BH3 mimetic ABT-737 sensitizes colorectal cancer cells to ixazomib through MCL-1 downregulation and autophagy inhibition.

The proteasome inhibitor MLN9708 is an orally administered drug that is hydrolyzed into its active form, MLN2238 (ixazomib). Compared with Bortezomib, MLN2238 has a shorter proteasome dissociation half-life and a lower incidence and severity of peripheral neuropathy, which makes it an attractive candidate for colorectal cancer treatment. In the present study, we observed that MLN2238 induced autophagy, as evidenced by conversion of the autophagosomal marker LC3 from LC3I to LC3II, in colorectal cancer cell lines. Mcl-1, an anti-apoptotic Bcl-2 family protein, was markedly elevated after treating a colorectal cancer cell line with MLN2238. We proved that inhibiting Mcl-1 expression enhances MLN2238 induced apoptosis and negatively regulates autophagy. Co-administration of BH3 mimetic ABT-737 with MLN2238 synergistically kills colorectal cancer cells through MCL-1 neutralization and autophagy inhibition. Furthermore, the synergistic killing effect of the combination therapy is correlated with P53 status in colorectal cancer. These data highlight that the combination of ABT-737 with MLN9708 is a promising therapeutic strategy for human colorectal cancer

How to select patients and timing for rectal indomethacin to prevent post-ERCP pancreatitis: a systematic review and meta-analysis

Egger’s publication bias plot. (TIF 998 kb

Criticality-Based Quantum Metrology in the Presence of Decoherence

Quantum metrology aims to use quantum resources to improve the precision of measurement. Quantum criticality has been presented as a novel and efficient resource. Generally, protocols of criticality-based quantum metrology often work without decoherence. In this paper, we address the issue whether the divergent feature of the inverted variance is indeed realizable in the presence of noise when approaching the QPT. Taking the quantum Rabi model (QRM) as an example, we obtain the analytical result for the inverted variance. We show that the inverted variance may be convergent in time due to the noise. When approaching the critical point, the maximum inverted variance demonstrates a power-law increase with the exponent -1.2, of which the absolute value is smaller than that for the noise-free case, i.e., 2. We also observe a power-law dependence of the maximum inverted variance on the relaxation rate and the temperature. Since the precision of the metrology is very sensitive to the noise, as a remedy, we propose performing the squeezing operation on the initial state to improve the precision under decoherence. In addition, we also investigate the criticality-based metrology under the influence of the two-photon relaxation. Contrary to the single-photon relaxation, the quantum dynamics of the inverted variance shows a completely-different behavior. It does not oscillate with the same frequency with respect to the re-scaled time for different dimensionless coupling strengths. Strikingly, although the maximum inverted variance still manifests a power-law dependence on the energy gap, the exponent is positive and depends on the dimensionless coupling strength. This observation implies that the criticality may not enhance but weaken the precision in the presence of two-photon relaxation. It can be well described by the non-linearity introduced by the two-photon relaxation.Comment: 6 pages, 5 figure

Spectral karyotyping reveals a comprehensive karyotype in an adult acute lymphoblastic leukemia

Cytogenetic abnormalities are frequently detected in patients with acute lymphoblastic leu-kemia (ALL). Comprehensive karyotype was related to poor prognosis frequently in ALL. We present a comprehensive karyotype in an adult ALL by spectral karyotyping (SKY) and R-banding. SKY not only confirmed the abnormalities previously seen by R-banding but also improved comprehensive karyotype analysis with the following result 47,XY,+9, ins(1;5)(q23;q23q34) t(6;7)(q23;p13). Our report demonstrated that SKY is able to provide more information accurately for prediction of disease prognosis in adult ALL with compre-hensive karyotype

Natural image restoration based on multi-scale group sparsity residual constraints

The Group Sparse Representation (GSR) model shows excellent potential in various image restoration tasks. In this study, we propose a novel Multi-Scale Group Sparse Residual Constraint Model (MS-GSRC) which can be applied to various inverse problems, including denoising, inpainting, and compressed sensing (CS). Our new method involves the following three steps: (1) finding similar patches with an overlapping scheme for the input degraded image using a multi-scale strategy, (2) performing a group sparse coding on these patches with low-rank constraints to get an initial representation vector, and (3) under the Bayesian maximum a posteriori (MAP) restoration framework, we adopt an alternating minimization scheme to solve the corresponding equation and reconstruct the target image finally. Simulation experiments demonstrate that our proposed model outperforms in terms of both objective image quality and subjective visual quality compared to several state-of-the-art methods

Analytical solution for nonlinear vertical vibration model of mill roll system based on improved complexification averaging method

Rolling mill is the core equipment in modern iron and steel industry, and the reliability of its mill roll system (MRS) is the key to ensure the rolling process with high precision, high speed, continuity and stability. However, the MRS possesses some features such as high nonlinearity, time variability and strong coupling. The vertical vibration easily happens in its working process. Nevertheless, the mathematical model of MRS is difficult to be established and hard to be solved. In this paper, the nonlinear dynamics theory and modern signal processing method were introduced to solve this difficult problem. A two degree of freedom (DOF) nonlinear vertical vibration model of MRS was established. And the model was analytically solved by using complexification averaging (CA) method. The solution error of CA method was thoroughly analyzed. Moreover, the CA method was improved by combining the fast empirical mode decomposition (FEMD) method. Research results indicate that the improved CA method presents a significant advantage in improving the solution precision, and can be used to solve strong nonlinear vibration system (NVS) with two DOF