The expression of Rho-GTPase and Rho-kinase in aneurismal aorta.

<p>AAA was created via intra-aortic PPE infusion as described in methods. The relative mRNA expression of RhoA, RhoB, RhoC, ROCK1 and ROCK2 in PPE or PBS infusion mice was examined by real-time PCR. The mRNA expression of each gene in aorteo in Sham-operated group is defined as one. Data show as Mean±SD, n = 7–9 mice for each group; Nonparametric Mann-Whitney test. *<i>P</i><0.05 vs PBS group; n.s. no significant.</p

NMR Characterization of PAMAM_G5.NH₂ Entrapped Atomic and Molecular Assemblies

High resolution NMR spectroscopy, NMR diffusiometry, and NMR cryoporometry have been used to investigate aqueous solution (D₂O) of PAMAM_G5.NH₂-(Au)_25–100 and PAMAM_G5.NH₂-(H₂O)₁₀₀₀–(H₂O)₄₀₀₀ systems. In the case of dendrimer entrapped gold nanoparticles, the detailed analysis of high resolution NMR spectra has shown that no precursor complex formation happens under the circumstances applied for reduction. Further PGSE results verify that gold nanoparticles of 1.9–2.6 nm size are entrapped in the outermost part of the dendrimers and probably more than one dendrimer molecule takes part in the stabilization process. This system looks like a transition state between dendrimer encapsulated nanoparticles (DENs) and dendrimer stabilized nanoparticles (DSNs), and we deal with it in details for what this means. NMR cryoporometry experiments were performed to detect the encapsulation of water molecules. The results show that, in the swelling PAMAM_G5.NH₂ dendrimers, by adding water step by step, there are specific cavities for water with diameters of 3.6 and 5.2 nm. These cavities have a penetrable wall for water molecules and probably exist very close to the terminal groups. The permeability of the cavities is increasing with the increase of the water content. In dilute solution, the formation of nanoparticles is determined by the ratio of the rate of nucleation and aggregation and the latter is affected by the PAMAM_G5.NH₂

Fasudil treatment attenuates the inflammatory cell infiltration in AAAs Histological staining of EVG, SMC, CD31+ blood vessels and CD68+ macrophages were performed to evaluate the development of AAAs.

<p>Aortic sections were stained with Elastin Masson Stain for elastin fibers or immunostained with antibody against SMC a-actin for SMCs, antibody against CD31 for blood vessels and antibody against CD68 for macrophages. (A): Representative aortic histology images for elastin, SMCs, MVD and macrophages in each group. Original magnification:×200. (B&C):Medial elastin fragmentation and SMCs destruction were scored as mild 1 to severe 5 using a histology grading system. (D&E): CD31+ blood vessels and CD68+ macrophages in media and adventitia were counted on each ACS, and data present as Mean and SD per ACS. n = 7–9 in each group. Nonparametric Mann-Whitney test. * <i>P</i><0.05 vs vehicle group.</p

Fasudil treatment in existing aneurysm.

<p>Mice were treated orally with vehicle or Fasudil thrice daily at dose of 200/kg/day during the period of day 4 to day 14 after PPE infusion. Changes in aortic diameter were measured on day 3 and 10 after Fasudil treatment. (A): Representative ultrasound images of aorta from PPE-infused mice treated with vehicle or Fasudil. (B): Mean and SD of aortic diameters changes after vehicle or Fasudil treatment. Nonparametric Mann-Whitney test, n = 7–9 mice in each group. * <i>P</i><0.05. (C): Aortic sections were stained with Elastin Masson stain or with an antibody against SMC a-actin, CD31 and CD68 respectively, representative images of tissue immunostaining have been shown. (D-G): EVG, SMCs, CD31+ blood vessels and CD68+ macrophages in media and adventitia were counted on each ACS, and data present as Mean and SD per ACS. n = 7–9 in each group. Nonparametric Mann-Whitney test. *<i>P</i><0.05 vs vehicle group.</p

Fasudil treatment inhibits AAA formation and progression Male C57BL/6 mice were orally administrated with vehicle or Fasudil at dose of 200 mg/kg/day during the period of day 1 prior to PPE infusion to day 14 after PPE infusion.

<p>AAAs diameter was measured by using ultrasonography. An AAA was defined as a more than 50% increasing in the aortic diameter over baseline level. (A): Representative ultrasound images of aorta from PPE-infused mice treated with vehicle or Fasudil. (B): Mean and SD of aortic diameters at day 0, 3, 7, 14 after PPE infusion, ANOVA followed by Nonparametric Mann-Whitney test, n = 7–9 mice in each group. *<i>P</i><0.05. (C): The incidence of AAA in PPE-infused mice with vehicle or Fasudil treatment was evaluated. Kaplan-Meier analysis, n = 7–9 mice in each group. *<i>P</i><0.05 vs vehicle group.</p

Editorial: Neural learning in life system and energy system

As well recognized, neural learning is one of the most powerful and popular techniques. The last decade has also witnessed the rapid advancements of neural learning techniques, which consists of various neural learning approaches such as neural networks, deep learning, evolutionary learning, etc. In recent years, to understand the interaction between components (i.e., cells, tissues and organisms) of life system and predict system behaviors, people have started using neural learning techniques to model and simulate life systems. Although significant progress has been made in the research of life systems, the recently developed neural learning methods still cannot match the demands of exploiting life systems due to the complexity of a life system. Meanwhile, neural learning techniques have been employed to model and control energy systems. However, with the widely use of information and communications techniques in energy system, the new problems such as cyber security pose huge challenges to energy system. Therefore, it has become critical to explore neural learning techniques for life system and energy system. This special issue collected nine papers reporting the recent developments of neural learning in life system and energy system

TF-miRNA co-regulatory network based on FFLs reconstructed from the prostate cancer dataset.

<p>Red circles indicate target genes; blue triangles and orange squares indicate TFs and miRNAs. Red T shape edge: miRNA regulation; blue arrow shape edge: TF regulation.</p

Comparison of classification performance using identified FFLs.

<p>Comparison of classification performance using identified FFLs.</p

Subnetwork of miRNA hsa-let-7e base on FFLs found in pan-cancer dataset.

<p>The subnetwork was drawn with all direct linked nodes of hsa-let-7e, which is shown to be the hub of the co-regulatory network.</p

Examples of the filter and wrapper feature selection process.

<p>(<b>A</b>) An example showing mutual information of all regulators in the filter feature selection process. We chose the top-ranking regulators selected by mRMR, which demonstrate larger mutual information values that indicate high relevance with the target gene. (<b>B</b>) An example illustrating <i>p</i>-value change of linear regression model in the wrapper feature selection process. When 17 features are removed, the optimal <i>p</i>-value (marked by red ‘*’) found by wrapper feature selection is 3.9×10⁻⁴.</p