Search

The development of calcific aortic valve disease (CAVD) is a complex process of ectopic calcification involving various factors that lead to aortic valve stenosis, hemodynamic changes, and, in severe cases, even sudden death. Currently, aortic valve replacement is the only effective method. The osteogenic differentiation of aortic valve interstitial cells (AVICs) is one of the key factors of valve calcification. Emerging evidence suggests that bone morphogenetic protein 2 (BMP2) can induce the proosteogenic activation of AVICs. However, the regulatory mechanism underlying this activation in AVICs is unclear. In the present study, we elucidated through high-throughput RNA sequencing and RT-qPCR that miR-664a-3p was evidently downregulated in the calcific aortic valve. We also proved that miR-664a-3p was involved in regulating osteogenic differentiation in AVICs. Target prediction analysis and dual-luciferase reporter gene assay confirmed that miR-664a-3p is preferentially bound to BMP2. Furthermore, the effect of the miR-664a-3p/BMP2 axis on osteogenic differentiation in AVICs was examined using the gain- and loss-of-function approach. Finally, we constructed a mouse CAVD model and verified the effect of the miR-664a-3p/BMP2 axis on the aortic valve calcification leaflets in vivo. In conclusion, miR-664a-3p regulates osteogenic differentiation in AVICs through negative regulation of BMP2, highlighting that miR-664a-3p may be a potential therapeutic target for CAVD. [ABSTRACT FROM AUTHOR]

Background. The aim of the study was to find the potential roles of B-type natriuretic peptide (BNP) and imaging markers on distinguishing cardioembolic (CE) stroke from non-CE stroke, so as to provide useful information for making individualized endovascular treatment (EVT) plan for the patients with acute ischemic stroke (AIS). Methods. The patients with unilateral anterior circulation large vessel occlusion who underwent EVT between March 2016 and December 2021 were analyzed in this study, retrospectively. The risk factors, laboratory test indicators, imaging parameters, and other factors were compared between the CE group and non-CE group. Logistic regression was used to analyze the risk factors of CE stroke. ROC curves were used to assess the values of different parameters on distinguishing CE stroke from non-CE stroke. The relationships between BNP and imaging parameters were assessed using the Spearman correlation analysis. Results. 160 patients were enrolled in the study and divided into the CE group (n = 66) and non-CE group (n = 94). BNP (odds ratio OR = 1.004 ; 95% CI, 1.001-1.009; p = 0.038), MMR (OR = 0.736 ; 95% CI, 0.573-0.945; p = 0.016), NIHSS (OR = 1.150 ; 95% CI, 1.022-1.294; p = 0.020), and AF (OR = 556.968 ; 95% CI, 51.739-5995.765; p < 0.001) were the independent predictive factors of CE stroke. The area under the curve (AUC) of BNP and mismatch ratio (MMR) were 0.846 (95% CI (0.780-0.898), p < 0.001) and 0.636 (95% CI (0.633-0.779), p < 0.001), respectively. The cut-off value of BNP was 249.23 pg/mL with the sensitivity of 74.24% and the specificity of 82.98%. BNP combined with MMR improved the predictive value for CE stroke. The AUC of the combination was 0.858 with the sensitivity of 84.85% and the specificity of 73.40%. BNP was correlated with 4D CTA collateral score, MMR, clot burden score, final infarct volume, infarct core volume, and ischemic penumbra volume (all, p < 0.05). Conclusion. BNP on admission combined with MMR is valuable for the risk prediction of CE stroke, which will promote the further screening of the high-risk patients with CE stroke and provide more diagnostic information for clinicians. [ABSTRACT FROM AUTHOR]

Povidone iodine (PVP‐I) is widely used as an efficient antiseptic disinfectant, which can kill various pernicious microbe. PVP‐I also exhibits certain toxic effects to the environment. To study the comprehensive toxic effects of PVP‐I on microalgae, different concentrations including 0, 7, 14, 28, 56 and 112 mg/L were set. The effects of PVP‐I on the growth performance, microstructure, photosynthesis, antioxidant levels and photosynthesis associated genes expressions of microalgae were investigated. The results showed that PVP‐I had significant effects on the growth and physiological functions of C. pyrenoidosa. Under the observation of scanning electron microscope, PVP‐I of 56 and 112 mg/L could destroy the cytoderm of C. pyrenoidosa directly. Under the PVP‐I exposure, the activity of SOD and CAT fluctuated up and down, while MDA content continued to rise. The relative gene expression of PsbA gene was significantly up‐regulated in high concentration of 112 mg/L PVP‐I. The relative gene expression of rbcL and rbcS gene were upregulated in 28 mg/L PVP‐I. The results of present study showed that PVP‐I could induce the production of oxidative stress response in C. pyrenoidosa, inhibit the expression of genes related to photosynthesis of C. pyrenoidosa and affect the photosynthesis of C. pyrenoidosa. The present study will provide a reference for the safe application of PVP‐I. [ABSTRACT FROM AUTHOR]

Background. Non-small-cell lung cancer (NSCLC) is a major component of lung cancer and is significantly correlated with poor prognosis. N6-methyladenosine (m6A) RNA methylation is closely related to the occurrence, progression, and prognosis of cancer. The potential biological functions and mechanisms of m6A RNA methylation in the immune microenvironment are still unclear. Methods. We assessed m6A RNA methylation modification patterns in 1326 NSCLC patient samples based on 20 m6A regulators, linking these clusters to the tumor microenvironment and immune cell infiltration. The m6Ascore was created to quantify the m6A modification patterns of individual tumors. We then assessed the value of NSCLC patients in terms of clinical prognosis and immunotherapy response. Results. According to different mRNA expression levels, two different m6A clusters were identified. m6A aggregation was significantly associated with clinical prognostic characteristics, the tumor microenvironment, and immune-related biological processes. Fifteen differential genes were screened based on these two m6A clusters, and to further investigate the mechanisms of action of these differential genes, they were subjected to unsupervised clustering analysis, which classified them into four different genomic isoforms. Prognostic analysis indicated that the survival advantage of the m6A gene cluster A modification mode was significantly prominent. We continued to construct the m6Ascore, which was used as a scoring tool to evaluate tumor typing, immunity, and prognosis. Patients with a low m6Ascore showed a significant survival advantage, and the group with a low m6Ascore had a better prognosis predicted by immunotherapy. The anti-PD-1/L1 immunotherapy cohort showed that a lower m6Ascore was associated with higher efficacy of immunotherapy. Conclusions. The results suggest that m6A RNA methylation regulators make an important difference in the tumor immune microenvironment of patients with NSCLC. m6A gene characterization and the construction of the m6Ascore provide us with a richer understanding of m6A RNA methylation modification patterns in NSCLC patients and help to predict clinical prognosis and immunotherapeutic response. [ABSTRACT FROM AUTHOR]

In order to model air quality in heavy pollution days, a dynamic emission monitoring system is implemented in the Beijing road network, which requires the input of hourly traffic flows. Floating car data (FCD) is increasingly employed for flow estimation based on the fundamental diagrams to supplement data provided by stationary detectors. However, existing studies often used a typical fundamental diagram without considering the hysteresis phenomena and the uncertainty of traffic flow estimation. This study aims to develop a multiperiod fundamental diagram for the traffic flow estimation from FCD considering the hysteresis phenomena. The result shows that the proposed multiperiod fundamental diagram can improve the accuracy of flow estimation. The uncertainty of traffic flow estimation at both 10 minutes and 1 hour is also quantified, and the result indicates that the variation of the estimation uncertainty at 1 hour is lower than that at 10 minutes, with an average 7% reduction of the range of 95% confidence interval (CI). But there is no significant difference in magnitudes of the estimation uncertainty at 1 hour compared with that at 10 minutes. Moreover, the uncertainty for congested flows is lower than that for free flows. In the case study, the proposed model is employed to develop the spatial and temporal distributions of flows and emissions for the metropolitan area in Beijing. [ABSTRACT FROM AUTHOR]

Retinal vessel segmentation has high value for the research on the diagnosis of diabetic retinopathy, hypertension, and cardiovascular and cerebrovascular diseases. Most methods based on deep convolutional neural networks (DCNN) do not have large receptive fields or rich spatial information and cannot capture global context information of the larger areas. Therefore, it is difficult to identify the lesion area, and the segmentation efficiency is poor. This paper presents a butterfly fully convolutional neural network (BFCN). First, in view of the low contrast between blood vessels and the background in retinal blood vessel images, this paper uses automatic color enhancement (ACE) technology to increase the contrast between blood vessels and the background. Second, using the multiscale information extraction (MSIE) module in the backbone network can capture the global contextual information in a larger area to reduce the loss of feature information. At the same time, using the transfer layer (T_Layer) can not only alleviate gradient vanishing problem and repair the information loss in the downsampling process but also obtain rich spatial information. Finally, for the first time in the paper, the segmentation image is postprocessed, and the Laplacian sharpening method is used to improve the accuracy of vessel segmentation. The method mentioned in this paper has been verified by the DRIVE, STARE, and CHASE datasets, with the accuracy of 0.9627, 0.9735, and 0.9688, respectively. [ABSTRACT FROM AUTHOR]

Retinal vessel segmentation has high value for the research on the diagnosis of diabetic retinopathy, hypertension, and cardiovascular and cerebrovascular diseases. Most methods based on deep convolutional neural networks (DCNN) do not have large receptive fields or rich spatial information and cannot capture global context information of the larger areas. Therefore, it is difficult to identify the lesion area, and the segmentation efficiency is poor. This paper presents a butterfly fully convolutional neural network (BFCN). First, in view of the low contrast between blood vessels and the background in retinal blood vessel images, this paper uses automatic color enhancement (ACE) technology to increase the contrast between blood vessels and the background. Second, using the multiscale information extraction (MSIE) module in the backbone network can capture the global contextual information in a larger area to reduce the loss of feature information. At the same time, using the transfer layer (T_Layer) can not only alleviate gradient vanishing problem and repair the information loss in the downsampling process but also obtain rich spatial information. Finally, for the first time in the paper, the segmentation image is postprocessed, and the Laplacian sharpening method is used to improve the accuracy of vessel segmentation. The method mentioned in this paper has been verified by the DRIVE, STARE, and CHASE datasets, with the accuracy of 0.9627, 0.9735, and 0.9688, respectively. [ABSTRACT FROM AUTHOR]

In this study, the changes during storage in the physicochemical, microbiological, and textural properties of semi‐dried noodles prepared with ozonated water were investigated. Results showed that ozonated water could significantly (p <.05) reduce the initial total plate count (TPC) of semi‐dried noodle products. Compared with the control, the initial TPC, bacillus content, and mold and yeast contents of treated noodles were reduced by 1.26 lgCFU/g, 0.34 lgCFU/g, and 0.39 lgCFU/g, respectively. The shelf life of semi‐dried noodles in the presence of ozonated water was prolonged by nearly 24 hr at room temperature. Higher whiteness value could be achieved for semi‐dried noodles and protein polymerization of which was promoted by employing the ozonated water. Ozonated water treatment decreased the cooking loss and improved the texture properties of semi‐dried noodles. Practical applications: Semi‐dried noodles are becoming increasingly popular among people due to the similar taste and flavor to fresh noodles. However, the high final moisture content of semi‐dried noodles, ranging from 20% to 25%, accelerates the growth of microorganisms, which shortens the shelf life of products and hinders the development of noodle industries. Normally, chemical preservatives are used to prevent the survival of microorganisms and minimize the deterioration of products. However, they are inconsistent with the concept of "green" consumerism. Based on the findings of this research, ozonated water could contribute to the shelf life extension and quality improvement of high moisture content noodles product, which is beneficial to consumers as well as food processing industries. [ABSTRACT FROM AUTHOR]

All-round development strategy of quality education makes primary and secondary school students not only pursue the improvement of achievement but also carry out physical exercise. Physical training is the material basis for students to study other disciplines, and the core is to improve students' own physical quality and increase their physique. Having a strong body helps students have certain physical strength to study in other courses. In recent years, in the background of the scientific era, college students in China obviously have some problems, such as insufficient awareness of physical exercise and serious decline in physical fitness. Nowadays, teenagers are addicted to games and go out to become members of the low-headed people. Nowadays, it is very unhealthy for teenagers to go out with their mobile phones as "low-headed people." In order to avoid college students getting rid of this living condition, colleges and universities carry out physical fitness tests every year to promote contemporary college students to strengthen exercise. College students, as the main force in the future construction of the motherland, should not only master professional knowledge but also improve their physical fitness. Good health is the greatest capital in one's life. Every year, some students fail to pass the physical fitness test in universities. It stands to reason that college students are in the age of high youth, and physical fitness test should be a piece of cake for them. In the face of the inconsistency between the predicted results and the actual results, this paper analyzes this. Based on the above situation, With the aim of improving students' training efficiency and physical performance, the physical performance prediction model of deep learning is designed and analyzed to predict the performance, analyze the influencing factors of the model and how to reduce the influencing components of the factors, and analyze and compare the performance of various prediction models to find out the best model, so as to make the predicted value closer to the true value. [ABSTRACT FROM AUTHOR]

This paper presents a miniaturized W‐band bandpass filter based on rectangular micro‐coaxial structure. The filter with third‐order Chebyshev response is analyzed and designed. It uses half‐wavelength resonators and realizes the coupling between resonant units by adding grounded cylinders. The center frequency is 97.5 GHz with 3‐dB fractional bandwidth (FBW) of 7.5%. Moreover, the prototype is fabricated by the surface micromachining technology, which greatly reduces its volume. The measured results are close to the simulations in operating band and the minimum insertion loss is 1.9 dB. [ABSTRACT FROM AUTHOR]

Purpose. Primary hypertrophic osteoarthropathy (PHO) is a rare, autosomal, recessive genetic disease characterized by digital clubbing, periostosis, and pachydermia. The underlying cause for the pathogenesis of this disease is a defect in prostaglandin E2 (PGE2) degradation, caused by mutations in HPGD or SLCO2A1. In this study, we describe the clinical characteristics, SLCO2A1 mutations, and bone metabolic markers of a PHO pedigree from a Chinese consanguineous twin family. Methods. Whole blood and urine samples were collected from all the family members. All the exons and exon-intron boundaries of the HPGD and SLCO2A1 genes were amplified using polymerase chain reaction (PCR) and sequenced. The biomarkers of mineral and bone metabolism, including calcium, phosphorus, parathyroid hormone (PTH), 25-hydroxyvitamin D (25(OH)D), bone Gla-protein (BGP), C-terminal telopeptide of type I collagen (β-CTX), and urinary calcium/creatinine ratio (Uca/Ucr) were detected. Results. A homozygous (nonsense) mutation in the SLCO2A1 gene (c.1807C >T/p.R603 ∗ ) was detected in the proband. Five heterozygous carriers were also identified among his relatives, including his twin brother. The serum BGP (225.5 ng/ml), β-CTX (4112 pg/ml), and Uca/Ucr (0.63) levels were significantly elevated, while the 25(OH)D (37.1 nmol/L) level was reduced in the proband. The proband's twin brother displayed increased levels of β-CTX (901 pg/ml) and insufficiency of 25(OH)D (67.29 nmol/L), while the other heterozygous carriers only displayed 25(OH)D insufficiency. Conclusion. The patients with PHO displayed an active state of bone reconstruction. There may be a lack of vitamin D, accompanied by an increase in BGP and β-CTX levels. Heterozygous mutations of SLCO2A1 might lead to mild PHO. [ABSTRACT FROM AUTHOR]

A real-time infrastructure, called MLRTI, is proposed in this paper to fulfill the requirement of real-time simulation in distributed environment. There are two novel contributions in this work. Firstly, a flexible timing mechanism is proposed to integrate external time source and local timer utility, enabling the distributed nodes to advance their timeline simultaneously at different speeds with high precision. A data transmission solution is also presented in which the reflective memory card (VMIC) is employed to provide fast data transmission with minimum delay. Secondly, a system partition schema is proposed in MLRTI to reduce the solution errors introduced by transforming a continuous system into distribution system, which is common in a class of control applications where the system is designed in centralized model but simulated in distributed environment for constrains on system structure or the need to balance computation load. Experiments are conducted and the results show this schema effectively reduces the possible errors by properly partitioning the system into parts that are suitable to be deployed in distributed environment. [ABSTRACT FROM AUTHOR]

To improve the stability of grapefruit seed extract (GSE) and prolong its antibacterial effect, a GSE nanoemulsion (GNE) was prepared by a high‐energy emulsifying method. The particle size and PDI of fresh GNE were 173.9 nm and 0.105, respectively. TEM images showed that uniform and closely distributed GNE droplets. The minimum inhibitory concentration (MIC) of GNE against Staphylococcus aureus and Escherichia coli were 0.6 wt% and 1.2 wt%, respectively, 25% and 14% improved compared to GSE. Besides, the GNE was proved to be more effective to destroy the cell wall of E. coli than that of S. aureus by measuring the concentration of alkaline phosphatase after treatment. The increase of conductivity, nucleic acid, and protein released from the cells indicated that the bacteria cell membrane has been severely damaged after GNE treatment. TEM results further illustrated that the internal microstructure of bacteria cells was significantly changed with GNE treatment. Novelty impact statement: In the present study, the grapefruit seed extract nanoemulsion (GNE) with more surface‐volume ratio, higher biological activity, and stronger bioavailability was successfully prepared using the high energy method. GNE has an inhibitory effect on S. aureus and E. coli by destroying the cell wall and cell membrane of the bacteria. This work provides support for expanding the application of grapefruit seed extract. [ABSTRACT FROM AUTHOR]

Back propagation (BP) neural network is used to approximate the dynamic character of nonlinear discrete-time system. Considering the unmodeling dynamics of the system, the weights of neural network are updated by using a dead-zone algorithm and a robust adaptive controller based on the BP neural network is proposed. For the situation that jumping change parameters exist, multiple neural networks with multiple weights are built to cover the uncertainty of parameters, and multiple controllers based on these models are set up. At every sample time, a performance index function based on the identification error will be used to choose the optimal model and the corresponding controller. Different kinds of combinations of fixed model and adaptive model will be used for robust multiple models adaptive control (MMAC). The proof of stability and convergence of MMAC are given, and the significant efficacy of the proposed methods is tested by simulation. [ABSTRACT FROM AUTHOR]

This study investigated the effects of two frozen storage temperatures (−20 and −40C) and four frozen storage periods (0, 4, 8 and 12 weeks) on quality of chicken meatballs. Results showed CIE L*, a*, T22 peak area ratio, water holding capacity (WHC), total extractable protein and textural decreased with increasing frozen storage temperature, but TBARs and chewiness increased. Besides, frozen storage at −40C was more effective in increasing a*, Hue ( h) and chewiness compared with −20C ( P < 0.05), and the WHC was higher than −20C ( P < 0.05) at the eight week. No significant effect on L*, b*, TBARs, extractable protein concentration and texture was observed between −20 and −40C ( P > 0.05). Meanwhile, all qualities were significantly influenced by frozen storage period ( P < 0.05), except for water- and salt-soluble proteins concentration ( P > 0.05). But, frozen storage for 8 weeks resulted in a further reduction in WHC and textural. Therefore, in consideration of economic situation, these results suggest that −20C and 8 weeks should be chosen as the most optimal frozen storage temperature and period. Practical Applications As one kind of welcomed prepared product, chicken meatballs are welcomed by purchasers, especially in the Chinese market. As we know, the best way to store these products is frozen. However, frozen storage can influence the eating qualities of meat and meat products. Therefore, this study was to determine the effect of different frozen storage temperature (−20 and −40C) and period (0, 4, 8 and 12 weeks) on the quality of chicken meatballs. The results of this study suggest that −20C and 8 weeks should be chosen as the most optimal frozen storage temperature and period. These results will provide theoretical basis for the production practice in the future. [ABSTRACT FROM AUTHOR]