Failure tolerance of motif structure in biological networks

Complex networks serve as generic models for many biological systems that have been shown to share a number of common structural properties such as power-law degree distribution and small-worldness. Real-world networks are composed of building blocks called motifs that are indeed specific subgraphs of (usually) small number of nodes. Network motifs are important in the functionality of complex networks, and the role of some motifs such as feed-forward loop in many biological networks has been heavily studied. On the other hand, many biological networks have shown some degrees of robustness in terms of their efficiency and connectedness against failures in their components. In this paper we investigated how random and systematic failures in the edges of biological networks influenced their motif structure. We considered two biological networks, namely, protein structure network and human brain functional network. Furthermore, we considered random failures as well as systematic failures based on different strategies for choosing candidate edges for removal. Failure in the edges tipping to high degree nodes had the most destructive role in the motif structure of the networks by decreasing their significance level, while removing edges that were connected to nodes with high values of betweenness centrality had the least effect on the significance profiles. In some cases, the latter caused increase in the significance levels of the motifs.     

Prediction of thermostability from amino acid attributes by combination of clustering with attribute weighting: a new vista in engineering enzymes

The engineering of thermostable enzymes is receiving increased attention. The paper, detergent, and biofuel industries, in particular, seek to use environmentally friendly enzymes instead of toxic chlorine chemicals. Enzymes typically function at temperatures below 60°C and denature if exposed to higher temperatures. In contrast, a small portion of enzymes can withstand higher temperatures as a result of various structural adaptations. Understanding the protein attributes that are involved in this adaptation is the first step toward engineering thermostable enzymes. We employed various supervised and unsupervised machine learning algorithms as well as attribute weighting approaches to find amino acid composition attributes that contribute to enzyme thermostability. Specifically, we compared two groups of enzymes: mesostable and thermostable enzymes. Furthermore, a combination of attribute weighting with supervised and unsupervised clustering algorithms was used for prediction and modelling of protein thermostability from amino acid composition properties. Mining a large number of protein sequences (2090) through a variety of machine learning algorithms, which were based on the analysis of more than 800 amino acid attributes, increased the accuracy of this study. Moreover, these models were successful in predicting thermostability from the primary structure of proteins. The results showed that expectation maximization clustering in combination with uncertainly and correlation attribute weighting algorithms can effectively (100%) classify thermostable and mesostable proteins. Seventy per cent of the weighting methods selected Gln content and frequency of hydrophilic residues as the most important protein attributes. On the dipeptide level, the frequency of Asn-Glu was the key factor in distinguishing mesostable from thermostable enzymes. This study demonstrates the feasibility of predicting thermostability irrespective of sequence similarity and will serve as a basis for engineering thermostable enzymes in the laboratory.     

The role of frozen section in surgical staging of low risk endometrial cancer

Background

The role of frozen section (FS) in intraoperative decision making for surgical staging of endometrial cancer is controversial. Objective of this study is to assess the agreement rate between the FS and paraffin section (PS); and the potential impact of the role of FS in the intra-operative decision making for the complete surgical staging in low risk endometrial cancer.

Methods

This is a retrospective analysis of patients diagnosed with intra-operative FS stage I, grade I or II endometrial cancer from 1995–2004. FS results were compared with final pathology results with regard to tumor grade, depth of myometrial invasion, cervical involvement, lymphovascular invasion, and lymph node involvement. Agreement statistic with kappa was calculated using SPSS statistical software. Categorical variables were tested using chi-square test with p value of ≤0.05 being statistically significant.

Results

Of the 457 patients with endometrial cancer, 146 were evaluated by intra-operative FS and met inclusion criteria. FS results were in disagreement with permanent section in 35% for the grade (kappa 0.58, p = 0.003), 28% for depth of myometrial invasion (kappa 0.61, p<0.0001), 13% for cervical involvement (kappa 0.78, p = 0.002), and 32% for lymphovascular invasion (kappa 0.6, p = 0.01). Permanent pathology upstaged 31.9% & 23.2% of FS stage IA, & IB specimen respectively. Lymph node dissection was done in 56.8%. Lymph node metastasis was identified in 8.4%. Use of intraoperative FS would have resulted in suboptimal surgical treatment in 13% stage IA and 6.6% of stage IB patients respectively by foregoing lymphadenectomy.

Conclusion

A significant number of patients with low risk endometrial cancer by FS were upstaged and upgraded on final pathology. Before placing absolute reliance on intraoperative FS to undertake complete surgical staging, the inherent limitation of the same in predicting final stage and grade highlighted by our data need to be carefully considered.     

Imidazolium or guanidinium/layered manganese (III, IV) oxide hybrid as a promising structural model for the water-oxidizing complex of Photosystem II for artificial photosynthetic systems

Photosystem II is responsible for the light-driven biological water-splitting system in oxygenic photosynthesis and contains a cluster of one calcium and four manganese ions at its water-oxidizing complex. This cluster may serve as a model for the design of artificial or biomimetic systems capable of splitting water into oxygen and hydrogen. In this study, we consider the ability of manganese oxide monosheets to self-assemble with organic compounds. Layered structures of manganese oxide, including guanidinium and imidazolium groups, were synthesized and characterized by scanning electron microscopy, transmission electron microscopy, X-ray diffraction spectrometry, and atomic absorption spectroscopy. The compounds can be considered as new structural models for the water-oxidizing complex of Photosystem II. The overvoltage of water oxidation for the compounds in these conditions at pH = 6.3 is ~0.6 V. These compounds may represent the first step to synthesize a hybrid of guanidinium or imidazole together with manganese as a biomimetic system for the water-oxidizing complex of Photosystem II.     

Investigation of deregulated genes of Notch signaling pathway in human T cell acute lymphoblastic leukemia cell lines and clinical samples

In diagnostic research challenges, quantitative real-time PCR (QPCR) has been widely utilized in gene expression analysis because of its sensitivity, accuracy, reproducibility, and most importantly, quantitativeness. Real-time PCR base kits are wildly applicable in cancer signaling pathways, especially in cancer investigations. T-cell acute lymphoblastic leukemia (T-ALL) is a type of leukemia that is more common in older children and teenagers. Deregulation of the Notch signaling pathway promotes proliferation and inhibits apoptosis of the lymphoblastic T cells. The aim of this study was to investigate the effect of Notch signaling activation on the expression of target genes using real-time QPCR and further use this method in clinical examination after validation. Two T-ALL cell lines, Jurkat and Molt-4, were used as models for activation of the Notch signaling via over-expression of the Notch1 intracellular domain. Expression analysis was performed for six downstream target genes (NCSTN, APH1, PSEN1, ADAM17, NOTCH1 and C-MYC) which play critical roles in the Notch signaling pathway. The results showed significant difference in the expression of target genes in the deregulated Notch signaling pathway. These results were also verified in 12 clinical samples bearing over-expression of the Notch signaling pathway. Identification of such downstream Notch target genes, which have not been studied inclusively, provides insights into the mechanisms of the Notch function in T cell leukemia, and may help identify novel diagnoses and therapeutic targets in acute lymphoblastic leukemia.     

An annotated checklist of Pythium species from Iran

The genus Pythium, with slightly over 280 described species has been classified traditionally with other filamentous, coenocytic, sporangia-producing fungi as “Phycomycetes”. However, with recent advances in chemical, ultrastructural and molecular studies Pythium spp. are now considered as “fungus-like organisms” or “pseudo-fungi” and are placed in the kingdom Chromista or kingdom Straminopila, distinct from the true fungi or the kingdom Fungi. Little is known about the biodiversity of Pythium in Iran. This paper attempts to assess the position of the genus Pythium and provides details of the historical development of the study of Pythium in Iran. The survey list contains 33 species, 4 species groups and 1 unknown species of Pythium.     

Inhibitory effect of Trichoderma isolates on growth of Alternaria alternata,the causal agent of leaf spot disease on sunflower,under laboratory conditions

Several species of the genus Alternaria are involved in leaf spot disease of sunflower, with Alternaria alternata being the dominant species responsible for this disease in Iran and many other sunflower-producing areas, worldwide. The disease causes a progressive destruction of the photosynthetic apparatus, resulting in annual yield loss. The routine disease management strategies are not effective for disease control; hence, alternative measures for disease management are of great interest. In the present study, the efficacy of Trichoderma harzianum T22 and Trichoderma sp. on biological control of the causal agent was evaluated under laboratory conditions. The effect of Trichoderma isolates on dry weight (DW) and radial growth (RG) rate of A. alternata was evaluated using dual culture, volatile and non-volatile cellular metabolites. The results obtained in this study revealed that in both Trichoderma isolates, non-volatile cellular metabolites had the highest inhibitory effect on DW and RG rate of the causal agent. Owing to explicit inhibitory effect of non-volatile cellular metabolites on A. alternata, the inhibitory effects of different concentrations of non-volatile cellular metabolites were evaluated on DW and RG rate of the A. alternata. The obtained results showed that non-autoclaved 75 and 50% concentrations and undiluted (100%) autoclaved non-volatile cellular metabolites from Trichoderma sp. had the highest inhibitory effect on DW and RG rate of the causal agent. The overall results of this study reveal that Trichoderma spp. have excellent efficacy on biological control of A. alternata under laboratory condition; such that, further studies on the potential of Trichoderma spp. in biological control of Alternaria leaf spot disease of sunflower under green house and field conditions are necessary.