remain unclear. In this study, we found that POS has potent cytotoxicity and inhibits cell viability and proliferation in GBM. In addition, we adopted a sphere formation assay to detect the self-renewal capacity, performed western blotting to measure cancer stem-like cells (CSCs) marker proteins (CD133, SOX2, Nanog and Oct4) and applied flow cytometry to monitor the subpopulation of CD144+/CD33+ cells, and the results all demonstrated that POS can remarkably weaken CSCs stemness. Furthermore, western blotting, immunoflurescence, transmission electron microscopy and acridine orange staining were performed to detect autophagy-related proteins (LC3, SQSTM1, Beclin 1 and Atg5), count the numbers of endogenous LC3 puncta, visually observe the ultrastructural morphology of autophagosomes and judge the formation of acidic vesicular organelles, respectively, and the results validated that POS promotes autophagy induction. Importantly, the suppressive effect of POS on CSCs stemness was partially relieved when autophagy was blocked by the autophagy inhibitor chloroquine (CQ) or Atg5 shRNA. Bioinformatic techniques, including weighted gene coexpression network analysis (WGCNA), gene set difference analysis (GSVA) and KEGG pathway analysis, combined with experimental validations showed that survivin, which is implicated in both autophagy and the stem cell index, is one of the target proteins of POS and that POS weakens CSCs stemness via suppressing the Wnt/β-catenin signaling pathway in GBM. Besides, POS-induced autophagy and the Wnt/β-catenin signaling pathway are negative regulators for each other. Finally, the antitumor activity of POS was confirmed in GBM xenograft models in vivo. Consistent with the in vitro conclusions, POS upregulated the expression of LC3 and decreased the expression of CD133, survivin and β-catenin, as shown by the immunohistochemistry analysis. In summary, this work provides an experimental foundation for exploiting POS as a CSCs-targeting antitumor drug for GBM treatment.

The dual tyrosine kinase (EGFR/HER2) inhibitor lapatinib is currently used to clinically treat HER2-positive breast cancer. However, a majority of patients do not respond to lapatinib therapy within 6 months. Therefore, potentiating the anti-tumor effect of lapatinib by combination treatment has a great potential to overcome the obstacle. Herein, we aim to investigate the anti-tumor activity of lapatinib in combination with brusatol and explore the potential mechanism involved in the combinatorial treatment. Our findings revealed that the Nrf2 inhibitor brusatol potently enhanced the anti-tumor effect of lapatinib against SK-BR-3, SK-OV-3 and AU565 cancer cells in a synergistic manner. Furthermore, we found that lapatinib plus brusatol more effectively decreased Nrf2 level and induced ROS generation in both SK-BR-3 and SK-OV-3 cells. Moreover, we also observed a significant reduction on the phosphorylation of HER2, EGFR, AKT and ERK1/2 in SK-BR-3 and SK-OV-3 cells when treated with lapatinib plus brusatol compared to either agent alone. More importantly, brusatol significantly augmented the anti-tumor effects of lapatinib in the SK-OV-3 xenograft model. In summary, these data provide a potential rationale for the combination of brusatol and lapatinib on the treatment of HER2-positive cancers.

Gifted children and normal controls can be distinguished by analyzing the structural connectivity (SC) extracted from MRI data. Previous studies have improved classification accuracy by extracting several features of the brain regions. However, the limited size of the database may lead to degradation when training deep neural networks as classification models. To this end, we propose to use a data augmentation method by adding artificial samples generated using graph empirical mode decomposition (GEMD). We decompose the training samples by GEMD to obtain the intrinsic mode functions (IMFs). Then, the IMFs are randomly recombined to generate the new artificial samples. After that, we use the original training samples and the new artificial samples to enlarge the training set. To evaluate the proposed method, we use a deep neural network architecture called BrainNetCNN to classify the SCs of MRI data with and without data augmentation. The results show that the data augmentation with GEMD can improve the average classification performance from 55.7 to 78%, while we get a state-of-the-art classification accuracy of 93.3% by using GEMD in some cases. Our results demonstrate that the proposed GEMD augmentation method can effectively increase the limited number of samples in the gifted children dataset, improving the classification accuracy. We also found that the classification accuracy is improved when specific features extracted from brain regions are used, achieving 93.1% for some feature selection methods.

Summary: Background: Albuminuria is a marker of vascular dysfunction and is associated with chronic renal and cardiovascular diseases. Data on the association between the longitudinal patterns of weight change early in life and albuminuria later in life are limited. We aimed to identify the body mass index (BMI) trajectory across a 30-year span and evaluate its association with middle-age albuminuria. Methods: Of the 4623 participants aged 6–18-year-old recruited by Hanzhong Adolescent Hypertension Study cohort in northern China from March 10, 1987 to June 3, 2017, a total of 1,825 participants followed up with 6 visits over 30 years were enrolled. Group-based trajectory modeling was used to identify distinct BMI trajectories in longitudinal analyses. Albuminuria was defined as a urinary albumin-to-creatinine ratio (uACR) ≥ 30 mg/g. Findings: Three distinct BMI trajectories were identified: low-increasing (n = 671, 36.8%), moderate-increasing (n = 940, 51.5%), and high-increasing (n = 214, 11.7%); male participants exhibited a steeper increase in BMI than females. The uACR was increased linearly from the low- to high-increasing group. A total of 201 individuals developed albuminuria, with an incidence of 11.0%. Compared with the low-increasing group, the odds ratio (OR) of albuminuria in middle age was 2.13(95% confidence interval [CI]: 1.26 to 3.61) for the high-increasing group after full adjustment for age, sex, smoking, alcohol consumption, marital status, systolic blood pressure, diabetes, and hyperlipidemia. The unadjusted ORs of the high-increasing BMI group were 5.08 (2.76–9.37) for males and 3.45 (1.78–6.69) for females, and the association remained significant in males in the fully adjusted models. Interpretation: Higher BMI trajectories are associated with higher uACR and an increased risk of albuminuria in middle age, especially in males. Identifying long-term BMI trajectories from an early age may assist in predicting the risk of renal diseases and cardiovascular disease later in life. Funding: This work was supported by the National Natural Science Foundation of China (81600327, 82070437, 81870319, 82070549, and 82170437), Natural Science Basic Research Program of Shaanxi Province (2021JM-257 and 2021JM-588), Institutional Foundation of the First Affiliated Hospital of Xi'an Jiaotong University (2019QN-06 and 2021ZXY-14), the Clinical Research Award of the First Affiliated Hospital of Xi'an Jiaotong University of China (XJTU1AF-CRF-2019-004, XJTU1AF2021CRF-021, and XJTU1AFCRF-2017-021), Research Incubation Fund of Xi'an People's Hospital (FZ-61), Grants from the Major Chronic Non-communicable Disease Prevention and Control Research Key Project of the Ministry of Science and Technology of China (2017YFC1307604 and 2016YFC1300104).

In order to explore an environmental removal method of grain mycotoxins and to overcome the problem of poor stability of biodegradation method, the Tibetan yeast strains were selected as the research object, and the strains with better degradation effects on zearalenone (ZEN) were screened to explore the functions and mechanisms in this study.The results showed that Tibet Rhodotorula mucilaginosa had a good degradation effect on ZEN, and the degradation effect gradually improved with the increase of the bacterial concentration.Through the evaluation of the toxin removal effect of different yeast treatment solutions, it was found that the removal mechanism of the yeast on ZEN was mainly adsorption, accompanied by a certain degree of intracellular biodegradation.The degradation products of ZEN were determined by liquid chromatography-mass spectrometry.It was found that the degradation products may be zearalenol and zearalenone, and the safety of the degradation products needed further verification.The stress tolerance test of Tibet R.mucilaginosa showed that it had a certain tolerance to low temperature and oxidative stress.

Abstract Quantum simulation can be implemented in pure digital or analog ways, each with their pros and cons. By taking advantage of the universality of a digital route and the efficiency of analog simulation, hybrid digital–analog approaches can enrich the possibilities for quantum simulation. We use a hybrid approach to experimentally perform a quantum simulation of phase-controlled dynamics resulting from a closed-contour interaction (CCI) within certain multi-level systems in superconducting quantum circuits. Due to symmetry constraints, such systems cannot host an inherent CCI. Nevertheless, by assembling analog modules corresponding to their natural evolutions and specially designed digital modules constructed from standard quantum logic gates, we can bypass such constraints and realize an effective CCI in these systems. Based on this realization, we demonstrate a variety of related and interesting phenomena, including phase-controlled chiral dynamics, separation of chiral enantiomers, and a mechanism to generate entangled states based on CCI.

Understanding light propagation in skin tissues with complex blood vessels can help improve clinical efficacy in the laser treatment of cutaneous vascular lesions. The voxel-based Monte Carlo (VMC) algorithm with simple blood vessel geometry is commonly used in studying the law of light propagation in tissues. However, unavoidable errors are expected in VMC because of the zigzag polygonal interface. A tetrahedron-based Monte Carlo with extended boundary condition (TMCE) solver is developed to discretize complex tissue boundaries accurately. Tetrahedra are generated along the interface, resulting in a polyhedron approximation to match the real interface. A comparison between TMCE and VMC shows neglected differences in the overall distribution of energy deposition of different models, but poor adaptability of the curved tissue interface in VMC leads to a higher energy deposition error than TMCE in a mostly deposited region in blood vessels. Replacing the real blood vessel with a cylinder-shaped vessel shows an error lower than that caused by VMC. Statistical significance analysis of energy deposition by TMCE shows that mean curvature has stronger relationship with energy deposition than the Gaussian curvature, which indicates the importance of this geometric parameter in predicting photon behavior in vascular lesions.

We report the experimental observation of the spin-wave moiré edge and cavity modes using Brillouin light scattering spectromicroscopy in a nanostructured magnetic moiré lattice consisting of two twisted triangle antidot lattices based on an yttrium iron garnet thin film. Spin-wave moiré edge modes are detected at an optimal twist angle and with a selective excitation frequency. At a given twist angle, the magnetic field acts as an additional degree of freedom for tuning the chiral behavior of the magnon edge modes. Micromagnetic simulations indicate that the edge modes emerge within the original magnonic band gap and at the intersection between a mini flatband and a propagation magnon branch. Our theoretical estimate for the Berry curvature of the magnon-magnon coupling suggests a nontrivial topology for the chiral edge modes and confirms the key role played by the dipolar interaction. Our findings shed light on the topological nature of the magnon edge mode for emergent moiré magnonics.

Abstract Owing to the merits of low cost, high safety and environmental benignity, rechargeable aqueous Zn-based batteries (ZBs) have gained tremendous attention in recent years. Nevertheless, the poor reversibility of Zn anodes that originates from dendrite growth, surface passivation and corrosion, severely hinders the further development of ZBs. To tackle these issues, here we report a Janus separator based on a Zn-ion conductive metal–organic framework (MOF) and reduced graphene oxide (rGO), which is able to regulate uniform Zn2+ flux and electron conduction simultaneously during battery operation. Facilitated by the MOF/rGO bifunctional interlayers, the Zn anodes demonstrate stable plating/stripping behavior (over 500 h at 1 mA cm−2), high Coulombic efficiency (99.2% at 2 mA cm−2 after 100 cycles) and reduced redox barrier. Moreover, it is also found that the Zn corrosion can be effectively retarded through diminishing the potential discrepancy on Zn surface. Such a separator engineering also saliently promotes the overall performance of Zn|MnO2 full cells, which deliver nearly 100% capacity retention after 2000 cycles at 4 A g−1 and high power density over 10 kW kg−1. This work provides a feasible route to the high-performance Zn anodes for ZBs.

Abstract Background BRAFV600E mutation is the most common mutation in thyroid cancer. It strongly activates MAPK/ERK pathway and indicates an invasive subtype of thyroid cancer. PLX4032 is a selective oral inhibitor of the BRAFV600 kinase although with limited effect in treating this panel of thyroid cancer, due to the feedback activation of MAPK/ERK as well as PI3K/AKT pathways. It was investigated that Vitamin C plays a positive role in inhibiting these pathways in thyroid cancer. However, whether Vitamin C could enhance the antitumor effect of PLX4032 remains largely unclear. Methods The antitumor efficacy of combination therapy with PLX4032 and Vitamin C on BRAFMT thyroid cancer cell was assessed by the MTT assay, EdU assay and colony formation, Chou-Talalay way was employed to analyze the synergistic effect. Flow cytometry were employed to assess cells’ apoptosis and cell cycle arrest in response to combination therapy. Xenograft models were used to test its in vivo antitumor activity. Western blot and IHC were applied to investigate the mechanism underlying synergistic effect. Results PLX4032 or Vitamin C monotherapy was mildly effective in treating BRAFMT thyroid cancer cell and xenografts model. The combination therapy significantly inhibited cancer cell proliferation and tumor growth in nude mice, and induced cell apoptosis and cell cycle arrest compared to either monotherapy. PLX4032 monotherapy induced feedback activation of MAPK/ERK as well as PI3K/AKT pathway; while combination therapy significantly relieved this feedback. Conclusion Vitamin C promotes the antitumor effect of PLX4032 in BRAFMT thyroid cancer cell and xenografts model via relieving the feedback activation of MAPK/ERK as well as PI3K/AKT pathway. PLX4032/Vitamin C combination may be a potential therapeutic approach to treat BRAFMT thyroid cancer.

Electroencephalography (EEG) is a non-invasive technology used for the human brain-computer interface. One of its important applications is the evaluation of the mental state of an individual, such as workload estimation. In previous works, common spatial pattern feature extraction methods have been proposed for the EEG-based workload detection. Recently, several novel methods were introduced to detect EEG pattern workloads. However, it is still unknown which one of these methods is the one that offers the best performance for the workload EEG pattern feature detection. In this article, four methods were used to extract workload EEG features: (a) common spatial pattern feature extraction; (b) temporally constrained sparse group spatial pattern feature extraction; (c) EEGnet; and (d) the new proposed shallow convolutional neural network for workload estimation (WLnet). The classification accuracy of these four methods was compared. Experimental results demonstrate that the proposed WLnet achieved the best detection accuracy in both stress and non-stress conditions. We believe that the proposed methods may be relevant to real-life applications of mental workload estimation.

Abstract Aqueous Zn‐based energy storage device (ZESD) is a promising candidate for large‐scale energy storage applications due to its significant merits like low cost, inherent safety, and environmental benignity. However, one shortcoming of ZESDs is the performance deficiency of pristine Zn anode caused by detrimental dendrite formation and side reactions. In this work, a novel boron nitride nano‐scale interface was established for ultra‐stable and wide temperature range tolerable anode (BN@Zn) by a scalable magnetron sputtering technique. The as‐introduced BN layers afford enhanced Zn deposition kinetics for a wide temperature application range from −20 to 60°C and effectively mitigated dendritic growth, which were ascribed to the strong interlayer bonds and uniform active sites as demonstrated by both experimental and density functional theory research results. Thus, the ultra‐thin BN interface could significantly improve the reaction kinetics and electrochemical stability of Zn anode, providing a new perspective towards the advanced ZESDs.

Summary: Background: Acute type A aortic dissection (AAAD) is a disease with high mortality, for which total aortic arch replacement (TAAR) combined with stent elephant implantation (SETI) is a reliable surgical treatment; however, it is associated with a high incidence of postoperative stroke. This retrospective study aimed to find preoperative and postoperative risk factors for postoperative stroke in patients with TAAR combined with SETI, and to provide predictive models and single-factor threshold suggestions. Methods: From October 2019 to March 2021, 229 AAAD patients who underwent TAAR and SETI were selected. Patients were divided into stroke group (n = 23) and non-stroke group (n = 206), and preoperative/intraoperative factors were evaluated by independent-samples T-test/ Mann-Whitney U test/Chi-Square test and odds ratio (OR) analysis. The Logistic regression equation and decision tree were used to construct the prediction model of the probability of postoperative stroke. Bayesian-learning model and 2-order derivation were used to calculate the inflection points of the continuous variables. Findings: Platelet count (PLT), International normalised ratio (INR) value, presence of diabetic history, and cardiopulmonary bypass (CPB) time were independent predictors of postoperative stroke (P-value < 0.05), and the above four factors were used to construct the Logistic regression equation. As for the decision-tree model, a radical model with higher accuracy in stroke predicting was chosen. Three inflection points for the effect of continuous variables (PLT count = 60 × 10^9/L; INR value = 1.82; CPB time = 300 min) on postoperative stroke were found by 2-order derivation. Interpretation: PLT count, INR value, presence of diabetic history, and CPB time were significant preoperative and intraoperative risk factors for postoperative stroke, and the identification and modeling of these factors can help us to take more active brain protection measures in high-risk patients. Funding: YS was funded by the National Natural Science Foundation of China (Grant ID 81671942).

The purpose of this study was to investigate the effects of three probiotics and their interactions on growth performance, intestinal digestion and absorption, and nutrient transporters in broilers. A total of 350 one-day-old male Arbor Acres broilers were randomly divided into seven groups: the control group (broilers receiving normal drinking water), groups P1, P2 and P3 (broilers receiving drinking water with 1% Lactobacillus casei, Lactobacillus acidophilus and Bifidobacterium lactis , respectively) and groups CP1, CP2 and CP3 (broilers receiving drinking water with a 1% compound probiotic mixture in 2:1:1, 1:2:1, 1:1:2 ratios, respectively). The feeding period was divided into two experimental periods: 1∼21 days and 22∼42 days. Compared to those in the control group, the broiler slaughter indexes and average daily feed intakes in the probiotics groups were not significantly different (P > 0.05), but the villus height in the small intestine increased significantly, and the crypt depth decreased significantly (P

Abstract Aims Sarcolipin (SLN) is a key regulator of sarcoplasmic reticulum calcium‐ATPase (SERCA)2a, which handles intracellular calcium re‐uptake. This study was aimed to investigate the involvement of SLN in post‐myocardial infarction (MI) heart failure (HF) in diabetes. Methods and results Diabetes/MI rat models were established. Altered SLN expression in diabetic hearts was screened out by microarray. A myocardiotropic viral vector was used to deliver siRNA to silence SLN. DNA methylation was evaluated by bisulfite sequencing. Cardiac functions were evaluated by invasive haemodynamic examinations. The SERCA2a activity, cytoplasmic calcium concentration ([Ca2+]i), calcium spark, and myocyte contraction were detected. Correlation between HF and diabetes was analysed in a cohort consisted of 101 ST‐segment elevated myocardial infarction (STEMI) patients between 2017 and 2019 [53.54 ± 4.64 years old; 61.4% male gender; HbA1c% 6.15 ± 2.00; and left ventricular ejection fraction (LVEF%) 40.64 ± 3.20%]. SLN expression was evaluated in left ventricular tissue sample from six STEMI patients complicated with diabetes and six STEMI patients without diabetes. Expressions of DNA methyltransferase 1a and DNA methyltransferase 3 were reduced in diabetic hearts, leading to down‐regulation of SLN promoter methylation, resulting in increased SLN expression in rats. Impaired heart systolic functions were found in experimental diabetic MI rats, which were attenuated by SLN silencing. SERCA2a activity reduction and [Ca2+]i elevation were attenuated by SLN silencing in diabetic animal hearts and high‐glucose incubated primary myocytes. SLN silencing suppressed calcium sparks and improved contraction and sarcoplasmic reticulum calcium re‐uptake in high‐glucose incubated primary myocytes. Expression of SLN was up‐regulated in LV sampled from STEMI patients complicated with diabetes compared with non‐diabetic ones (P

ObjectiveRenalase, a novel secretory flavoprotein with amine oxidase activity, is secreted into the blood by the kidneys and is hypothesized to participate in blood pressure (BP) regulation. We investigated the associations of renalase with BP and the risk of hypertension by examining renalase single nucleopeptide polymorphism (SNPs), serum renalase levels, and renal expression of renalase in humans.Methods① Subjects (n = 514) from the original Baoji Salt-Sensitive Study cohort were genotyped to investigate the association of renalase SNPs with longitudinal BP changes and the risk of hypertension during 14 years of follow-up. ② Two thousand three hundred and ninety two participants from the Hanzhong Adolescent Hypertension Study cohort were used to examine the association of serum renalase levels with hypertension. Renalase expression in renal biopsy specimens from 193 patients were measured by immunohistochemistry. ③ Renalase expression was compared in hypertensive vs. normotensive patients.Results① SNP rs7922058 was associated with 14-year change in systolic BP, and rs10887800, rs796945, rs1935582, rs2296545, and rs2576178 were significantly associated with 14-year change in diastolic BP while rs1935582 and rs2576178 were associated with mean arterial pressure change over 14 years. In addition, SNPs rs796945, rs1935582, and rs2576178 were significantly associated with hypertension incidence. Gene-based analysis found that renalase gene was significantly associated with hypertension incidence over 14-year follow-up after adjustment for multiple measurements. ② Hypertensive subjects had higher serum renalase levels than normotensive subjects (27.2 ± 0.4 vs. 25.1 ± 0.2 μg/mL). Serum renalase levels and BPs showed a linear correlation. In addition, serum renalase was significantly associated with the risk of hypertension [OR = 1.018 (1.006–1.030)]. ③ The expression of renalase in human renal biopsy specimens significantly decreased in hypertensive patients compared to non-hypertensive patients (0.030 ± 0.001 vs. 0.038 ± 0.004).ConclusionsThese findings indicate that renalase may play an important role in BP progression and development of hypertension.

The treatment and prevention of hypertension has been a worldwide medical challenge. The key pathological hallmark of hypertension is altered arterial vascular structure and function, i.e., increased peripheral vascular resistance due to vascular remodeling. The aim of this review is to elucidate the molecular mechanisms of vascular remodeling in hypertension and the protective mechanisms of aerobic exercise against vascular remodeling during the pathological process of hypertension. The main focus is on the mechanisms of oxidative stress and inflammation in the pathological condition of hypertension and vascular phenotypic transformation induced by the trilaminar structure of vascular endothelial cells, smooth muscle cells and extracellular matrix, and the peripheral adipose layer of the vasculature. To further explore the possible mechanisms by which aerobic exercise ameliorates vascular remodeling in the pathological process of hypertension through anti-proliferative, anti-inflammatory, antioxidant and thus inhibiting vascular phenotypic transformation. It provides a new perspective to reveal the intervention targets of vascular remodeling for the prevention and treatment of hypertension and its complications.

The massively and rapidly spreading disinformation on social network platforms poses a serious threat to public safety and social governance. Therefore, early and accurate detection of rumors in social networks is of vital importance before they spread on a large scale. Considering the small-world property of social networks, the source tweet-word graph is decomposed from the global graph of rumors, and a rumor detection method based on graph attention network of source tweet-word graph is proposed to fully learn the structure of rumor propagation and the deep representation of text contents. Specifically, the proposed model can adequately capture the contextual semantic association representation of source tweets during the propagation and extract semantic features. For the data sparseness of the early stage of information dissemination, text attention mechanism based on opinion similarity can aggregate and capture more tweet propagation structure features to help improve the efficiency of early detection of rumors. Through the analysis of the experimental results on real public datasets, the rumor detection performance of the proposed method is better than that of other baseline methods. Especially in the early rumor detection tasks, the proposed method can detect rumors with an accuracy of nearly 90% in the early stage of information dissemination. And it still has good robustness with noise interference.

Abstract Aqueous zinc‐ion batteries (ZIBs) are one of the most ideal candidates for grid‐scale energy storage applications due to their excellent price and safety advantages. However, formation of Zn dendrites and continuous side reactions during cycling result in serious instability problems for ZIBs. In this work, the authors develop a facile and versatile plasma‐induced nitrogen‐doped Zn (N‐Zn) foil for dendrite‐free Zn metal anode. Benefitting from the uniform nucleation sites and enhanced surface kinetics, the N‐Zn anode exhibits exceptionally low overpotential (around 23 mV) at 1 mA cm−2 and can be cycled for over 3000 h under 1 mA cm−2 because of the enhanced interface behavior. The potential application of N‐Zn anode is also confirmed by introducing a full Zn/MnO2 battery with outstanding capacity stability for 2000 cycles at 1 A g–1. Overall, this work offers new fundamental insights into homogenizing Zn electrodeposition processes by pre‐introduced active nucleation sites and provides a novel direction of interface design engineering for ultra‐stable Zn metal anode.

Ultra-responsive single-crystal silicon MEMS thermopiles for differential thermal analysis (DTA) are developed. Facilitated by a unique “microholes interetch and sealing (MIS)” technique, pairs of suspended thermopiles are batch fabricated in a differential form, with high-density (54 pairs) n-type/p-type single-crystal silicon thermocouples integrated within each thermopile (sample area ~0.045 mm2). The fabricated MEMS thermopile sensors exhibit outstanding power responsivity of 99.5 V/W and temperature responsivity of 27.8 mV/°C, which are more than 4 times higher than those reported for material thermal analysis. The high-responsivity MEMS DTA chips allow us to accurately measure the indium melting point at different heating rates of ~1–100 °C/s. We also perform DTA measurement of the dehydration process of CuSO4·5H2O and the crystals show three stages of losing water of crystallization before becoming anhydrous copper sulfate salt. Our high-performance, cost-effective MEMS sensing chips hold promise for rapid and accurate DTA characterization for a wide range of applications.

With the rapid development of global trade, the turnover of shipping containers has increased rapidly. How to use port resources reasonably and efficiently has become one of the main challenges that ports need to deal with when planning for the future. In order to develop scientific and efficient berth plans to improve operational efficiency and service level, this paper proposes a hybrid prediction model based on Principal Component Analysis (PCA) and Extreme Learning Machine (ELM) optimized by Improved Particle Swarm Optimization (IPSO), namely, the PCA-IPSO-ELM model. After assessing the uncertain factors influencing the operation time of the container ship at berth, this work reduces the dimensionality of the investigational data by the PCA method. Aiming to solve easy premature convergence of the traditional particle swarm algorithm, this paper introduces an improved particle swarm optimization algorithm via dynamic adjustment of nonlinear parameters. This improved particle swarm algorithm is mainly used to optimize the weights and thresholds of the extreme learning machine. Thus, a PCA-IPSO-ELM model which aims to forecast the operation time of a container ship at berth, is constructed. Using the historical operation data of the Tianjin Port Container Shipping Company as the prediction sample, this PCA-IPSO-ELM model is compared and assessed with traditional models. The results show that compared with other models, the PCA-IPSO-ELM prediction model has the characteristics of high prediction accuracy, fast running rate and strong stability, and it has a higher coefficient of determination and a better fitting degree.

Background: Uromodulin, also named Tamm Horsfall protein, has been associated with renal function and regulation of sodium homeostasis. We aimed to examine the associations of serum uromodulin levels and its genetic variants with longitudinal blood pressure (BP) changes and hypertension incidence/risk.Methods: A total of 514 participants from the original Baoji Salt-Sensitive Study cohort were genotyped to examine the associations of genetic variations in uromodulin gene with the longitudinal BP changes and the incidence of hypertension over 8 years of follow-up. In addition, 2,210 subjects from the cohort of Hanzhong Adolescent Hypertension Study were used to investigate the relationships between serum uromodulin levels and the risk of hypertension.Results: SNPs rs12917707 and rs12708631 in the uromodulin gene were significantly associated with the longitudinal BP changes over 8 years of follow-up. SNP rs12708631 was significantly associated with the incidence of hypertension over 8 years. In addition, gene-based analyses supported the associations of uromodulin gene with the longitudinal BP changes and hypertension incidence in Baoji Salt-Sensitive Study cohort. Furthermore, serum uromodulin levels in the hypertensive subjects were lower than in the normotensive subjects (25.5 ± 1.1 vs. 34.7 ± 0.7 ng/mL). Serum uromodulin levels decreased gradually as BP levels increased (34.6, 33.2, 27.8, and 25.0 ng/mL for subjects with normotension, high-normal, grade 1 hypertension, and grade 2 hypertension, respectively). Serum uromodulin was significantly associated with the lower risk of hypertension [0.978 (0.972–0.984)] in Hanzhong Adolescent Hypertension Study cohort.Conclusion: This study shows that uromodulin is associated with blood pressure progression and development of hypertension.

This study aimed to study compound probiotics’ (Lactobacillus casei, Lactobacillus acidophilus and Bifidobacterium) effects on production performance, lipid metabolism and meat quality in heat-stressed broilers. A total of 400 one-day-old AA broilers were randomly divided into four groups, each containing the same five replicates, with 20 broilers in each replicate. The control (21 °C) and experiment 2 were fed a basic corn–soybean meal diet. Experiment 1 (21 °C) and experiment 3 were fed a basic corn–soybean meal diet with 10 g/kg compound probiotics on days 7 and 28, respectively. The ambient temperature of experiment 2 and experiment 3 was increased to 30–32 °C (9:00–17:00) for 28–42 days, while the temperature for the other time was kept at 21 °C. The results showed that, compared with the control, the production performance and the content of high-density lipoprotein cholesterol in experiment 1 and triglyceride (TG) in experiment 2 increased (p < 0.05). Compared with experiment 2, TG decreased and the production performance increased in experiment 3 (p < 0.05). However, there was no significant change in meat quality indicators. Weighted gene co-expression network analysis (WGCNA) was used to analyze the intramuscular fat, abdominal fat and five blood lipid indicators. We found five related modules. Fatty acid biosynthesis, glycerolipid metabolism, and fat digestion and absorption were the pathways for KEGG enrichment. Additionally, NKX2-1, TAS2R40, PTH, CPB1, SLCO1B3, GNB3 and AQP7 may be the hub genes of compound probiotics regulating lipid metabolism in heat-stressed broilers. In conclusion, this study identified the key genes of compound probiotics regulating lipid metabolism and provided a theoretical basis for the poultry breeding industry to alleviate heat stress.

The COVID-19 outbreak has been a worldwide challenge for the higher education community. Under lockdown measures, meeting students’ needs and encouraging their engagement in academic work have never been more urgent and challenging. In this study, we investigated the relationship between students’ satisfaction with institutional strategies, students’ optimism and pessimism, satisfaction with basic psychological needs, engagement in academic work, intention to drop out from studies, depression, and well-being. We conducted an online self-report study on N = 477 German college and university students (77.25% females, mean age = 23.96 years, SD = 4.78). The results of structural equation models showed that students’ satisfaction with institutional strategies was positively related to their basic psychological need satisfaction and engagement. Students’ optimism was positively associated with need satisfaction and engagement, whereas pessimism was negatively associated with them. Furthermore, students’ academic engagement was negatively linked to dropout intentions, whereas psychological need satisfaction was linked to depression and well-being. The findings of this study suggest that acknowledging students timely about the institutional strategies of examinations and courses and supporting students to engage academic activities are important institutional tasks during crisis.

Abstract Background Epidemiological observations have demonstrated that ambient fine particulate matter with d p

Abstract Background The aim of this study is to explore the molecular mechanism of the LIM protein Ajuba and the transcription factor SP1 in the pathogenesis and progression of PDAC. Ajuba is a newly defined transcriptional co-regulator and plays important role in various cancer development, while SP1 is a classic transcription factor, and is closely related with a variety of gene expression and cancer development including PDAC. Methods The expression of Ajuba and SP1 in PDAC tissues was detected by immunohistochemistry (IHC), and the correlation between expression level and clinical prognosis of Ajuba and SP1 was extensively analyzed using online tools. The interaction between Ajuba and SP1 was examined by co-immunoprecipitation (co-IP) and GST-pulldown assays. Stable cell lines were established via lentiviral infection, and was examined by qRT-PCR and western blot assays. The effects of Ajuba/SP1 on PDAC cell proliferation were examined using CCK8 and colony formation assays. Luciferase reporter and chromatin immunoprecipitation (ChIP) assays were employed to examine the transcription activity. Results The expression level (protein and mRNA) of Ajuba and SP1 was elevated in PDAC tissues and was positively correlated; patients with high Ajuba and SP1 expression had a poor prognosis. Mechanistically, Ajuba binds to the C-terminus of SP1 and functions as a co-activator to enhance SP1 gene expression and promote cell proliferation; the promoter of Ajuba contains functional SP1 responsive elements and Ajuba itself is a target gene of SP1. Conclusion Ajuba functions as a co-activator of SP1 to induce its target gene, and that Ajuba itself is a target genes of SP1. Ajuba/SP1 complex could form a feed forward loop to drive SP1 target gene transcription and promote cell proliferation of pancreatic cancer cells. Ajuba and SP1 might be biomarkers for PDAC diagnostics, prognosis and targets for new therapeutics.

Appearance-based gaze estimation techniques have been greatly advanced in these years. However, using a single camera for appearance-based gaze estimation has been limited to short distance in previous studies. In addition, labeling of training samples has been a time-consuming and unfriendly step in previous appearance-based gaze estimation studies. To bridge these significant gaps, this paper presents a new long-distance gaze estimation paradigm: train a camera to perform eye tracking by another eye tracker, named Learning-based Single Camera eye tracker (LSC eye-tracker). In the training stage, the LSC eye-tracker simultaneously acquired gaze data by a commercial trainer eye tracker and face appearance images by a long-distance trainee camera, based on which deep convolutional neural network (CNN) models are utilized to learn the mapping from appearance images to gazes. In the application stage, the LSC eye-tracker works alone to predict gazes based on the acquired appearance images by the single camera and the trained CNN models. Our experimental results show that the LSC eye-tracker enables both population-based eye tracking and personalized eye tracking with promising accuracy and performance.

The undersea collecting vehicle is one of the three main parts in the deep-sea exploitation system. The Coandă effect-based collector picks up manganese nodules by providing an adverse pressure difference over the nodule, through the jet flowing around a curved wall. In order to overcome the drawbacks of repeated prototyping and experimenting in the traditional design procedure of the Coandă effect-based collector, the theoretical guide should be well placed to ensure correct design of the strongly related parameters of the collector. In this paper, a simplified model of curved wall jets was developed and the solution of approximate closed form was obtained to predict the lift force of the nodules. The variational tendencies of velocity, pressure and single-particle lift index perpendicular to the curved wall were investigated and the Coandă effects were found to be stronger with higher initial velocity, higher non-dimensional jet slot height and lower non-dimensional wall height. A CFD-DEM simulation of a number of particles was additionally performed to give more insight into the predictive accuracy of the simplified theory. Target lift force was found to be related to high efficiency in collection of particles, resulting in certain predictability of the theoretical model to the nodule lifting in a pre-prototype hydraulic device based on the Coandă effect.

In this work, we designed a series of new carbohydrate-based coumarin carbonic anhydrase IX inhibitors by using 1,2,3-triazoles as linker. Next, these designed compounds were synthesized by the optimized one-pot click chemistry reaction condition. Subsequently, these target compounds were assayed for the inhibition of three carbonic anhydrase isoforms (CA I, CA II and CA IX). Intriguingly, all the compounds showed better CA IX inhibitory activity than initial coumarin fragments. Among them, compound 10a (IC50: 11 nM) possessed the most potent CA IX inhibitory activity, which was more potent than the reference drug acetazolamide (IC50: 30 nM). Notably, compound 10a showed 3018-fold, 1955-fold selectivity relative to CA I and CA II, respectively. Meanwhile, representative compounds could reduce tumor cell viability and the extracellular acidification in HT-29 and MDA-MB-231 cancer cell lines. Even more interestingly, our target compounds had no apparent cytotoxicity toward MCF-10A cell line. In addition, the in vitro stability assays also indicated our developed compounds possessed good liver microsomal metabolic stabilities and plasma stability. Furthermore, representative compounds revealed relatively low hERG cardiac toxicity and acute toxicity. Furthermore, docking studies were carried out to understand the interactions of our target compounds with the protein target CA IX. Collectively, our results suggest that compound 10a, as a selective CA IX inhibitor, could be an important lead compound for further optimization and development as an anticancer agent.

The flammability and toxicity of the currently used electrolytes are the concerns that must be addressed. Here the authors show a non-fluorinated and non-toxic ionomeric aqueous gel electrolyte called water-in-ionomer that allows an enlargement of electrochemical stability window and design of environmentally friendly battery cell chemistries.

Aluminum (Al) toxicity severely decreases plant growth and productivity in acidic soil globally. Ectomycorrhizal (ECM) fungi can promote host plant’s Al-tolerance by acting as a physical barrier or bio-filter. However, little information is available on the role of ECM fungus on Al immobilization with respect to Al-tolerance. This present study aimed to screen a promising indigenous ECM fungus with high Al-tolerance and to understand its role in Al immobilization related to Al-tolerance. Two ECM fungal strains (Lactarius deliciosus 2 and Pisolithus tinctorius 715) isolated from forest stands in Southwest China were cultured in vitro with 0.0, 1.0 or 2.0 mM Al addition for 21 days to compare their Al accumulation and Al-tolerance. Meanwhile, fungal mycelia were incubated in 0.037 mM Al3+ solutions, and then Al3+ concentrations in the solution were determined at time 2, 5, 10, 20, 40, 60, 120, 180, and 240 min, and the Al3+ immobilization characteristics were evaluated using the pseudo-first order, pseudo-second order and intraparticle diffusion models. Results showed that 1.0 or 2.0 mM Al3+ addition significantly increased fungal biomass production by 23% or 41% in L. deliciosus 2, not in P. tinctorius 715. Fungal Al3+ concentrations in L. deliciosus 2 and P. tinctorius 715 were significantly increased by 293% and 103% under 2.0 mM than under 1.0 mM Al3+ addition. The pH values in the culture solution were significantly decreased by 0.43 after 21 d fungus growth but no changes between these two fungi under the same Al3+ addition. Fungal Al3+ immobilization showed a three-stage trend with initially a rapid rate followed a relatively slower rate until reaching equilibrium. The pseudo-second order model was the best (R2 = 0.98 and 0.99 for L. deliciosus 2 and P. tinctorius 715) to fit the experimentally observed data among the three models. Compared to P. tinctorius 715, L. deliciosus 2 also had greater intercept value, cation exchange capacity (CEC), and extracellular Al3+ proportion in fungal mycelia. Additionally, bio-concentration on Al3+, active site numbers for Al3+, boundary layer thickness, CEC, and immobilization on the cell wall in fungal mycelia were involved in ECM fungal Al-tolerance. These results show that both ECM fungi are Al-tolerant while L. deliciosus 2 is a promising indigenous ECM isolate with higher Al-tolerance in Southwest China, and they can be hence applied to the afforestation and ecological restoration in acidic soil.

Objectives To develop a model of in-hospital mortality using medical record front page (MRFP) data and assess its validity in case-mix standardisation by comparison with a model developed using the complete medical record data.Design A nationally representative retrospective study.Setting Representative hospitals in China, covering 161 hospitals in modelling cohort and 156 hospitals in validation cohort.Participants Representative patients admitted for acute myocardial infarction. 8370 patients in modelling cohort and 9704 patients in validation cohort.Primary outcome measures In-hospital mortality, which was defined explicitly as death that occurred during hospitalisation, and the hospital-level risk standardised mortality rate (RSMR).Results A total of 14 variables were included in the model predicting in-hospital mortality based on MRFP data, with the area under receiver operating characteristic curve of 0.78 among modelling cohort and 0.79 among validation cohort. The median of absolute difference between the hospital RSMR predicted by hierarchical generalised linear models established based on MRFP data and complete medical record data, which was built as ‘reference model’, was 0.08% (10th and 90th percentiles: −1.8% and 1.6%). In the regression model comparing the RSMR between two models, the slope and intercept of the regression equation is 0.90 and 0.007 in modelling cohort, while 0.85 and 0.010 in validation cohort, which indicated that the evaluation capability from two models were very similar.Conclusions The models based on MRFP data showed good discrimination and calibration capability, as well as similar risk prediction effect in comparison with the model based on complete medical record data, which proved that MRFP data could be suitable for risk adjustment in hospital performance measurement.

Atherosclerosis is the leading cause of heart disease and stroke, and one of the leading causes of death and disability worldwide. The phenotypic transformation of vascular smooth muscle cells (VSMCs) plays an important role in the pathological process of atherosclerosis. The present study aimed to identify differently expressed mRNAs in atherosclerosis by analyzing GSE6088 database. Our results revealed there were totally 467 increased and 490 decreased differential expressed genes (DEGs) in atherosclerosis. Bioinformatics analysis demonstrated that the DEGs substantially existed in pathways, including Glyoxylate and dicarboxylate metabolism, Tyrosine metabolism, Tryptophan metabolism, Beta-Alanine metabolism, Fatty acid biosynthesis and Starch and sucrose metabolism. Next, we constructed a protein-protein interaction (PPI) network to identify hub genes in atherosclerosis. Also, we identified CDK6 as a key regulator of atherosclerosis. In this study, we found that CDK6 knockdown suppressed HASMC and HUASMC cell proliferation. Circular RNA (CircRNA) is a non-coding RNA which is reported to have an unusual influence on tumorigenesis process and other aspects in the last few years. Previous studies showed circRNAs could act as miRNAs sponging in multiple biological processes. Bioinformatics prediction and luciferase analysis showed that CDK6 were targeted and regulated by circHIPK3/miR-637. Moreover, silencing circHIPK3 could also significantly induce the arrest and apoptosis of cell cycle. In conclusion, this study discovered the important regulatory role of circHIPK3 in the proliferation and apoptosis of VSMCs by influencing the miR-637/CDK6 axis.

Along with the pressing demand for the long-distance transportation of coarse particles in the deep-sea mining industry, evaluating the slurry pump’s passing through and erosive wear by studying the particle motion characteristics and the slurry behavior is becoming increasingly important. Research on the influence of leakage flow through the clearance and balancing devices on the motion characteristic of granular grain flow is of great significance but has been seldom studied. This study coupled the discrete element method with the CFD method to investigate the comprehensive effect of a double-stage slurry pump’s main flow and leakage flow on the motion characteristics of particles with a 10 mm diameter. Results show that the leakage flow occupation in main flow falls from 26%–27% to 8%–9% for the two stages, with the flow rate increasing from 80 m3/h to 200 m3/h. In the first stage with leakage, accumulation of coarse particles was observed at the impeller eye, which should be paid much attention to slurry pumps’ operation to eliminate the chance of blockage. In the nonleak situation, although the increment of the average kinetic energy of particles through the impeller is more significant than in the leak case, most of them dissipate primarily by more than 10% collision in the bowl diffuser. In the leak or nonleak case, the average kinetic energy of particles was more than twice through the first stage but only 1.1 times through the second stage. The selection of stages in the slurry pump design should consider the limitation of particle velocity improvement.

Along with the crucial requirement for efficiency improvement in the cutting-edge petrochemical technology, the evaluation of the dynamic performance characteristics of high-speed pump is becoming increasingly important. It has become a main topic in the research of high-speed pump to minimize the pressure pulsation induced by the fluid in the pump body, so as to reduce the mechanical vibration. Although the research on the transient flow characteristic and pressure fluctuation of a high-speed pump with straight blades is of great significance, it has been seldom explored. In this work, the flow instability of a 16 straight-blade high-speed centrifugal pump is studied numerically at a rotational speed of 8500 rpm and flow rate of 3 m3/h. Results show that with the influence of rotor-stator interaction, time-domain pressure signals at the tongue show double peak characteristic, whereas a single peak characteristic exists at the diffuser wall. The pressure fluctuation near the tongue is reduced to approximately half of that at the volute wall by the water ring effect accompanied with the high-pressure factor. At the tongue region, the amplitude of the blade passing frequency is reduced by the unsteady flow, whereas the harmonic wave was increased at 2–4 times of the blade passing frequency.

Voltage sag state estimation on the basis of a limited number of installed monitors is essential to dividing the responsibility for the voltage sag and taking corresponding measurements for improvement in voltage quality. Therefore, a deep learning methodology via bidirectional WaveNet for the voltage sag state estimation is proposed in this paper. The presented method can simultaneously estimate voltage sag state at non-monitored buses via limited monitors. Especially, the proposed deep learning method using the bidirectional WaveNet is designed to explore the long-term and long-range temporal dependencies in both the forward and backward directions. In this way, only by using original measured voltages through monitors, high accuracy for voltage sag state estimation can be achieved without restructured or redesign of the raw monitored data. An excellent advantage of the presented algorithm is that it can be implemented without system parameters or operating conditions or any other prior information. The presented methodology was verified by the IEEE 30-bus benchmark system. The experimental results illustrated that the accuracy of the voltage sag state estimation results was over 99.83%. Furthermore, a comparison among different models, including the bidirectional GRU-based model, one-way WaveNet-based model, and bidirectional WaveNet-based model, was also conducted. The results illustrated that the proposed bidirectional WaveNet-based model achieved the highest accuracy and quickest convergence speed.