The Therapeutic Effect of Cytokine-Induced Killer Cells on Pancreatic Cancer Enhanced by Dendritic Cells Pulsed with K-Ras Mutant Peptide

Objective. This study is to investigate the role of the CIKs cocultured with K-ras-DCs in killing of pancreatic cancer cell lines, PANC-1 (K-ras+) and SW1990 (K-ras−). Methods. CIKs induced by IFN-γ, IL-2, and anti-CD3 monoantibody, K-ras-DCCIKs obtained by cocultivation of k-ras-DCs and CIKs. Surface markers examined by FACS. IFN-γ IL-12 ,CCL19 and CCL22 detected by ELISA. Proliferation of various CIKs tested via 3H-TdR. Killing activities of k-ras-DCCIKs and CTLs examined with 125IUdR. Results. CD3+CD56+ and CD3+CD8+ were highly expressed by K-ras-DCCIKs. In its supernatant, IFN-γ, IL-12, CCL19 and CCL22 were significantly higher than those in DCCIK and CIK. The killing rate of K-ras-DCCIK was greater than those of CIK and CTL. CTL induced by K-ras-DCs only inhibited the PANC-1 cells. Conclusions. The k-ras-DC can enhance CIK's proliferation and increase the killing effect on pancreatic cancer cell. The CTLs induced by K-ras-DC can only inhibit PANC-1 cells. In this study, K-ras-DCCIKs also show the specific inhibition to PANC-1 cells, their tumor suppression is almost same with the CTLs, their total tumor inhibitory efficiency is higher than that of the CTLs

Correcting soft errors online in fast fourier transform

While many algorithm-based fault tolerance (ABFT) schemes have been proposed to detect soft errors offline in the fast Fourier transform (FFT) after computation finishes, none of the existing ABFT schemes detect soft errors online before the computation finishes. This paper presents an online ABFT scheme for FFT so that soft errors can be detected online and the corrupted computation can be terminated in a much more timely manner. We also extend our scheme to tolerate both arithmetic errors and memory errors, develop strategies to reduce its fault tolerance overhead and improve its numerical stability and fault coverage, and finally incorporate it into the widely used FFTW library - one of the today's fastest FFT software implementations. Experimental results demonstrate that: (1) the proposed online ABFT scheme introduces much lower overhead than the existing offline ABFT schemes; (2) it detects errors in a much more timely manner; and (3) it also has higher numerical stability and better fault coverage

A social recommendation framework based on multi-scale continuous conditional random fields

This paper addresses the issue of social recommendation based on collaborative filtering (CF) algorithms. Social rec-ommendation emphasizes utilizing various attributes infor-mation and relations in social networks to assist recom-mender systems. Although recommendation techniques have obtained distinct developments over the decades, traditional CF algorithms still have these following two limitations: (1) relational dependency within predictions, an important fac-tor especially when the data is sparse, is not being uti-lized effectively; and (2) straightforward methods for com-bining features like linear integration suffer from high com-puting complexity in learning the weights by enumerating the whole value space, making it difficult to combine var-ious information into an unified approach. In this paper, we propose a novel model, Multi-scale Continuous Condi-tional Random Fields (MCCRF), as a framework to solve above problems for social recommendations. In MCCRF, relational dependency within predictions is modeled by the Markov property, thus predictions are generated simultane-ously and can help each other. This strategy has never been employed previously. Besides, diverse information and rela-tions in social network can be modeled by state and edge feature functions in MCCRF, whose weights can be opti-mized globally. Thus both problems can be solved under this framework. In addition, We propose to utilize Markov chain Monte Carlo (MCMC) estimation methods to solve the difficulties in training and inference processes of MCCRF. Experimental results conducted on two real world data have demonstrated that our approach outperforms traditional CF algorithms. Additional experiments also show the improve-ments from the two factors of relational dependency and feature combination, respectively

MonoNeuralFusion: Online Monocular Neural 3D Reconstruction with Geometric Priors

High-fidelity 3D scene reconstruction from monocular videos continues to be challenging, especially for complete and fine-grained geometry reconstruction. The previous 3D reconstruction approaches with neural implicit representations have shown a promising ability for complete scene reconstruction, while their results are often over-smooth and lack enough geometric details. This paper introduces a novel neural implicit scene representation with volume rendering for high-fidelity online 3D scene reconstruction from monocular videos. For fine-grained reconstruction, our key insight is to incorporate geometric priors into both the neural implicit scene representation and neural volume rendering, thus leading to an effective geometry learning mechanism based on volume rendering optimization. Benefiting from this, we present MonoNeuralFusion to perform the online neural 3D reconstruction from monocular videos, by which the 3D scene geometry is efficiently generated and optimized during the on-the-fly 3D monocular scanning. The extensive comparisons with state-of-the-art approaches show that our MonoNeuralFusion consistently generates much better complete and fine-grained reconstruction results, both quantitatively and qualitatively.Comment: 12 pages, 12 figure

7-Piperazinethylchrysin inhibits melanoma cell proliferation by targeting Mek 1/2 kinase activity

Purpose: To investigate the growth-inhibitory effect of 7-piperazinethylchrysin (PEC) on melanoma cell lines.Methods: Cell viability was analyzed by trypan blue exclusion assays and the cell cycle by flow cytometry using ModFit LT software. Specifically, cells were stained with propidium iodide (0.5 mg/mL) supplemented with RNase A (50 mg/mL), and analyzed using flow cytometry and ModFit LT software.Results: In A375 and B16F10 cell cultures, proliferation was reduced to 79 and 72 %, respectively, on treatment with 30 μM PEC. PEC increased the proportion of A375 cells in G1/G0 phase to 71.23 %, versus 42.76 % in untreated cells. In B16F10 and A375 cells, treatment with PEC caused the inhibition of Mek 1/2 kinase activity and suppressed Erk 1/2 phosphorylation. The level of cAMP-response element binding protein was increased by PEC. The expression of microphthalmia-linked transcription factor was also increased by PEC treatment. Marked enhancement was observed in the level of tyrosinase in melanoma cells on treatment with PEC. Analysis of PBG-D expression showed a marked increase in B16F10 and A375 cells on the addition of PEC to cell cultures at 72 h. The level of PBG D expression was increased by 9- and 8.5-fold in B16F10 and A375 cells, respectively, on incubation with 30 μM PEC. The addition of a Mek 1/2 inhibitor (U0126) to the cultures promoted PEC-mediated growth inhibition.Conclusion: PEC inhibited melanoma cell proliferation, apparently by blocking the cell cycle at G0/G1 and downregulating the Ras/Raf/Mek/Erk pathway.Keywords: Tyrosinase, Kinase, Microphthalmia, Phosphorylation, 7-Piperazinethylchrysi

Cost-effective fabrication of bio-inspired nacre-like composite materials with high strength and toughness

A cost-effective one-step densification process based on bi-directional freeze casting was investigated to produce nacre-like alumina/poly (methyl methacrylate) (PMMA) composites with a unique micro-layered (μL) architecture. This method has the advantage of shorter processing time, as it requires only sintering once instead of twice as in the fabrication of conventional brick-and-mortar (BM) composites via freeze casting. By tuning the processing parameters, composites with different ceramic content and layer thickness were obtained. The resultant mechanical properties of μL composites showed that ceramic content and wall thickness affected mechanical properties significantly. The μL composite with fine ceramic walls (8 μm) and relatively high ceramic fraction (72 vol%) exhibited an exceptional combination of high flexural strength (178 MPa) and fracture toughness (12.5 MPa m1/2). The μL composites were also compared with the conventional BM composites. Although the fracture behaviour of both composites exhibited similar extrinsic toughening mechanisms, the μL composites with longer ceramic walls displayed superior mechanical properties in terms of strength and fracture toughness in comparison with the BM composites comprising short ceramic walls (i.e. bricks), due to the effectiveness of stress transfer of load-bearing ceramic phase within the composites