Effects of the lncRNA MALAT1 gene region rs664589 site mutation on acute myocardial infarction in Chinese Han.

We aimed to study the association between the non-coding region of the lncRNA MALAT1 gene, the non-coding region rs664589 C>G variant, and the risk of acute myocardial infarction (AMI) in the Chinese Han population. 165 NSTEMI and 135 STEMI patients were enrolled in the study. An additional 150 healthy individuals were enrolled as the controls. All subjects were analyzed for the MALAT1 rs664589 locus genotype. The receiver operating curve (ROC) was used to determine the effect of MALAT1 rs664589 single nucleotide polymorphism (SNP) on the diagnosis of AMI by plasma lncRNA MALAT1. The MALAT1 rs664589 site G allele carrier was 1.39 times more likely to have NSTEMI than the C allele carrier (95% CI: 1.16-1.61, P = 0.001) and 1.59 times more likely to have STEMI than the C allele carrier (95% CI: 1.31-1.85, P < 0.001). The MALAT1 rs664589 site C>G mutation resulted in an increase in the area under the ROC curve (AUC) of the plasma lncRNA MALAT1 level for the diagnosis of AMI. The plasma lncRNA MALAT1 levels in AMI patients were negatively correlated with hsa-miR-1972, hsa-miR-194-5p, hsa-miR-4717-5p, hsa-miR-6735-3p, and hsa-miR-3677-5p (r = -0.81, -0.75, -0.66, -0.71, and -0.88). The C>G mutation of MAL6641 rs664589 causes an increased risk of AMI in the Chinese Han population. The SNP at this site affects the value of plasma lncRNA MALAT1 in the diagnosis of AMI. The specific mechanism may indicate that the C>G mutation of the MALAT1 rs664589 changes the regulation of miRNAs expression by lncRNA MALAT1.

Isoprene selective hydrogenation using AgCu-promoted Pd nanoalloys.

Alloying is an effective approach to improve the catalysis performance of Pd-based catalysts for the selective hydrogenation of diolefins towards monoolefines. Herein, PdAgCu ternary nanoalloy catalysts were synthesised by a stepwise impregnation method for isoprene selective hydrogenation. The addition of a moderate amount of Ag and Cu to Pd significantly enhances the isoamylene selectivity in the isoprene hydrogenation, and decreases the non-desired over-hydrogenation. In addition, the loading molar ratio of PdAgCu with 3 : 2 : 3 as the optimal ternary nanoalloy composition maximizes the isoprene conversion (98%) and the monoolefins yield (92%). The surface structure of the catalyst was probed using H2-TPR, TEM, XRD, and XPS characterization methods, and it was confirmed that the surface Pd composition ratio between the metallic and oxidized states shows significant effects on the monoolefines yield. This work demonstrates the advantages of PdAgCu ternary nanoalloy catalysts for isoprene selective hydrogenation, which also provides guidelines for the development of other Pd-based ternary nanoalloys for diolefins selective hydrogenation.

DMCA-GAN: Dual Multilevel Constrained Attention GAN for MRI-Based Hippocampus Segmentation.

Precise segmentation of the hippocampus is essential for various human brain activity and neurological disorder studies. To overcome the small size of the hippocampus and the low contrast of MR images, a dual multilevel constrained attention GAN for MRI-based hippocampus segmentation is proposed in this paper, which is used to provide a relatively effective balance between suppressing noise interference and enhancing feature learning. First, we design the dual-GAN backbone to effectively compensate for the spatial information damage caused by multiple pooling operations in the feature generation stage. Specifically, dual-GAN performs joint adversarial learning on the multiscale feature maps at the end of the generator, which yields an average Dice coefficient (DSC) gain of 5.95% over the baseline. Next, to suppress MRI high-frequency noise interference, a multilayer information constraint unit is introduced before feature decoding, which improves the sensitivity of the decoder to forecast features by 5.39% and effectively alleviates the network overfitting problem. Then, to refine the boundary segmentation effects, we construct a multiscale feature attention restraint mechanism, which forces the network to concentrate more on effective multiscale details, thus improving the robustness. Furthermore, the dual discriminators D1 and D2 also effectively prevent the negative migration phenomenon. The proposed DMCA-GAN obtained a DSC of 90.53% on the Medical Segmentation Decathlon (MSD) dataset with tenfold cross-validation, which is superior to the backbone by 3.78%.

Overexpression of zmm28 increases maize grain yield in the field.

Increasing maize grain yield has been a major focus of both plant breeding and genetic engineering to meet the global demand for food, feed, and industrial uses. We report that increasing and extending expression of a maize MADS-box transcription factor gene, zmm28, under the control of a moderate-constitutive maize promoter, results in maize plants with increased plant growth, photosynthesis capacity, and nitrogen utilization. Molecular and biochemical characterization of zmm28 transgenic plants demonstrated that their enhanced agronomic traits are associated with elevated plant carbon assimilation, nitrogen utilization, and plant growth. Overall, these positive attributes are associated with a significant increase in grain yield relative to wild-type controls that is consistent across years, environments, and elite germplasm backgrounds.

Identification and characterization of a novel stay-green QTL that increases yield in maize.

Functional stay-green is a valuable trait that extends the photosynthetic period, increases source capacity and biomass and ultimately translates to higher grain yield. Selection for higher yields has increased stay-green in modern maize hybrids. Here, we report a novel QTL controlling functional stay-green that was discovered in a mapping population derived from the Illinois High Protein 1 (IHP1) and Illinois Low Protein 1 (ILP1) lines, which show very different rates of leaf senescence. This QTL was mapped to a single gene containing a NAC-domain transcription factor that we named nac7. Transgenic maize lines where nac7 was down-regulated by RNAi showed delayed senescence and increased both biomass and nitrogen accumulation in vegetative tissues, demonstrating NAC7 functions as a negative regulator of the stay-green trait. More importantly, crosses between nac7 RNAi parents and two different elite inbred testers produced hybrids with prolonged stay-green and increased grain yield by an average 0.29 megagram/hectare (4.6 bushel/acre), in 2 years of multi-environment field trials. Subsequent RNAseq experiments, one employing nac7 RNAi leaves and the other using leaf protoplasts overexpressing Nac7, revealed an important role for NAC7 in regulating genes in photosynthesis, chlorophyll degradation and protein turnover pathways that each contribute to the functional stay-green phenotype. We further determined the putative target of NAC7 and provided a logical extension for the role of NAC7 in regulating resource allocation from vegetative source to reproductive sink tissues. Collectively, our findings make a compelling case for NAC7 as a target for improving functional stay-green and yields in maize and other crops.

Temperature impacts on the growth of hydrogen bubbles during ultrasonic vibration-enhanced hydrogen generation.

To improve the hydrogen precipitation performance on the surface of the catalytic layer of the proton exchange membrane (PEM) hydrogen cathode, ultrasonic vibration was employed to accelerate the detachment of hydrogen bubbles on the surface of the catalytic layer. Based on the energy and mechanical analyses of nano and microbubbles, the hydrogen bubble generation mechanism and the effect of temperature on bubble parameters during the evolution process when the ultrasonic field is coupled with the electric field are investigated. The nucleation frequency of the hydrogen bubbles, the relationship between the pressure and temperature and the operating temperature during the generation and detachment of bubbles as well as the detachment radius of bubbles under the action of the ultrasonic field are obtained. The effects of ultrasound and temperature on hydrogen production were verified by visual experiments. The results show that the operating temperature affects the nucleation, growth, and detachment processes of hydrogen bubbles. The effect of temperature on the nucleation frequency of bubbles mainly comes from the Gibbs free energy required for the electrolysis reaction. The bubble radius and growth rate are both related to the temperature to the power of one-third. Ultrasonic waves enhance the separation of hydrogen bubbles from the catalyst surface by acoustic cavitation and impact effects. An increase in the working temperature reduces the activation energy barriers to be overcome for the electrolysis reaction of water, which together with a decrease in the Gibbs free energy and the surface tension coefficient, leads to an increase in the nucleation frequency of the catalytic layer and a decrease in the radius of bubble detachment, and thus improves the hydrogen precipitation performance. Visualization experiments show that in actual PEM hydrogen production, ultrasonic intensification can promote the formation of nucleation sites. The ultrasonic induced fine bubble flow not only has a drag effect on the bubble, but also intensifies the polymerization growth of the bubble due to the impact of the fine bubble flow, thus speeding up the detachment of the bubble, shortening the covering time of the hydrogen bubble on the surface of the catalytic electrode, reducing the activation voltage loss and improve the hydrogen production efficiency of PEM. The experimental results show that when the electrolyte is 60°C, the maximum hydrogen production efficiency of ultrasound is increased by 7.34%, and the average hydrogen production efficiency is increased by 5.83%.

Study on the influence of ultrasound on the kinetic behaviour of hydrogen bubbles produced by proton exchange membrane electrolysis with water.

Ultrasonic technology has a significant degassing effect and can increase the efficiency of hydrogen production in the proton exchange membrane electrolysis of water. However, further research is needed to understand its influence mechanism on hydrogen bubbles. In this work, a kinetic analysis is performed to investigate the principle of hydrogen production and the kinetic behaviour of hydrogen bubble evolution by applying the ultrasonic amplification technique under static and flow dynamics in the proton exchange membrane electrolysis cell. The evolution of hydrogen bubbles in the static and in the flow dynamic of the aqueous electrolyte solution under ultrasound was characterised by imaging. The results show that the aqueous electrolyte solution in the flow state reduces the size of hydrogen bubbles and increases the detachment speed compared to the static state, which promotes the process of hydrogen bubble evolution, and that the thermal effect of ultrasound on the temperature of the aqueous electrolyte solution in the flow state is very small compared to the static state and can be ignored. Ultrasound has different effects on the different stages of hydrogen bubble evolution. In the nucleation stage, the ultrasonic cavitation effect increases the highly reactive radicals such as •OH, H•, etc., and the mechanical vibration effect of ultrasound increases the nucleation sites, which are denser and more evenly distributed. In the growth phase, the ultrasonic cavitation effect and the mechanical vibration effect promote the breaking of hydrogen bonds of water molecules and improve mass transport, which promotes the growth of hydrogen bubbles, and the fluctuating energy of positive and negative ultrasound promotes the growth of hydrogen bubbles with the vibration speed. In the detachment phase, the radius of the hydrogen bubbles is influenced by the ultrasound. The radius of the hydrogen bubbles changes with the positive and negative ultrasonic pressure, the radius of the hydrogen bubbles at negative ultrasonic pressure increases, the positive ultrasonic pressure decreases, the changing effect of the radius of the hydrogen bubbles favours the detachment of the hydrogen bubbles. In the polymerisation phase, the ultrasound leads to increased polymerisation of the fine bubble streams. Ultrasound contributes to the hydrogen production effect of proton exchange membrane water electrolysis in actual operation.

Causal relationship between type 2 diabetes mellitus and aortic dissection: insights from two-sample Mendelian randomization and mediation analysis.

Objective: Some evidence suggests a reduced prevalence of type 2 diabetes mellitus (T2DM) in patients with aortic dissection (AD), a catastrophic cardiovascular illness, compared to general population. However, the conclusions were inconsistent, and the causal relationship between T2DM and AD remains unclear. Methods: In this study, we aimed to explore the causal relationship between T2DM and AD using bidirectional Mendelian randomization (MR) analysis. Mediation MR analysis was conducted to explore and quantify the possible mediation effects of 1400 metabolites in T2DM and AD. Results: The results of 26 datasets showed no causal relationship between T2DM and AD (P>0.05). Only one dataset (ebi-a-GCST90006934) showed that T2DM was a protective factor for AD (I9-AORTDIS) (OR=0.815, 95%CI: 0.692-0.960, P=0.014), and did not show horizontal pleiotropy (P=0.808) and heterogeneity (P=0.525). Vanillic acid glycine plays a mediator in the causal relationship between T2DM and AD. The mediator effect for vanillic acid glycine levels was -0.023 (95%CI: -0.066-0.021). Conclusion: From the perspective of MR analysis, there might not be a causal relationship between T2DM and AD, and T2DM might not be a protective factor for AD. If a causal relationship does exist between T2DM and AD, with T2DM serving as a protective factor, vanillic acid glycine may act as a mediator and enhance such a protective effect.

Two-dimensional speckle tracking imaging cardiac motion-based quantitative evaluation of global longitudinal strain among patients with coronary Heart Disease and functions of left ventricular ischemic myocardial segment.

To investigate two-dimensional speckle tracking imaging (2D-STI)-based quantitative evaluation of the influences of different levels of coronary artery stenosis on left ventricular functions and its clinical diagnostic values, 120 patients with coronary heart disease (CHD) were divided into control group (30 cases), mild stenosis group (30 cases), moderate stenosis group (30 cases), and severe stenosis group (30 cases) according to coronary angiography (CAG) results. They underwent routine ultrasound examination and 2D-STI examination. Receiver operating characteristic (ROC) curves were drawn to evaluate the sensitivity and specificity of different levels of coronary artery stenosis. Global longitudinal strain (GLS) of left ventricular myocardium among patients in moderate and severe stenosis groups remarkably declined (P < 0.05). Global radial strain (GRS) and global circular strain (GCS) among patients in severe stenosis group dramatically reduced (P < 0.05). ROC curves revealed that available GLS=-17.2 was the cut-off value for screening moderate coronary stenosis. The sensitivity, specificity, and area under the curve (AUC) amounted to 57.3%, 58.4%, and 0.573, respectively. GLS, GRS, and GCS could be used to screen severe coronary stenosis. When GLS=-16.5 was the cut-off value for screening severe coronary stenosis, sensitivity, specificity, and AUC amounted to 84.3%, 82.5%, and 0.893, respectively. With the aggravation of stenosis, left ventricular systolic function of CHD patients was impaired more significantly. 2D-STI technique could be adopted for the quantitative evaluation of left ventricular strain of patients with coronary stenosis and provided a new method for early clinical diagnosis of CHD.

Ozone exposure response for U.S. soybean cultivars: linear reductions in photosynthetic potential, biomass, and yield.

Current background ozone (O(3)) concentrations over the northern hemisphere's midlatitudes are high enough to damage crops and are projected to increase. Soybean (Glycine max) is particularly sensitive to O(3); therefore, establishing an O(3) exposure threshold for damage is critical to understanding the current and future impact of this pollutant. This study aims to determine the exposure response of soybean to elevated tropospheric O(3) by measuring the agronomic, biochemical, and physiological responses of seven soybean genotypes to nine O(3) concentrations (38-120 nL L(-1)) within a fully open-air agricultural field location across 2 years. All genotypes responded similarly, with season-long exposure to O(3) causing a linear increase in antioxidant capacity while reducing leaf area, light absorption, specific leaf mass, primary metabolites, seed yield, and harvest index. Across two seasons with different temperature and rainfall patterns, there was a robust linear yield decrease of 37 to 39 kg ha(-1) per nL L(-1) cumulative O(3) exposure over 40 nL L(-1). The existence of immediate effects of O(3) on photosynthesis, stomatal conductance, and photosynthetic transcript abundance before and after the initiation and termination of O(3) fumigation were concurrently assessed, and there was no evidence to support an instantaneous photosynthetic response. The ability of the soybean canopy to intercept radiation, the efficiency of photosynthesis, and the harvest index were all negatively impacted by O(3), suggesting that there are multiple targets for improving soybean responses to this damaging air pollutant.

Unsupervised deep consistency learning adaptation network for cardiac cross-modality structural segmentation.

Deep neural networks have recently been succeessful in the field of medical image segmentation; however, they are typically subject to performance degradation problems when well-trained models are tested in another new domain with different data distributions. Given that annotated cross-domain images may inaccessible, unsupervised domain adaptation methods that transfer learnable information from annotated source domains to unannotated target domains with different distributions have attracted substantial attention. Many methods leverage image-level or pixel-level translation networks to align domain-invariant information and mitigate domain shift issues. However, These methods rarely perform well when there is a large domain gap. A new unsupervised deep consistency learning adaptation network, which adopts input space consistency learning and output space consistency learning to realize unsupervised domain adaptation and cardiac structural segmentation, is introduced in this paper The framework mainly includes a domain translation path and a cross-modality segmentation path. In domain translation path, a symmetric alignment generator network with attention to cross-modality features and anatomy is introduced to align bidirectional domain features. In the segmentation path, entropy map minimization, output probability map minimization and segmentation prediction minimization are leveraged to align the output space features. The model conducts supervised learning to extract source domain features and conducts unsupervised deep consistency learning to extract target domain features. Through experimental testing on two challenging cross-modality segmentation tasks, our method has robust performance compared to that of previous methods. Furthermore, ablation experiments are conducted to confirm the effectiveness of our framework.

A task-unified network with transformer and spatial-temporal convolution for left ventricular quantification.

Quantification of the cardiac function is vital for diagnosing and curing the cardiovascular diseases. Left ventricular function measurement is the most commonly used measure to evaluate the function of cardiac in clinical practice, how to improve the accuracy of left ventricular quantitative assessment results has always been the subject of research by medical researchers. Although considerable efforts have been put forward to measure the left ventricle (LV) automatically using deep learning methods, the accurate quantification is yet a challenge work as a result of the changeable anatomy structure of heart in the systolic diastolic cycle. Besides, most methods used direct regression method which lacks of visual based analysis. In this work, a deep learning segmentation and regression task-unified network with transformer and spatial-temporal convolution is proposed to segment and quantify the LV simultaneously. The segmentation module leverages a U-Net like 3D Transformer model to predict the contour of three anatomy structures, while the regression module learns spatial-temporal representations from the original images and the reconstruct feature map from segmentation path to estimate the finally desired quantification metrics. Furthermore, we employ a joint task loss function to train the two module networks. Our framework is evaluated on the MICCAI 2017 Left Ventricle Full Quantification Challenge dataset. The results of experiments demonstrate the effectiveness of our framework, which achieves competitive cardiac quantification metric results and at the same time produces visualized segmentation results that are conducive to later analysis.

Enhancing Arabidopsis leaf growth by engineering the BRASSINOSTEROID INSENSITIVE1 receptor kinase.

The BRASSINOSTEROID INSENSITIVE1 (BRI1) receptor kinase has recently been shown to possess tyrosine kinase activity, and preventing autophosphorylation of the tyrosine-831 regulatory site by site-directed mutagenesis enhances shoot growth. In this study, we characterized the increased leaf growth of Arabidopsis (Arabidopsis thaliana) plants expressing BRI1(Y831F)-Flag compared with BRI1-Flag (both driven by the native promoter and expressed in the bri1-5 weak allele background) and provide insights into the possible mechanisms involved. On average, relative leaf growth rate was increased 16% in the Y831F plants (in the bri1-5 background), and the gain of function of the Y831F-directed mutant was dominant in the wild-type background. Leaves were larger as a result of increased cell numbers and had substantially increased vascularization. Transcriptome analysis indicated that genes associated with brassinolide biosynthesis, secondary cell wall biosynthesis and vascular development, and regulation of growth were altered in expression and may contribute to the observed changes in leaf architecture and whole plant growth. Analysis of gas exchange and chlorophyll fluorescence indicated that Y831F mutant plants had higher rates of photosynthesis, and metabolite analysis documented enhanced accumulation of starch, sucrose, and several amino acids, most prominently glycine and proline. These results demonstrate that mutation of BRI1 can enhance photosynthesis and leaf growth/vascularization and may suggest new approaches to increase whole plant carbon assimilation and growth.

Metoprolol Improves Myocardial Remodeling and Cardiac Function in Patients with Permanent Pacemaker Implantation.

In China, the incidence of arrhythmia has also increased to approximately 20% of all cardiovascular diseases. The incidence of cardiovascular diseases in China has certain characteristics, which are generally low in the south and high in the north, and they tend to be younger and growing. Permanent pacemaker implantation is currently the most effective means of treating arrhythmia and preventing sudden death. To explore the clinical application value of metoprolol in patients after permanent pacemaker implantation. Ninety patients with permanent dual-chamber pacemaker implantation in our hospital are selected and divided into a metoprolol group and a control group according to whether metoprolol is used one week after the operation and 45 patients in each group. After one postoperative week, the LVEF%, LVEDd, LAD, and E/A of the metoprolol and the control groups had no statistically significant differences (p > 0.05). Twelve months postoperatively, the E/A of the metoprolol group is higher than that of the control group (p < 0.05), and LVEDd and LAD are lower than those of the control group (P < 0.05). The NT-proBNP and hs-CRP levels between the metoprolol and control groups had no significant differences (p > 0.05) in the values recorded immediately postoperatively. The NT-proBNP of the metoprolol group is lower than that of the control group (p < 0.05) at 12 months following pacemaker implantation. At one week after surgery, QTd, Pd, and Tp-Te are not significantly different (P > 0.05) between the metoprolol group and the control group, whereas the QTd and Pd times in the metoprolol group are lower than those in the control group (p < 0.05) at the 12-month follow-up. At one week postoperatively, the SDNN, SDANN, and RMSSD between the metoprolol and control groups did not show any statistically significant differences (p > 0.05). The SDANN of the metoprolol group is higher than that in the control group (p < 0.05) in the 12-month evaluation. One week after the operation, the serum IL-6 and TNF-α levels are not significantly different between the metoprolol and control groups (p > 0.05). At 12 months after surgery, the serum IL-6 and TNF-α levels in the metoprolol group are lower than those in the control group (p < 0.05). The incidence of adverse events in the metoprolol group is 9.30% lower than 26.83% in the control group within 12 months after the operation (p < 0.05). The use of metoprolol in patients with permanent pacemaker implantation after surgery can reduce the expansionary remodeling of the left atrium and have less impact on the QT-dispersion and Pd time.

MLRD-Net: 3D multiscale local cross-channel residual denoising network for MRI-based brain tumor segmentation.

The precise segmentation of multimodal MRI images is the primary stage of tumor diagnosis and treatment. Current segmentation strategies often underutilize multiscale features, which can easily lead to loss of contextual information, reduction of low-level features and noise interference. To overcome these issues, a 3D multiscale local cross-channel residual denoising network (MLRD-Net) for an MRI-based brain tumor segmentation algorithm is proposed in this paper. Specifically, we employ encoder-decoder structure to connect local and global features, and enhance the receptive field of the network. Random slice operation has been conducted to enhance robustness. Then, residual blocks with pre-activation operation are developed in down-sampling stage, which effectively improves signal propagation along the network and alleviates network overfitting. Finally, the local cross-channel denoising mechanism is established to eliminate unimportant features without dimensionality reduction. Our proposal was evaluated in Brain Tumor Segmentation 2020 dataset (BraTS 2020), obtaining significantly improved results with mean Dice Similarity Coefficient metric of 0.91, 0.79, and 0.73 for the complete, tumor core, and enhancing tumor regions respectively. Besides, we conduct further practice on BraTS 2019, with the mean Dice Similarity Coefficient metric of 0.89, 0.80, and 0.75. Massive experiments demonstrate that our method is powerful and reliable. It increases little model complexity while achieving very competitive performance.

Decrease in leaf sucrose synthesis leads to increased leaf starch turnover and decreased RuBP regeneration-limited photosynthesis but not Rubisco-limited photosynthesis in Arabidopsis null mutants of SPSA1.

We investigated the individual effect of null mutations of each of the four sucrose-phosphate synthase (SPS) genes in Arabidopsis (SPSA1, SPSA2, SPSB and SPSC) on photosynthesis and carbon partitioning. Null mutants spsa1 and spsc led to decreases in maximum SPS activity in leaves by 80 and 13%, respectively, whereas null mutants spsa2 and spsb had no significant effect. Consistently, isoform-specific antibodies detected only the SPSA1 and SPSC proteins in leaf extracts. Leaf photosynthesis at ambient [CO2] was not different among the genotypes but was 20% lower in spsa1 mutants when measured under saturating [CO2] levels. Carbon partitioning at ambient [CO2] was altered only in the spsa1 null mutant. Cold treatment of plants (4 °C for 96 h) increased leaf soluble sugars and starch and increased the leaf content of SPSA1 and SPSC proteins twofold to threefold, and of the four null mutants, only spsa1 reduced leaf non-structural carbohydrate accumulation in response to cold treatment. It is concluded that SPSA1 plays a major role in photosynthetic sucrose synthesis in Arabidopsis leaves, and decreases in leaf SPS activity lead to increased starch synthesis and starch turnover and decreased Ribulose 1,5-bisphosphate regeneration-limited photosynthesis but not ribulose 1·5-bisphosphate carboxylase/oxygenase (Rubisco)-limited photosynthesis, indicating a limitation of triose-phosphate utilization (TPU).

Anti-inflammatory and Anti-thrombotic Efficacy of Targeted Ultrasound Microbubbles on LPS-induced HUVEC Cells.

BACKGROUND/AIM: The early stage of atherosclerosis (AS) demonstrates a lipid-driven inflammatory cytokine increase. In the present study, we aimed to use ultrasound-targeted microbubble delivery (UTMD) therapy with the Endostar-loaded target microbubbles (MBs) to reduce AS-related inflammatory response. MATERIALS AND METHODS: Normal and lipopolysaccharide (LPS) induced human umbilical vein endothelial cells (HUVECs) were placed in a parallel-plate flow chamber. MBs were perfused through the parallel-plate flow chamber to mimic physiological blood flow. Five groups were set up: G1: Negative control (normal HUVECs); G2: LPS control (LPS induced HUVECs); G3: ICAM-1-loaded-MBs (MBi); G4: Endostar-loaded-MBs (MBe) and G5: Endostar-ICAM-1-loaded-MBs (MBei). mRNA expression of inflammatory factors and release of inflammatory cytokines were detected by RT-PCR and ELISA, respectively. RESULTS: After treatment with MBei, the mRNA expression of cell adhesion molecule-1 (CD31) (p=0.004), endothelin-1 (ET-1) (p=0.010), von willebrand factor (vWF) (p=0.018), extracellular regulated protein kinases (ERK) (p=0.046) and nuclear factor kappa B (NF-κB) (p=0.003) were significantly reduced compared to LPS-induced HUVECs. Release of inflammatory cytokines including tissue factor (TF) (p=0.033), tissue factor pathway inhibitor (TF-PI) (p=0.019), ET-1 (p=0.014), vWF (p=0.030) and blood-coagulation factor VIIα (FVIIα) (p=0.000) were also significantly reduced compared to LPS-induced HUVECs. CONCLUSION: UTMD therapy can inhibit the inflammatory response by reducing atherosclerotic-related inflammatory factors, suggesting a potential treatment at the early-stage of AS.

Ultrasound Microbubble Delivery Targeting Intraplaque Neovascularization Inhibits Atherosclerotic Plaque in an APOE-deficient Mouse Model.

BACKGROUND/AIM: Intraplaque neovascularization is often associated with plaque formation, development and instability, and clinical symptoms in atherosclerosis. The aim of the present study was to investigate a new strategy for treating athrosclerosis by ultrasound-targeted microbubble delivery (UTMD) targeting intraplaque neovascularization in an APOE-deficient mouse model of atherosclerosis. MATERIALS AND METHODS: A mouse model of atherosclerosis was induced by feeding Apoe-/- mice a hypercholesterolemic diet and was verified with hematoxylin and eosin staining and intercellular adhesion molecule 1 (ICAM-1) expression. Targeted microbubbles (MB) were prepared by conjugating microbubbles with biotinylated antibody to ICAM1 (MBi) or with both biotinylated anti-ICAM1 and the angiogenesis inhibitor Endostar (MBie). The targeted microbubbles were analyzed with epifluorescence microscopy and flow cytometry. The animals with induced atherosclerotic plaques received MBi or MBie followed by UTMD treatment. Endostar treatment alone was given to other animals for comparison. Morphological assessment of atherosclerotic plaques was performed after treatment. The expression of angiogenesis marker CD31 was detected by immunohistochemical analysis. RESULTS: Atherosclerotic plaques developed in the entire aorta with significant intraplaque ICAM-1 expression in the APOE-deficient mice following a 30-week hypercholesterolemic diet. Microbubbles were successfully conjugated with anti-ICAM-1 and Endostar, with a conjugation rate of 98.3% and 63.5%, respectively. UTMD with MBie significantly reduced the area of atherosclerotic plaque as compared to the model control (p<0.05). Treatment with Endostar and UTMD with MBie significantly reduced CD31 expression compared with the model control group (p<0.01). Greater significant inhibitory effect on CD31 expression was found in the group treated with UTMD and MBie compared to the Endostar- and UTMD with MBi groups (p<0.01). CONCLUSION: UTMD targeting intraplaque neovascularization was found to inhibit atherosclerotic plaque in a mouse model of atherosclerosis, suggesting the potential of microbubble-mediated ultrasound technology in aiding drug delivery for atherosclerosis treatment.

Modelling photosynthesis in flag leaves of winter wheat (Triticum aestivum) considering the variation in photosynthesis parameters during development.

The Farquhar-von Caemmerer-Berry (FvCB) model of photosynthesis has been widely used to estimate the photosynthetic C flux of plants under different growth conditions. However, the seasonal fluctuation of some photosynthesis parameters (e.g. the maximum carboxylation rate of Rubisco (Vcmax), the maximum electron transport rate (Jmax) and internal mesophyll conductance to CO2 transport (gm)) is not considered in the FvCB model. In this study, we investigated the patterns of the FvCB parameters during flag leaf development based on measured photosynthesis-intercellular CO2 curves in two cultivars of winter wheat (Triticum aestivum L.). Parameterised seasonal patterns of photosynthesis parameters in the FvCB model have subsequently been applied in order to predict the photosynthesis of flag leaves. The results indicate that the Gaussian curve characterises the dynamic patterns of Vcmax, Jmax and gm well. Compared with the model with fixed photosynthesis parameter values, updating the FvCB model by considering seasonal changes in Vcmax and Jmax during flag leaf development slightly improved predictions of photosynthesis. However, if the updated FvCB model incorporated the seasonal patterns of Vcmax and Jmax, and also of gm, predictions of photosynthesis was improved a lot, matching well with the measurements (R2=0.87, P<0.0001). This suggests that the dynamics of photosynthesis parameters, particularly gm, play an important role in estimating the photosynthesis rate of winter wheat.

Impacts of rising tropospheric ozone on photosynthesis and metabolite levels on field grown soybean.

The response of leaf photosynthesis and metabolite profiles to ozone (O3) exposure ranging from 37 to 116 ppb was investigated in two soybean cultivars Dwight and IA3010 in the field under fully open-air conditions. Leaf photosynthesis, total non-structural carbohydrates (TNC) and total free amino acids (TAA) decreased linearly with increasing O3 levels in both cultivars with average decrease of 7% for an increase in O3 levels by 10 ppb. Ozone interacted with developmental stages and leaf ages, and caused higher damage at later reproductive stages and in older leaves. Ozone affected yield mainly via reduction of maximum rate of Rubisco carboxylation (Vcmax) and maximum rates of electron transport (Jmax) as well as a shorter growing season due to earlier onset of canopy senescence. For all parameters investigated the critical O3 levels (∼50 ppb) for detectable damage fell within O3 levels that occur routinely in soybean fields across the US and elsewhere in the world. Strong correlations were observed in O3-induced changes among yield, photosynthesis, TNC, TAA and many metabolites. The broad range of metabolites that showed O3 dose dependent effect is consistent with multiple interaction loci and thus multiple targets for improving the tolerance of soybean to O3.