Finding rule groups to classify high dimensional gene expression datasets

Microarray data provides quantitative information about the transcription profile of cells. To analyze microarray datasets, methodology of machine learning has increasingly attracted bioinformatics researchers. Some approaches of machine learning are widely used to classify and mine biological datasets. However, many gene expression datasets are extremely high dimensionality, traditional machine learning methods can not be applied effectively and efficiently. This paper proposes a robust algorithm to find out rule groups to classify gene expression datasets. Unlike the most classification algorithms, which select dimensions (genes) heuristically to form rules groups to identify classes such as cancerous and normal tissues, our algorithm guarantees finding out best-k dimensions (genes), which are most discriminative to classify samples in different classes, to form rule groups for the classification of expression datasets. Our experiments show that the rule groups obtained by our algorithm have higher accuracy than that of other classification approaches

Measuring moral judgement and the implications of cooperative education and rule-based learning

The Defining Issues Test (DIT), developed by Rest (1986), measures a person's level of moral development using hypothetical social dilemmas. Although the DIT is useful for measuring moral development in social settings, it might not adequately capture an individual's moral judgement abilities in solving work-related problems (Weber, 1990; Trevino, 1992; Welton et al., 1994). In the present study, the moral judgement levels of 97 accounting students were measured over a 1 year period using two separate test instruments, the DIT and a context-specific instrument developed by Welton et al. (1994). The test scores are significantly higher on the DIT than the Welton instrument (between the instruments and over time), suggesting that accounting students use higher levels of moral reasoning in resolving hypothetical social dilemmas and lower levels of moral reasoning in resolving context-specific dilemmas. The difference in test scores was highest during cooperative education (work placement programme), implying that the environment is a significant determinant on students' test scores.

Induction of epithelial to mesenchymal transition in PMC42-LA human breast carcinoma cells by carcinoma-associated fibroblast secreted factors

Background
Breast carcinoma is accompanied by changes in the acellular and cellular components of the microenvironment, the latter typified by a switch from fibroblasts to myofibroblasts.


Methods
We utilised conditioned media cultures, Western blot analysis and immunocytochemistry to investigate the differential effects of normal mammary fibroblasts (NMFs) and mammary cancer-associated fibroblasts (CAFs) on the phenotype and behaviour of PMC42-LA breast cancer cells. NMFs were obtained from a mammary gland at reduction mammoplasty, and CAFs from a mammary carcinoma after resection.


Results
We found greater expression of myofibroblastic markers in CAFs than in NMFs. Medium from both CAFs and NMFs induced novel expression of α-smooth muscle actin and cytokeratin-14 in PMC42-LA organoids. However, although conditioned media from NMFs resulted in distribution of vimentin-positive cells to the periphery of PMC42-LA organoids, this was not seen with CAF-conditioned medium. Upregulation of vimentin was accompanied by a mis-localization of E-cadherin, suggesting a loss of adhesive function. This was confirmed by visualizing the change in active β-catenin, localized to the cell junctions in control cells/cells in NMF-conditioned medium, to inactive β-catenin, localized to nuclei and cytoplasm in cells in CAF-conditioned medium.


Conclusion
We found no significant difference between the influences of NMFs and CAFs on PMC42-LA cell proliferation, viability, or apoptosis; significantly, we demonstrated a role for CAFs, but not for NMFs, in increasing the migratory ability of PMC42-LA cells. By concentrating NMF-conditioned media, we demonstrated the presence of factor(s) that induce epithelial-mesenchymal transition in NMF-conditioned media that are present at higher levels in CAF-conditioned media. Our in vitro results are consistent with observations in vivo showing that alterations in stroma influence the phenotype and behaviour of surrounding cells and provide evidence for a role for CAFs in stimulating cancer progression via an epithelial-mesenchymal transition. These findings have implications for our understanding of the roles of signalling between epithelial and stromal cells in the development and progression of mammary carcinoma.

Early induction of chalpains in rotenone-mediated neuronal apoptosis

Rotenone is an inhibitor of mitochondrial complex I that produces a model of Parkinson's disease (PD), where neurons undergo apoptosis by caspase-dependent and/or caspase-independent pathways. Inhibition of calpains has recently been shown to attenuate neuronal apoptosis. This study aims to establish for the first time, the time-point of calpain activation with respect to the caspase activation and the possibility of cell cycle re-entry in rotenone-mediated cell death. Immunoblot results revealed calpain activation occurred at 5, 10 h prior to caspase-3 activation (at 15 h), suggesting calpain activation was an earlier cellular event compared to caspase activation in the rotenone-mediated apoptosis. In addition, an upregulation of phospho-p53 was observed at 21 h. However, no expression or upregulation of cell cycle regulatory proteins including cdc25a, cyclin-D1 and cyclin-D3 were observed, strongly suggesting that cell cycle re-entry did not occur. These findings provide new insights into the differential patterns of calpain and caspase activation that result from rotenone poisoning and which may be relevant to the therapeutic management of PD.

Induction of propranolol metabolism by Ginkgo biloba extract EGb 761 in rats

Ginkgo biloba is one of the most popular herbal medicines in the world, due to its purported pharmacological effects, including memory-enhancing, cognition-improving, and antiplatelet effects. When used in the elderly, Ginkgo has a high potential for interactions with cardiovascular drugs. This study aimed to investigate the effects of the standard Ginkgo biloba extract (EGB 761) treatment on the pharmacokinetics of propranolol and its metabolism to form Ndesisopropylpropranolol (NDP) in rats. We also examined the activity and expression of cytochrome P450 (CYP) 1A and other CYPs in rats treated with EGb 761 at 10 and 100 mg/kg/day for 10 days. A single oral dose of propranolol (10 mg/kg) was administered on day 11 and the concentrations of both propranolol and NDP were determined using validated liquid chromatography-mass spectrometry (LC-MS) methods. The levels of mRNA and protein of various CYPs were determined by RT-PCR and Western blotting analysis, respectively. Pretreatment of EGb 761 at 100 mg/kg, but not 10 mg/kg, for 10 days significantly reduced the area under the plasma concentration-time curve (AUC) and maximum plasma concentration (C max) of propranolol, whereas those values of NDP were significantly increased. CYP1A1, 1A2, 2B1/2, and 3A1 activities and gene expression in the rat liver were significantly increased in a dose-dependent manner by pretreatment with EGb 761. The ex-vivo formation of NDP in liver microsomes from rats pretreated with EGb 761 was markedly enhanced. The formation of NDP from propranolol in liver microsomes was significantly inhibited by α- naphthoflavone (ANF, a selective CYP1A2 inhibitor), but not by quinidine (a CYP2D inhibitor). These results indicated that EGb 761 pretreatment decreased the plasma concentrations of propranolol by accelerated conversion of parental drug to NDP due to induction of CYP1A2. EGb 761 pretreatment also significantly induced CYP2B1/2 and CYP3A1, suggesting potential interactions with substrate drugs for these two enzymes. Further study is needed to explore the potential for gingko-drug interactions and the clinical impact.

The rule of law as an Australian constitutionalist promise

The author poses the question whether the rule of law is a constitutionalist promise that protects all Australians or whether it is simply a juridical principle that may be balanced against certain social factors.  Constitutionalist promises involve the limiting and supporting of state power. The author examines several instances of state power exercised in Australia and concludes that we should not rely on the rule of law as an absolute means of achieving equality, human rights, justice, freedom and even democracy.

Rule-based dependency models for security protocol analysis

Security protocol analysis has been discussed for quite some time in the past few years. Although formal methods have been widely used to identify various vulnerabilities, mainly susceptibility to freshness attacks and impersonation, the arisen inconsistent data between principals and collusion attacks held by a group of dishonest principals have been largely ignored. Moreover, the previous methods focus on reasoning about certain security-related properties and detecting known attacks against secure message, whereas there have been insufficient efforts to handle the above hidden but powerful attacks. In this paper, we address these critical issues and prove the efficiency and intuitiveness of rule-based dependency models in defending a protocol against the attacks. This is able to provide a numerical estimation to measure he occurrence of these attacks. It will be useful in enhancing the current protocol analysis.

A rule-based intelligent energy management system for an internal combustion engine vehicle

An intelligent energy management system (IEMS) is developed to improve fuel efficiency of an internal combustion engine vehicle. It helps determine the best approach to run the engine system through dynamically analysing various factors relating to vehicle. The energy balance technique is implemented and utilised. The simulation outcome of the IEMS is compared against that of a conventional system under the same driving factors. The results show that the IEMS reduces the fuel consumption around 5.6% for the tested conditions.

Where the home in valley meets the damp dirty prison : a human rights perspective on therapeutic jurisprudence and the rule of forensic psychologists in correctional settings

The roles of forensic psychologists in coerced environments such as corrections include that of treatment provider (for the offender) and that of organizational consultant (for the community). This dual role raises ethical issues between offender rights and community rights; an imbalance results in the violation of human rights. A timely reminder of a slippery ethical slope that can arise is the failure of the American Psychological Association to manage this balance regarding interrogation and torture of detainees under the Bush administration. To establish a “bright-line position” regarding ethical practice, forensic psychologists need to be cognizant of international human rights law. In this endeavor, international covenants and a universal ethical code ought to guide practice, although seemingly unresolveable conflicts between the law and ethics codes may arise. A solution to this problem is to devise an ethical framework that is based on enforceable universally shared human values regarding dignity and rights. To this end, the legal theory of therapeutic jurisprudence can assist psychologists to understand the law, the legal system, and their role in applying the law therapeutically to support offender dignity, freedom, and well-being. In this way, a moral stance is taken and the forensic role of treatment provider and/or organizational consultant is not expected to trump the prescriptions and the proscriptions of the law.

The application of a fuzzy rule based system in an exposition of the antecedents of sedge warbler song flight

The utilization of a fuzzy aspect within data analysis attempts to move from a quantitative to a more qualitative investigative environment. As such, this may allow the more non-quantitative researchers results they can use, based on sets of linguistic terms. In this paper an inductive fuzzy decision tree approach is utilized to construct a fuzzy-rule-based system for the first time in a biological setting. The specific biological problem considered attempts to identify the antecedents (conditions in the fuzzy decision rules) which characterize the length of song flight of the male sedge warbler when attempting to attract a mate. Hence, for a non-quantitative investigator the resultant set of fuzzy rules allows an insight into the linguistic interpretation on the relationship between associated characteristics and the respective song flight duration.

Convex hulls in concept induction

Classification learning is dominated by systems which induce large numbers of small axis-orthogonal decision surfaces. This strongly biases such systems towards particular hypothesis types but there is reason believe that many domains have underlying concepts which do not involve axis orthogonal surfaces. Further, the multiplicity of small decision regions mitigates against any holistic appreciation of the theories produced by these systems, notwithstanding the fact that many of the small regions are individually comprehensible. This thesis investigates modeling concepts as large geometric structures in n-dimensional space. Convex hulls are a superset of the set of axis orthogonal hyperrectangles into which axis orthogonal systems partition the instance space. In consequence, there is reason to believe that convex hulls might provide a more flexible and general learning bias than axis orthogonal regions. The formation of convex hulls around a group of points of the same class is shown to be a usable generalisation and is more general than generalisations produced by axis-orthogonal based classifiers, without constructive induction, like decision trees, decision lists and rules. The use of a small number of large hulls as a concept representation is shown to provide classification performance which can be better than that of classifiers which use a large number of small fragmentary regions for each concept. A convex hull based classifier, CH1, has been implemented and tested. CH1 can handle categorical and continuous data. Algorithms for two basic generalisation operations on hulls, inflation and facet deletion, are presented. The two operations are shown to improve the accuracy of the classifier and provide moderate classification accuracy over a representative selection of typical, largely or wholly continuous valued machine learning tasks. The classifier exhibits superior performance to well-known axis-orthogonal-based classifiers when presented with domains where the underlying decision surfaces are not axis parallel. The strengths and weaknesses of the system are identified. One particular advantage is the ability of the system to model domains with approximately the same number of structures as there are underlying concepts. This leads to the possibility of extraction of higher level mathematical descriptions of the induced concepts, using the techniques of computational geometry, which is not possible from a multiplicity of small regions.