Engineering topics
Tan, Jun
Publications and source records attributed to Tan, Jun.
miR-137 attenuates Aβ-induced neurotoxicity through inactivation of NF-κB pathway by targeting TNFAIP1 in Neuro2a cells
Background: Accumulation of β-amyloid (Aβ) and neuroinflammation are implicated in the pathogenesis and development of Alzheimer's disease (AD). Neuron-enriched miR-137 was aberrantly downregulated and may be associated with the pathogenesis of AD. However, the detailed function of miR-137 in AD pathogenesis and the molecular mechanism have not been elucidated. Methods: The expressions of miR-137 and tumor necrosis factor alpha (TNFα)-induced protein 1 (TNFAIP1) at mRNA and protein levels in primary mouse cortical neurons and Neuro2a (N2a) cells exposed to different concentrations of Aβ{sub 25-35} were examined by qRT-PCR and western blot. Luciferase reporter assay was used to confirm the potential target of miR-137. MTT assay, flow cytometry analysis, caspase-3 activity assay, Enzyme-linked immunosorbent assay (ELISA), and western blot were used to detect cell viability, apoptosis, caspase-3 activity, Nuclear factor-kappa B (NF-κB) activity and level, respectively. Results: Aβ{sub 25-35} downregulated miR-137 and upregulated TNFAIP1 in primary mouse cortical neurons and N2a cells. In addition, miR-137 was found to directly target TNFAIP1 and suppress its mRNA and protein levels. Moreover, miR-137 restoration and TNFAIP1 knockdown facilitate Aβ{sub 25-35}-induced cell toxicity, apoptosis, caspase-3 activity, and activated NF-κB in N2a cells, which was partially abolished by TNFAIP1 overexpression. Conclusion: miR-137 attenuated Aβ-induced neurotoxicity through inactivation of NF-κB pathway by targeting TNFAIP1 in N2a cells, shedding light on the molecular mechanism of miR-137 underlying Aβ-induced neurotoxicity. - Highlights: • Aβ{sub 25-35} downregulated miR-137 and upregulated TNFAIP1 in cortical neurons and N2a cells. • miR-137 suppressed TNFAIP1 expression through direct binding at the 3′UTR. • miR-137 overexpression contributed to Aβ{sub 25-35}-induced cell toxicity and apoptosis. • miR-137 overexpression on Aβ{sub 25-35}-induced neurotoxicity activated NF-κB pathway.
Antibiotic tigecycline enhances cisplatin activity against human hepatocellular carcinoma through inducing mitochondrial dysfunction and oxidative damage
Targeting mitochondrial metabolism has been recently demonstrated to be a promising therapeutic strategy for the treatment of various cancer. In this work, we demonstrate that antibiotic tigecycline is selectively against hepatocellular carcinoma (HCC) through inducing mitochondrial dysfunction and oxidative damage. Tigecycline is more effective in inhibiting proliferation and inducing apoptosis of HCC than normal liver cells. Importantly, tigecycline significantly enhances the inhibitory effects of chemotherapeutic drug cisplatin in HCC in vitro and in vivo. Mechanistically, tigecycline specifically inhibits mitochondrial translation as shown by the decreased protein levels of Cox-1 and -2 but not Cox-4 or Grp78, and increased mRNA levels of Cox-1 and -2 but not Cox-4 in HCC cells exposed to tigecycline. In addition, tigecycline significantly induces mitochondrial dysfunction in HCC cells via decreasing mitochondrial membrane potential, complex I and IV activities, mitochondrial respiration and ATP levels. Tigecycline also increases levels of mitochondrial superoxide, hydrogen peroxide and ROS levels. Consistent with oxidative stress, oxidative damage on DNA, protein and lipid are also observed in tigecycline-treated cells. Importantly, antioxidant N-acetyl-L-cysteine (NAC) reverses the effects of tigecycline, suggesting that oxidative stress is required for the action of tigecycline in HCC cells. We further show that HCC cells have higher level of mitochondrial biogenesis than normal liver cells which might explain the different sensitivity to tigecycline between HCC and normal liver cells. Our work is the first to demonstrate that tigecycline is a promising candidate for HCC treatment and highlight the therapeutic value of targeting mitochondrial metabolism in HCC. - Highlights: • Tigecycline selectively targets HCC in vitro and in vivo. • Tigecycline enhances HCC cell response to chemotherapeutic drug. • Tigecycline inhibits mitochondrial translation and functions in HCC cells. • Tigecycline induces oxidative stress and damage in HCC cells. • Mitochondrial biogenesis and respiration is higher in HCC than normal liver cells.
Accelerated fast iterative shrinkage thresholding algorithms for sparsity-regularized cone-beam CT image reconstruction
Purpose: The development of iterative image reconstruction algorithms for cone-beam computed tomography (CBCT) remains an active and important research area. Even with hardware acceleration, the overwhelming majority of the available 3D iterative algorithms that implement nonsmooth regularizers remain computationally burdensome and have not been translated for routine use in time-sensitive applications such as image-guided radiation therapy (IGRT). In this work, two variants of the fast iterative shrinkage thresholding algorithm (FISTA) are proposed and investigated for accelerated iterative image reconstruction in CBCT. Methods: Algorithm acceleration was achieved by replacing the original gradient-descent step in the FISTAs by a subproblem that is solved by use of the ordered subset simultaneous algebraic reconstruction technique (OS-SART). Due to the preconditioning matrix adopted in the OS-SART method, two new weighted proximal problems were introduced and corresponding fast gradient projection-type algorithms were developed for solving them. We also provided efficient numerical implementations of the proposed algorithms that exploit the massive data parallelism of multiple graphics processing units. Results: The improved rates of convergence of the proposed algorithms were quantified in computer-simulation studies and by use of clinical projection data corresponding to an IGRT study. The accelerated FISTAs were shown to possess dramatically improved convergence properties as compared to the standard FISTAs. For example, the number of iterations to achieve a specified reconstruction error could be reduced by an order of magnitude. Volumetric images reconstructed from clinical data were produced in under 4 min. Conclusions: The FISTA achieves a quadratic convergence rate and can therefore potentially reduce the number of iterations required to produce an image of a specified image quality as compared to first-order methods. We have proposed and investigated accelerated FISTAs for use with two nonsmooth penalty functions that will lead to further reductions in image reconstruction times while preserving image quality. Moreover, with the help of a mixed sparsity-regularization, better preservation of soft-tissue structures can be potentially obtained. The algorithms were systematically evaluated by use of computer-simulated and clinical data sets.
Multi-GPU implementation of a VMAT treatment plan optimization algorithm
Purpose: Volumetric modulated arc therapy (VMAT) optimization is a computationally challenging problem due to its large data size, high degrees of freedom, and many hardware constraints. High-performance graphics processing units (GPUs) have been used to speed up the computations. However, GPU’s relatively small memory size cannot handle cases with a large dose-deposition coefficient (DDC) matrix in cases of, e.g., those with a large target size, multiple targets, multiple arcs, and/or small beamlet size. The main purpose of this paper is to report an implementation of a column-generation-based VMAT algorithm, previously developed in the authors’ group, on a multi-GPU platform to solve the memory limitation problem. While the column-generation-based VMAT algorithm has been previously developed, the GPU implementation details have not been reported. Hence, another purpose is to present detailed techniques employed for GPU implementation. The authors also would like to utilize this particular problem as an example problem to study the feasibility of using a multi-GPU platform to solve large-scale problems in medical physics. Methods: The column-generation approach generates VMAT apertures sequentially by solving a pricing problem (PP) and a master problem (MP) iteratively. In the authors’ method, the sparse DDC matrix is first stored on a CPU in coordinate list format (COO). On the GPU side, this matrix is split into four submatrices according to beam angles, which are stored on four GPUs in compressed sparse row format. Computation of beamlet price, the first step in PP, is accomplished using multi-GPUs. A fast inter-GPU data transfer scheme is accomplished using peer-to-peer access. The remaining steps of PP and MP problems are implemented on CPU or a single GPU due to their modest problem scale and computational loads. Barzilai and Borwein algorithm with a subspace step scheme is adopted here to solve the MP problem. A head and neck (H and N) cancer case is then used to validate the authors’ method. The authors also compare their multi-GPU implementation with three different single GPU implementation strategies, i.e., truncating DDC matrix (S1), repeatedly transferring DDC matrix between CPU and GPU (S2), and porting computations involving DDC matrix to CPU (S3), in terms of both plan quality and computational efficiency. Two more H and N patient cases and three prostate cases are used to demonstrate the advantages of the authors’ method. Results: The authors’ multi-GPU implementation can finish the optimization process within ∼1 min for the H and N patient case. S1 leads to an inferior plan quality although its total time was 10 s shorter than the multi-GPU implementation due to the reduced matrix size. S2 and S3 yield the same plan quality as the multi-GPU implementation but take ∼4 and ∼6 min, respectively. High computational efficiency was consistently achieved for the other five patient cases tested, with VMAT plans of clinically acceptable quality obtained within 23–46 s. Conversely, to obtain clinically comparable or acceptable plans for all six of these VMAT cases that the authors have tested in this paper, the optimization time needed in a commercial TPS system on CPU was found to be in an order of several minutes. Conclusions: The results demonstrate that the multi-GPU implementation of the authors’ column-generation-based VMAT optimization can handle the large-scale VMAT optimization problem efficiently without sacrificing plan quality. The authors’ study may serve as an example to shed some light on other large-scale medical physics problems that require multi-GPU techniques.
Quantifying Unnecessary Normal Tissue Complication Risks due to Suboptimal Planning: A Secondary Study of RTOG 0126
Purpose: The purpose of this study was to quantify the frequency and clinical severity of quality deficiencies in intensity modulated radiation therapy (IMRT) planning in the Radiation Therapy Oncology Group 0126 protocol. Methods and Materials: A total of 219 IMRT patients from the high-dose arm (79.2 Gy) of RTOG 0126 were analyzed. To quantify plan quality, we used established knowledge-based methods for patient-specific dose-volume histogram (DVH) prediction of organs at risk and a Lyman-Kutcher-Burman (LKB) model for grade ≥2 rectal complications to convert DVHs into normal tissue complication probabilities (NTCPs). The LKB model was validated by fitting dose-response parameters relative to observed toxicities. The 90th percentile (22 of 219) of plans with the lowest excess risk (difference between clinical and model-predicted NTCP) were used to create a model for the presumed best practices in the protocol (pDVH{sub 0126,top10%}). Applying the resultant model to the entire sample enabled comparisons between DVHs that patients could have received to DVHs they actually received. Excess risk quantified the clinical impact of suboptimal planning. Accuracy of pDVH predictions was validated by replanning 30 of 219 patients (13.7%), including equal numbers of presumed “high-quality,” “low-quality,” and randomly sampled plans. NTCP-predicted toxicities were compared to adverse events on protocol. Results: Existing models showed that bladder-sparing variations were less prevalent than rectum quality variations and that increased rectal sparing was not correlated with target metrics (dose received by 98% and 2% of the PTV, respectively). Observed toxicities were consistent with current LKB parameters. Converting DVH and pDVH{sub 0126,top10%} to rectal NTCPs, we observed 94 of 219 patients (42.9%) with ≥5% excess risk, 20 of 219 patients (9.1%) with ≥10% excess risk, and 2 of 219 patients (0.9%) with ≥15% excess risk. Replanning demonstrated the predicted NTCP reductions while maintaining the volume of the PTV receiving prescription dose. An equivalent sample of high-quality plans showed fewer toxicities than low-quality plans, 6 of 73 versus 10 of 73 respectively, although these differences were not significant (P=.21) due to insufficient statistical power in this retrospective study. Conclusions: Plan quality deficiencies in RTOG 0126 exposed patients to substantial excess risk for rectal complications.