Hepatic progenitor cells from adult human livers for cell transplantation.

Objective: Liver regeneration is mainly based on cellular self-renewal including progenitor cells. Efforts have been made to harness this potential for cell transplantation, but shortage of hepatocytes and premature differentiated progenitor cells from extra-hepatic organs are limiting factors. Histological studies implied that resident cells in adult liver can proliferate, have bipotential character and may be a suitable source for cell transplantation. Methods: Particular cell populations were isolated after adequate tissue dissociation. Single cell suspensions were purified by Thy-1 positivity selection, characterised in vitro and transplanted in immunodeficient Pfp/Rag2 mice. Results: Thy-1+ cells that are mainly found in the portal tract and the surrounding parenchyma, were isolated from surgical liver tissue with high yields from specimens with histological signs of regeneration. Thy-1+ cell populations were positive for progenitor (CD34, c-kit, CK14, M2PK, OV6), biliary (CK19) and hepatic (HepPar1) markers revealing their progenitor as well as hepatic and biliary nature. The potential of Thy-1+ cells for differentiation in vitro was demonstrated by increased mRNA and protein expression for hepatic (CK18, HepPar1) and biliary (CK7) markers during culture while progenitor markers CK14, chromogranin A and nestin were reduced. After transplantation of Thy-1+ cells into livers of immunodeficient mice, engraftment was predominantly seen in the periportal portion of the liver lobule. Analysis of in situ material revealed that transplanted cells express human hepatic markers HepPar1 and albumin, indicating functional engraftment. Conclusion: Bipotential progenitor cells from human adult livers can be isolated using Thy-1 and might be a potential candidate for cell treatment in liver diseases

Using Comparative Preference Statements in Hypervolume-Based Interactive Multiobjective Optimization

International audienceThe objective functions in multiobjective optimization problems are often non-linear, noisy, or not available in a closed form and evolutionary multiobjective optimization (EMO) algorithms have been shown to be well applicable in this case. Here, our objective is to facilitate interactive decision making by saving function evaluations outside the "interesting" regions of the search space within a hypervolume-based EMO algorithm. We focus on a basic model where the Decision Maker (DM) is always asked to pick the most desirable solution among a set. In addition to the scenario where this solution is chosen directly, we present the alternative to specify preferences via a set of so-called comparative preference statements. Examples on standard test problems show the working principles, the competitiveness, and the drawbacks of the proposed algorithm in comparison with the recent iTDEA algorithm

Multi-Objective Optimization with an Adaptive Resonance Theory-Based Estimation of Distribution Algorithm: A Comparative Study

Proceedings of: 5th International Conference, LION 5, Rome, Italy, January 17-21, 2011.The introduction of learning to the search mechanisms of optimization algorithms has been nominated as one of the viable approaches when dealing with complex optimization problems, in particular with multi-objective ones. One of the forms of carrying out this hybridization process is by using multi-objective optimization estimation of distribution algorithms (MOEDAs). However, it has been pointed out that current MOEDAs have a intrinsic shortcoming in their model-building algorithms that hamper their performance. In this work we argue that error-based learning, the class of learning most commonly used in MOEDAs is responsible for current MOEDA underachievement. We present adaptive resonance theory (ART) as a suitable learning paradigm alternative and present a novel algorithm called multi-objective ART-based EDA (MARTEDA) that uses a Gaussian ART neural network for model-building and an hypervolume-based selector as described for the HypE algorithm. In order to assert the improvement obtained by combining two cutting-edge approaches to optimization an extensive set of experiments are carried out. These experiments also test the scalability of MARTEDA as the number of objective functions increases.This work was supported by projects CICYT TIN2008-06742-C02-02/TSI, CICYT TEC2008-06732-C02-02/TEC, CAM CONTEXTS (S2009/TIC-1485) and DPS2008-07029-C02-02.Publicad

Decisional Conflict and User Acceptance of Multicriteria Decision-Making Aids *

Despite the development of increasingly sophisticated and refined multicriteria decision-making (MCDM) methods, an examination of the experimental evidence indicates that users most often prefer relatively unsophisticated methods. In this paper, we synthesize theories and empirical findings from the psychology of judgment and choice to provide a new theoretical explanation for such user preferences. Our argument centers on the assertion that the MCDM method preferred by decision makers is a function of the degree to which the method tends to introduce decisional conflict. The model we develop relates response mode, decision strategy, and the salience of decisional conflict to user preferences among decision aids. We then show that the model is consistent with empirical results in MCDM studies. Next, the role of decisional conflict in problem formulation aids is briefly discussed. Finally, we outline future research needed to thoroughly test the theoretical mechanisms we have proposed.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/73461/1/j.1540-5915.1991.tb00371.x.pd

Investigating the influence of product perception and geometric features

Research in emotional design and Kansei Engineering has shown that aesthetics play a significant role in the appeal of a product. This paper contributes to establishing a methodology to identify the relationships between perceptions, aesthetic features, desire to own and background of consumers. Surveys were conducted with 71 participants to gather their perceptions of 11 vase concepts. Advanced statistical analyses, including mixed models, were applied to allow generalisation of the results beyond the data sample. Significant relations between the desire to own a product and how the product is perceived were found (the desire to own was found to be related to beautiful, expensive, elegant, exciting, feminine, common and dynamic vases), as well as between the perceptions and the parameters describing the form of the vases (a vase was perceived as beautiful if it had many curved lines and was simple and tall). An automated mixed model analysis was conducted and revealed that general rules can be found between aesthetic features, perceptions and ownership, which can apply across gender and culture. The findings include design rules that link aesthetic features with perceptions. These contribute to research as guidelines for design synthesis and can either be implemented via shape grammars or parametric modelling approaches. These rules are also interesting for 3D printing applications, especially important when the consumer is the designer. Some of these design rules are linked to the desire to own a product, they have implications for industry, and they offer guidelines to creating attractive products that people want to own

Visualising Evolution History in Multi- and Many-Objective Optimisation

Evolutionary algorithms are widely used to solve optimisation problems. However, challenges of transparency arise in both visualising the processes of an optimiser operating through a problem and understanding the problem features produced from many-objective problems, where comprehending four or more spatial dimensions is difficult. This work considers the visualisation of a population as an optimisation process executes. We have adapted an existing visualisation technique to multi- and many-objective problem data, enabling a user to visualise the EA processes and identify specific problem characteristics and thus providing a greater understanding of the problem landscape. This is particularly valuable if the problem landscape is unknown, contains unknown features or is a many-objective problem. We have shown how using this framework is effective on a suite of multi- and many-objective benchmark test problems, optimising them with NSGA-II and NSGA-III

Cytogenetic analysis of HER1/EGFR, HER2, HER3 and HER4 in 278 breast cancer patients

INTRODUCTION: The HER (human EGFR related) family of receptor tyrosine kinases (HER1/EGFR (epidermal growth factor receptor)/c-erbB1, HER2/c-erbB2, HER3/c-erbB3 and HER4/c-erbB4) shares a high degree of structural and functional homology. It constitutes a complex network, coupling various extracellular ligands to intracellular signal transduction pathways resulting in receptor interaction and cross-activation. The most famous family member is HER2, which is a target in Herceptin therapy in metastatic status and also in adjuvant therapy of breast cancer in the event of dysregulation as a result of gene amplification and resulting protein overexpression. The HER2-related HER receptors have been shown to interact directly with HER2 receptors and thereby mutually affect their activity and subsequent malignant growth potential. However, the clinical outcome with regard to total HER receptor state remains largely unknown. METHODS: We investigated HER1-HER4, at both the DNA and the protein level, using fluorescence in situ hybridisation (FISH) probes targeted to all four receptor loci and also immunohistochemistry in tissue microarrays derived from 278 breast cancer patients. RESULTS: We retrospectively found HER3 gene amplification with a univariate negative impact on disease-free survival (hazard ratio 2.35, 95% confidence interval 1.08 to 5.11, p = 0.031), whereas HER4 amplification showed a positive trend in overall and disease-free survival. Protein expression revealed no additional information. CONCLUSION: Overall, the simultaneous quantification of HER3 and HER4 receptor genes by means of FISH might enable the rendering of a more precise stratification of breast cancer patients by providing additional prognostic information. The continuation of explorative and prospective studies on all HER receptors will be required for an evaluation of their potential use for specific therapeutic targeting with respect to individualised therapy

Insights into the Binding of Phenyltiocarbamide (PTC) Agonist to Its Target Human TAS2R38 Bitter Receptor

Humans' bitter taste perception is mediated by the hTAS2R subfamily of the G protein-coupled membrane receptors (GPCRs). Structural information on these receptors is currently limited. Here we identify residues involved in the binding of phenylthiocarbamide (PTC) and in receptor activation in one of the most widely studied hTAS2Rs (hTAS2R38) by means of structural bioinformatics and molecular docking. The predictions are validated by site-directed mutagenesis experiments that involve specific residues located in the putative binding site and trans-membrane (TM) helices 6 and 7 putatively involved in receptor activation. Based on our measurements, we suggest that (i) residue N103 participates actively in PTC binding, in line with previous computational studies. (ii) W99, M100 and S259 contribute to define the size and shape of the binding cavity. (iii) W99 and M100, along with F255 and V296, play a key role for receptor activation, providing insights on bitter taste receptor activation not emerging from the previously reported computational models