255 research outputs found
The empirical accuracy of uncertain inference models
Uncertainty is a pervasive feature of the domains in which expert systems are designed to function. Research design to test uncertain inference methods for accuracy and robustness, in accordance with standard engineering practice is reviewed. Several studies were conducted to assess how well various methods perform on problems constructed so that correct answers are known, and to find out what underlying features of a problem cause strong or weak performance. For each method studied, situations were identified in which performance deteriorates dramatically. Over a broad range of problems, some well known methods do only about as well as a simple linear regression model, and often much worse than a simple independence probability model. The results indicate that some commercially available expert system shells should be used with caution, because the uncertain inference models that they implement can yield rather inaccurate results
Comparative transcriptomics in the Triticeae
<p>Abstract</p> <p>Background</p> <p>Barley and particularly wheat are two grass species of immense agricultural importance. In spite of polyploidization events within the latter, studies have shown that genotypically and phenotypically these species are very closely related and, indeed, fertile hybrids can be created by interbreeding. The advent of two genome-scale Affymetrix GeneChips now allows studies of the comparison of their transcriptomes.</p> <p>Results</p> <p>We have used the Wheat GeneChip to create a "gene expression atlas" for the wheat transcriptome (cv. Chinese Spring). For this, we chose mRNA from a range of tissues and developmental stages closely mirroring a comparable study carried out for barley (cv. Morex) using the Barley1 GeneChip. This, together with large-scale clustering of the probesets from the two GeneChips into "homologous groups", has allowed us to perform a genomic-scale comparative study of expression patterns in these two species. We explore the influence of the polyploidy of wheat on the results obtained with the Wheat GeneChip and quantify the correlation between conservation in gene sequence and gene expression in wheat and barley. In addition, we show how the conservation of expression patterns can be used to elucidate, probeset by probeset, the reliability of the Wheat GeneChip.</p> <p>Conclusion</p> <p>While there are many differences in expression on the level of individual genes and tissues, we demonstrate that the wheat and barley transcriptomes appear highly correlated. This finding is significant not only because given small evolutionary distance between the two species it is widely expected, but also because it demonstrates that it is possible to use the two GeneChips for comparative studies. This is the case even though their probeset composition reflects rather different design principles as well as, of course, the present incomplete knowledge of the gene content of the two species. We also show that, in general, the Wheat GeneChip is not able to distinguish contributions from individual homoeologs. Furthermore, the comparison between the two species leads us to conclude that the conservation of both gene sequence as well as gene expression is positively correlated with absolute expression levels, presumably reflecting increased selection pressure on genes coding for proteins present at high levels. In addition, the results indicate the presence of a correlation between sequence and expression conservation within the Triticeae.</p
Synthesis and pharmacological profiling of analogues of benzyl quinolone carboxylic acid (BQCA) as allosteric modulators of the M1 muscarinic receptor
Established therapy in Alzheimer’s disease involves potentiation of the endogenous orthosteric ligand, acetylcholine, at the M1 muscarinic receptors found in higher concentrations in the cortex and hippocampus. Adverse effects, due to indiscriminate activation of other muscarinic receptor subtypes, are common. M1 muscarinic positive allosteric modulators/allosteric agonists such as BQCA offer an attractive solution, being exquisitely M1-selective over other muscarinic subtypes. A common difficulty with allosteric ligands is interpreting SAR, based on composite potency values derived in the presence of fixed concentration of agonist. In reality these values encompass multiple pharmacological parameters, each potentially and differentially sensitive to structural modification of the ligand. We report novel BQCA analogues which appear to augment ligand affinity for the receptor (pKB), intrinsic efficacy (τB), and both binding (α) and functional (β) cooperativity with acetylcholine. Ultimately, development of such enriched SAR surrounding allosteric modulators will provide insight into their mode of action
Intelligent analysis and data visualisation for teacher assistance tools: the case of exploratory learning
While it is commonly accepted that Learning Analytics tools can support teachers’ awareness and classroom orchestration, not all forms of pedagogy are congruent to the types of data generated by digital technologies or the algorithms used to analyse them. One such pedagogy that has been so far underserved by Learning Analytics is exploratory learning, exemplified by tools such as simulators, virtual labs, microworlds and some interactive educational games. This paper argues that the combination of intelligent analysis of interaction data from such an exploratory learning environment (ELE) and the targeted design of visualisations has the benefit of supporting classroom orchestration and consequently enabling the adoption of this pedagogy to the classroom. We present a case study of learning analytics in the context of an ELE supporting the learning of algebra. We focus on the formative qualitative evaluation of a suite of Teacher Assistance tools. We draw conclusions relating to the value of the tools to teachers and reflect with transferable lessons for future related work
Dopamine Inhibits Mitochondrial Motility in Hippocampal Neurons
The trafficking of mitochondria within neurons is a highly regulated process. In an earlier study, we found that serotonin (5-HT), acting through the 5-HT1A receptor subtype, promotes axonal transport of mitochondria in cultured hippocampal neurons by increasing Akt activity, and consequently decreasing glycogen synthase kinase (GSK3beta) activity. This finding suggests a critical role for neuromodulators in the regulation of mitochondrial trafficking in neurons. In the present study, we investigate the effects of a second important neuromodulator, dopamine, on mitochondrial transport in hippocampal neurons.Here, we show that dopamine, like 5-HT, regulates mitochondrial motility in cultured hippocampal neurons through the Akt-GSK3beta signaling cascade. But, in contrast to the stimulatory effect of 5-HT, administration of exogenous dopamine or bromocriptine, a dopamine 2 receptor (D2R) agonist, caused an inhibition of mitochondrial movement. Moreover, pretreatment with bromocriptine blocked the stimulatory effect of 5-HT on mitochondrial movement. Conversely, in cells pretreated with 5-HT, no further increases in movement were observed after administration of haloperidol, a D2R antagonist. In contrast to the effect of the D2R agonist, addition of SKF38393, a dopamine 1 receptor (D1R) agonist, promoted mitochondrial transport, indicating that the inhibitory effect of dopamine was actually the net summation of opposing influences of the two receptor subtypes. The most pronounced effect of dopamine signals was on mitochondria that were already moving directionally. Western blot analysis revealed that treatment with either a D2R agonist or a D1R antagonist decreased Akt activity, and conversely, treatment with either a D2R antagonist or a D1R agonist increased Akt activity.Our observations strongly suggest a role for both dopamine and 5-HT in regulating mitochondrial movement, and indicate that the integrated effects of these two neuromodulators may be important in determining the distribution of energy sources in neurons
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