Tumor growth suppression induced by biomimetic silk fibroin hydrogels

Protein-based hydrogels with distinct conformations which enable encapsulation or differentiation of cells are of great interest in 3D cancer research models. Conformational changes may cause macroscopic shifts in the hydrogels, allowing for its use as biosensors and drug carriers. In depth knowledge on how 3D conformational changes in proteins may affect cell fate and tumor formation is required. Thus, this study reports an enzymatically crosslinked silk fibroin (SF) hydrogel system that can undergo intrinsic conformation changes from random coil to β-sheet conformation. In random coil status, the SF hydrogels are transparent, elastic, and present ionic strength and pH stimuli-responses. The random coil hydrogels become β-sheet conformation after 10 days in vitro incubation and 14 days in vivo subcutaneous implantation in rat. When encapsulated with ATDC-5 cells, the random coil SF hydrogel promotes cell survival up to 7 days, whereas the subsequent β-sheet transition induces cell apoptosis in vitro. HeLa cells are further incorporated in SF hydrogels and the constructs are investigated in vitro and in an in vivo chick chorioallantoic membrane model for tumor formation. In vivo, Angiogenesis and tumor formation are suppressed in SF hydrogels. Therefore, these hydrogels provide new insights for cancer research and uses of biomaterials.The authors would like to thank the Portuguese Foundation for Science and Technology (FCT) project grants OsteoCart (PTDC/CTM-BPC/115977/2009) and Tissue2Tissue (PTDC/CTM/105703/2008) which supported this study. Research leading to these results has also received funding from the European Union's Seventh Framework Programme (FP7/2007-2013) under grant agreement no REGPOT-CT2012-316331-POLARIS. Le-Ping Yan was awarded a PhD scholarship from FCT (SFRH/BD/64717/2009). We also would like to thank FCT for the distinction attributed to J.M. Oliveira under the Investigador FCT program (IF/00423/2012). The authors also like to acknowledge Dr. Mariana B. Oliveira for technical assistance on the dynamic mechanical analysis of the cell-laden hydrogels

Channel Output Error (COE) for Channel Order Estimation

A new channel order estimation method is proposed for single-input multi-output (SIMO) systems. The method is based on a cost function which is constructed from the channel output error (COE). Proposed method uses the least-squares-smoothing (LSS) technique for channel estimation and Moore-Penrose pseudoinverse for the estimation of input. Channel outputs are obtained using the estimated channel coefficients and the input data sequence extracted from the estimated input data matrix via data unstacking. The cost function is calculated from the difference between the observed and the estimated channel output. It is proven that the cost function has a global minimum. The proposed method performs significantly better than the alternative algorithms. The proposed algorithm is more robust to changes in channel order and the number of channels, and gives exact result from limited number of samples in case of free noise

Effects of Modulation Type on Blind SIMO Commmunications Systems

In frame based communication systems, blind identification of frame length and offset from limited number of observations has an important affect on the performance of blind channel identification and equalization algorithms. In [1], for guard interval transmission schemes, a novel blind frame length and offset estimation method is proposed. In this paper, the performance of methods proposed in [1] for fixed frame length transmission are studied

A new channel order estımatıon algorıthm for fır sımo channels

Channel order estimation problem is considered for FIR (Finite Impulse Response) modeled single-input multi-output (SIMO) communication systems. The performance of the channel estimation algorithms depends on the accuracy and robustness of the channel order estimation. A new channel order estimation algorithm with high accuracy and robustness is proposed for SIMO systems. The proposed algorithm is based on the least squares smoothing (LSS) algorithm for channel estimation. It is guaranteed to find the true channel order from finite number of samples for noise free case. Several experiments are performed and it is shown that the proposed algorithm significantly enhances the performance in channel order estimation in noisy observations. The comparisons with the alternative techniques show that the proposed method is very effective for the channel order estimation. © EURASIP, 2009

Channel Matrix Recursion for Blind Effective Channel Order Estimation

Channel order estimation is a critical task for blind system identification. The performance of the blind system identification algorithms depends on the accuracy and robustness of the channel order estimation. In this paper, a new effective channel order estimation algorithm with high accuracy and robustness is proposed for single-input multi-output (SIMO) systems. The proposed algorithm is guaranteed to find the true channel order for the noise-free case and it performs significantly better than the alternative algorithms for noisy observations. This algorithm shows a consistent performance when the number of observations, channels and channel order are changed. The proposed algorithm is integrated with the least squares smoothing (LSS) algorithm for blind identification of the channel coefficients. Comparisons are done with a variety of different algorithms including linear prediction (LP) based methods. It is shown that significant gain can be obtained compared to the alternative approaches in effective channel order estimation

An application of a circular economy approach to design an energy-efficient heat recovery system

This paper aims to develop an optimal real-life energy-efficient design for a production plant within the concept of the circular economy. The problem is to install a Heat Recovery System (HRS) that utilizes the hot oil used by the compressors to heat the water for the central heating system. To achieve the desired level of energy efficiency this design problem must be formulated from both the optimization and sustainability points of view. Additionally, this design problem must also consider the investment cost. In line with this purpose, this paper formulates this design problem as an optimization problem employing a mathematical programming approach as a single objective, and as a multi-objective optimization problem through a goal programming approach. Besides, this paper uses the return on investment as a key performance indicator, since it deals with a real-life design problem with an investment cost. The related design problem is solved with the single objective and multiobjective versions of the developed mathematical programming model via a commercial solver to identify different design alternatives and hence giving the decision-maker to make a selection option. Finally, the capability of the developed mathematical programming model is tested on a set of randomly generated problems. The obtained results indicate that the developed mathematical programming model is a successful decision support system since its single and multi-objective versions are capable of identifying energy-efficient production designs within the context of the real-life problem on hand and the circular economy

A vehicle scheduling problem with fixed trips and time limitations

We consider minimum-cost scheduling of different vehicle types on a predetermined set of one-way trips. Trips have predetermined ready times, deadlines and associated demands. All trips Must be performed. The total time of operations on any vehicle is limited. We develop a mixed integer model to find the optimal number of vehicles at a minimum cost. Based on the hard nature of the problem, we propose six heuristics. Computational results reveal that heuristics return exceptionally good solutions for problem instances with up to 100 jobs in very small computation times, and are likely to perform well for larger instances. (C) 2008 Elsevier B.V. All rights reserved

Diepoxide-Triggered Conformational Transition of Silk Fibroin: Formation of Hydrogels

Silk fibroin hydrogels with tunable properties could be obtained from aqueous fibroin solutions (4.2 w/v %) in a short period of time. This was achieved by the addition of ethylene glycol diglycidyl ether (EGDE) into the reaction solution. Introduction of EGDE cross-links between the fibroin molecules decreases the mobility of the chains, which triggers the conformational transition from random-coil to β-sheet structure and hence fibroin gelation. Dynamic rheological measurements conducted at 50 °C show the formation of strong to weak hydrogels depending on the pH of the reaction solution. Although EGDE attacks the amino groups of fibroin and forms interstrand cross-links, β-sheets acting as physical cross-links dominate the elasticity of the hydrogels. Mechanical response of low-modulus fibroin hydrogels formed above pH 9.7 is highly nonlinear with strong strain hardening behavior (700%) arising from the alignment of the crystallizable amino acid segments