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PubMed1998

Description and analysis of switchlike regulatory networks exemplified by a model of cellular iron homeostasis.

The post-transcriptional regulation of factors involved in the maintenance of cellular iron homeostasis is exerted by iron regulatory proteins (IRPs), which bind to mRNA structures known as iron regulatory elements (IREs). The IRP-IRE interactions are regulated by the intracellular iron level by affecting the binding affinity, synthesis and stability of the IRPs. A model of this homeostasis phenomenon is described and analysed within a methodological framework specifically designed for handling complex systems with steep sigmoidal input/output relationships between the state variables. According to the analysis there is only one threshold regulated homeostatic point. Approximate values for its coordinates, and the conditions ensuring its existence, may be given in terms of parameters. The analysis also provides some tentative insight into the evolution of the regulatory system. A comparison between analytical and numerical estimates of the position of the stationary point as a function of the steepness of the sigmoidal interactions show that the analytical approximations agree quite well with the numerical ones. The results show that we are able to obtain a deeper analytical insight by this methodological framework than what is achievable by most alternative approaches. We find this type of insight to be of considerable heuristic value in connection with the numerical simulation work which normally must be done to unfold the predictive potential of a complex model.

Animals↗
PubMedDate not supplied

Analyze of hospital computer networks.

Methods for the analysis of hospital computer networks have been developed without the need for a large-scale computer simulation of the queueing events in the problem. A table-driven methodology and a simple computer program are provided for an analysis of the computer utilization and channel utilization for a network of computers supporting hospital tasks. An example, using a DEC 11/780 VAX and six DEC 11/44's is given. The example network is also analyzed by large-scale computer simulation techniques, and the results are compared.

Computers↗
PubMed2004

Global analysis of the regulatory network structure of gene expression in Saccharomyces cerevisiae.

Gene expression in eukaryotic cells is controlled by the concerted action of various transcription factors. To help clarify these complex mechanisms, we attempted to develop a method for extracting maximal information regarding the transcriptional control pathways. To this end, we first analyzed the expression profiles of numerous transcription factors in yeast cells, under the assumption that the expression levels of these factors would be elevated under conditions in which the factors were active in the cells. Based on the results, we successfully categorized about 400 transcription factors into three groups based on their expression profiles. We then analyzed the effect of the loss of function of various induced transcription factors on the global expression profile to investigate the above-mentioned assumption of a correlation between transcription elevation and functional activity. By comparing the expression profiles of wild-type with those of disruption mutants using microarrays, we were able to detect a substantial number of relations between transcription factors and the genes they regulate. The results of these experiments suggested that our approach is useful for understanding the global transcriptional networks of eukaryotic cells, in which most genes are regulated in a temporal and conditional manner.

DNA-Binding Proteins↗
PubMed2006

Transcriptional coordination of the metabolic network in Arabidopsis.

Patterns of coexpression can reveal networks of functionally related genes and provide deeper understanding of processes requiring multiple gene products. We performed an analysis of coexpression networks for 1,330 genes from the AraCyc database of metabolic pathways in Arabidopsis (Arabidopsis thaliana). We found that genes associated with the same metabolic pathway are, on average, more highly coexpressed than genes from different pathways. Positively coexpressed genes within the same pathway tend to cluster close together in the pathway structure, while negatively correlated genes typically occupy more distant positions. The distribution of coexpression links per gene is highly skewed, with a small but significant number of genes having numerous coexpression partners but most having fewer than 10. Genes with multiple connections (hubs) tend to be single-copy genes, while genes with multiple paralogs are coexpressed with fewer genes, on average, than single-copy genes, suggesting that the network expands through gene duplication, followed by weakening of coexpression links involving duplicate nodes. Using a network-analysis algorithm based on coexpression with multiple pathway members (pathway-level coexpression), we identified and prioritized novel candidate pathway members, regulators, and cross pathway transcriptional control points for over 140 metabolic pathways. To facilitate exploration and analysis of the results, we provide a Web site (http://www.transvar.org/at_coexpress/analysis/web) listing analyzed pathways with links to regression and pathway-level coexpression results. These methods and results will aid in the prioritization of candidates for genetic analysis of metabolism in plants and contribute to the improvement of functional annotation of the Arabidopsis genome.

Arabidopsis↗
PubMed2005

Targeted disruption of glycerol kinase gene in mice: expression analysis in liver shows alterations in network partners related to glycerol kinase activity.

Glycerol kinase deficiency (GKD) is an X-linked inborn error of metabolism with metabolic and neurological crises. Liver shows the highest level of glycerol kinase (GK) activity in humans and mice. Absence of genotype-phenotype correlations in patients with GKD indicates the involvement of modifier genes, including other network partners. To understand the molecular pathogenesis of GKD, we performed microarray analysis on liver mRNA from neonatal glycerol kinase (Gyk) knockout (KO) and wild-type (WT) mice. Unsupervised learning revealed that the overall gene expression profile of the KO mice was different from that of WT. Real-time PCR confirmed the differences for selected genes. Functional gene enrichment analysis was used to find 56 increased and 37 decreased gene functional categories. PathwayAssist analysis identified changes in gene expression levels of genes involved in organic acid metabolism indicating that GK was part of the same metabolic network which correlates well with the patients with GKD having metabolic acidemia during their episodic crises. Network component analysis (NCA) showed that transcription factors sterol regulatory element-binding protein (SREBP)-1c, carbohydrate response element-binding protein (ChREBP), hepatocyte nuclear factor-4 alpha (HNF-4alpha) and peroxisome proliferative-activated receptor-alpha (PPARalpha) had increased activity in the Gyk KO mice compared with WT mice, whereas SREBP-2 was less active in the Gyk KO mice. These studies show that Gyk deletion causes alterations in expression of genes in several regulatory networks and is the first time NCA has been used to expand on microarray data from a mouse KO model of a human disease.

Animals↗
PubMed2004

Knowledge representation model for systems-level analysis of signal transduction networks.

A Petri-net based model for knowledge representation has been developed to describe as explicitly and formally as possible the molecular mechanisms of cell signaling and their pathological implications. A conceptual framework has been established for reconstructing and analyzing signal transduction networks on the basis of the formal representation. Such a conceptual framework renders it possible to qualitatively understand the cell signaling behavior at systems-level. The mechanisms of the complex signaling network are explored by applying the established framework to the signal transduction induced by potent proinflammatory cytokines, IL-1beta and TNF-alpha The corresponding expert-knowledge network is constructed to evaluate its mechanisms in detail. This strategy should be useful in drug target discovery and its validation.

Computer Graphics↗
PubMed2006

Expression profiling and mutant analysis reveals complex regulatory networks involved in Arabidopsis response to Botrytis infection.

The expression profiles of Botrytis-inoculated Arabidopsis plants were studied to determine the nature of the defense transcriptome and to identify genes involved in host responses to the pathogen. Normally resistant Arabidopsis wild-type plants were compared with coi1, ein2, and nahG plants that are defective in various defense responses and/or show increased susceptibility to Botrytis. In wild-type plants, the expression of 621 genes representing approximately 0.48% of the Arabidopsis transcriptome was induced greater than or equal to twofold after infection. Of these 621 Botrytis-induced genes (BIGs), 462 were induced at or before 36 h post-inoculation, and may be involved in resistance to the pathogen. The expression of 181 BIGs was dependent on a functional COI1 gene required for jasmonate signaling, whereas the expression of 63 and 80 BIGs were dependent on ethylene (ET) signaling or salicylic acid accumulation, respectively, based on results from ein2 and nahG plants. BIGs encode diverse regulatory and structural proteins implicated in pathogen defense and abiotic and oxidative-stress responses. Thirty BIGs encode putative DNA-binding proteins that belong to ET response, zinc-finger, MYB, WRKY, and HD-ZIP family transcription-factor proteins. Fourteen BIGs were studied in detail to determine their role in resistance to Botrytis. T-DNA insertion alleles of ZFAR1 (At2G40140), the gene encoding a putative zinc-finger protein with ankyrin-repeat domains, showed increased local susceptibility to Botrytis and sensitivity to germination in the presence of abscisic acid (ABA), supporting the role of ABA in mediating responses to Botrytis infection. In addition, two independent T-DNA insertion alleles in the WRKY70 gene showed increased susceptibility to Botrytis. The transcriptional activation of genes involved in plant hormone signaling and synthesis, removal of reactive oxygen species, and defense and abiotic-stress responses, coupled with the susceptibility of the wrky70 and zfar1 mutants, highlights the complex genetic network underlying defense responses to Botrytis in Arabidopsis.

Ankyrin Repeat↗
PubMed2004

Solid-phase microextraction, gas chromatography, and mass spectrometry coupled with discriminant factor analysis and multilayer perceptron neural network for detection of Escherichia coli.

This study was performed to investigate the ability of using discriminant factor analysis (DFA) and an artificial neural network (ANN) to identify and quantify the number of Escherichia coli (ATCC 25922) in nutrient media from data generated by analysis of E. coli volatile metabolic compounds using solid-phase microextraction (SPME) coupled with gas chromatography (GC) and mass spectrometry (MS). E. coli was grown in super broth and incubated at 37 degrees C for 2 to 12 h. Numbers of E. coli were followed using a colony counting method. An SPME device was used to collect the volatiles from the headspace above the samples, and the volatiles were identified using GC-MS. DFA was used to classify the samples from different incubation times. From DFA, it was possible to differentiate super broth from media containing E. coli when cell numbers were 10(5) CFU or more. The potential to predict the number of E. coli from the SPME-GC-MS data was investigated using a multilayer perceptron (MLP) neural network with back propagation training. The MLP comprised an input layer, one hidden layer, and an output layer, with a hyperbolic tangent sigmoidal transfer function in the hidden layer and a linear transfer function in the output layer. Good prediction was found as measured by a regression coefficient (R2 = 0.996) between actual and predicted data.

Colony Count, Microbial↗
PubMed1985

A cost-benefit analysis of the Quebec Network of Genetic Medicine.

Certain serious diseases, including several major genetic disorders, cannot be treated effectively unless they are detected before symptoms appear. In such cases, only systematic population screening can ensure that the necessary preventive treatment can be administered to affected individuals. The question of whether to establish such screening programs, which may be relatively costly, is a pressing problem for many public administrations. This study of the costs and benefits of the Quebec Network of Genetic Medicine has as its main objective the development of an analytical framework which can be generally applied to such problems. In this article, we attempt to evaluate the profitability of the Network to society. For the evaluation of the less tangible costs and benefits, we adopted the minimum profitability principle, which essentially involves establishing a lower bound on the value of the profitability of the Network. The net benefits assessed by this study, although certainly underestimated, are still very significant. Since the Network is administered by a team of researchers, the study also throws some light on the links existing between research and development activities on the one hand and public services on the other, and hence on the general question of the socioeconomic profitability of biomedical research.

Biomedical Research↗
PubMed2025

Investigating the molecular mechanism of Yangxin decoction in treating major depressive disorder using network pharmacology and molecular docking technology approaches.

Yangxin decoction has been used to treat major depressive disorder (MDD). This study aims to identify the active components and potential mechanisms of Yangxin decoction in treating MDD using network pharmacology and molecular docking technology. The active components and targets of Yangxin decoction were screened, and MDD-related targets were predicted. Networks of "herbal medicine-active components-potential targets" and protein-protein interaction were constructed. Core components and core targets were identified through network topology analysis. Gene ontology functional and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed on candidate genes. Molecular docking was conducted using AutoDock software (Olson Laboratory of the Scripps Research Institute, San Diego) to explore the interactions between core targets and active components, and the results were visualized using PyMOL (DeLano Scientific LLC, South San Francisco). A total of 433 active components and 392 targets of Yangxin decoction were identified, along with 11,796 MDD-related targets. There were 680 overlapping targets between Yangxin decoction and MDD, associated with 104 active components. Core targets identified through network topology analysis and molecular docking included serine/threonine kinase 1 (AKT1), tumor necrosis factor, interleukin-6, tumor protein P53, and proto-oncogene tyrosine-protein kinase Src. Gene ontology enrichment analysis revealed 1606 biological processes, 191 cellular components, and 373 molecular functions. Kyoto Encyclopedia of Genes and Genomes pathway analysis identified 212 signaling pathways, with significant enrichment in caffeine metabolism, bladder cancer, advanced glycation end products-receptor for advanced glycation end products signaling pathway in diabetic complications, and vascular endothelial growth factor signaling pathway. Molecular docking results showed strong binding energy between core active components and core targets. Yangxin decoction exhibits multi-component, multi-pathway, and multi-target therapeutic characteristics. It primarily regulates targets such as AKT1, tumor necrosis factor, interleukin-6, tumor protein P53, and proto-oncogene tyrosine-protein kinase Src through advanced glycation end products-receptor for advanced glycation end products, vascular endothelial growth factor, and ErbB signaling pathways, exerting anti-inflammatory, immune-regulating, and oxidative stress-inhibiting effects to alleviate MDD.

Molecular Docking Simulation↗
PubMed2026

Active components and potential mechanisms of Wuzhuyu decoction in the treatment of ethanol-induced acute gastric mucosal injury: a network pharmacology and experimental verification.

OBJECTIVE: To investigate the underlying mechanisms and active components of Wuzhuyu decoction (, WD) in alleviating ethanol-induced acute gastric mucosal injury (GMI) using an integrated approach of network pharmacology and experimental verification. METHODS: Sprague-Dawley rats were randomly divided into six groups: control (Con), model (Mod), bismuth potassium citrate (BPC), WD at low (WD-L), medium (WD-M), and high (WD-H) doses. Following seven days of continuous intragastric administration of the respective treatments, an ethanol-induced gastric mucosal injury model was established in all groups except the control group by oral gavage of anhydrous ethanol. The gastric mucosal injury index was evaluated, and pathological changes were assessed viahematoxylin and eosin (HE) staining. Levels of tumor necrosis factor-alpha (TNF-α), interleukin-1 beta (IL-1β), malondialdehyde (MDA), superoxide dismutase (SOD), and glutathione peroxidase (GSH-Px) were measured by enzyme-linked immunosorbent assay (ELISA). The chemical composition was identified by ultra-performance liquid chromatography-tandem mass spectrometry. Active compounds were screened using the Swiss-absorption, distribution, metabolism, and excretion database, and their potential targets were predicted using the Swiss Target Prediction database and bioinformatics annotation database for molecular mechanism. Simultaneously, disease targets related to GMI were retrieved from the online mendelian inheritance in man and GeneCards databases. A protein-protein interaction (PPI) network was constructed, and functional enrichment analyses of gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) enrichment analyses were performed using the Metascape database. Key predictions from the network pharmacology analysis were subsequently verified through animal experiments. Protein expression levels of B-cell lymphoma-2 (Bcl-2), Bcl-2-associated X protein (Bax), Cleaved Caspase-3, and Cleaved Caspase-9 were analyzed by Western blot. Finally, molecular docking was performed using AutoDock Vina to investigate the interactions between the active components and core targets. RESULTS: WD treatment significantly reduced the gastric mucosal injury index and the levels of TNF-α, IL-1β, MDA, while it increased the activities of SOD and GSH-Px. Histopathological examination revealed marked improvement in gastric tissue morphology. A total of 145 compounds were identified in WD. Network pharmacology analysis identified 440 overlapping targets between WD and GMI. GO and KEGG enrichment analyses highlighted the apoptosis signaling pathway as a key mechanism for WD's protective effect against ethanol-induced GMI. Experimental validation demonstrated that WD treatment reduced the apoptosis of gastric mucosal epithelial cells, promoted the expression of Bcl-2, and inhibited the expression of Bax, Cleaved Caspase-3 and Cleaved Caspase-9. Molecular docking results indicated that dehydroevodiamine, rutaecarpine, evodiamine, hexahydrocurcumin, and isorhamnetin are potential active components in WD that contribute to the inhibition of apoptosis. CONCLUSIONS: WD alleviates ethanol-induced acute GMI, at least in part, by inhibiting the apoptosis. The primary active components responsible for this effect are dehydroevodiamine, rutaecarpine, evodiamine, hexahydrocurcumin, and isorhamnetin.

Drugs, Chinese Herbal↗
PubMed1999

Determining the geographic origin of potatoes with trace metal analysis using statistical and neural network classifiers.

The objective of this research was to develop a method to confirm the geographical authenticity of Idaho-labeled potatoes as Idaho-grown potatoes. Elemental analysis (K, Mg, Ca, Sr, Ba, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, Mo, S, Cd, Pb, and P) of potato samples was performed using ICPAES. Six hundred eight potato samples were collected from known geographic growing sites in the U.S. and Canada. An exhaustive computational evaluation of the 608 x 18 data sets was carried out using statistical (PCA, CDA, discriminant function analysis, and k-nearest neighbors) and neural network techniques. The neural network classification of the samples into two geographic regions (defined as Idaho and non-Idaho) using a bagging technique had the highest percentage of correct classifications, with a nearly 100% degree of accuracy. We report the development of a method combining elemental analysis and neural network classification that may be widely applied to the determination of the geographical origin of unprocessed, fresh commodities.

Analysis of Variance↗
PubMed2004

ARTSTREAM: a neural network model of auditory scene analysis and source segregation.

Multiple sound sources often contain harmonics that overlap and may be degraded by environmental noise. The auditory system is capable of teasing apart these sources into distinct mental objects, or streams. Such an 'auditory scene analysis' enables the brain to solve the cocktail party problem. A neural network model of auditory scene analysis, called the ARTSTREAM model, is presented to propose how the brain accomplishes this feat. The model clarifies how the frequency components that correspond to a given acoustic source may be coherently grouped together into a distinct stream based on pitch and spatial location cues. The model also clarifies how multiple streams may be distinguished and separated by the brain. Streams are formed as spectral-pitch resonances that emerge through feedback interactions between frequency-specific spectral representations of a sound source and its pitch. First, the model transforms a sound into a spatial pattern of frequency-specific activation across a spectral stream layer. The sound has multiple parallel representations at this layer. A sound's spectral representation activates a bottom-up filter that is sensitive to the harmonics of the sound's pitch. This filter activates a pitch category which, in turn, activates a top-down expectation that is also sensitive to the harmonics of the pitch. Resonance develops when the spectral and pitch representations mutually reinforce one another. Resonance provides the coherence that allows one voice or instrument to be tracked through a noisy multiple source environment. Spectral components are suppressed if they do not match harmonics of the top-down expectation that is read-out by the selected pitch, thereby allowing another stream to capture these components, as in the 'old-plus-new heuristic' of Bregman. Multiple simultaneously occurring spectral-pitch resonances can hereby emerge. These resonance and matching mechanisms are specialized versions of Adaptive Resonance Theory, or ART, which clarifies how pitch representations can self-organize during learning of harmonic bottom-up filters and top-down expectations. The model also clarifies how spatial location cues can help to disambiguate two sources with similar spectral cues. Data are simulated from psychophysical grouping experiments, such as how a tone sweeping upwards in frequency creates a bounce percept by grouping with a downward sweeping tone due to proximity in frequency, even if noise replaces the tones at their intersection point. Illusory auditory percepts are also simulated, such as the auditory continuity illusion of a tone continuing through a noise burst even if the tone is not present during the noise, and the scale illusion of Deutsch whereby downward and upward scales presented alternately to the two ears are regrouped based on frequency proximity, leading to a bounce percept. Since related sorts of resonances have been used to quantitatively simulate psychophysical data about speech perception, the model strengthens the hypothesis that ART-like mechanisms are used at multiple levels of the auditory system. Proposals for developing the model to explain more complex streaming data are also provided.

Acoustic Stimulation↗
PubMed1999

The proteolytic procaspase activation network: an in vitro analysis.

In general, apoptotic stimuli lead to activation of caspases. Once activated, a caspase can induce intracellular signaling pathways involving proteolytic activation of other caspase family members. We report the in vitro processing of eight murine procaspases by their enzymatically active counterparts. Caspase-8 processed all procaspases examined. Caspase-1 and -11 processed the effector caspases procaspase-3 and -7, and to a lesser extent procaspase-6. However, vice versa, none of the caspase-1-like procaspases was activated by the effector caspases. This suggests that the caspase-1 subfamily members either act upstream of the apoptosis effector caspases or else are part of a totally separate activation pathway. Procaspase-2 was maturated by caspase-8 and -3, and to a lesser extent by caspase-7, while the active caspase-2 did not process any of the procaspases examined, except its own precursor. Hence, caspase-2 might not be able to initiate a wide proteolytic signaling cascade. Additionally, cleavage data reveal not only proteolytic amplification between caspase-3 and -8, caspase-6 and -3, and caspase-6 and -7, but also positive feedback loops involving multiple activated caspases. Our results suggest the existence of a hierarchic proteolytic procaspase activation network, which would lead to a dramatic increase in multiple caspase activities once key caspases are activated. The proteolytic procaspase activation network might allow that different apoptotic stimuli result in specific cleavage of substrates responsible for typical processes at the cell membrane, the cytosol, the organelles, and the nucleus, which characterize a cell dying by apoptosis.

Animals↗
PubMed1998

Neural network classifications and correlation analysis of EEG and MEG activity accompanying spontaneous reversals of the Necker cube.

It has recently been suggested that reentrant connections are essential in systems that process complex information [A. Damasio, H. Damasio, Cortical systems for the retrieval of concrete knowledge: the convergence zone framework, in: C. Koch, J.L. Davis (Eds.), Large Scale Neuronal Theories of the Brain, The MIT Press, Cambridge, 1995, pp. 61-74; G. Edelman, The Remembered Present, Basic Books, New York, 1989; M.I. Posner, M. Rothbart, Constructing neuronal theories of mind, in: C. Koch, J.L. Davis (Eds.), Large Scale Neuronal Theories of the Brain, The MIT Press, Cambridge, 1995, pp. 183-199; C. von der Malsburg, W. Schneider, A neuronal cocktail party processor, Biol. Cybem., 54 (1986) 29-40]. Reentry is not feedback, but parallel signalling in the time domain between spatially distributed maps, similar to a process of correlation between distributed systems. Accordingly, it was expected that during spontaneous reversals of the Necker cube, complex patterns of correlations between distributed systems would be present in the cortex. The present study included EEG (n=4) and MEG recordings (n=5). Two experimental questions were posed: (1) Can distributed cortical patterns present during perceptual reversals be classified differently using a generalised regression neural network (GRNN) compared to processing of a two-dimensional figure? (2) Does correlated cortical activity increase significantly during perception of a Necker cube reversal? One-second duration single trials of EEG and MEG data were analysed using the GRNN. Electrode/sensor pairings based on cortico-cortical connections were selected to assess correlated activity in each condition. The GRNN significantly classified single trials recorded during Necker cube reversals as different from single trials recorded during perception of a two-dimensional figure for both EEG and MEG. In addition, correlated cortical activity increased significantly in the Necker cube reversal condition for EEG and MEG compared to the perception of a non-reversing stimulus. Coherent MEG activity observed over occipital, parietal and temporal regions is believed to represent neural systems related to the perception of Necker cube reversals.

Adolescent↗
PubMed2005

Bayesian sparse hidden components analysis for transcription regulation networks.

MOTIVATION: In systems like Escherichia Coli, the abundance of sequence information, gene expression array studies and small scale experiments allows one to reconstruct the regulatory network and to quantify the effects of transcription factors on gene expression. However, this goal can only be achieved if all information sources are used in concert. RESULTS: Our method integrates literature information, DNA sequences and expression arrays. A set of relevant transcription factors is defined on the basis of literature. Sequence data are used to identify potential target genes and the results are used to define a prior distribution on the topology of the regulatory network. A Bayesian hidden component model for the expression array data allows us to identify which of the potential binding sites are actually used by the regulatory proteins in the studied cell conditions, the strength of their control, and their activation profile in a series of experiments. We apply our methodology to 35 expression studies in E.Coli with convincing results. AVAILABILITY: www.genetics.ucla.edu/labs/sabatti/software.html SUPPLEMENTARY INFORMATION: The supplementary material are available at Bioinformatics online.

Algorithms↗
PubMed2000

The influence of conventional and cross-reactive group HLA matching on cardiac transplant outcome: an analysis from the United Network of Organ Sharing Scientific Registry.

BACKGROUND: The short tolerable cold ischemia time and the importance of other risk factors have generally superseded the role of HLA matching in the allocation of donor hearts. Recent advances in the accuracy and time required to perform HLA typing and crossmatching, however, have led us to re-examine the United Network of Organ Sharing Transplant Registry for the effects of the HLA incompatibility on outcome in relation to other possible risk factors. METHODS: These include conventional HLA-A, -B, and cross-reactive group (CREG) mismatching (mm), HLA-DR mm, pretransplantation panel-reactive antibody (PRA), recipient and donor race and donor age, cold ischemia time, and the pretransplantation use of either a left ventricular assist device or an intra-aortic balloon pump. RESULTS: Three-year survival was clearly inferior in non-white (0.6921) as compared with white (0.7632) recipients, but this difference could not be accounted for by the degree of donor-recipient HLA mm that had occurred by chance. Nevertheless, the degree of mm that did occur seemed to have an impact on survival. The importance of HLA-DR mm was confirmed, and it ranked only behind the use of an assist device and recipient race in the multivariate analysis. HLA-A and B mm exerted an additional effect, but this was only true in white recipients. Of these, HLA-A achieved statistical significance as an independent risk factor. In general, CREG mm was not a significant variable. However, more than twice as many 0-1 or 0-2 CREG, 0 DR mm as compared with 0-1 or 0-2 A,B, 0 DR mm transplants enjoyed approximately equal and very good 1- and 3-year survival. Assuming no change is cold ischemia time, the potential number of 0 CREG, 0 DR mm, ABO-compatible transplants that could be achieved when an Organ Procurement Organization had 50-100 patients on their waiting list was calculated. The surprisingly high frequency of approximately 24-36% suggests that this favorable match could be considered along with other important factors in the local allocation process. When pretransplantation PRA was analyzed as a continuous variable from 0 to 100%, it was a highly significant risk factor, but this effect was more strikingly evident when the PRA was analyzed in 20% increments above zero. Recently, left ventricular assist device usage has become increasingly common, and it has been associated with strikingly increased pretransplantation PRA levels. When they occur together, the data indicates that these patients are at a very high risk for graft failure. CONCLUSIONS: We believe that newer typing and crossmatching techniques make it possible to add HLA criteria to the allocation protocol of donor cardiac organs and would lead to improved long-term survival.

Chi-Square Distribution↗
PubMed2004

Analysis of the inflammatory network in benign prostate hyperplasia and prostate cancer.

INTRODUCTION: The complexity of acute and chronic inflammatory processes may either lead to benign prostate hyperplasia (BPH) and/or prostate cancer. Obviously, various tissue cells are activated by chemokines via different chemotaxin receptors which then trigger subsequent processes in angiogenesis, cellular growth, and extravasation as well as neoplasia. METHODS: Using the surgically obtained tissue of patients (n = 36) with BPH or prostate carcinoma (PCA), we studied among others the expression of chemokines (Rantes, IL-8), chemotaxin receptors (CXCR-3 and -4, CCR-3, CCR-5), of matrixmetalloproteinases (MMP-2 and 9), of Toll-like (TL) receptors 1, 2, 3, 4, 5, 7, and 9 and of the inducible cyclooxygenase-2 (cox-2) by RT-PCR. Further support for the different properties of tissue from PCA was obtained using two different PCA cell lines (PC3 = androgen resistant cell) or LNCAP cells (androgen sensitive) with emphasis on IL-8, Il-6, and PGE(2) release. Cell lines were stimulated with either the tumor necrosis factor-alpha (TNF-alpha) and lipopolysacharide (LPS) over time. In addition to cytokine release, the quantification of mRNA by lightcycler for cox-2, IL-6, and IL-8 was performed on these cell lines. RESULTS: Remarkable differences in expression were obtained by RT-PCR when BPH tissue versus PCA was analyzed. Expression of CXCR-1 after incubation with LPS and TNF-alpha showed time-dependent differences for androgen-sensitive LNCAP as compared to androgen-resistant PC-3 cells. TNF-alpha incubation leads to a time-dependent induction of cox-2 expression unlike to activation with LPS. Differences with regard to cox-2, IL-6, and IL-8 expression were seen by quantitative lightcycler analysis. Significant differences were also observed when TL receptors 4, 5, 7, and 9 were analyzed which were significantly expressed in BPH- as compared to PCA-tissue. CONCLUSIONS: Our data clearly demonstrate that various inflammatory and cell biological cascades are involved which either lead to BPH or can be linked to the development of PCA. The exact cell biological mechanisms may provide novel therapeutic options in the treatment of both diseases.

Acute Disease↗