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The NAD+-dependent deacetylase, sirtuin 1 (SIRT1), has been recently been suspected to have a role in tumorigenesis. We investigated the expression of SIRT1 in pancreatic cancer and the effect of SIRT1-targeted RNA interference (RNAi) on cell proliferation and tumor formation in a pancreatic cancer cell line, PANC1. The expression of SIRT1 was investigated in 49 specimens of pancreatic cancer and adjacent normal pancreatic tissues. SIRT1 was overexpressed in pancreatic cancer tissues at both the mRNA and protein levels, with increased SIRT1 positivity associated with tumors from patients over 60 years old, tumors larger than 4 cm, higher TNM (extent of tumor (T), the extent of spread to lymph nodes (N), and presence of distant metastasis (M)) stage or the presence of lymph node or hepatic metastases. The PANC-1 was stably transfected with a SIRT1 small hairpin RNA (shRNA) expression plasmid and compared with untransfected and PANC-1-negative RNAi cells. Proliferation of PANC-1-SIRT1-RNAi cells was significantly reduced, accompanied by increased rates of apoptosis, G1 arrest and senescence. Furthermore, FOXO3a expression was markedly upregulated in PANC-1-SIRT1-RNAi cells, but no significant difference in p53 expression was observed. The invasive ability of PANC-1-SIRT1-RNAi cells was markedly reduced in vitro, which was linked to increased E-cadherin and reduced-MMP expression. Additionally, PANC-1-SIRT1-RNAi cells had a significantly reduced capacity to form tumors in vivo compared with untransfected and PANC-1-negative RNAi cells. These results suggest that SIRT1 may promote cell proliferation and tumor formation in pancreatic cancer, and downregulation of SIRT1 using shRNA could provide a novel therapeutic treatment. Gene Therapy (2011) 18, 920-928; doi:10.1038/gt.2011.81; published online 16 June 2011Keywords: SIRT1; RNAi; pancreatic cancer; proliferation; apoptosis INTRODUCTION Pancreatic cancer is one of the most aggressive solid malignancies, the third most common gastrointestinal malignancy, the fifth leading cause of cancer mortality and is a leading cause of cancer-related deaths in the developed world. 1 One key characteristic of pancreatic cancer is early systemic metastasis and extremely rapid local tumor progression. 2 Resistance to existing chemotherapeutic agents occurs commonly in pancreatic cancer therapy, 3 and therefore, there is an urgent need to elucidate the molecular mechanisms that underlie the malignant behavior of pancreatic cancer.It has been recently suspected that sirtuin 1 (SIRT1) is involved in tumorigenesis. 4,5 SIRT1 is one of seven members of the sirtuin family of nicotinamide adenine dinucleotide (NAD+)-dependent class III histone deacetylases, with sequence homology to the enzymatic domain of yeast silent information regulator 2 (sir2). 6,7 SIRT1 has a large number of histone and non-histone substrates, which are involved in the regulation of metabolism, differentiation, proliferation, senescence, protein degradation and apoptosis. 8 Overexpression of SIRT1 provides a cell su...

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Purpose: The aim of this study was to design and fabricate a three-dimensional (3D) printed artificial ovary. Methods: We first compared the printability of gelatin-methacryloyl (GelMA), alginate and GelMA-alginate bioinks, of which GelMA was selected for further investigation. The swelling properties, degradation kinetics and shape fidelity of GelMA scaffolds were characterized by equilibrium swelling/ lyophilization, collagenase processing and micro-computed tomography evaluation. Commercial ovarian tumor cell lines (COV434, KGN, ID8) and primary culture ovarian somatic cells were utilized to perform cell-laden 3D printing, and the results were evaluated by live/dead assays and TUNEL detection. Murine ovarian follicles were seeded in the ovarian scaffold and their diameters were recorded every day. Finally, in vitro maturation was performed, and the ovulated oocytes were collected and observed. Results: Our results indicated that GelMA was suitable for 3D printing fabrication. Its scaffolds performed well in terms of hygroscopicity, degradation kinetics and shape fidelity. The viability of ovarian somatic cells was lower than that of commercial cell lines, suggesting that extrusion-based 3D culture fabrication is not suitable for primary ovarian cells. Nevertheless, the GelMA-based 3D printing system provided an appropriate microenvironment for ovarian follicles, which successfully grew and ovulated in the scaffolds. Metaphase II oocytes were also observed after in vitro maturation. Conclusions: The GelMA-based 3D printing culture system is a viable alternative option for follicular growth, development and transfer. Accordingly, it shows promise for clinical application in the treatment of female endocrine and reproductive conditions.

The probabilistic behavior of the fiber-reinforced concrete is usually represented by the common probability density functions, which will lead to the biased results. This study aims to develop a stochastic multiphase micromechanical framework with Legendre orthogonal polynomial to investigate the unbiased probabilistic behavior of the fiber-reinforced concrete's moduli. The different phase volume fractions are analytically calculated based on the aggregate grading and the material's effective properties are quantitatively reached by employing the multilevel micromechanical homogenization schemes. The Monte Carlo simulations are adopted to attain the different order moments of fiber-reinforced concrete's effective properties, with which the unbiased probability density functions are reached by using the Legendre orthogonal polynomial approximations and the linear transformations. Numerical examples indicate that the proposed framework is accurate and computationally efficient to characterize the fiber-reinforced concrete's probabilistic behavior.

A new growing and pruning algorithm is proposed for radial basis function (RBF) neural network structure design in this paper, which is named as self-organizing RBF (SORBF). The structure of the RBF neural network is introduced in this paper first, and then the growing and pruning algorithm is used to design the structure of the RBF neural network automatically. The growing and pruning approach is based on the radius of the receptive field of the RBF nodes. Meanwhile, the parameters adjusting algorithms are proposed for the whole RBF neural network. The performance of the proposed method is evaluated through functions approximation and dynamic system identification. Then, the method is used to capture the biochemical oxygen demand (BOD) concentration in a wastewater treatment system. Experimental results show that the proposed method is efficient for network structure optimization, and it achieves better performance than some of the existing algorithms.

The effects of the spin transition on the electronic structure, thermal expansivity and lattice thermal conductivity of ferropericlase are studied by first principles calculations at high pressures. The electronic structures indicate that ferropericlase is an insulator for high-spin and low-spin states. Combined with the quasiharmonic approximation, our calculations show that the thermal expansivity is larger in the high-spin state than in the low-spin state at ambient pressure, while the magnitude exhibits a crossover between high-spin and low-spin with increasing pressure. The calculated lattice thermal conductivity exhibits a drastic reduction upon the inclusion of ferrous iron, which is consistent with previous experimental studies. However, a subsequent enhancement in the thermal conductivity is obtained, which is associated with the spin transition. Mechanisms are discussed for the variation in thermal conductivity by the inclusion of ferrous iron and the spin transition.