Ecological Tipping Points: Uncertainties and Policy Approaches

Ecological tipping points have captured policymakers’ imaginations for framing local and global environmental change: if an environmental driver becomes too significant, an ecosystem may flip into an alternate state, often with catastrophic and far-reaching consequences. The article first explores the science of ecological tipping points and the uncertainties that limit their validity and value in providing a threshold marking abrupt ecosystem collapse across scales. I then argue that ecological tipping points may be more useful not as a scientific instrument to predict environmental change, but as a gauge of anthropogenic environmental trajectories and a socio-environmental imaginary to mobilise environmental action. Given the complexity and uncertainty of ecological science, I suggest that the science-policy interface of ecological tipping points will benefit from further research in threshold dynamics and ecosystems in transition due to human activity. Furthermore, a pluralistic, deliberative approach to policymaking that brings together different knowledge domains will facilitate adaptive environmental governance to effectively respond to changes in the physical environment and our understandings of it

ASSESSMENT OF SUSTAINED CASING PRESSURE ON WELL INTEGRITY

Sustained casing pressure (SCP) is commonly known as one of the well integrity problems in oil and gas industry. In fact, the term of „annular pressure‟ implies a similar definition to SCP (Attard, 1991) if the annular pressure is unmanageable or leaking in well components. The leaking problem can be due to tubing/casing leak, poor primary cementing job and interuption to cement integrity due to the pressure and temperature changes when the well starts to produce hydrocarbon. Hence, there is a necessity to manage SCP effectively in order to ensure the integrity of well. This project is based on modeling approach, where the objective is develop a series of computer codes with the reference of existing pressure bleed-off time Mathematical model. The results generated from the model is based on effect of temperature, type of gases filled in annulus and depth of well. These 3 type of parameters can affect the pressure bleed-off time in annulus itself, provided the condition where the size of needle valve is fixed. From the model generated in Wolfram Mathematica 8.0, it is able to notify engineer to receive any early sign of warning if the well is suspected a leakage. Meanwhile, based on the matching process of field data and modeled data, engineers will be able to aware and determine whether the occurence of annular pressure is due to thermal induced annular pressure buildup or it is because of the leakage in well components. Finally, this model is economic and able to save cost until the well is needed for any further confirmation. In addition, the project also studied the effect of SCP on the well integrity. With this, the well will eventually loss in production, severe failure in well‟s integrity or consider the worst case scenario, the excessive of SCP may cause an underground blowout at subsurface. Currently, the report was referred 18 documents as references in this research topic

Going your own way: Self-guidance mechanisms in cell migration

How cells and tissues migrate from one location to another is a question of significant biological and medical relevance. Migration is generally thought to be controlled by external hardwired guidance cues, which cells follow by polarizing their internal locomotory machinery in the imposed direction. However, a number of recently discovered ‘self-guidance’ mechanisms have revealed that migrating cells have more control over the path they follow than previously thought. Here, directional information is generated by the migrating cells themselves via a dynamic interplay of cell-intrinsic and -extrinsic regulators. In this review, we discuss how self-guidance can emerge from mechanisms acting at different levels of scale and how these enable cells to rapidly adapt to environmental challenges

ASSESSMENT OF SUSTAINED CASING PRESSURE ON WELL INTEGRITY

Sustained casing pressure (SCP) is commonly known as one of the well integrity problems in oil and gas industry. In fact, the term of „annular pressure‟ implies a similar definition to SCP (Attard, 1991) if the annular pressure is unmanageable or leaking in well components. The leaking problem can be due to tubing/casing leak, poor primary cementing job and interuption to cement integrity due to the pressure and temperature changes when the well starts to produce hydrocarbon. Hence, there is a necessity to manage SCP effectively in order to ensure the integrity of well. This project is based on modeling approach, where the objective is develop a series of computer codes with the reference of existing pressure bleed-off time Mathematical model. The results generated from the model is based on effect of temperature, type of gases filled in annulus and depth of well. These 3 type of parameters can affect the pressure bleed-off time in annulus itself, provided the condition where the size of needle valve is fixed. From the model generated in Wolfram Mathematica 8.0, it is able to notify engineer to receive any early sign of warning if the well is suspected a leakage. Meanwhile, based on the matching process of field data and modeled data, engineers will be able to aware and determine whether the occurence of annular pressure is due to thermal induced annular pressure buildup or it is because of the leakage in well components. Finally, this model is economic and able to save cost until the well is needed for any further confirmation. In addition, the project also studied the effect of SCP on the well integrity. With this, the well will eventually loss in production, severe failure in well‟s integrity or consider the worst case scenario, the excessive of SCP may cause an underground blowout at subsurface. Currently, the report was referred 18 documents as references in this research topic

Annotation of gene function in citrus using gene expression information and co-expression networks

Background The genus Citrus encompasses major cultivated plants such as sweet orange, mandarin, lemon and grapefruit, among the world’s most economically important fruit crops. With increasing volumes of transcriptomics data available for these species, Gene Co-expression Network (GCN) analysis is a viable option for predicting gene function at a genome-wide scale. GCN analysis is based on a “guilt-by-association” principle whereby genes encoding proteins involved in similar and/or related biological processes may exhibit similar expression patterns across diverse sets of experimental conditions. While bioinformatics resources such as GCN analysis are widely available for efficient gene function prediction in model plant species including Arabidopsis, soybean and rice, in citrus these tools are not yet developed Results We have constructed a comprehensive GCN for citrus inferred from 297 publicly available Affymetrix Genechip Citrus Genome microarray datasets, providing gene co-expression relationships at a genome-wide scale (33,000 transcripts). The comprehensive citrus GCN consists of a global GCN (condition-independent) and four condition-dependent GCNs that survey the sweet orange species only, all citrus fruit tissues, all citrus leaf tissues, or stress-exposed plants. All of these GCNs are clustered using genome-wide, gene-centric (guide) and graph clustering algorithms for flexibility of gene function prediction. For each putative cluster, gene ontology (GO) enrichment and gene expression specificity analyses were performed to enhance gene function, expression and regulation pattern prediction. The guide-gene approach was used to infer novel roles of genes involved in disease susceptibility and vitamin C metabolism, and graph-clustering approaches were used to investigate isoprenoid/phenylpropanoid metabolism in citrus peel, and citric acid catabolism via the GABA shunt in citrus fruit Conclusions Integration of citrus gene co-expression networks, functional enrichment analysis and gene expression information provide opportunities to infer gene function in citrus. We present a publicly accessible tool, Network Inference for Citrus Co-Expression (NICCE, http://citrus.adelaide.edu.au/nicce/home.aspx), for the gene co-expression analysis in citru

An image-based data-driven analysis of cellular architecture in a developing tissue

Quantitative microscopy is becoming increasingly crucial in efforts to disentangle the complexity of organogenesis, yet adoption of the potent new toolbox provided by modern data science has been slow, primarily because it is often not directly applicable to developmental imaging data. We tackle this issue with a newly developed algorithm that uses point cloud-based morphometry to unpack the rich information encoded in 3D image data into a straightforward numerical representation. This enabled us to employ data science tools, including machine learning, to analyze and integrate cell morphology, intracellular organization, gene expression and annotated contextual knowledge. We apply these techniques to construct and explore a quantitative atlas of cellular architecture for the zebrafish posterior lateral line primordium, an experimentally tractable model of complex self-organized organogenesis. In doing so, we are able to retrieve both previously established and novel biologically relevant patterns, demonstrating the potential of our data-driven approach

Learning with multiple representations: An example of a revision lesson in mechanics

We describe an example of learning with multiple representations in an A-level revision lesson on mechanics. The context of the problem involved the motion of a ball thrown vertically upwards in air and studying how the associated physical quantities changed during its flight. Different groups of students were assigned to look at the ball's motion using various representations: motion diagrams, vector diagrams, free-body diagrams, verbal description, equations and graphs, drawn against time as well as against displacement. Overall, feedback from students about the lesson was positive. We further discuss the benefits of using computer simulation to support and extend student learning.Comment: 10 pages, 5 figures, 2 tables http://iopscience.iop.org/0031-912

Canine olfactory ensheathing cells from the olfactory mucosa can be engineered to produce active chondroitinase ABC

A multitude of factors must be overcome following spinal cord injury (SCI) in order to achieve clinical improvement in patients. It is thought that by combining promising therapies these diverse factors could be combatted with the aim of producing an overall improvement in function. Chondroitin sulphate proteoglycans (CSPGs) present in the glial scar that forms following SCI present a significant block to axon regeneration. Digestion of CSPGs by chondroitinase ABC (ChABC) leads to axon regeneration, neuronal plasticity and functional improvement in preclinical models of SCI. However, the enzyme activity decays at body temperature within 24–72 h, limiting the translational potential of ChABC as a therapy. Olfactory ensheathing cells (OECs) have shown huge promise as a cell transplant therapy in SCI. Their beneficial effects have been demonstrated in multiple small animal SCI models as well as in naturally occurring SCI in canine patients. In the present study, we have genetically modified canine OECs from the mucosa to constitutively produce enzymatically active ChABC. We have developed a lentiviral vector that can deliver a mammalian modified version of the ChABC gene to mammalian cells, including OECs. Enzyme production was quantified using the Morgan-Elson assay that detects the breakdown products of CSPG digestion in cell supernatants. We confirmed our findings by immunolabelling cell supernatant samples using Western blotting. OECs normal cell function was unaffected by genetic modification as demonstrated by normal microscopic morphology and the presence of the low affinity neurotrophin receptor (p75NGF) following viral transduction. We have developed the means to allow production of active ChABC in combination with a promising cell transplant therapy for SCI repair

Constructing Integrated Networks for Identifying New Secondary Metabolic Pathway Regulators in Grapevine: Recent Applications and Future Opportunities

Representing large biological data as networks is becoming increasingly adopted for predicting gene function while elucidating the multifaceted organization of life processes. In grapevine (Vitis vinifera L.), network analyses have been mostly adopted to contribute to the understanding of the regulatory mechanisms that control berry composition. Whereas, some studies have used gene co-expression networks to find common pathways and putative targets for transcription factors related to development and metabolism, others have defined networks of primary and secondary metabolites for characterizing the main metabolic differences between cultivars throughout fruit ripening. Lately, proteomic-related networks and those integrating genome-wide analyses of promoter regulatory elements have also been generated. The integration of all these data in multilayered networks allows building complex maps of molecular regulation and interaction. This perspective article describes the currently available network data and related resources for grapevine. With the aim of illustrating data integration approaches into network construction and analysis in grapevine, we searched for berry-specific regulators of the phenylpropanoid pathway. We generated a composite network consisting of overlaying maps of co-expression between structural and transcription factor genes, integrated with the presence of promoter cis-binding elements, microRNAs, and long non-coding RNAs (lncRNA). This approach revealed new uncharacterized transcription factors together with several microRNAs potentially regulating different steps of the phenylpropanoid pathway, and one particular lncRNA compromising the expression of nine stilbene synthase (STS) genes located in chromosome 10. Application of network-based approaches into multi-omics data will continue providing supplementary resources to address important questions regarding grapevine fruit quality and compositio

New insights into the evolutionary history of plant sorbitol dehydrogenase

BACKGROUND: Sorbitol dehydrogenase (SDH, EC 1.1.1.14) is the key enzyme involved in sorbitol metabolism in higher plants. SDH genes in some Rosaceae species could be divided into two groups. L-idonate-5-dehydrogenase (LIDH, EC 1.1.1.264) is involved in tartaric acid (TA) synthesis in Vitis vinifera and is highly homologous to plant SDHs. Despite efforts to understand the biological functions of plant SDH, the evolutionary history of plant SDH genes and their phylogenetic relationship with the V. vinifera LIDH gene have not been characterized RESULTS: A total of 92 SDH genes were identified from 42 angiosperm species. SDH genes have been highly duplicated within the Rosaceae family while monocot, Brassicaceae and most Asterid species exhibit singleton SDH genes. Core Eudicot SDHs have diverged into two phylogenetic lineages, now classified as SDH Class I and SDH Class II. V. vinifera LIDH was identified as a Class II SDH. Tandem duplication played a dominant role in the expansion of plant SDH family and Class II SDH genes were positioned in tandem with Class I SDH genes in several plant genomes. Protein modelling analyses of V. vinifera SDHs revealed 19 putative active site residues, three of which exhibited amino acid substitutions between Class I and Class II SDHs and were influenced by positive natural selection in the SDH Class II lineage. Gene expression analyses also demonstrated a clear transcriptional divergence between Class I and Class II SDH genes in V. vinifera and Citrus sinensis (orange) CONCLUSIONS: Phylogenetic, natural selection and synteny analyses provided strong support for the emergence of SDH Class II by positive natural selection after tandem duplication in the common ancestor of core Eudicot plants. The substitutions of three putative active site residues might be responsible for the unique enzyme activity of V. vinifera LIDH, which belongs to SDH Class II and represents a novel function of SDH in V. vinifera that may be true also of other Class II SDHs. Gene expression analyses also supported the divergence of SDH Class II at the expression level. This study will facilitate future research into understanding the biological functions of plant SDH