Association of Genetic Structure and Diversity in Iranian Wild Germplasms of Mentha longifolia L. Based on Phenotypical,Biochemical, and Molecular Markers

Mentha longifolia L. is well-known to be one of the most pervasive wild-growing species of the Lamiaceae family, which has extensive beneficial properties in the fields of pharmacology and biological products. In the present study, the correlation between Inter-simple sequence repeat (ISSR) markers and morpho-chemical parameters of twenty different M. longifolia accessions (MLACs) were assessed. The geographic information system (GIS) has been employed to interpret the original habitat of the accessions in Iran. ISSR analysis indicated a remarkable difference in the studied accessions, segregated them into three main groups, constructed by an unweighted pair-group method with arithmetic (UPGMA) and principal coordinate analysis (PCoA). A total of 89 bands were generated by 12 ISSR primers, among which 82 (91.97 %) of them were polymorphic. The cluster analysis based on agro-morphological data scattered MLACs into two main groups. The essential oils (EOs) were analyzed through GC/FID/MS, and four chemotypes were characterized according to the major constituents. Pulegone ranged from 0.17 to 69.50 % was the main oil constituent with the highest content. Also, HPLC-PDA was employed to identify and to quantify the phenolic compounds in the MeOH extracts of MLACs. Heatmap cluster based on phenolic compounds produced three main categories of accessions. The components identified in the extracts were rosmarinic acid, rutin, vanillic acid, ferulic acid, chlorogenic acid, caffeic acid, 3,4-dihydroxybenzoic acid, 2,5-dihydroxybenzoic acid, and p-coumaric acid, which among them rosmarinic acid (RA) varied from 39.16 to 261.55 mg/100 g (DW) as a predominant constituent. Subsequently, multiple regression analyses between ISSR fragments and morpho-chemical data illustrated considerable relationships in the plant materials. The high variation and correlation observed in metabolic and phenotypic traits of MLACs establish an adequate source to conduct reserves conservation programs.     

Estimates of relatedness and inbreeding in goose strains from DNA fingerprints

The purpose of this study was to determine if DNA fingerprints (DFPs) could be used to estimate relatedness and inbreeding of strains of geese and to compare three methods of calculating relatedness indices. Strains included a control and selected strain from each of the Chinese and Synthetic (Chinese, Hungarian and Pilgrim) breeds. DFP patterns for each strain were based on individual DNA samples from six females, or on pooled DNA from 15 females different from those used for individual samples. Three relatedness indices were used, namely, genetic distance, modified Rogers distance and band sharing. All relatedness indices showed a closer relationship of strains within than between breeds. Correlation coefficients among relatedness indices were higher based on pooled DNA (r ≥|0·97|) than those based on individual DNA (r ≥|0·741). Inbreeding estimates were higher for selected compared with control strains. It appears that the use of DFPs to estimate relatedness, regardless of index used, and inbreeding can be valuable for studying geese where there is a limited breeding history.     

From mutations to mechanisms and dysfunction via computation and mining of protein energy landscapes

Background

The protein energy landscape underscores the inherent nature of proteins as dynamic molecules interconverting between structures with varying energies. Reconstructing a protein’s energy landscape holds the key to characterizing a protein’s equilibrium conformational dynamics and its relationship to function. Many pathogenic mutations in protein sequences alter the equilibrium dynamics that regulates molecular interactions and thus protein function. In principle, reconstructing energy landscapes of a protein’s healthy and diseased variants is a central step to understanding how mutations impact dynamics, biological mechanisms, and function.

Results

Recent computational advances are yielding detailed, sample-based representations of protein energy landscapes. In this paper, we propose and describe two novel methods that leverage computed, sample-based representations of landscapes to reconstruct them and extract from them informative local structures that reveal the underlying organization of an energy landscape. Such structures constitute landscape features that, as we demonstrate here, can be utilized to detect alterations of landscapes upon mutation.

Conclusions

The proposed methods detect altered protein energy landscape features in response to sequence mutations. By doing so, the methods allow formulating hypotheses on the impact of mutations on specific biological activities of a protein. This work demonstrates that the availability of energy landscapes of healthy and diseased variants of a protein opens up new avenues to harness the quantitative information embedded in landscapes to summarize mechanisms via which mutations alter protein dynamics to percolate to dysfunction.

     

Reduction of marginal mass required for successful islet transplantation in a diabetic rat model using adipose tissue–derived mesenchymal stromal cells

Background aims

Adipose tissue–derived mesenchymal stromal cells (AT-MSCs), widely known as multipotent progenitors, release several cytokines that support cell survival and repair. There are in vitro and in vivo studies reporting the regenerative role of AT-MSCs possibly mediated by their protective effects on functional islet cells as well as their capacity to differentiate into insulin-producing cells (IPCs).

Toward <Emphasis Type="Italic">Escherichia coli</Emphasis> bacteria machine for water oxidation

Nature uses a Mn oxide-based catalyst for water oxidation in plants, algae, and cyanobacteria. Mn oxides are among major candidates to be used as water-oxidizing catalysts. Herein, we used two straightforward and promising methods to form Escherichia coli bacteria/Mn oxide compounds. In one of the methods, the bacteria template was intact after the reaction. The catalysts were characterized by X-ray photoelectron spectroscopy, visible spectroscopy, scanning electron microscopy, high-resolution transmission electron microscopy, diffuse reflectance infrared Fourier transform spectroscopy, Raman spectroscopy, and X-ray diffraction spectrometry. Electrochemical properties of the catalysts were studied, and attributed redox potentials were assigned. The water oxidation of the compounds was examined under electrochemical condition. Linear sweep voltammetry showed that the onsets of water oxidation in our experimental condition for bacteria and Escherichia coli bacteria/Mn oxide were 1.68 and 1.56 V versus the normal hydrogen electrode (NHE), respectively. Thus, the presence of Mn oxide in the catalyst significantly decreased (~?120 mV) the overpotential needed for water oxidation.     

L-Arginine inhibits vasopressin-stimulated mesangial cell Ca2+

L-Arginine (L-Arg) affects variousparameters that modulate the progression of renal disease. These samefactors [e.g., glomerular filtration rate, changes in mesangialcell (MC) tension, and production of NO] are all controlled atleast in part by changes in MC intracellular Ca²⁺concentration([Ca²⁺]_i). Wetherefore evaluated the effect of L-Arg on MC[Ca²⁺]_i. We found thatL-Arg inhibits the vasopressin-stimulated rise in MC[Ca²⁺]_i both in rat andmurine cell cultures. This effect does not appear to be due tometabolism of L-Arg to either NO or L-ornithine (L-Orn). Blocking the metabolism of L-Arg withN-monomethyl-L-arginine, an NOsynthase inhibitor, or with 20 mM L-valine(L-Val), an inhibitor of Orn formation,does not reverse the inhibition. However, other cationic amino acids,as well guanidine, the functional group ofL-Arg, all inhibit thevasopressin-stimulated rise in[Ca²⁺]_i,consistent with a structural basis for this effect. We conclude that1)L-Arg inhibitsvasopressin-stimulated murine and rat MC [Ca²⁺]_irise, 2) this inhibition is notmediated by metabolism of L-Arg to either NO or L-Orn, and3) the effect ofL-Arg is due to its cationicfunctional group, guanidine.

     

Inhibition of Notch signaling pathway using γ-secretase inhibitor delivered by a low dose of Triton-X100 in cultured oral cancer cells

How to effectively delivering therapeutic agents, including γ-secretase inhibitors (GSIs), into live cells, remains a significant challenge. This study assessed the effect of Notch signaling inhibition by examining levels of the Notch1 intracellular domain (N1ICD) in cultured oral cancer cells analyzed with random stitched images (2D) and 3D visualizations using confocal microscopy and quantitative gene analysis. Substantially, we have developed a novel method to assist the delivery of γ-secretase inhibitor, DAPT, into live cells in the presence of an effective minimum concentration of Triton-X100 (0.001%) without damaging cell activity and membrane integrity assessed with cell proliferation assays. The images obtained in this study showed that DAPT alone could not block the γ-secretase inhibitor despite inhibiting cell growth. Further analysis of quantitative gene expressions of Notch signaling canonical pathway to verify the effectiveness of the novel method for delivering inhibitor into live cells, displayed deregulation of Notch1, Delta-like ligand 1 (DLL1) and hairy and enhancer of split 1 (Hes1). Our data suggest that Notch1/Hes1 signaling pathway is deactivated using DAPT with a low dose of Triton-X100 in this cancer cells. And the finding also suggests that Notch1 could be engaged by DLL1 to promote differentiation in oral cancer cells. Using this approach, we demonstrate that Triton-X100 is a promising and effective permeabilization agent to deliver γ-secretase inhibitor DAPT into live oral epithelial cells. This strategy has the potential to implicate in the treatment of cancer diseases.     

Energy aware resource allocation of cloud data center: review and open issues

The demand for cloud computing is increasing dramatically due to the high computational requirements of business, social, web and scientific applications. Nowadays, applications and services are hosted on the cloud in order to reduce the costs of hardware, software and maintenance. To satisfy this high demand, the number of large-scale data centers has increased, which consumes a high volume of electrical power, has a negative impact on the environment, and comes with high operational costs. In this paper, we discuss many ongoing or implemented energy aware resource allocation techniques for cloud environments. We also present a comprehensive review on the different energy aware resource allocation and selection algorithms for virtual machines in the cloud. Finally, we come up with further research issues and challenges for future cloud environments.     

Expression of Vascular Endothelial Growth Factor A and Its Type 1 Receptor in Supratentorial Neoplasm

Background:Vascular endothelial growth factor (VEGF) is one of the primary angiogenesis regulators in solid cancers. Brain solid tumors are life-threatening diseases in which angiogenesis is an important phase of tumor development and progression. In the present study, VEGF-A and VEGF receptor (VEGF-R1) gene expression was evaluated in CNS brain tumors.Methods:VEGF-A and VEGF-R1 expression was quantified using real-time PCR on fresh biopsies of 38 supratentorial brain tumors compared to 30 non-tumoral tissues. Then, the correlations were investigated with clinic-pathological and demographic factors of the patients.Results:PCR product sequencing confirmed the validity of qRT-PCR. Although VEGF-A and VEGF-R1 expression showed increasing trends with the progression of cell proliferation in different stages of astrocytoma, VEGF-R1 did not meet the 95% confidence interval in other brain tumors. An increasing trend in VEGF-A expression and a declining trend in VEGF-R1 expression from Stage I to II were observed in meningioma. VEGF-A and VEGF-R1 expression had no significant correlation with age and gender. Although peritumoral brain edema (PTBE) in astrocytoma was significantly associated with tumor stages, VEGF-A and VEGF-R1 were not correlated with PTBE in meningioma and metastasis.Conclusion:VEGF-A is a valuable factor for the prognosis of PTBE and malignancy in astrocytoma and is helpful in monitoring treatment approaches.Key Words: Angiogenesis, Brain edema, Brain neoplasm, Peritumoral brain, VEGF, VEGFR1