Electrically driven intracellular and extracellular nanomanipulators evoke neurogenic/cardiomyogenic differentiation in human mesenchymal stem cells

Nanomechanical intervention through electroactuation is an effective strategy to guide stem cell differentiation for tissue engineering and regenerative medicine. In the present study, we elucidate that physical forces exerted by electroactuated gold nanoparticles (GNPs) have a strong influence in regulating the lineage commitment of human mesenchymal stem cells (hMSCs). A novel platform that combines intracellular and extracellular GNPs as nano-manipulators was designed to trigger neurogenic/cardiomyogenic differentiation in hMSCs, in electric field stimulated culture condition. In order to mimic the native microenvironment of nerve and cardiac tissues, hMSCs were treated with physiologically relevant direct current electric field (DC EF) or pulsed electric field (PEF) stimuli, respectively. When exposed to regular intermittent cycles of DC EF stimuli, majority of the GNP actuated hMSCs acquired longer filopodial extensions with multiple branch-points possessing neural-like architecture. Such morphological changes were consistent with higher mRNA expression level for neural-specific markers. On the other hand, PEF elicited cardiomyogenic differentiation, which is commensurate with the tubelike morphological alterations along with the upregulation of cardiac specific markers. The observed effect was significantly promoted even by intracellular actuation and was found to be substrate independent. Further, we have substantiated the participation of oxidative signaling, G0/G1 cell cycle arrest and intracellular calcium Ca2+] elevation as the key upstream regulators dictating GNP assisted hMSC differentiation. Thus, by adopting dual stimulation protocols, we could successfully divert the DC EF exposed cells to differentiate predominantly into neural-like cells and PEF treated cells into cardiomyogenic-like cells, via nanoactuation of GNPs. Such a novel multifaceted approach can be exploited to combat tissue loss following brain injury or heart failure. (C) 2015 Elsevier Ltd. All rights reserved.

Kernelization complexity of possible winner and coalitional manipulation problems in voting

In the POSSIBLE WINNER problem in computational social choice theory, we are given a set of partial preferences and the question is whether a distinguished candidate could be made winner by extending the partial preferences to linear preferences. Previous work has provided, for many common voting rules, fixed parameter tractable algorithms for the POSSIBLE WINNER problem, with number of candidates as the parameter. However, the corresponding kernelization question is still open and in fact, has been mentioned as a key research challenge 10]. In this paper, we settle this open question for many common voting rules. We show that the POSSIBLE WINNER problem for maximin, Copeland, Bucklin, ranked pairs, and a class of scoring rules that includes the Borda voting rule does not admit a polynomial kernel with the number of candidates as the parameter. We show however that the COALITIONAL MANIPULATION problem which is an important special case of the POSSIBLE WINNER problem does admit a polynomial kernel for maximin, Copeland, ranked pairs, and a class of scoring rules that includes the Borda voting rule, when the number of manipulators is polynomial in the number of candidates. A significant conclusion of our work is that the POSSIBLE WINNER problem is harder than the COALITIONAL MANIPULATION problem since the COALITIONAL MANIPULATION problem admits a polynomial kernel whereas the POSSIBLE WINNER problem does not admit a polynomial kernel. (C) 2015 Elsevier B.V. All rights reserved.