Physiological Environment Induces Quick Response – Slow Exhaustion Reactions

In vivo environments are highly crowded and inhomogeneous, which may affect reaction processes in cells. In this study we examined the effects of intracellular crowding and an inhomogeneity on the behavior of in vivo reactions by calculating the spectral dimension (ds), which can be translated into the reaction rate function. We compared estimates of anomaly parameters obtained from fluorescence correlation spectroscopy (FCS) data with fractal dimensions derived from transmission electron microscopy (TEM) image analysis. FCS analysis indicated that the anomalous property was linked to physiological structure. Subsequent TEM analysis provided an in vivo illustration; soluble molecules likely percolate between intracellular clusters, which are constructed in a self-organizing manner. We estimated a cytoplasmic spectral dimension ds to be 1.39 ± 0.084. This result suggests that in vivo reactions initially run faster than the same reactions in a homogeneous space; this conclusion is consistent with the anomalous character indicated by FCS analysis. We further showed that these results were compatible with our Monte-Carlo simulation in which the anomalous behavior of mobile molecules correlates with the intracellular environment, leading to description as a percolation cluster, as demonstrated using TEM analysis. We confirmed by the simulation that the above-mentioned in vivo like properties are different from those of homogeneously concentrated environments. Additionally, simulation results indicated that crowding level of an environment might affect diffusion rate of reactant. Such knowledge of the spatial information enables us to construct realistic models for in vivo diffusion and reaction systems

The stem cell factor/c-kit receptor pathway enhances proliferation and invasion of pancreatic cancer cells

BACKGROUND: The transmembrane protein c-kit is a receptor tyrosine kinase (KIT) and KIT is expressed in solid tumors and hematological malignancies such as gastrointestinal stromal tumor (GIST), small-cell lung cancer and chronic myelogenous leukemia (CML). KIT plays a critical role in cell proliferation and differentiation and represents a logical therapeutic target in GIST and CML. In pancreatic cancer, c-kit expression has been observed by immunohistochemical techniques. In this study, we examined the influence of c-kit expression on proliferation and invasion using five pancreatic cancer cell lines. In addition, the inhibitory effect of imatinib mesylate on stem cell factor (SCF)-induced proliferation and invasion was evaluated. Finally, we also analyzed KIT and SCF expression in pancreatic cancer tissues using immunohistochemistry and correlated the results with clinical features. RESULTS: RT-PCR revealed that two pancreatic cancer cell lines, PANC-1 and SW1990, expressed c-kit mRNA. By Western blot analysis, c-kit protein was also present in those lines. In KIT-positive pancreatic cancer cell lines, proliferation and invasion were significantly enhanced by addition of SCF. In contrast, SCF did not enhance proliferation and invasion in the three KIT-negative lines (BxPC-3, Capan-2 and MIA PaCa-2). 5 μM imatinib mesylate significantly inhibited SCF-enhanced proliferation to the same extent compared with the control. Similarly, SCF-enhanced invasive ability was significantly inhibited by 5 μM imatinib mesylate. KIT was expressed in 16 of 42 clinical specimens by immunohistochemistry, and KIT expression was significantly related to venous system invasion. Furthermore, patients expressing both KIT and SCF had a somewhat lower survival. CONCLUSION: Our results demonstrated that the SCF-KIT pathway enhanced the proliferation and invasiveness in KIT-positive pancreatic cancer cell lines and that the enhanced proliferation and invasion were inhibited by imatinib mesylate. We propose that inhibitors of c-kit tyrosine kinase receptor have the potential to slow the progression of KIT-positive pancreatic cancers

Successful paclitaxel-based chemotherapy for an alpha-fetoprotein-producing gastric cancer patient with multiple liver metastases

<p>Abstract</p> <p>Background</p> <p>Alpha-fetoprotein (AFP)-producing gastric cancer is known to frequently cause multiple liver metastases and to have an extremely poor prognosis.</p> <p>Case presentation</p> <p>A 64-year-old Japanese man admitted to our hospital was diagnosed with gastric cancer with liver metastases. He underwent a total gastrectomy with splenectomy, and pathological stage IV disease according to the classification proposed by the Japanese Gastric Cancer Association was assigned. The histological diagnosis was poorly differentiated adenocarcinoma, and tumor production of AFP was confirmed by immunohistochemical staining. Following surgery, the patient received combination chemotherapy consisting of TS-1 and paclitaxel. Initially, AFP levels decreased dramatically and computed tomography (CT) revealed regression of liver metastases. However, multiple new liver metastases appeared and serum AFP levels increased after 5 months. A regimen of 5-FU plus paclitaxel followed by paclitaxel monotherapy was used next. Serum AFP levels once again decreased and CT showed regression or disappearance of liver metastases. The patient currently has a very good quality of life, and is receiving weekly paclitaxel monotherapy as an outpatient. No progression of liver metastases has been observed to date.</p> <p>Conclusion</p> <p>We consider this rare case to have significant value with respect to treatment of AFP-producing gastric cancer with multiple liver metastases, and propose that combining surgery with chemotherapeutic agents such as paclitaxel may lead to a better prognosis in such cases.</p

Granulocyte-colony stimulating factor producing rectal cancer

This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens

From microscopy data to in silico environments for in vivo-oriented simulations

In our previous study, we introduced a combination methodology of Fluorescence Correlation Spectroscopy (FCS) and Transmission Electron Microscopy (TEM), which is powerful to investigate the effect of intracellular environment to biochemical reaction processes. Now, we developed a reconstruction method of realistic simulation spaces based on our TEM images. Interactive raytracing visualization of this space allows the perception of the overall 3D structure, which is not directly accessible from 2D TEM images. Simulation results show that the diffusion in such generated structures strongly depends on image post-processing. Frayed structures corresponding to noisy images hinder the diffusion much stronger than smooth surfaces from denoised images. This means that the correct identification of noise or structure is significant to reconstruct appropriate reaction environment in silico in order to estimate realistic behaviors of reactants in vivo. Static structures lead to anomalous diffusion due to the partial confinement. In contrast, mobile crowding agents do not lead to anomalous diffusion at moderate crowding levels. By varying the mobility of these non-reactive obstacles (NRO), we estimated the relationship between NRO diffusion coefficient (Dnro) and the anomaly in the tracer diffusion (α). For Dnro=21.96 to 44.49 μ m2/s, the simulation results match the anomaly obtained from FCS measurements. This range of the diffusion coefficient from simulations is compatible with the range of the diffusion coefficient of structural proteins in the cytoplasm. In addition, we investigated the relationship between the radius of NRO and anomalous diffusion coefficient of tracers by the comparison between different simulations. The radius of NRO has to be 58 nm when the polymer moves with the same diffusion speed as a reactant, which is close to the radius of functional protein complexes in a cell.ISSN:1687-4145ISSN:1687-415

An FPGA-Based, Multi-model Simulation Method for Biochemical Systems

Modeling and simulation of a cellular system on computers are now becoming an essential process in biological researches. However, modern PCs can\u27t provide enough performance to simulate large-scale biochemical networks. ReCSiP is the alternative FPGA-based solution for biochemical simulations. In this paper, the novel method of biochemical simulation with multiple reaction models on an FPGA is proposed. The method generates optimal circuit and its optimal schedule for each simulation models written in SBML, the standard markup language in systems biology. ReCSiP has a Xilinx\u27s XC2VP70 and achieved over 20-fold speedup compared to Intel’s PentiumIII 1.13GHz.19th IEEE International Parallel and Distributed Processing Symposium (IPDPS\u2705), April 4-8, 2005, Denver, Colorad

Pipeline scheduling with input port constraints for an FPGA-based biochemical simulator

This paper discusses design methodology of high-throughput arithmetic pipeline modules for an FPGA-based biochemical simulator. Since limitation of data-input bandwidth caused by port constraints often has a negative impact on pipeline scheduling results, we propose a priority assignment method of input data which enables efficient arithmetic pipeline scheduling under given input port constraints. Evaluation results with frequently used rate-law functions in biochemical models revealed that the proposed method achieved shorter latency compared to ASAP and ALAP scheduling with random input orders, reducing hardware costs by 17.57% and by 27.43% on average, respectively.The original publication is available at www.springerlink.co

The systems biology simulation core algorithm

Background: With the increasing availability of high dimensional time course data for metabolites, genes, and fluxes, the mathematical description of dynamical systems has become an essential aspect of research in systems biology. Models are often encoded in formats such as SBML, whose structure is very complex and difficult to evaluate due to many special cases. Results: This article describes an efficient algorithm to solve SBML models that are interpreted in terms of ordinary differential equations. We begin our consideration with a formal representation of the mathematical form of the models and explain all parts of the algorithm in detail, including several preprocessing steps. We provide a flexible reference implementation as part of the Systems Biology Simulation Core Library, a community-driven project providing a large collection of numerical solvers and a sophisticated interface hierarchy for the definition of custom differential equation systems. To demonstrate the capabilities of the new algorithm, it has been tested with the entire SBML Test Suite and all models of BioModels Database. Conclusions: The formal description of the mathematics behind the SBML format facilitates the implementation of the algorithm within specifically tailored programs. The reference implementation can be used as a simulation backend for Java™-based programs. Source code, binaries, and documentation can be freely obtained under the terms of the LGPL version 3 from http://simulation-core.sourceforge.net. Feature requests, bug reports, contributions, or any further discussion can be directed to the mailing list [email protected]