Acetylation is increasingly recognized as an important metabolic regulatory post-translational protein modification, yet the metabolic consequence of mitochondrial protein hyperacetylation is unknown. We find that high-fat diet (HFD) feeding induces hepatic mitochondrial protein hyperacetylation in mice and downregulation of the major mitochondrial protein deacetylase SIRT3. Mice lacking SIRT3 (SIRT3KO) placed on a HFD show accelerated obesity, insulin resistance, hyperlipidemia, and steatohepatitis compared to wild-type (wt) mice. The lipogenic enzyme stearoyl-CoA desaturase 1 is highly induced in SIRT3KO mice, and its deletion rescues both wt and SIRT3KO mice from HFD-induced hepatic steatosis and insulin resistance. We further identify a single nucleotide polymorphism in the human SIRT3 gene that is suggestive of a genetic association with the metabolic syndrome. This polymorphism encodes a point-mutation in the SIRT3 protein, which reduces its overall enzymatic efficiency. Our findings show loss of SIRT3 and dysregulation of mitochondrial protein acetylation contribute to the metabolic syndrome.
Representative animal models for diabetes-associated vascular complications are extremely relevant in assessing potential therapeutic drugs. While several rodent models for type 2 diabetes (T2D) are available, their relevance in recapitulating renal and cardiovascular features of diabetes in man is not entirely clear. Here we evaluate at the molecular level the similarity between Zucker diabetic fatty (ZDF) rats, as a model of T2D-associated vascular complications, and human disease by urinary proteome analysis. Urine analysis of ZDF rats at early and late stages of disease compared to age- matched LEAN rats identified 180 peptides as potentially associated with diabetes complications. Overlaps with human chronic kidney disease (CKD) and cardiovascular disease (CVD) biomarkers were observed, corresponding to proteins marking kidney damage (eg albumin, alpha-1 antitrypsin) or related to disease development (collagen). Concordance in regulation of these peptides in rats versus humans was more pronounced in the CVD compared to the CKD panels. In addition, disease-associated predicted protease activities in ZDF rats showed higher similarities to the predicted activities in human CVD. Based on urinary peptidomic analysis, the ZDF rat model displays similarity to human CVD but might not be the most appropriate model to display human CKD on a molecular level.
The disruption of cholesterol homeostasis leads to an increase in cholesterol levels which results in the development of cardiovascular disease. Mitogen Inducible Gene 6 (Mig-6) is an immediate early response gene that can be induced by various mitogens, stresses, and hormones. To identify the metabolic role of Mig-6 in the liver, we conditionally ablated Mig-6 in the liver using the Albumin-Cre mouse model (Albcre/+Mig-6f/f; Mig-6d/d). Mig-6d/d mice exhibit hepatomegaly and fatty liver. Serum levels of total, LDL, and HDL cholesterol and hepatic lipid were significantly increased in the Mig-6d/d mice. The daily excretion of fecal bile acids was significantly decreased in the Mig-6d/d mice. DNA microarray analysis of mRNA isolated from the livers of these mice showed alterations in genes that regulate lipid metabolism, bile acid, and cholesterol synthesis, while the expression of genes that regulate biliary excretion of bile acid and triglyceride synthesis showed no difference in the Mig-6d/d mice compared to Mig-6f/f controls. These results indicate that Mig-6 plays an important role in cholesterol homeostasis and bile acid synthesis. Mice with liver specific conditional ablation of Mig-6 develop hepatomegaly and increased intrahepatic lipid and provide a novel model system to investigate the genetic and molecular events involved in the regulation of cholesterol homeostasis and bile acid synthesis. Defining the molecular mechanisms by which Mig-6 regulates cholesterol homeostasis will provide new insights into the development of more effective ways for the treatment and prevention of cardiovascular disease.
Adipocyte infiltration of the musculoskeletal system is well recognized as a hallmark of aging, obesity, and type 2 diabetes. Intermuscular adipocytes might serve as a benign storage site for surplus lipid or play a role in disrupting energy homeostasis as a result of dysregulated lipolysis or secretion of proinflammatory cytokines. This investigation sought to understand the net impact of local adipocytes on skeletal myocyte metabolism.
RESEARCH DESIGN AND METHODS
Interactions between these two tissues were modeled using a coculture system composed of primary human adipocytes and human skeletal myotubes derived from lean or obese donors. Metabolic analysis of myocytes was performed after coculture with lipolytically silent or activated adipocytes and included transcript and metabolite profiling along with assessment of substrate selection and insulin action.
Cocultured adipocytes increased myotube mRNA expression of genes involved in oxidative metabolism, regardless of the donor and degree of lipolytic activity. Adipocytes in the basal state sequestered free fatty acids, thereby forcing neighboring myotubes to rely more heavily on glucose fuel. Under this condition, insulin action was enhanced in myotubes from lean but not obese donors. In contrast, when exposed to lipolytically active adipocytes, cocultured myotubes shifted substrate use in favor of fatty acids, which was accompanied by intracellular accumulation of triacylglycerol and even-chain acylcarnitines, decreased glucose oxidation, and modest attenuation of insulin signaling.
The effects of cocultured adipocytes on myocyte substrate selection and insulin action depended on the metabolic state of the system. These findings are relevant to understanding the metabolic consequences of intermuscular adipogenesis.
The poststimulus blood oxygenation level-dependent (BOLD) undershoot has been attributed to two main plausible origins: delayed vascular compliance based on delayed cerebral blood volume (CBV) recovery and a sustained increased oxygen metabolism after stimulus cessation. To investigate these contributions, multimodal functional magnetic resonance imaging was employed to monitor responses of BOLD, cerebral blood flow (CBF), total CBV, and arterial CBV (CBVa) in human visual cortex after brief breath hold and visual stimulation. In visual experiments, after stimulus cessation, CBVa was restored to baseline in 7.9±3.4 seconds, and CBF and CBV in 14.8±5.0 seconds and 16.1±5.8 seconds, respectively, all significantly faster than BOLD signal recovery after undershoot (28.1±5.5 seconds). During the BOLD undershoot, postarterial CBV (CBVpa, capillaries and venules) was slightly elevated (2.4±1.8%), and cerebral metabolic rate of oxygen (CMRO2) was above baseline (10.6±7.4%). Following breath hold, however, CBF, CBV, CBVa and BOLD signals all returned to baseline in ∼20 seconds. No significant BOLD undershoot, and residual CBVpa dilation were observed, and CMRO2 did not substantially differ from baseline. These data suggest that both delayed CBVpa recovery and enduring increased oxidative metabolism impact the BOLD undershoot. Using a biophysical model, their relative contributions were estimated to be 19.7±15.9% and 78.7±18.6%, respectively.
BOLD undershoot; cerebral blood flow; cerebral blood volume; hypercapnia; MRI; oxygen metabolism
Obesity has reached epidemic proportions worldwide. Several animal models of obesity exist, but studies are lacking that compare traditional lard-based high fat diets (HFD) to “Cafeteria diets" (CAF) consisting of nutrient poor human junk food. Our previous work demonstrated the rapid and severe obesogenic and inflammatory consequences of CAF compared to HFD including rapid weight gain, markers of Metabolic Syndrome, multi-tissue lipid accumulation, and dramatic inflammation. To identify potential mediators of CAF-induced obesity and Metabolic Syndrome, we used metabolomic analysis to profile serum, muscle, and white adipose from rats fed CAF, HFD, or standard control diets. Principle component analysis identified elevations in clusters of fatty acids and acylcarnitines. These increases in metabolites were associated with systemic mitochondrial dysfunction that paralleled weight gain, physiologic measures of Metabolic Syndrome, and tissue inflammation in CAF-fed rats. Spearman pairwise correlations between metabolites, physiologic, and histologic findings revealed strong correlations between elevated markers of inflammation in CAF-fed animals, measured as crown like structures in adipose, and specifically the pro-inflammatory saturated fatty acids and oxidation intermediates laurate and lauroyl carnitine. Treatment of bone marrow-derived macrophages with lauroyl carnitine polarized macrophages towards the M1 pro-inflammatory phenotype through downregulation of AMPK and secretion of pro-inflammatory cytokines. Results presented herein demonstrate that compared to a traditional HFD model, the CAF diet provides a robust model for diet-induced human obesity, which models Metabolic Syndrome-related mitochondrial dysfunction in serum, muscle, and adipose, along with pro-inflammatory metabolite alterations. These data also suggest that modifying the availability or metabolism of saturated fatty acids may limit the inflammation associated with obesity leading to Metabolic Syndrome.
For more than a century, thyroid hormones (THs) have been known to exert powerful catabolic effects, leading to weight loss. Although much has been learned about the molecular mechanisms used by TH receptors (TRs) to regulate gene expression, little is known about the mechanisms by which THs increase oxidative metabolism. Here, we report that TH stimulation of fatty acid β-oxidation is coupled with induction of hepatic autophagy to deliver fatty acids to mitochondria in cell culture and in vivo. Furthermore, blockade of autophagy by autophagy-related 5 (ATG5) siRNA markedly decreased TH-mediated fatty acid β-oxidation in cell culture and in vivo. Consistent with this model, autophagy was altered in livers of mice expressing a mutant TR that causes resistance to the actions of TH as well as in mice with mutant nuclear receptor corepressor (NCoR). These results demonstrate that THs can regulate lipid homeostasis via autophagy and help to explain how THs increase oxidative metabolism.
Most major genome projects and sequence databases provide a GO annotation of their data, either automatically or through human annotators, creating a large corpus of data written in the language of GO. Texts written in natural language show a statistical power law behaviour, Zipf’s law, the exponent of which can provide useful information on the nature of the language being used. We have therefore explored the hypothesis that collections of GO annotations will show similar statistical behaviours to natural language.
Annotations from the Gene Ontology Annotation project were found to follow Zipf’s law. Surprisingly, the measured power law exponents were consistently different between annotation captured using the three GO sub-ontologies in the corpora (function, process and component). On filtering the corpora using GO evidence codes we found that the value of the measured power law exponent responded in a predictable way as a function of the evidence codes used to support the annotation.
Techniques from computational linguistics can provide new insights into the annotation process. GO annotations show similar statistical behaviours to those seen in natural language with measured exponents that provide a signal which correlates with the nature of the evidence codes used to support the annotations, suggesting that the measured exponent might provide a signal regarding the information content of the annotation.
Metabolic profiling might provide insight into the biologic underpinnings of disability in older adults.
A targeted mass spectrometry–based platform was used to identify and quantify 45 plasma acylcarnitines in 77 older men with a mean age of 79 years and average body mass index of 28.4 kg/m2. To control for type I error inherent in a test of multiple analytes, principal components analysis was employed to reduce the acylcarnitines from 45 separate metabolites, into a single “acylcarnitine factor.” We then tested for an association between this acylcarnitine factor and multiple indices of physical performance and self-reported function.
The acylcarnitine factor accounted for 40% of the total variance in 45 acylcarnitines. Of the metabolites analyzed, those that contributed most to our one-factor solution were even-numbered medium and long-chain species with side chains containing 10–18 carbons (factor loadings ≥0.70). Odd-numbered chain species, in contrast, had factor loadings 0.50 or less. Acylcarnitine factor scores were inversely related to physical performance as measured by the Short Physical Performance Battery total score, two of its three component scores (gait and chair stands Short Physical Performance Battery), and usual and maximal gait speeds (ρ = −0.324, −0.348, −0.309, −0.241, and −0.254, respectively; p < .05).
Higher acylcarnitine factor scores were associated with lower levels of objectively measured physical performance in this group of older, largely overweight men. Metabolic profiles of rodents exhibiting lipid-induced mitochondrial dysfunction show a similar phenotypic predominance of medium- and long-chain acylcarnitines.
Physical performance; Physical function; Metabolic profiling; Acylcarnitine; Aging
Ontologies such as the Gene Ontology (GO) and their use in annotations make cross species comparisons of genes possible, along with a wide range of other analytical activities. The bio-ontologies community, in particular the Open Biomedical Ontologies (OBO) community, have provided many other ontologies and an increasingly large volume of annotations of gene products that can be exploited in query and analysis. As many annotations with different ontologies centre upon gene products, there is a possibility to explore gene products through multiple ontological perspectives at the same time. Questions could be asked that link a gene product’s function, process, cellular location, phenotype and disease. Current tools, such as AmiGO, allow exploration of genes based on their GO annotations, but not through multiple ontological perspectives. In addition, the semantics of these ontology’s representations should be able to, through automated reasoning, afford richer query opportunities of the gene product annotations than is currently possible.
To do this multi-perspective, richer querying of gene product annotations, we have created the Logical Gene Ontology, or GOAL ontology, in OWL that combines the Gene Ontology, Human Disease Ontology and the Mammalian Phenotype Ontology, together with classes that represent the annotations with these ontologies for mouse gene products. Each mouse gene product is represented as a class, with the appropriate relationships to the GO aspects, phenotype and disease with which it has been annotated. We then use defined classes to query these protein classes through automated reasoning, and to build a complex hierarchy of gene products. We have presented this through a Web interface that allows arbitrary queries to be constructed and the results displayed.
This standard use of OWL affords a rich interaction with Gene Ontology, Human Disease Ontology and Mammalian Phenotype Ontology annotations for the mouse, to give a fine partitioning of the gene products in the GOAL ontology. OWL in combination with automated reasoning can be effectively used to query across ontologies to ask biologically rich questions. We have demonstrated that automated reasoning can be used to deliver practical on-line querying support for the ontology annotations available for the mouse.
The GOAL Web page is to be found at http://owl.cs.manchester.ac.uk/goal.
To determine if caloric restriction (CR) would cause changes in plasma metabolic intermediates in response to a mixed meal, suggestive of changes in the capacity to adapt fuel oxidation to fuel availability or metabolic flexibility, and to determine how any such changes relate to insulin sensitivity (SI).
Forty-six volunteers were randomized to a weight maintenance diet (Control), 25% CR, or 12.5% CR plus 12.5% energy deficit from structured aerobic exercise (CR+EX), or a liquid calorie diet (890 kcal/d until 15% reduction in body weight)for six months. Fasting and postprandial plasma samples were obtained at baseline, three, and six months. A targeted mass spectrometry-based platform was used to measure concentrations of individual free fatty acids (FFA), amino acids (AA), and acylcarnitines (AC). SI was measured with an intravenous glucose tolerance test.
Over three and six months, there were significantly larger differences in fasting-to-postprandial (FPP) concentrations of medium and long chain AC (byproducts of FA oxidation) in the CR relative to Control and a tendency for the same in CR+EX (CR-3 month P = 0.02; CR-6 month P = 0.002; CR+EX-3 month P = 0.09; CR+EX-6 month P = 0.08). After three months of CR, there was a trend towards a larger difference in FPP FFA concentrations (P = 0.07; CR-3 month P = 0.08). Time-varying differences in FPP concentrations of AC and AA were independently related to time-varying SI (P<0.05 for both).
Based on changes in intermediates of FA oxidation following a food challenge, CR imparted improvements in metabolic flexibility that correlated with improvements in SI.
Recent years have seen an explosion in the availability of data in the chemistry domain. With this information explosion, however, retrieving relevant results from the available information, and organising those results, become even harder problems. Computational processing is essential to filter and organise the available resources so as to better facilitate the work of scientists. Ontologies encode expert domain knowledge in a hierarchically organised machine-processable format. One such ontology for the chemical domain is ChEBI. ChEBI provides a classification of chemicals based on their structural features and a role or activity-based classification. An example of a structure-based class is 'pentacyclic compound' (compounds containing five-ring structures), while an example of a role-based class is 'analgesic', since many different chemicals can act as analgesics without sharing structural features. Structure-based classification in chemistry exploits elegant regularities and symmetries in the underlying chemical domain. As yet, there has been neither a systematic analysis of the types of structural classification in use in chemistry nor a comparison to the capabilities of available technologies.
We analyze the different categories of structural classes in chemistry, presenting a list of patterns for features found in class definitions. We compare these patterns of class definition to tools which allow for automation of hierarchy construction within cheminformatics and within logic-based ontology technology, going into detail in the latter case with respect to the expressive capabilities of the Web Ontology Language and recent extensions for modelling structured objects. Finally we discuss the relationships and interactions between cheminformatics approaches and logic-based approaches.
Systems that perform intelligent reasoning tasks on chemistry data require a diverse set of underlying computational utilities including algorithmic, statistical and logic-based tools. For the task of automatic structure-based classification of chemical entities, essential to managing the vast swathes of chemical data being brought online, systems which are capable of hybrid reasoning combining several different approaches are crucial. We provide a thorough review of the available tools and methodologies, and identify areas of open research.
Prevalent in critically ill patients, delirium remains poorly understood and difficult to treat. In a cross-sectional study conducted in 12 countries, delirium was identified in close to one third of patients and was independently associated with increased mortality. While such epidemiological accounts represent an important cornerstone for research, scientific efforts are needed to elucidate the causes of delirium and the mechanisms underlying its association with poor outcomes.
Ontologies are being developed for the life sciences to standardise the way we describe and interpret the wealth of data currently being generated. As more ontology based applications begin to emerge, tools are required that enable domain experts to contribute their knowledge to the growing pool of ontologies. There are many barriers that prevent domain experts engaging in the ontology development process and novel tools are needed to break down these barriers to engage a wider community of scientists.
We present Populous, a tool for gathering content with which to construct an ontology. Domain experts need to add content, that is often repetitive in its form, but without having to tackle the underlying ontological representation. Populous presents users with a table based form in which columns are constrained to take values from particular ontologies. Populated tables are mapped to patterns that can then be used to automatically generate the ontology's content. These forms can be exported as spreadsheets, providing an interface that is much more familiar to many biologists.
Populous's contribution is in the knowledge gathering stage of ontology development; it separates knowledge gathering from the conceptualisation and axiomatisation, as well as separating the user from the standard ontology authoring environments. Populous is by no means a replacement for standard ontology editing tools, but instead provides a useful platform for engaging a wider community of scientists in the mass production of ontology content.
To understand relationships between exercise training-mediated improvements in insulin sensitivity (SI) and changes in circulating concentrations of metabolic intermediates, hormones, and inflammatory mediators.
RESEARCH DESIGN AND METHODS
Targeted mass spectrometry and enzyme-linked immunosorbent assays were used to quantify metabolic intermediates, hormones, and inflammatory markers at baseline, after 6 months of exercise training, and 2 weeks after exercise training cessation (n = 53). A principal components analysis (PCA) strategy was used to relate changes in these intermediates to changes in SI.
PCA reduced the number of intermediates from 90 to 24 factors composed of biologically related components. With exercise training, improvements in SI were associated with reductions in by-products of fatty acid oxidation and increases in glycine and proline (P < 0.05, R2 = 0.59); these relationships were retained 15 days after cessation of exercise training (P < 0.05, R2 = 0.34).
These observations support prior observations in animal models that exercise training promotes more efficient mitochondrial β-oxidation and challenges current hypotheses regarding exercise training and glycine metabolism.
Interest is growing in physical activity-friendly community designs, but few tests exist of communities explicitly designed to be walkable. We test whether students living in a new urbanist community that is also a pilot LEED_ND (Leadership in Energy and Environmental Design-Neighborhood Development) community have greater accelerometer-measured moderate-to-vigorous physical activity (MVPA) across particular time periods compared to students from other communities. We test various time/place periods to see if the data best conform to one of three explanations for MVPA. Environmental effects suggest that MVPA occurs when individuals are exposed to activity-friendly settings; selection effects suggest that walkable community residents prefer MVPA, which leads to both their choice of a walkable community and their high levels of MVPA; catalyst effects occur when walking to school creates more MVPA, beyond the school commute, on schooldays but not weekends.
Fifth graders (n = 187) were sampled from two schools representing three communities: (1) a walkable community, Daybreak, designed with new urbanist and LEED-ND pilot design standards; (2) a mixed community (where students lived in a less walkable community but attended the walkable school so that part of the route to school was walkable), and (3) a less walkable community. Selection threats were addressed through controlling for parental preferences for their child to walk to school as well as comparing in-school MVPA for the walkable and mixed groups.
Minutes of MVPA were tested with 3 × 2 (Community by Gender) analyses of covariance (ANCOVAs). Community walkability related to more MVPA during the half hour before and after school and, among boys only, more MVPA after school. Boys were more active than girls, except during the half hour after school. Students from the mixed and walkable communities--who attended the same school--had similar in-school MVPA levels, and community groups did not differ in weekend MVPA, providing little evidence of selection effects.
Even after our controls for selection effects, we find evidence of environmental effects on MVPA. These results suggest that walkable community design, according to new urbanist and LEED_ND pilot design standards, is related to higher MVPA among students at certain times.
Walkability; new urbanism; LEED_ND; neighborhood design; walk to school; accelerometer
Gluconeogenesis makes a major contribution to hepatic glucose production, a process critical for survival in mammals. In this study, we identify the p160 family member, SRC-1, as a key coordinator of the hepatic gluconeogenic program in vivo. SRC-1 null mice displayed hypoglycemia secondary to a deficit in hepatic glucose production. Selective re-expression of SRC-1 in the liver restored blood glucose levels to a normal range. SRC-1 was found induced upon fasting to coordinate in a cell-autonomous manner, the gene expression of rate-limiting enzymes of the gluconeogenic pathway. At the molecular level, the main role of SRC-1 was to modulate the expression and the activity of C/EBPα through a feed-forward loop in which SRC-1 used C/EBPα to transactivate pyruvate carboxylase, a crucial gene for initiation of the gluconeogenic program. We propose that SRC-1, acts as a novel and critical mediator of glucose homeostasis in the liver by adjusting the transcriptional activity of key genes involved in the hepatic glucose production machinery.
We examine the relationship between time use choices and healthy body weight as measured by survey respondents' body mass index (BMI). Using data from the 2006 and 2007 American Time Use Surveys, we expand upon earlier research by including more detailed measures of time spent eating as well as measures of physical activity time and sedentary time. We also estimate three alternative models that relate time use to BMI.
Our results suggest that time use and BMI are simultaneously determined. The preferred empirical model reveals evidence of an inverse relationship between time spent eating and BMI for women and men. In contrast, time spent drinking beverages while simultaneously doing other things and time spent watching television/videos are positively linked to BMI. For women only, time spent in food preparation and clean-up is inversely related to BMI while for men only, time spent sleeping is inversely related to BMI. Models that include grocery prices, opportunity costs of time, and nonwage income reveal that as these economic variables increase, BMI declines.
In this large, nationally representative data set, our analyses that correct for time use endogeneity reveal that the Americans' time use decisions have implications for their BMI. The analyses suggest that both eating time and context (i.e., while doing other tasks simultaneously) matters as does time spent in food preparation, and time spent in sedentary activities. Reduced form models suggest that shifts in grocery prices, opportunity costs of time, and nonwage income may be contributing to alterations in time use patterns and food choices that have implications for BMI.
Body mass index; time use; time spent eating; physical (in)activity time; wage rates; and grocery prices
Acyl-CoA synthetase-1 (ACSL) contributes 80% of total ACSL activity in adipose tissue and was believed to be essential for the synthesis of triacylglycerol. We predicted that an adipose-specific knockout of ACSL1 (Acsl1A−/−) would be lipodystrophic, but, compared to controls, Acsl1A−/− mice had 30% greater fat mass when fed a low fat diet, and gained weight normally when fed a high fat diet. Acsl1A−/− adipocytes incorporated [14C]oleate into glycerolipids normally, but fatty acid oxidation rates were 50–90% lower than in control adipocytes and mitochondria. Acsl1A−/− mice were markedly cold intolerant, and β3-adrenergic agonists did not increase oxygen consumption, despite normal adrenergic signaling in brown adipose tissue. The reduced adipose FA oxidation and marked cold intolerance of Acsl1A−/− mice indicate that normal activation of FA for oxidation in adipose tissue in vivo requires ACSL1. Thus, ACSL1 has a specific function in directing the metabolic partitioning of fatty acids towards β-oxidation.
fatty acid oxidation; cold thermogenesis; brown adipose; triacylglycerol
The effect of hyperglycaemia on the brain cells of septic shock patients is unknown. The objective of this study was to evaluate the relationship between hyperglycaemia and apoptosis in the brains of septic shock patients.
In a prospective study of 17 patients who died from septic shock, hippocampal tissue was assessed for neuronal ischaemia, neuronal and microglial apoptosis, neuronal Glucose Transporter (GLUT) 4, endothelial inducible Nitric Oxide Synthase (iNOS), microglial GLUT5 expression, microglial and astrocyte activation. Blood glucose (BG) was recorded five times a day from ICU admission to death. Hyperglycaemia was defined as a BG 200 mg/dL g/l and the area under the BG curve (AUBGC) > 2 g/l was assessed.
Median BG over ICU stay was 2.2 g/l. Neuronal apoptosis was correlated with endothelial iNOS expression (rho = 0.68, P = 0.04), while microglial apoptosis was associated with AUBGC > 2 g/l (rho = 0.70; P = 0.002). Neuronal and microglial apoptosis correlated with each other (rho = 0.69, P = 0.006), but neither correlated with the duration of septic shock, nor with GLUT4 and 5 expression. Neuronal apoptosis and ischaemia tended to correlate with duration of hypotension.
In patients with septic shock, neuronal apoptosis is rather associated with iNOS expression and microglial apoptosis with hyperglycaemia, possibly because GLUT5 is not downregulated. These data provide a mechanistic basis for understanding the neuroprotective effects of glycemic control.
Text definitions for entities within bio-ontologies are a cornerstone of the effort to gain a consensus in understanding and usage of those ontologies. Writing these definitions is, however, a considerable effort and there is often a lag between specification of the main part of an ontology (logical descriptions and definitions of entities) and the development of the text-based definitions. The goal of natural language generation (NLG) from ontologies is to take the logical description of entities and generate fluent natural language. The application described here uses NLG to automatically provide text-based definitions from an ontology that has logical descriptions of its entities, so avoiding the bottleneck of authoring these definitions by hand.
To produce the descriptions, the program collects all the axioms relating to a given entity, groups them according to common structure, realises each group through an English sentence, and assembles the resulting sentences into a paragraph, to form as ‘coherent’ a text as possible without human intervention. Sentence generation is accomplished using a generic grammar based on logical patterns in OWL, together with a lexicon for realising atomic entities. We have tested our output for the Experimental Factor Ontology (EFO) using a simple survey strategy to explore the fluency of the generated text and how well it conveys the underlying axiomatisation. Two rounds of survey and improvement show that overall the generated English definitions are found to convey the intended meaning of the axiomatisation in a satisfactory manner. The surveys also suggested that one form of generated English will not be universally liked; that intrusion of too much ‘formal ontology’ was not liked; and that too much explicit exposure of OWL semantics was also not liked.
Our prototype tools can generate reasonable paragraphs of English text that can act as definitions. The definitions were found acceptable by our survey and, as a result, the developers of EFO are sufficiently satisfied with the output that the generated definitions have been incorporated into EFO. Whilst not a substitute for hand-written textual definitions, our generated definitions are a useful starting point.
An on-line version of the NLG text definition tool can be found at http://swat.open.ac.uk/tools/. The questionaire and sample generated text definitions may be found at http://mcs.open.ac.uk/nlg/SWAT/bio-ontologies.html.
Chronic renal disease is a global health problem. The identification of suitable biomarkers could facilitate early detection and diagnosis and allow better understanding of the underlying pathology. One of the challenges in meeting this goal is the necessary integration of experimental results from multiple biological levels for further analysis by data mining. Data integration in the life science is still a struggle, and many groups are looking to the benefits promised by the Semantic Web for data integration.
We present a Semantic Web approach to developing a knowledge base that integrates data from high-throughput experiments on kidney and urine. A specialised KUP ontology is used to tie the various layers together, whilst background knowledge from external databases is incorporated by conversion into RDF. Using SPARQL as a query mechanism, we are able to query for proteins expressed in urine and place these back into the context of genes expressed in regions of the kidney.
The KUPKB gives KUP biologists the means to ask queries across many resources in order to aggregate knowledge that is necessary for answering biological questions. The Semantic Web technologies we use, together with the background knowledge from the domain’s ontologies, allows both rapid conversion and integration of this knowledge base. The KUPKB is still relatively small, but questions remain about scalability, maintenance and availability of the knowledge itself.
The KUPKB may be accessed via http://www.e-lico.eu/kupkb.
There have been a number of recent efforts (e.g. BioCatalogue, BioMoby) to systematically catalogue bioinformatics tools, services and datasets. These efforts rely on manual curation, making it difficult to cope with the huge influx of various electronic resources that have been provided by the bioinformatics community. We present a text mining approach that utilises the literature to automatically extract descriptions and semantically profile bioinformatics resources to make them available for resource discovery and exploration through semantic networks that contain related resources.
The method identifies the mentions of resources in the literature and assigns a set of co-occurring terminological entities (descriptors) to represent them. We have processed 2,691 full-text bioinformatics articles and extracted profiles of 12,452 resources containing associated descriptors with binary and tf*idf weights. Since such representations are typically sparse (on average 13.77 features per resource), we used lexical kernel metrics to identify semantically related resources via descriptor smoothing. Resources are then clustered or linked into semantic networks, providing the users (bioinformaticians, curators and service/tool crawlers) with a possibility to explore algorithms, tools, services and datasets based on their relatedness. Manual exploration of links between a set of 18 well-known bioinformatics resources suggests that the method was able to identify and group semantically related entities.
The results have shown that the method can reconstruct interesting functional links between resources (e.g. linking data types and algorithms), in particular when tf*idf-like weights are used for profiling. This demonstrates the potential of combining literature mining and simple lexical kernel methods to model relatedness between resource descriptors in particular when there are few features, thus potentially improving the resource description, discovery and exploration process. The resource profiles are available at http://gnode1.mib.man.ac.uk/bioinf/semnets.html
The aim of this study was to determine the relationship between hormonal status and mortality in patients with protracted critical illness.
We conducted a prospective observational study in four medical and surgical intensive care units (ICUs). ICU patients who regained consciousness after 7 days of mechanical ventilation were included. Plasma levels of insulin-like growth factor 1 (IGF-1), prolactin, thyroid-stimulating hormone, follicle-stimulating hormone, luteinizing hormone, estradiol, progesterone, testosterone, dehydroepiandrosterone (DHEA), dehydroepiandrosterone sulfate (DHEAS) and cortisol were measured on the first day patients were awake and cooperative (day 1). Mean blood glucose from admission to day 1 was calculated.
We studied 102 patients: 65 men and 37 women (29 of the women were postmenopausal). Twenty-four patients (24%) died in the hospital. The IGF-1 levels were higher and the cortisol levels were lower in survivors. Mean blood glucose was lower in women who survived, and DHEA and DHEAS were higher in men who survived.
These results suggest that, on the basis of sex, some endocrine or metabolic markers measured in the postacute phase of critical illness might have a prognostic value.