The economics of producing sustainable aviation fuel: a regional case study in Queensland,Australia

The airline industry has a strong interest in developing sustainable aviation fuels, in order to reduce their exposure to increasing oil prices and cost liability for greenhouse gas emissions. The feasibility and cost of producing sustainable biomass‐based jet fuels at a sufficient scale to materially address these issues is an enormous challenge. This paper builds directly on the biophysical study by H.T. Murphy, D.A. O'Connell, R.J. Raison, A.C. Warden, T.H. Booth, A. Herr, A.L. Braid, D.F. Crawford, J.A. Hayward, T. Javonovic, J.G. McIvor, M.H. O'Connor, M.L. Poole, D. Prestwidge, N. Raisbeck‐Brown & L. Rye, In review, which examined a 25 year scale‐up strategy to produce 5% of projected jet fuel demand in Australia in 2020 (470 mL) in the Fitzroy region of Queensland, Australia. The strategy was based on the use of a mixed ligno‐cellulosic biomass feedstock and assumed, for the sake of exploring and quantifying the scenario, a simplified two‐step conversion process – conversion of biomass to crude bio‐oil within the region, and upgrade to jet fuel at a central Brisbane facility. This paper provides details on the costs of production in this scenario, focusing on two different strategies for biomass utilization, and two types of novel small–medium scale conversion technologies. The cost analyses have taken into account technology learning curves, different economies of scale and key cost sensitivities. The cost of biomass‐based jet fuels is estimated to be between 0.70 and 1.90 The airline industry has a strong interest in developing sustainable aviation fuels, in order to reduce their exposure to increasing oil prices and cost liability for greenhouse gas emissions. The feasibility and cost of producing sustainable biomass‐based jet fuels at a sufficient scale to materially address these issues is an enormous challenge. This paper builds directly on the biophysical study by H.T. Murphy, D.A. O'Connell, R.J. Raison, A.C. Warden, T.H. Booth, A. Herr, A.L. Braid, D.F. Crawford, J.A. Hayward, T. Javonovic, J.G. McIvor, M.H. O'Connor, M.L. Poole, D. Prestwidge, N. Raisbeck‐Brown & L. Rye, In review, which examined a 25 year scale‐up strategy to produce 5% of projected jet fuel demand in Australia in 2020 (470 mL) in the Fitzroy region of Queensland, Australia. The strategy was based on the use of a mixed ligno‐cellulosic biomass feedstock and assumed, for the sake of exploring and quantifying the scenario, a simplified two‐step conversion process – conversion of biomass to crude bio‐oil within the region, and upgrade to jet fuel at a central Brisbane facility. This paper provides details on the costs of production in this scenario, focusing on two different strategies for biomass utilization, and two types of novel small–medium scale conversion technologies. The cost analyses have taken into account technology learning curves, different economies of scale and key cost sensitivities. The cost of biomass‐based jet fuels is estimated to be between 0.70 and 1.90 $ L^?1 when the efficiency of conversion of biomass to biocrude and subsequently to aviation fuel is varied by ±10% of published values, with an average value of 1.10 $ L^?1. This is within the range of the projected 2035 conventional jet fuel price of 1.50 $ L^?1. Therefore, biomass‐based jet fuel has the potential to contribute to supply of Australia's jet fuel needs in the future.     

Identification of conformational B-cell Epitopes in an antigen from its primary sequence

Background

One of the major challenges in the field of vaccine design is to predict conformational B-cell epitopes in an antigen. In the past, several methods have been developed for predicting conformational B-cell epitopes in an antigen from its tertiary structure. This is the first attempt in this area to predict conformational B-cell epitope in an antigen from its amino acid sequence.

Results

All Support vector machine (SVM) models were trained and tested on 187 non-redundant protein chains consisting of 2261 antibody interacting residues of B-cell epitopes. Models have been developed using binary profile of pattern (BPP) and physiochemical profile of patterns (PPP) and achieved a maximum MCC of 0.22 and 0.17 respectively. In this study, for the first time SVM model has been developed using composition profile of patterns (CPP) and achieved a maximum MCC of 0.73 with accuracy 86.59%. We compare our CPP based model with existing structure based methods and observed that our sequence based model is as good as structure based methods.

Conclusion

This study demonstrates that prediction of conformational B-cell epitope in an antigen is possible from is primary sequence. This study will be very useful in predicting conformational B-cell epitopes in antigens whose tertiary structures are not available. A web server CBTOPE has been developed for predicting B-cell epitope http://www.imtech.res.in/raghava/cbtope/.     

Support Vector Machine-based method for predicting subcellular localization of mycobacterial proteins using evolutionary information and motifs

Background

Annotations that describe the function of sequences are enormously important to researchers during laboratory investigations and when making computational inferences. However, there has been little investigation into the data quality of sequence function annotations. Here we have developed a new method of estimating the error rate of curated sequence annotations, and applied this to the Gene Ontology (GO) sequence database (GOSeqLite). This method involved artificially adding errors to sequence annotations at known rates, and used regression to model the impact on the precision of annotations based on BLAST matched sequences.

Results

We estimated the error rate of curated GO sequence annotations in the GOSeqLite database (March 2006) at between 28% and 30%. Annotations made without use of sequence similarity based methods (non-ISS) had an estimated error rate of between 13% and 18%. Annotations made with the use of sequence similarity methodology (ISS) had an estimated error rate of 49%.

Conclusion

While the overall error rate is reasonably low, it would be prudent to treat all ISS annotations with caution. Electronic annotators that use ISS annotations as the basis of predictions are likely to have higher false prediction rates, and for this reason designers of these systems should consider avoiding ISS annotations where possible. Electronic annotators that use ISS annotations to make predictions should be viewed sceptically. We recommend that curators thoroughly review ISS annotations before accepting them as valid. Overall, users of curated sequence annotations from the GO database should feel assured that they are using a comparatively high quality source of information.     

Models for the study of tendinopathy

Tendinopathy refers to the clinical presentation of activity-related pain, focal tendon tenderness, and intratendinous imaging changes. The underlying pathology was once thought to be due to inflammation ('tendinitis'), but is now considered to predominantly result from degeneration ('tendinosis'). While some progress has been made in understanding tendinosis, the condition remains poorly understood and a need exists for suitable exploratory preclinical models. It is unlikely that one suitable model exists because of the complexity of the underlying pathology and myriad of possible causes. This paper provides an overview of current models utilized in tendinopathy research. It progresses hierarchically from in vitro and ex vivo models to in vivo models. For each model, rationale for use, pertinent findings, and advantages and disadvantages are discussed. By improving on these models, new methods for the prevention and treatment of tendinopathy may be explored with the ultimate outcome being a reduction in the occurrence and effects of the condition in humans.     

Correlation and prediction of gene expression level from amino acid and dipeptide composition of its protein

Background  

A large number of papers have been published on analysis of microarray data with particular emphasis on normalization of data, detection of differentially expressed genes, clustering of genes and regulatory network. On other hand there are only few studies on relation between expression level and composition of nucleotide/protein sequence, using expression data. There is a need to understand why particular genes/proteins express more in particular conditions. In this study, we analyze 3468 genes of Saccharomyces cerevisiae obtained from Holstege et al., (1998) to understand the relationship between expression level and amino acid composition.     

Epistatic interaction between two nonstructural loci on chromosomes 7 and 3 influences hepatic lipase activity in BSB mice

BSB mice exhibit a wide range of obesity despite being produced by a backcross of lean C57BL/6J (B) x lean Mus spretus (SPRET/Pt) F1 animals x B. Previous linkage studies identified a quantitative trait locus (QTL) on mouse chromosome 7 with coincident peaks for hepatic lipase activity, obesity, and plasma cholesterol. However, these mice were not analyzed for gene x gene epistasis. Hepatic lipase activity is correlated with obesity and plasma cholesterol levels. In this study, we identified QTLs for plasma hepatic lipase activity with three statistical mapping methods: maximum likelihood interval mapping, Bayesian nonepistatic mapping, and Bayesian epistatic mapping. Bayesian epistatic mapping detected not only the QTL on chromosome 7 but also an additional QTL on chromosome 3, which has a weak main effect but a strong interaction with chromosome 7. SPRET/Pt alleles of the QTL on each chromosome promote hepatic lipase activity. The proportion of phenotypic variance explained by the epistatic effect is higher than that explained by the main effect of the QTL on chromosome 7.     

The control of fracture healing and its therapeutic targeting: Improving upon nature

Fracture repair is a complex process involving timed cellular recruitment, gene expression, and synthesis of compounds that regenerate native tissue to restore the mechanical integrity, and thus function of injured bone. While the majority of fractures heal without complication, this takes time and a subset of patients (～10%) experience healing delays, extending their morbidity and treatment costs. Consequently, there is a need for efficacious therapeutics for the intervention of fracture healing. Recent studies into the molecular control of fracture repair and advances in the understanding of the skeleton as a whole have resulted in the identification of numerous novel targets and compounds for such intervention. These include traditional agents such bone morphogenetic proteins and other growth factors, but also relatively newer compounds such as parathyroid hormone and modulators of the Wnt signaling pathway. These agents, along with others, are discussed in the current article in terms of their investigative status and potential for clinical implementation. Hopefully, these agents, as well as others yet to be discovered, will demonstrate sufficient clinical utility for successful intervention of fracture healing. This may have significant implications for the duration of morbidity and costs associated with traumatic bone fractures. J. Cell. Biochem. 109: 302–311, 2010. © 2009 Wiley‐Liss, Inc.