Mathematical modeling in understanding NFkB signaling pathway

Chronic diseases, cancers and diabetes are associated with dysregulation of many biochemical cues. These biochemical cues are proteins that regulate cellular activity migration and death. The synthesis of these proteins is regulated by nuclear transcription factors. One of the most studied transcription factor is nuclear factor kappa B (NFkappaB). Many different proteins have been identified that regulate the activity of NFkappaB. Yet, how these proteins regulate NFkappaB is still unclear.;Understanding the regulation of NFkappaB is important for developing drugs to treat these diseases. Our long term goal is to understand the mechanisms that regulate NFkappaB activity. The goal of this research is to identify how NFkappaB activity is regulated. As a model system, we will use LPS to stimulate macrophage cells with or without 3, 4-dichloropropionanilide (DCPA) treatment. DCPA is a post-emergent herbicide used for controlling weeds in rice crops. Exposure to DCPA causes increases in liver and spleen weight demonstrated by toxicity study on rats. Previous study in our lab showed that DCPA could modulate NFkappaB activity. Our central hypothesis is that a mathematical model can be used to infer the regulation steps that are altered following DCPA treatment. To test our central hypothesis, we performed the following specific aim: Establish that NFkappaB is differentially regulated by IkappaBalpha and IkappaBbeta and that these proteins are in turn differentially regulated by DCPA. Moreover, a mathematical model was used to establish observed dynamics of NFkappaB activities. Our working hypothesis is that an ordinary differential equation (ODE)-based model that includes NFkappaB regulation by IkappaBalpha proteins can capture the observed dynamics. Furthermore, we used an empirical Bayesian approach to establish confidence in model parameters. Then, we included IkappaBbeta in the model to more realistically describe the regulation of NFkappaB activity in macrophages.;We expect that the results of this research will lead to greater understanding of the regulatory mechanism of NFkappaB signaling pathway in macrophages and have important implication for human health. This improved understanding may also inspire new ideas to treat these diseases

Activation of the hedgehog pathway in chronic myelogeneous leukemia patients

<p>Abstract</p> <p>Background</p> <p>Hedgehog (Hh) signaling pathway is involved in regulation of many tissues development and oncogenesis. Recently, Hh signaling has been identified as a required functional pathway for leukemia stem cells(LSCs), and loss of this pathway impairs leukemia progression.</p> <p>Objectives</p> <p>The aim of this study was to determine the expression of Hedgehog signaling molecules in Chronic Myelogeneous Leukemia (CML) patients and normal people by semiquantitative polymerase chain reaction (PCR) and to correlate mRNA expression to patients' clinical data.</p> <p>Results</p> <p>Here, we showed that Sonic hedgehog (Shh), Smoothened (Smo), and Gli1 genes of Hh signaling were significantly upregulated in CML patients when compared with normal people (P < 0.001). The levels of Shh, Smo mRNA in chronic phase of CML patients were obviously lower than that in blast crisis (p < 0.05). There were no significant differences of Shh, Ptch1, Smo, Gli1 mRNA expression found when comparing CML patients of chronic phase(CP) with imatinib(IM) treated or not(p > 0.05).</p> <p>Conclusions</p> <p>These findings suggested that activation of the Hh pathway maybe associated with CML progression. Treatment of CML with imatinib, a selective inhibitor of the BCR-ABL tyrosine kinase inhibitor, has no significant influence on the inhibition of Hh pathway of CML-CP patients.</p

Comparison of algorithms for road surface temperature prediction

Purpose - The influence of road surface temperature (RST) on vehicles is becoming more and more obvious. Accurate predication of RST is distinctly meaningful. At present, however, the prediction accuracy of RST is not satisfied with physical methods or statistical learning methods. To find an effective prediction method, this paper selects five representative algorithms to predict the road surface temperature separately. Design/methodology/approach - Multiple linear regressions, least absolute shrinkage and selection operator, random forest and gradient boosting regression tree (GBRT) and neural network are chosen to be representative predictors. Findings - The experimental results show that for temperature data set of this experiment, the prediction effect of GBRT in the ensemble algorithm is the best compared with the other four algorithms. Originality/value - This paper compares different kinds of machine learning algorithms, observes the road surface temperature data from different angles, and finds the most suitable prediction method

Sivelestat sodium attenuates acute lung injury by inhibiting JNK/NF-κB and activating Nrf2/HO-1 signaling pathways

Sivelestat sodium (SIV), a neutrophil elastase inhibitor, is mainly used for the clinical treatment of acute respiratory distress syndrome (ARDS) or acute lung injury (ALI). However, studies investigating the effects of SIV treatment of ALI are limited. Therefore, this study investigated the potential molecular mechanism of the protective effects of SIV against ALI. Human pulmonary microvascular endothelial cells (HPMECs) were stimulated with tumor necrosis factor α (TNF-α), and male Sprague-Dawley rats were intratracheally injected with Klebsiella pneumoniae (KP) and treated with SIV, ML385, and anisomycin (ANI) to mimic the pathogenetic process of ALI in vitro and in vivo, respectively. The levels of inflammatory cytokines and indicators of oxidative stress were assessed in vitro and in vivo. The wet/dry (W/D) ratio of lung tissues, histopathological changes, inflammatory cells levels in bronchoalveolar lavage fluid (BALF), and survival rates of rats were analyzed. The JNK/NF-κB (p65) and Nrf2/HO-1 levels in the HPMECs and lung tissues were analyzed by western blot and immunofluorescence analyses. Administration of SIV reduced the inflammatory factors levels, intracellular reactive oxygen species (ROS) production, and malondialdehyde (MDA) levels and increased the levels of superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px) in lung tissues. Meanwhile, SIV alleviated pathological injuries, decreased the W/D ratio, and inflammatory cell infiltration in lung tissue. In addition, SIV also inhibited the activation of JNK/NF-κB signaling pathway, promoted nuclear translocation of Nrf2, and upregulated the expression of heme oxygenase 1 (HO-1). However, ANI or ML385 significantly reversed these changes. SIV effectively attenuated the inflammatory response and oxidative stress. Its potential molecular mechanism was related to the JNK/NF-κB activation and Nrf2/HO-1 signaling pathway inhibition. This further deepened the understanding of the protective effects of SIV against ALI

Treatment of chronic-phase chronic myeloid leukemia in patients randomized to dasatinib or imatinib after suboptimal responses to three months of imatinib therapy: final 5-year results from DASCERN

Early molecular response (EMR) at 3 months is predictive of improved overall survival (OS) and progression-free survival (PFS) in patients with chronic myeloid leukemia in the chronic phase (CML-CP). Although about one-third of patients treated with first-line imatinib do not achieve EMR, long-term OS and PFS are still observed in most patients. DASCERN (NCT01593254) is a prospective, phase IIb, randomized trial evaluating a switch to dasatinib in patients who have not achieved EMR after 3 months of treatment with first-line imatinib. Early analysis demonstrated an improved major molecular response (MMR) rate at 12 months with dasatinib versus imatinib (29% vs. 13%, P=0.005). Here, we report results from the final 5-year follow-up. In total, 174 patients were randomized to dasatinib and 86 to remain on imatinib. Forty-six (53%) patients who remained on imatinib but subsequently experienced failure were allowed to cross over to dasatinib per protocol. At a minimum follow-up of 60 months, the cumulative MMR rate was significantly higher in patients randomized to dasatinib versus imatinib (77% vs. 44%,

Gossypol Inhibits Non-small Cell Lung Cancer Cells Proliferation by Targeting EGFRL858R/T790M

Background: Overexpression of epidermal growth factor receptor (EGFR) has been reported to be implicated in the pathogenesis of non-small cell lung cancer (NSCLC). Several EGFR inhibitors have been used in clinical treatment of NSCLC, but the emergence of EGFRL858R/T790M resistant mutation has reduced the efficacy of the clinical used EGFR inhibitors. There is an urgent need to develop novel EGFRL858R/T790M inhibitors for better NSCLC treatment.Methods: By screening a natural product library, we have identified gossypol as a novel potent inhibitor targeting EGFRL858R/T790M. The activity of gossypol on NSCLC cells was evaluated by cell proliferation, cell apoptosis and cell migration assays. Kinase activity inhibition assay and molecular docking were used to study the inhibition mechanism of gossypol to EGFRL858R/T790M. Western blotting was performed to study the molecular mechanism of gossypol inhibiting the downstream pathways of EGFR.Results: Gossypol inhibited the cell proliferation and cell migration of NSCLC cells, and induced caspase-dependent cell apoptosis of NSCLC cells by upregulating the expression of pro-apoptotic protein BAD. Molecular docking revealed that gossypol could bind to the kinase domain of EGFRL858R/T790M with good binding affinity through hydrogen bonds and hydrophobic interactions. Gossypol inhibited the kinase activity of EGFRL858R/T790M with EC50 of 150.1 nM. Western blotting analysis demonstrated that gossypol inhibited the phosphorylation of EGFR and its downstream signal pathways in a dose-dependent manner.Conclusion: Gossypol inhibited cell proliferation and induced apoptosis of NSCLC cells by targeting EGFRL858R/T790M. Our findings provided a basis for developing novel EGFRL858R/T790M inhibitors for treatment of NSCLC

Effect of Surface Topography and Structural Parameters on the Lubrication Performance of a Water-Lubricated Bearing: Theoretical and Experimental Study

This study explored the influence of the surface topography of a bushing on the lubrication performance of a water-lubricated bearing. Bushing deformations were considered in the mathematical model. Theoretical calculations and experiments were performed. The test data corresponded well with the simulation. The main stiffness and cross stiffness coefficients were measured and compared with the theoretical values, and the empirical formula of friction coefficient was fitted based on the test data