Biomedical subjects

Kwang-Hyun Cho

Publications and source records attributed to Kwang-Hyun Cho.

At least 19 recordsLinked to original sources

PubMed2006

Serotonin inhibits the induction of NMDA receptor-dependent long-term potentiation in the rat primary visual cortex.

An increase in serotonin [5-hydroxytryptamine (5-HT)] levels in the rat visual cortex is correlated with the developmental decrease in long-term potentiation (LTP), and 5-HT may play an important role in the closure of the critical period by regulating LTP. The effect of 5-HT on the induction of N-methyl-D-aspartate receptor (NMDAR)-dependent and metabotropic glutamate receptor (mGluR)-dependent LTP in visual cortex slices from young rats was investigated. The field potential in layer II/III was recorded by stimulating the underlying layer IV. NMDAR-dependent LTP was induced in slices from 3-week-old rats by theta-burst stimulation (TBS) but not in slices from 5-week-old rats. However, LTP was induced in 5-HT-depleted slices from 5-week-old rats by incubation with para-chloroamphetamine (10 microM, 2 h), a 5-HT-depleting agent. The reinstated LTP in 5-HT-depleted slices was inhibited by the application of D-aminopentanoate, an NMDAR antagonist (50 microM) and 5-HT (10 and 30 microM). In contrast, the induction of mGluR-dependent LTP by weak TBS in disinhibited slices with picrotoxin (1 microM) in the bath was not affected by 5-HT application. The coapplication of 5-HT1A and 5-HT2 receptor agonists inhibited the induction of NMDAR-dependent LTP in 5-HT-depleted slices. 5-HT levels in the visual cortex increased with age. Based on these findings, we conclude that NMDAR-dependent LTP is specifically inhibited by coactivation of 5-HT1A and 5-HT2 receptors with the increase in 5-HT levels in the rat visual cortex at the end of the critical period.

Animals↗

PubMed2006

Wnt pathway mutations selected by optimal beta-catenin signaling for tumorigenesis.

Mutations in components of the Wnt/beta-catenin pathway are observed to be the earliest initiating event for most colorectal tumors. The majority of the mutations occur in the tumor suppressor adenomatous polyposis coli (APC), even though there are other genes that are capable of modulating the pathway activity. Moreover, the specific APC mutations associated in colon cancer indicate the possibility that the tumor selects for certain truncated forms of APC that partially retain its function, namely, inhibition of beta-catenin. We estimated the effects of various mutations in APC and other known mutations using a recent mathematical model of the Wnt pathway that was constructed to represent the conserved core molecular events. We provide evidence that APC mutations are selected not based on the maximal level of beta-catenin but rather based on distinct state of activity that appears to be optimal for the tissue-specific tumorigenesis. This optimal level is determined by balancing beta-catenin signaling and the induction of Axin2 that acts as a potent negative feedback. The predominant pattern of APC mutations may provide synergistic oncogenic effects that promote colorectal tumorigenesis: the optimal signaling for cell survival and renewal, disrupted cell adhesion, chromosomal instability, and altered asymmetric division of stem cells.

Adenomatous Polyposis Coli↗

PubMed2006

Inferring biomolecular regulatory networks from phase portraits of time-series expression profiles.

Reverse engineering of biomolecular regulatory networks such as gene regulatory networks, protein interaction networks, and metabolic networks has received an increasing attention as more high-throughput time-series measurements become available. In spite of various approaches developed from this motivation, it still remains as a challenging subject to develop a new reverse engineering scheme that can effectively uncover the functional interaction structure of a biomolecular network from given time-series expression profiles (TSEPs). We propose a new reverse engineering scheme that makes use of phase portraits constructed by projection of every two TSEPs into respective phase planes. We introduce two measures of a slope index (SI) and a winding index (WI) to quantify the interaction properties embedded in the phase portrait. Based on the SI and WI, we can reconstruct the functional interaction network in a very efficient and systematic way with better inference results compared to previous approaches. By using the SI, we can also estimate the time-lag accompanied with the interaction between molecular components of a network.

Animals↗

PubMed2006

Identification of biochemical networks by S-tree based genetic programming.

MOTIVATION: Most previous approaches to model biochemical networks have focused either on the characterization of a network structure with a number of components or on the estimation of kinetic parameters of a network with a relatively small number of components. For system-level understanding, however, we should examine both the interactions among the components and the dynamic behaviors of the components. A key obstacle to this simultaneous identification of the structure and parameters is the lack of data compared with the relatively large number of parameters to be estimated. Hence, there are many plausible networks for the given data, but most of them are not likely to exist in the real system. RESULTS: We propose a new representation named S-trees for both the structural and dynamical modeling of a biochemical network within a unified scheme. We further present S-tree based genetic programming to identify the structure of a biochemical network and to estimate the corresponding parameter values at the same time. While other evolutionary algorithms require additional techniques for sparse structure identification, our approach can automatically assemble the sparse primitives of a biochemical network in an efficient way. We evaluate our algorithm on the dynamic profiles of an artificial genetic network. In 20 trials for four settings, we obtain the true structure and their relative squared errors are <5% regardless of releasing constraints about structural sparseness. In addition, we confirm that the proposed algorithm is robust within +/-10% noise ratio. Furthermore, the proposed approach ensures a reasonable estimate of a real yeast fermentation pathway. The comparatively less important connections with non-zero parameters can be detected even though their orders are below 10(-2). To demonstrate the usefulness of the proposed algorithm for real experimental biological data, we provide an additional example on the transcriptional network of SOS response to DNA damage in Escherichia coli. We confirm that the proposed algorithm can successfully identify the true structure except only one relation.

Algorithms↗

PubMed2006

Spatial profile of back-propagating action potential-evoked Ca2+ transients in basal dendrites.

Calcium influx in basal dendrites evoked by back-propagating action potentials is important for understanding the input-specific modulation of synaptic transmission. Calcium transients evoked by back-propagating action potentials were measured for the basal dendrites of layer II/III pyramidal neurons in visual cortex slices. In contrast to apical dendrites, the peak calcium transients evoked by a single somatic action potential increased with distance from the soma. The peak calcium transients evoked by bursts of back-propagating action potentials (three or five pulses, 20 Hz) were greater than those evoked by a single back-propagating action potential. These different spatial profiles for calcium transients triggered by back-propagating action potentials between apical and basal dendrites suggest that the segregated inputs from brain areas might be modulated in different ways, according to their synaptic location.

Action Potentials↗

PubMed2006

The influence of the signal dynamics of activated form of IKK on NF-kappaB and anti-apoptotic gene expressions: a systems biology approach.

NF-kappaB activation plays a crucial role in anti-apoptotic responses in response to the apoptotic signaling during tumor necrosis factor (TNF)-alpha stimulation. TNF-alpha induces apoptosis sensitive to the hepatitis B virus (HBV) infected cells, despite sustained NF-kappaB activation. Our results indicate that the HBV infection induces sustained NF-kappaB activation, in a manner similar to the TNF-alpha stimulation. However, these effects are not merely combined. Computational simulations show that the level of form of the IKK complex activated by phosphorylation (IKK-p) affects the dynamic pattern of NF-kappaB activation during TNF-alpha stimulation in the following ways: (i) the initial level of IKK-p determines the incremental change in IKK-p at the same level of TNF-alpha stimulation, (ii) the incremental change in IKK-p determines the amplitudes of active NF-kappaB oscillation, and (iii) the steady state level of IKK-p after the incremental change determines the period of active NF-kappaB oscillation. Based on experiments, we observed that the initial level of IKK-p was upregulated and the active NF-kappaB oscillation showed smaller amplitudes for a shorter period in HepG2.2.15 cells (HBV-producing cells) during TNF-alpha stimulation, as was indicated by the computational simulations. Furthermore, we found that during TNF-alpha stimulation, NF-kappaB-regulated anti-apoptotic genes were upregulated in HepG2 cells but were downregulated in HepG2.2.15 cells. Based on the previously mentioned results, we can conclude that the IKK-p-level changes induced by HBV infection modulate the dynamic pattern of active NF-kappaB and thereby could affect NF-kappaB-regulated anti-apoptotic gene expressions. Finally, we postulate that the sensitive apoptotic response of HBV-infected cells to TNF-alpha stimulation is governed by the dynamic patterns of active NF-kappaB based on IKK-p level changes.

Apoptosis↗

PubMed2006

Bee venom injection significantly reduces nociceptive behavior in the mouse formalin test via capsaicin-insensitive afferents.

UNLABELLED: Peripheral bee venom (BV) administration produces 2 contrasting effects, nociception and antinociception. This study was designed to evaluate whether the initial nociceptive effect induced by BV injection into the Zusanli acupoint is involved in producing the more prolonged antinociceptive effect observed in the mouse formalin test, and whether capsaicin-sensitive primary afferents are involved in these effects. BV injection into the Zusanli point increased spinal Fos expression but not spontaneous nociceptive behavior. BV pretreatment 10 minutes before intraplantar formalin injection dose-dependently attenuated nociceptive behavior associated with the second phase of the formalin test. The destruction of capsaicin-sensitive primary afferents by resiniferatoxin (RTX) pretreatment selectively decreased BV-induced spinal Fos expression but did not affect BV-induced antinociception. Furthermore, BV injection increased Fos expression in tyrosine hydroxylase immunoreactive neurons in the locus caeruleus, and this expression was unaltered by RTX pretreatment. Finally, BV's antinociception was blocked by intrathecal injection of 10 microg idazoxan, and this effect was not modified by RTX pretreatment. These findings suggest that subcutaneous BV stimulation of the Zusanli point activates central catecholaminergic neurons via capsaicin-insensitive afferent fibers without induction of nociceptive behavior. This in turn leads to the activation of spinal alpha2-adrenoceptors, which ultimately reduces formalin-evoked nociceptive behaviors. PERSPECTIVE: This study demonstrates that BV acupuncture produces a significant antinociception without nociceptive behavior in rodents, which is mediated by capsaicin-insensitive afferents and involves activation of central adrenergic circuits. These results further suggest that BV stimulation into this acupuncture point might be a valuable alternative to traditional electrical or mechanical acupoint stimulation.

Acupuncture Analgesia↗

PubMed2005

Distinct sets of genetic alterations in melanoma.

BACKGROUND: Exposure to ultraviolet light is a major causative factor in melanoma, although the relationship between risk and exposure is complex. We hypothesized that the clinical heterogeneity is explained by genetically distinct types of melanoma with different susceptibility to ultraviolet light. METHODS: We compared genome-wide alterations in the number of copies of DNA and mutational status of BRAF and N-RAS in 126 melanomas from four groups in which the degree of exposure to ultraviolet light differs: 30 melanomas from skin with chronic sun-induced damage and 40 melanomas from skin without such damage; 36 melanomas from palms, soles, and subungual (acral) sites; and 20 mucosal melanomas. RESULTS: We found significant differences in the frequencies of regional changes in the number of copies of DNA and mutation frequencies in BRAF among the four groups of melanomas. Samples could be correctly classified into the four groups with 70 percent accuracy on the basis of the changes in the number of copies of genomic DNA. In two-way comparisons, melanomas arising on skin with signs of chronic sun-induced damage and skin without such signs could be correctly classified with 84 percent accuracy. Acral melanoma could be distinguished from mucosal melanoma with 89 percent accuracy. Eighty-one percent of melanomas on skin without chronic sun-induced damage had mutations in BRAF or N-RAS; the majority of melanomas in the other groups had mutations in neither gene. Melanomas with wild-type BRAF or N-RAS frequently had increases in the number of copies of the genes for cyclin-dependent kinase 4 (CDK4) and cyclin D1 (CCND1), downstream components of the RAS-BRAF pathway. CONCLUSIONS: The genetic alterations identified in melanomas at different sites and with different levels of sun exposure indicate that there are distinct genetic pathways in the development of melanoma and implicate CDK4 and CCND1 as independent oncogenes in melanomas without mutations in BRAF or N-RAS.

Adult↗

PubMed2005

A unified framework for unraveling the functional interaction structure of a biomolecular network based on stimulus-response experimental data.

We propose a unified framework for the identification of functional interaction structures of biomolecular networks in a way that leads to a new experimental design procedure. In developing our approach, we have built upon previous work. Thus we begin by pointing out some of the restrictions associated with existing structure identification methods and point out how these restrictions may be eased. In particular, existing methods use specific forms of experimental algebraic equations with which to identify the functional interaction structure of a biomolecular network. In our work, we employ an extended form of these experimental algebraic equations which, while retaining their merits, also overcome some of their disadvantages. Experimental data are required in order to estimate the coefficients of the experimental algebraic equation set associated with the structure identification task. However, experimentalists are rarely provided with guidance on which parameters to perturb, and to what extent, to perturb them. When a model of network dynamics is required then there is also the vexed question of sample rate and sample time selection to be resolved. Supplying some answers to these questions is the main motivation of this paper. The approach is based on stationary and/or temporal data obtained from parameter perturbations, and unifies the previous approaches of Kholodenko et al. (PNAS 99 (2002) 12841-12846) and Sontag et al. (Bioinformatics 20 (2004) 1877-1886). By way of demonstration, we apply our unified approach to a network model which cannot be properly identified by existing methods. Finally, we propose an experiment design methodology, which is not limited by the amount of parameter perturbations, and illustrate its use with an in numero example.

Computational Biology↗

PubMed2005

The dynamic systems approach to control and regulation of intracellular networks.

Systems theory and cell biology have enjoyed a long relationship that has received renewed interest in recent years in the context of systems biology. The term 'systems' in systems biology comes from systems theory or dynamic systems theory: systems biology is defined through the application of systems- and signal-oriented approaches for an understanding of inter- and intra-cellular dynamic processes. The aim of the present text is to review the systems and control perspective of dynamic systems. The biologist's conceptual framework for representing the variables of a biochemical reaction network, and for describing their relationships, are pathway maps. A principal goal of systems biology is to turn these static maps into dynamic models, which can provide insight into the temporal evolution of biochemical reaction networks. Towards this end, we review the case for differential equation models as a 'natural' representation of causal entailment in pathways. Block-diagrams, commonly used in the engineering sciences, are introduced and compared to pathway maps. The stimulus-response representation of a molecular system is a necessary condition for an understanding of dynamic interactions among the components that make up a pathway. Using simple examples, we show how biochemical reactions are modelled in the dynamic systems framework and visualized using block-diagrams.

Animals↗

PubMed2005

Erythrodiol-3-acetate, pentacyclic triterpenoid from Styrax japonica, expressions of matrix metalloproteinase-1,2 in cultured human skin fibroblasts.

Although many studies have been performed to elucidate the molecular consequences of ultraviolet irradiation, little is known about the effect of natural products. Ultraviolet irradiation is widely considered to be an environmental stress. Here we investigated the effect of erythrodiol-3-acetate on the expressions of MMP-1,2 in cultured human skin fibroblasts. Erythrodiol-3-acetate was isolated from the stems of Styrax japonica (Styracaceae). Erythrodiol-3-acetate reduced the expression of MMP-1 but not MMP-2, at the mRNA and protein levels in a dose-dependent manner by ultraviolet irradiation. Taken together, our results suggest that erythrodiol-3-acetate an important role in the reduction of MMP-1 induction by ultraviolet irradiation.

Acetates↗

PubMed2005

Cross-linking of 4-1BB activates TCR-signaling pathways in CD8+ T lymphocytes.

Cross-linking of 4-1BB, a member of the TNFR family, increased tyrosine phosphorylation of TCR-signaling molecules such as CD3epsilon, CD3zeta, Lck, the linker for activation of T cells, and SH2 domain-containing leukocyte phosphoprotein of 76 kDa (SLP-76). In addition, incubation of activated CD8+ T cells with p815 cells expressing 4-1BBL led to redistribution of the lipid raft domains and Lck, protein kinase C-theta;, SLP-76, and phospholipase C-gamma1 (PLC-gamma1) on the T cell membranes to the areas of contact with the p815 cells and recruitment of 4-1BB, TNFR-associated factor 2, and phospho-tyrosine proteins to the raft domains. 4-1BB ligation also caused translocation of TNFR-associated factor 2, protein kinase C-theta;, PLC-gamma1, and SLP-76 to detergent-insoluble compartments in the CD8+ T cells, and cross-linking of 4-1BB increased intracellular Ca2+ levels apparently by activating PLC-gamma1. The redistribution of lipid rafts and Lck, as well as translocation of PLC-gamma1, and degradation of IkappaB-alpha in response to 4-1BB were inhibited by disrupting the formation of lipid rafts with methyl-beta-cyclodextrin. These findings demonstrate that 4-1BB is a T cell costimulatory receptor that activates TCR-signaling pathways in CD8+ T cells.

4-1BB Ligand↗

PubMed2005

In silico identification of the key components and steps in IFN-gamma induced JAK-STAT signaling pathway.

Systems biology efforts are increasingly adopting quantitative, mechanistic modeling to study cellular signal transduction pathways and other networks. However, it is uncertain whether the particular set of kinetic parameter values of the model closely approximates the corresponding biological system. We propose that the parameters be assigned statistical distributions that reflect the degree of uncertainty for a comprehensive simulation analysis. From this analysis, we globally identify the key components and steps in signal transduction networks at a systems level. We investigated a recent mathematical model of interferon gamma induced Janus kinase-signal transducers and activators of transcription (JAK-STAT) signaling pathway by applying multi-parametric sensitivity analysis that is based on simultaneous variation of the parameter values. We find that suppressor of cytokine signaling-1, nuclear phosphatases, cytoplasmic STAT1, and the corresponding reaction steps are sensitive perturbation points of this pathway.

Computational Biology↗

PubMed2005

A hybrid systems framework for cellular processes.

With the availability of technologies that allow us to obtain stimulus-response time series data for modeling and system identification, there is going to be an increasing need for conceptual frameworks in which to formulate and test hypotheses about intra- and inter-cellular dynamics, in general and not just dependent on a particular cell line, cell type, organism, or technology. While the semantics can be quite different, biologists and systems scientists use in many cases a similar language (notion of feedback, regulation, etc.). A more abstract system-theoretic framework for signals, systems, and control could provide the biologist with an interface between the domains. Apart from recent examples to identify functional elements and describing them in engineering terms, there have been various more abstract developments to describe dynamics at the cell level in the past. This includes Rosen's (M,R)-systems. This paper presents an abstract and general compact mathematical framework of intracellular dynamics, regulation and regime switching inspired by (M,R)-theory and based on hybrid automata.

Algorithms↗

PubMed2005

Identification of small scale biochemical networks based on general type system perturbations.

New technologies enable acquisition of large data-sets containing genomic, proteomic and metabolic information that describe the state of a cell. These data-sets call for systematic methods enabling relevant information about the inner workings of the cell to be extracted. One important issue at hand is the understanding of the functional interactions between genes, proteins and metabolites. We here present a method for identifying the dynamic interactions between biochemical components within the cell, in the vicinity of a steady-state. Key features of the proposed method are that it can deal with data obtained under perturbations of any system parameter, not only concentrations of specific components, and that the direct effect of the perturbations does not need to be known. This is important as concentration perturbations are often difficult to perform in biochemical systems and the specific effects of general type perturbations are usually highly uncertain, or unknown. The basis of the method is a linear least-squares estimation, using time-series measurements of concentrations and expression profiles, in which system states and parameter perturbations are estimated simultaneously. An important side-effect of also employing estimation of the parameter perturbations is that knowledge of the system's steady-state concentrations, or activities, is not required and that deviations from steady-state prior to the perturbation can be dealt with. Time derivatives are computed using a zero-order hold discretization, shown to yield significant improvements over the widely used Euler approximation. We also show how network interactions with dynamics that are too fast to be captured within the available sampling time can be determined and excluded from the network identification. Known and unknown moiety conservation relationships can be processed in the same manner. The method requires that the number of samples equals at least the number of network components and, hence, is at present restricted to relatively small-scale networks. We demonstrate herein the performance of the method on two small-scale in silico genetic networks.

Cell Physiological Phenomena↗

PubMed2005

Unravelling the functional interaction structure of a cellular network from temporal slope information of experimental data.

Due to the unavoidable nonbiological variations accompanying many experiments, it is imperative to consider a way of unravelling the functional interaction structure of a cellular network (e.g. signalling cascades or gene networks) by using the qualitative information of time-series experimental data instead of computation through the measured absolute values. In this spirit, we propose a very simple but effective method of identifying the functional interaction structure of a cellular network based on temporal ascending or descending slope information from given time-series measurements. From this method, we can gain insight into the acceptable measurement error ranges in order to estimate the correct functional interaction structure and we can also find guidance for a new experimental design to complement the insufficient information of a given experimental dataset. We developed experimental sign equations, making use of the temporal slope sign information from time-series experimental data, without a specific assumption on parameter perturbations for each network node. Based on these equations, we further describe the available specific information from each part of experimental data in detail and show the functional interaction structure obtained by integrating such information. In this procedure, we use only simple algebra on sign changes without complicated computations on the measured absolute values of the experimental data. The result is, however, verified through rigorous mathematical definitions and proofs. The present method provides us with information about the acceptable measurement error ranges for correct estimation of the functional interaction structure and it further leads to a new experimental design to complement the given experimental data by informing us about additional specific sampling points to be chosen for further required information.

Cell Physiological Phenomena↗

PubMed2004

Alteration of the TGF-beta/SMAD pathway in intrinsically and UV-induced skin aging.

In an effort to characterize transforming growth factor (TGF-beta) signaling and to determine its association with the aging and photoaging processes, we directly compared the expressions of TGF-beta/SMAD in intrinsically aged and photoaged human skin in vivo. By using an RNase protection assay and by immunohistochemistry, we found that the expression levels of TbetaRII mRNA and protein in the epidermis of the forearm (sun-exposed) of the elderly were significantly lower than that of the upper-inner arm (sun-protected) skin of the same individual. In the epidermis, the expressions of Smad7 mRNA in both the intrinsically aged and photoaged skin of the elderly were higher than in the sun-protected skin of the young, and this was elevated in the photoaged epidermis. Decreased pSmad2 immunoreactivity was observed in the epidermis of photoaged forearm skin versus matched intrinsically aged skin. This decrease was also found in the epidermis of upper-inner arm skin of the elderly versus the young. These results suggest that the UV-induced down-regulation of TbetaRII and the concerted over-expression of Smad7 may trigger the inhibition of the TGF-beta-induced phosphorylation of Smad2.

Adult↗

PubMed2004

The effects of epidermal keratinocytes and dermal fibroblasts on the formation of cutaneous basement membrane in three-dimensional culture systems.

The cutaneous basement membrane (BM) plays an important role in normal and pathological conditions. However, few studies have addressed the formation of the cutaneous BM using three-dimensional culture systems. In this study, to elucidate the effects of human epidermal keratinocytes and dermal fibroblasts on the formation of the cutaneous BM, keratinocytes were cultured on several dermal substrates in the presence or absence of fibroblasts at the air-liquid interface. After 2 weeks of culture, immunohistochemical stainings for the components of the BM and electron microscopic studies of the BM zone (BMZ) were performed. In cultures of keratinocytes alone on dead reticular dermis or collagen gel without fibroblasts, beta4 integrin chain, laminin, type IV and VII collagens were all expressed. However, ultrastructurally, BMZ was not formed. In cultures of keratinocytes on fibroblast-populated collagen matrix, laminin, and type IV and VII collagens were expressed more strongly than in the absence of fibroblasts. In addition, elements of the BMZ such as hemidesmosomes, lamina lucida, lamina densa and anchoring fibrils were formed, although it was still incomplete. In the culture of keratinocytes alone on de-epidermized dermis (DED) (surface up), beta4 integrin chain, laminin, and type IV and VII collagens were strongly expressed. Also, the BMZ appeared similar to that in normal skin. In cocultures of keratinocytes and fibroblasts on DED or cultures of keratinocytes on DED combined with fibroblast-populated collagen matrix, type IV collagen was expressed more strongly than in cultures of keratinocytes alone. Ultrastructurally, similar findings to those of cultures of keratinocytes alone on DED were seen. Interestingly, when keratinocytes and fibroblasts were cocultured on DED, some fibroblasts were seen in the upper dermis as a result of migration into the dermis through partial loss of the lamina densa. These results show that keratinocytes produce most of the components of the BM such as laminin, and type IV and VII collagens. In addition, fibroblasts stimulate the expression of the components of the BM and the formation of a BMZ, suggesting that fibroblasts may produce laminin, and type IV and VII collagens or influence the effects of keratinocytes on the formation of the BM through a keratinocyte-fibroblast interaction.

Basement Membrane↗