Identification of Alkaloid Compounds Arborinine and Graveoline from Ruta angustifolia (L.) Pers for their Antifungal Potential against Isocitrate lyase (ICL1) gene of Candida albicans

Mycopathologia - Candida albicans has been reported globally as the most widespread pathogenic species contributing candidiasis from superficial to systemic infections in immunocompromised...     

Analysis of movement in primary maize roots

Studying plant root kinematics is important for understanding certain aspects of root growth and movement, which are strictly correlated in plants. However, there is little available data on autonomous movements in plant roots, such as nutations, and the data that are available are poorly described. We investigated the autonomous movements during growth in primary maize roots by estimating the main kinematic parameters of nutations (i.e., the period of duration and amplitude) and the growth rate. The estimations of nutation parameters were performed by developing dedicated methods, which are based on the analysis of root tip displacement and tip velocity. The data relative to the tip displacements were obtained using tip tracing software developed by our team specifically for this purpose. The results confirmed that the nutational phenomenon covers the continuous range of periods and amplitudes, with certain dominant period-amplitude types, which we clustered into three groups: i) amplitudes less than 0.1 mm and 4–16 min periods, ii) amplitudes less than 0.1 mm and 20–120 min periods, and iii) amplitudes greater than 0.1 mm and 24–120 min periods.     

Diversity of the cassiicolin gene in Corynespora cassiicola and relation with the pathogenicity in Hevea brasiliensis

Corynespora cassiicola is an important plant pathogenic Ascomycete causing the damaging Corynespora Leaf Fall (CLF) disease in rubber tree (Hevea brasiliensis). A small secreted glycoprotein named cassiicolin was previously described as an important effector of C. cassiicola. In this study, the diversity of the cassiicolin-encoding gene was analysed in C. cassiicola isolates sampled from various hosts and geographical origins. A cassiicolin gene was detected in 47 % of the isolates, encoding up to six distinct protein isoforms. In three isolates, two gene variants encoding cassiicolin isoforms Cas2 and Cas6 were found in the same isolate. A phylogenetic tree based on four combined loci and elucidating the diversity of the whole collection was strongly structured by the toxin class, as defined by the cassiicolin isoform. The isolates carrying the Cas1 gene (toxin class Cas1), all grouped in the same highly supported clade, were found the most aggressive on two rubber tree cultivars. Some isolates in which no Cas gene was detected could nevertheless generate moderate symptoms, suggesting the existence of other yet uncharacterized effectors. This study provides a useful base for future studies of C. cassiicola population biology and epidemiological surveys in various host plants.     

Patients with ovarian carcinoma excrete different altered levels of urine CD59, kininogen-1 and fragments of inter-alpha-trypsin inhibitor heavy chain H4 and albumin

Background  

Diagnosis of ovarian carcinoma is in urgent need for new complementary biomarkers for early stage detection. Proteins that are aberrantly excreted in the urine of cancer patients are excellent biomarker candidates for development of new noninvasive protocol for early diagnosis and screening purposes. In the present study, urine samples from patients with ovarian carcinoma were analysed by two-dimensional gel electrophoresis and the profiles generated were compared to those similarly obtained from age-matched cancer negative women.     

Rapid bioremediation of Alizarin Red S and Quinizarine Green SS dyes using <Emphasis Type="Italic">Trichoderma lixii</Emphasis> F21 mediated by biosorption and enzymatic processes

In this study, a newly isolated ascomycete fungus Trichoderma lixii F21 was explored to bioremediate the polar [Alizarin Red S (ARS)] and non-polar [Quinizarine Green SS (QGSS)] anthraquinone dyes. The bioremediation of ARS and QGSS by T. lixii F21 was found to be 77.78 and 98.31 %, respectively, via biosorption and enzymatic processes within 7 days of incubation. The maximum biosorption (ARS = 33.7 % and QGSS = 74.7 %) and enzymatic biodegradation (ARS = 44.1 % and QGSS = 23.6 %) were observed at pH 4 and 27 °C in the presence of glucose and yeast extract. The laccase and catechol 1,2-dioxygenase produced by T. lixii F21 were involved in the molecular conversions of ARS and QGSS to phenolic and carboxylic acid compounds, without the formation of toxic aromatic amines. This study suggests that T. lixii F21 may be a good candidate for the bioremediation of industrial effluents contaminated with anthraquinone dyes.     

Aquatic environments: A potential source of antimicrobial-resistant Vibrio spp.

Vibrio spp. are associated with water and seafood-related outbreaks worldwide. They are naturally present in aquatic environments such as seawater, brackish water and freshwater environments. These aquatic environments serve as the main reservoirs of antimicrobial-resistant genes and promote the transfer of antimicrobial-resistant bacterial species to aquatic animals and humans through the aquatic food chain. Vibrio spp. are known as etiological agents of cholera and non-cholera Vibrio infections in humans and animals. Antimicrobial-resistant Vibrio species have become a huge threat in regard to treating Vibrio infections in aquaculture and public health. Most of the Vibrio spp. possess resistance towards the commonly used antimicrobials, including β-lactams, aminoglycosides, tetracyclines, sulphonamides, quinolones and macrolides. The aim of this review is to summarize the antimicrobial resistance properties of Vibrio spp. isolated from aquatic environments to provide awareness about potential health risks related to Vibrio infections in aquaculture and public health.     

Stimulatory Effects of Polysaccharide Fraction from Solanum nigrum on RAW 264.7 Murine Macrophage Cells

The polysaccharide fraction from Solanum nigrum Linne has been shown to have antitumor activity by enhancing the CD4⁺/CD8⁺ ratio of the T-lymphocyte subpopulation. In this study, we analyzed a polysaccharide extract of S. nigrum to determine its modulating effects on RAW 264.7 murine macrophage cells since macrophages play a key role in inducing both innate and adaptive immune responses. Crude polysaccharide was extracted from the stem of S. nigrum and subjected to ion-exchange chromatography to partially purify the extract. Five polysaccharide fractions were then subjected to a cytotoxicity assay and a nitric oxide production assay. To further analyze the ability of the fractionated polysaccharide extract to activate macrophages, the phagocytosis activity and cytokine production were also measured. The polysaccharide fractions were not cytotoxic, but all of the fractions induced nitric oxide in RAW 264.7 cells. Of the five fractions tested, SN-ppF3 was the least toxic and also induced the greatest amount of nitric oxide, which was comparable to the inducible nitric oxide synthase expression detected in the cell lysate. This fraction also significantly induced phagocytosis activity and stimulated the production of tumor necrosis factor-α and interleukin-6. Our study showed that fraction SN-ppF3 could classically activate macrophages. Macrophage induction may be the manner in which polysaccharides from S. nigrum are able to prevent tumor growth.     

Global Warming: Predicting OPEC Carbon Dioxide Emissions from Petroleum Consumption Using Neural Network and Hybrid Cuckoo Search Algorithm

Background

Global warming is attracting attention from policy makers due to its impacts such as floods, extreme weather, increases in temperature by 0.7°C, heat waves, storms, etc. These disasters result in loss of human life and billions of dollars in property. Global warming is believed to be caused by the emissions of greenhouse gases due to human activities including the emissions of carbon dioxide (CO₂) from petroleum consumption. Limitations of the previous methods of predicting CO₂ emissions and lack of work on the prediction of the Organization of the Petroleum Exporting Countries (OPEC) CO₂ emissions from petroleum consumption have motivated this research.

Methods/Findings

The OPEC CO₂ emissions data were collected from the Energy Information Administration. Artificial Neural Network (ANN) adaptability and performance motivated its choice for this study. To improve effectiveness of the ANN, the cuckoo search algorithm was hybridised with accelerated particle swarm optimisation for training the ANN to build a model for the prediction of OPEC CO₂ emissions. The proposed model predicts OPEC CO₂ emissions for 3, 6, 9, 12 and 16 years with an improved accuracy and speed over the state-of-the-art methods.

Conclusion

An accurate prediction of OPEC CO₂ emissions can serve as a reference point for propagating the reorganisation of economic development in OPEC member countries with the view of reducing CO₂ emissions to Kyoto benchmarks—hence, reducing global warming. The policy implications are discussed in the paper.