Modelling India’s coal production with a negatively skewed curve-fitting model

India’s coal demand is forecast to increase at a rapid pace in the future due to the country’s economic and population growth. Analyzing the scope for future production of India’s domestic coal resources, therefore, plays a vital role in the country’s development of sound energy policies. This paper presents a quantitative scenario analysis of India’s potential future coal production by using a negatively skewed curve-fitting model and a range of estimates of the country’s ultimately recoverable resources (URR) of coal. The results show that the resource base is sufficient for India’s coal production to keep increasing over the next few decades, to reach between 2400 and 3200 Mt/y at 2050, depending on the assumed value of URR. A further analysis shows that the high end of this range, which corresponds to our ‘GSI’ scenario, can be considered as the probable upper-bound to India’s domestic coal production. Comparison of production based on the ‘GSI’ scenario with India’s predicted demand shows that the domestic production of coal will be insufficient to meet the country’s rising coal demand, with the gap between demand and production increasing from its current value of about 268 Mt/y to reach 300 Mt/y in 2035, and 700 Mt/y by 2050. This increasing gap will be challenging for the energy security of India

Prolonged Antibiotic Treatment does not Prevent Intra-Abdominal Abscesses in Perforated Appendicitis

Contains fulltext : 89619.pdf (publisher's version ) (Open Access)BACKGROUND: Children with perforated appendicitis have a relatively high risk of intra-abdominal abscesses. There is no evidence that prolonged antibiotic treatment after surgery reduces intra-abdominal abscess formation. We compared two patient groups with perforated appendicitis with different postoperative antibiotic treatment protocols. METHODS: We retrospectively reviewed patients younger than age 18 years who underwent appendectomy for perforated appendicitis at two academic hospitals between January 1992 and December 2006. Perforation was diagnosed during surgery and confirmed during histopathological evaluation. Patients in hospital A received 5 days of antibiotics postoperatively, unless decided otherwise on clinical grounds. Patients in hospital B received antibiotics for 5 days, continued until serum C-reactive protein (CRP) was <20 mg/l. Univariate logistic regression analysis was performed on intention-to-treat basis. p < 0.05 was considered significant. RESULTS: A total of 149 children underwent appendectomy for perforated appendicitis: 68 in hospital A, and 81 in hospital B. As expected, the median (range) use of antibiotics was significantly different: 5 (range, 1-16) and 7 (range, 2-32) days, respectively (p < 0.0001). However, the incidence of postoperative intra-abdominal abscesses was similar (p = 0.95). Regression analysis demonstrated that sex (female) was a risk factor for abscess formation, whereas surgical technique and young age were not. CONCLUSIONS: Prolonged use of antibiotics after surgery for perforated appendicitis in children based on serum CRP does not reduce postoperative abscess formation.1 december 201

Texture analysis of thick bismuth ferrite lead titanate layers

The template grain growth technique was used to synthesis textured 60BiFeO3-PbTiO3(60:40BFPT) by using platelets of BaTiO3 as template. Synchrotron measurement clearly showed textured 60:40BFPT. Moreover, in situ high energy synchrotron radiation was employed to investigate the influence of an external electric filed on crystallographic structure of mixed phase 60:40BFPT. Application of an electric field ≥ 1 kV/mm resulted in phase transformation from mixed rhombohedral/tetragonal phases (≈ 73.5% tetragonal / 26.5% rhombohedral) to predominately tetragonal phase (≈ 95%) at applied field of 6 kV/mm. A crystallographic texture refinement was done by using software package materials analysis using diffraction (MAUD) with a 4th order spherical harmonic orientation distribution function (ODF). This refinement was completed using a P4mm+Cm structure model. Texture coefficients were constrained such that the equivalent texture coefficients of each phase are the same. The resulting texture refinement determined that sample has a 1.3 multiples of random distribution (MRD) {100} crystallographic texture

Sorting Signals, N-Terminal Modifications and Abundance of the Chloroplast Proteome

Characterization of the chloroplast proteome is needed to understand the essential contribution of the chloroplast to plant growth and development. Here we present a large scale analysis by nanoLC-Q-TOF and nanoLC-LTQ-Orbitrap mass spectrometry (MS) of ten independent chloroplast preparations from Arabidopsis thaliana which unambiguously identified 1325 proteins. Novel proteins include various kinases and putative nucleotide binding proteins. Based on repeated and independent MS based protein identifications requiring multiple matched peptide sequences, as well as literature, 916 nuclear-encoded proteins were assigned with high confidence to the plastid, of which 86% had a predicted chloroplast transit peptide (cTP). The protein abundance of soluble stromal proteins was calculated from normalized spectral counts from LTQ-Obitrap analysis and was found to cover four orders of magnitude. Comparison to gel-based quantification demonstrates that ‘spectral counting’ can provide large scale protein quantification for Arabidopsis. This quantitative information was used to determine possible biases for protein targeting prediction by TargetP and also to understand the significance of protein contaminants. The abundance data for 550 stromal proteins was used to understand abundance of metabolic pathways and chloroplast processes. We highlight the abundance of 48 stromal proteins involved in post-translational proteome homeostasis (including aminopeptidases, proteases, deformylases, chaperones, protein sorting components) and discuss the biological implications. N-terminal modifications were identified for a subset of nuclear- and chloroplast-encoded proteins and a novel N-terminal acetylation motif was discovered. Analysis of cTPs and their cleavage sites of Arabidopsis chloroplast proteins, as well as their predicted rice homologues, identified new species-dependent features, which will facilitate improved subcellular localization prediction. No evidence was found for suggested targeting via the secretory system. This study provides the most comprehensive chloroplast proteome analysis to date and an expanded Plant Proteome Database (PPDB) in which all MS data are projected on identified gene models

Peak intensity prediction in MALDI-TOF mass spectrometry: A machine learning study to support quantitative proteomics

Timm W, Scherbart A, Boecker S, Kohlbacher O, Nattkemper TW. Peak intensity prediction in MALDI-TOF mass spectrometry: A machine learning study to support quantitative proteomics. BMC Bioinformatics. 2008;9(1):443.Background: Mass spectrometry is a key technique in proteomics and can be used to analyze complex samples quickly. One key problem with the mass spectrometric analysis of peptides and proteins, however, is the fact that absolute quantification is severely hampered by the unclear relationship between the observed peak intensity and the peptide concentration in the sample. While there are numerous approaches to circumvent this problem experimentally (e. g. labeling techniques), reliable prediction of the peak intensities from peptide sequences could provide a peptide-specific correction factor. Thus, it would be a valuable tool towards label-free absolute quantification. Results: In this work we present machine learning techniques for peak intensity prediction for MALDI mass spectra. Features encoding the peptides' physico-chemical properties as well as string-based features were extracted. A feature subset was obtained from multiple forward feature selections on the extracted features. Based on these features, two advanced machine learning methods (support vector regression and local linear maps) are shown to yield good results for this problem (Pearson correlation of 0.68 in a ten-fold cross validation). Conclusion: The techniques presented here are a useful first step going beyond the binary prediction of proteotypic peptides towards a more quantitative prediction of peak intensities. These predictions in turn will turn out to be beneficial for mass spectrometry-based quantitative proteomics

Identification of surface proteins in Enterococcus faecalis V583

<p>Abstract</p> <p>Background</p> <p>Surface proteins are a key to a deeper understanding of the behaviour of Gram-positive bacteria interacting with the human gastro-intestinal tract. Such proteins contribute to cell wall synthesis and maintenance and are important for interactions between the bacterial cell and the human host. Since they are exposed and may play roles in pathogenicity, surface proteins are interesting targets for drug design.</p> <p>Results</p> <p>Using methods based on proteolytic "shaving" of bacterial cells and subsequent mass spectrometry-based protein identification, we have identified surface-located proteins in <it>Enterococcus faecalis </it>V583. In total 69 unique proteins were identified, few of which have been identified and characterized previously. 33 of these proteins are predicted to be cytoplasmic, whereas the other 36 are predicted to have surface locations (31) or to be secreted (5). Lipid-anchored proteins were the most dominant among the identified surface proteins. The seemingly most abundant surface proteins included a membrane protein with a potentially shedded extracellular sulfatase domain that could act on the sulfate groups in mucin and a lipid-anchored fumarate reductase that could contribute to generation of reactive oxygen species.</p> <p>Conclusions</p> <p>The present proteome analysis gives an experimental impression of the protein landscape on the cell surface of the pathogenic bacterium <it>E. faecalis</it>. The 36 identified secreted (5) and surface (31) proteins included several proteins involved in cell wall synthesis, pheromone-regulated processes, and transport of solutes, as well as proteins with unknown function. These proteins stand out as interesting targets for further investigation of the interaction between <it>E. faecalis </it>and its environment.</p

Impact of today's media on university student's body image in Pakistan: a conservative, developing country's perspective

<p>Abstract</p> <p>Background</p> <p>Living in a world greatly controlled by mass media makes it impossible to escape its pervading influence. As media in Pakistan has been free in the true sense of the word for only a few years, its impact on individuals is yet to be assessed. Our study aims to be the first to look at the effect media has on the body image of university students in a conservative, developing country like Pakistan. Also, we introduced the novel concept of body image dissatisfaction as being both negative and positive.</p> <p>Methods</p> <p>A cross-sectional study was conducted among 7 private universities over a period of two weeks in the city of Karachi, Pakistan's largest and most populous city. Convenience sampling was used to select both male and female undergraduate students aged between 18 and 25 and a sample size of 783 was calculated.</p> <p>Results</p> <p>Of the 784 final respondents, 376 (48%) were males and 408 (52%) females. The mean age of males was 20.77 (+/- 1.85) years and females was 20.38 (+/- 1.63) years. Out of these, 358 (45.6%) respondents had a positive BID (body image dissatisfaction) score while 426 (54.4%) had a negative BID score. Of the respondents who had positive BID scores, 93 (24.7%) were male and 265 (65.0%) were female. Of the respondents with a negative BID score, 283 (75.3%) were male and 143 (35.0%) were female. The results for BID vs. media exposure were similar in both high and low peer pressure groups. Low media exposure meant positive BID scores and vice versa in both groups (p < 0.0001) showing a statistically significant association between high media exposure and negative body image dissatisfaction. Finally, we looked at the association between gender and image dissatisfaction. Again a statistically significant association was found between positive body image dissatisfaction and female gender and negative body image dissatisfaction and male gender (p < 0.0001).</p> <p>Conclusions</p> <p>Our study confirmed the tendency of the media to have an overall negative effect on individuals' body image. A striking feature of our study, however, was the finding that negative body image dissatisfaction was found to be more prevalent in males as compared to females. Likewise, positive BID scores were more prevalent amongst females.</p

LC-MSsim – a simulation software for liquid chromatography mass spectrometry data

<p>Abstract</p> <p>Background</p> <p>Mass Spectrometry coupled to Liquid Chromatography (LC-MS) is commonly used to analyze the protein content of biological samples in large scale studies. The data resulting from an LC-MS experiment is huge, highly complex and noisy. Accordingly, it has sparked new developments in Bioinformatics, especially in the fields of algorithm development, statistics and software engineering. In a quantitative label-free mass spectrometry experiment, crucial steps are the detection of peptide features in the mass spectra and the alignment of samples by correcting for shifts in retention time. At the moment, it is difficult to compare the plethora of algorithms for these tasks. So far, curated benchmark data exists only for peptide identification algorithms but no data that represents a ground truth for the evaluation of feature detection, alignment and filtering algorithms.</p> <p>Results</p> <p>We present <it>LC-MSsim</it>, a simulation software for LC-ESI-MS experiments. It simulates ESI spectra on the MS level. It reads a list of proteins from a FASTA file and digests the protein mixture using a user-defined enzyme. The software creates an LC-MS data set using a predictor for the retention time of the peptides and a model for peak shapes and elution profiles of the mass spectral peaks. Our software also offers the possibility to add contaminants, to change the background noise level and includes a model for the detectability of peptides in mass spectra. After the simulation, <it>LC-MSsim </it>writes the simulated data to mzData, a public XML format. The software also stores the positions (monoisotopic m/z and retention time) and ion counts of the simulated ions in separate files.</p> <p>Conclusion</p> <p><it>LC-MSsim </it>generates simulated LC-MS data sets and incorporates models for peak shapes and contaminations. Algorithm developers can match the results of feature detection and alignment algorithms against the simulated ion lists and meaningful error rates can be computed. We anticipate that <it>LC-MSsim </it>will be useful to the wider community to perform benchmark studies and comparisons between computational tools.</p

Examination of polymorphic glutathione S-transferase (GST) genes, tobacco smoking and prostate cancer risk among Men of African Descent: A case-control study

<p>Abstract</p> <p>Background</p> <p>Polymorphisms in <it>glutathione S-transferase </it>(GST) genes may influence response to oxidative stress and modify prostate cancer (PCA) susceptibility. These enzymes generally detoxify endogenous and exogenous agents, but also participate in the activation and inactivation of oxidative metabolites that may contribute to PCA development. Genetic variations within selected <it>GST </it>genes may influence PCA risk following exposure to carcinogen compounds found in cigarette smoke and decreased the ability to detoxify them. Thus, we evaluated the effects of polymorphic <it>GSTs </it>(<it>M1</it>, <it>T1</it>, and <it>P1</it>) alone and combined with cigarette smoking on PCA susceptibility.</p> <p>Methods</p> <p>In order to evaluate the effects of <it>GST </it>polymorphisms in relation to PCA risk, we used TaqMan allelic discrimination assays along with a multi-faceted statistical strategy involving conventional and advanced statistical methodologies (e.g., Multifactor Dimensionality Reduction and Interaction Graphs). Genetic profiles collected from 873 men of African-descent (208 cases and 665 controls) were utilized to systematically evaluate the single and joint modifying effects of <it>GSTM1 </it>and <it>GSTT1 </it>gene deletions, <it>GSTP1 </it>105 Val and cigarette smoking on PCA risk.</p> <p>Results</p> <p>We observed a moderately significant association between risk among men possessing at least one variant <it>GSTP1 </it>105 Val allele (OR = 1.56; 95%CI = 0.95-2.58; p = 0.049), which was confirmed by MDR permutation testing (p = 0.001). We did not observe any significant single gene effects among <it>GSTM1 </it>(OR = 1.08; 95%CI = 0.65-1.82; p = 0.718) and <it>GSTT1 </it>(OR = 1.15; 95%CI = 0.66-2.02; p = 0.622) on PCA risk among all subjects. Although the <it>GSTM1</it>-<it>GSTP1 </it>pairwise combination was selected as the best two factor LR and MDR models (p = 0.01), assessment of the hierarchical entropy graph suggested that the observed synergistic effect was primarily driven by the <it>GSTP1 </it>Val marker. Notably, the <it>GSTM1</it>-<it>GSTP1 </it>axis did not provide additional information gain when compared to either loci alone based on a hierarchical entropy algorithm and graph. Smoking status did not significantly modify the relationship between the <it>GST </it>SNPs and PCA.</p> <p>Conclusion</p> <p>A moderately significant association was observed between PCA risk and men possessing at least one variant <it>GSTP1 </it>105 Val allele (p = 0.049) among men of African descent. We also observed a 2.1-fold increase in PCA risk associated with men possessing the <it>GSTP1 </it>(Val/Val) and <it>GSTM1 </it>(*1/*1 + *1/*0) alleles. MDR analysis validated these findings; detecting <it>GSTP1 </it>105 Val (p = 0.001) as the best single factor for predicting PCA risk. Our findings emphasize the importance of utilizing a combination of traditional and advanced statistical tools to identify and validate single gene and multi-locus interactions in relation to cancer susceptibility.</p

MicroRNome Analysis Unravels the Molecular Basis of SARS Infection in Bronchoalveolar Stem Cells

Severe acute respiratory syndrome (SARS), caused by the coronavirus SARS-CoV, is an acute infectious disease with significant mortality. A typical clinical feature associated with SARS is pulmonary fibrosis and associated lung failure. In the aftermath of the SARS epidemic, although significant progress towards understanding the underlying molecular mechanism of the infection has been made, a large gap still remains in our knowledge regarding how SARS-CoV interacts with the host cell at the onset of infection. The rapidly changing viral genome adds another variable to this equation. We have focused on a novel concept of microRNA (miRNA)–mediated host–virus interactions in bronchoalveolar stem cells (BASCs) at the onset of infection by correlating the “BASC–microRNome” with their targets within BASCs and viral genome. This work encompasses miRNA array data analysis, target prediction, and miRNA–mRNA enrichment analysis and develops a complex interaction map among disease-related factors, miRNAs, and BASCs in SARS pathway, which will provide some clues for diagnostic markers to view an overall interplay leading to disease progression. Our observation reveals the BASCs (Sca-1+ CD34+ CD45- Pecam-), a subset of Oct-4+ ACE2+ epithelial colony cells at the broncho-alveolar duct junction, to be the prime target cells of SARS-CoV infection. Upregulated BASC miRNAs-17*, -574-5p, and -214 are co-opted by SARS-CoV to suppress its own replication and evade immune elimination until successful transmission takes place. Viral Nucleocapsid and Spike protein targets seem to co-opt downregulated miR-223 and miR-98 respectively within BASCs to control the various stages of BASC differentiation, activation of inflammatory chemokines, and downregulation of ACE2. All these effectively accounts for a successful viral transmission and replication within BASCs causing continued deterioration of lung tissues and apparent loss of capacity for lung repair. Overall, this investigation reveals another mode of exploitation of cellular miRNA machinery by virus to their own advantage