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At least 739 records · Page 41Linked to original sources
PubMed1992

Evidence for a systemic immune activation during depression: results of leukocyte enumeration by flow cytometry in conjunction with monoclonal antibody staining.

Several studies have reported a suppressed immune function (e.g. blast transformation) during depression. In an attempt to define the cellular basis of the reported immune disorders, the present study investigates the leukocyte cell subset profile of minor, simple major, and melancholic depressives, versus normal controls. We have counted the number of white blood cells (WBC) lymphocytes, monocytes, and granulocytes, while the number of lymphocyte (sub)populations has been identified by phenotype, using monoclonal antibody staining in conjunction with flow cytometry. The following cell surface antigens were determined: CD3+ (pan T), CD19+ (pan B), CD4+ (T helper/inducer), CD8+ (T suppressor/cytotoxic), CD4+CD45RA (T-memory cells), CD4+CD45RA+ (T-virgin cells), surface Ig, class II MHC HLA-DR, and CD25+ (IL-2 receptor). By means of pattern recognition methods, we established distinct immunological changes in minor and simple major depressed and in melancholic patients, setting them apart from the reference population. Depression, per se, is characterized by a higher number of WBC, monocytes, class II MHC HLA-DR, and memory T cells. Minor and simple major depressives exhibited an increased T helper/suppressor ratio. Increased numbers of IL-2 receptor bearing cells are a hallmark for major depression. Melancholics showed an increased number of pan T, pan B and T suppressor/cytotoxic cells. It was concluded that the established immune cell profile of depressed patients may point towards the existence of a systemic immune activation during that illness.

Adjustment Disorders↗
PubMed2001

Prediction of the coupling specificity of G protein coupled receptors to their G proteins.

UNLABELLED: G protein coupled receptors (GPCRs) are found in great numbers in most eukaryotic genomes. They are responsible for sensing a staggering variety of structurally diverse ligands, with their activation resulting in the initiation of a variety of cellular signalling cascades. The physiological response that is observed following receptor activation is governed by the guanine nucleotide-binding proteins (G proteins) to which a particular receptor chooses to couple. Previous investigations have demonstrated that the specificity of the receptor-G protein interaction is governed by the intracellular domains of the receptor. Despite many studies it has proven very difficult to predict de novo, from the receptor sequence alone, the G proteins to which a GPCR is most likely to couple. We have used a data-mining approach, combining pattern discovery with membrane topology prediction, to find patterns of amino acid residues in the intracellular domains of GPCR sequences that are specific for coupling to a particular functional class of G proteins. A prediction system was then built, being based upon these discovered patterns. We can report this approach was successful in the prediction of G protein coupling specificity of unknown sequences. Such predictions should be of great use in providing in silico characterisation of newly cloned receptor sequences and for improving the annotation of GPCRs stored in protein sequence databases. AVAILABILITY: http://www.ebi.ac.uk/~croning/coupling.html.

Amino Acid Sequence↗
PubMed1992

Automated site-directed drug design using molecular lattices.

Receptor-based drug design is predicated on the knowledge of the structure of a target receptor and the principles of molecule recognition. The objective is to produce a wide diversity of structures that are sterically and electrostatically complementary to a specified receptor site. Many drug-receptor interactions are controlled by a few key receptor groups. This observation leads to a design approach in which one focuses on chemical fragments that putatively interact with the key receptor groups. There then remains the difficult task of joining the fragments into molecular structures that match the spatial patterns of recognition forces in the receptor site. In this paper, we describe a new modeling program, BUILDER, that combines database searching techniques and structure generation algorithms within an interactive graphics modeling environment (MidasPlus). A novel tool for process communication (delegate) is introduced and examples of its use are given. To demonstrate the functionality of the package and its ability to produce novel structures, we examine the active site of HIV-1 protease.

Algorithms↗
PubMed2005

Automated derivation and refinement of sequence length patterns for protein sequences using evolutionary computation.

Several stratagems are used in protein bioinformatics for the classification of proteins based on sequence, structure or function. We explore the concept of a minimal signature embedded in a sequence that defines the likely position of a protein in a classification. Specifically, we address the derivation of sparse profiles for the G-protein coupled receptor (GPCR) clan of integral membrane proteins. We present an evolutionary algorithm (EA) for the derivation of sparse profiles (signatures) without the need to supply a multiple alignment. We also apply an evolution strategy (ES) to the problem of pattern and profile refinement. Patterns were derived for the GPCR 'superfamily' and GPCR families 1-3 individually from starting populations of randomly generated signatures, using a database of integral membrane protein sequences and an objective function using a modified receiver operator characteristic (ROC) statistic. The signature derived for the family 1 GPCR sequences was shown to perform very well in a stringent cross-validation test, detecting 76% of unseen GPCR sequences at 5% error. Application of the ES refinement method to a signature developed by a previously described method [Sadowski, M.I., Parish, J.H., 2003. Automated generation and refinement of protein signatures: case study with G-protein coupled receptors. Bioinformatics 19, 727-734] resulted in a 6% increase of coverage for 5% error as measured in the validation test. We note that there might be a limit to this or any classification of proteins based on patterns or schemata.

Algorithms↗
PubMed2005

Superantigen recognition by HLA class II on monocytes up-regulates toll-like receptor 4 and enhances proinflammatory responses to endotoxin.

The devastating systemic effects of bacterial superantigens may be explained by powerful proinflammatory synergy with lipopolysaccharide (LPS). However, the mechanism underlying this phenomenon remains unclear and has never been investigated in humans. Specifically, there is no known link between superantigen-induced immune effects and the pattern recognition of LPS at toll-like receptor 4 (TLR4). Here we show that bacterial superantigens induce rapid transcription and increased membrane expression of TLR4 in primary human monocytes by ligation of major histocompatibility complex (MHC) class II. We also demonstrate that superantigens are solely responsible for monocyte TLR4 up-regulation induced by products from Gram-positive bacteria. In parallel with enhanced TLR4 expression, priming of purified monocytes or mixed peripheral blood mononuclear cells with superantigens significantly enhanced the induction of proinflammatory cytokines by known TLR4 ligands. Staphylococcal enterotoxin A constructs containing targeted mutations were used to demonstrate a requirement for MHC class II ligation in both TLR4 up-regulation and enhanced responses to endotoxin. In contrast to results from animal models, superantigen-endotoxin interaction was not dependent on T-cell receptor ligation by superantigen or interferon gamma production. Pattern recognition of bacterial superantigens by MHC class II receptors may exacerbate the proinflammatory response of monocytes to Gram-negative infection or endotoxin by up-regulation of TLR4.

Cytokines↗
PubMed1995

Increasing doses of l-sulpiride reveal dose- and spatial frequency-dependent effects of D2 selective blockade in the human electroretinogram.

The amplitude and phase of the second harmonic (15 Hz) of the electroretinographic responses to three different spatial frequency grating stimuli (0.25, 1 and 4 c/deg), reversed at 7.5 Hz, were studied i normal human subjects, before and 30 min after the systemic administration of three doses (0.071, 0.357 or 1.428 mg/kg) of a selective D2 blocker, l-sulpiride, to three populations of 18, 19, or 20 subjects. The effect of the drug on the pattern electroretinogram (PERG) was clearly dose-dependent, being greatest on the responses to 4 c/deg. The mean decrease in second harmonic amplitude was -13.8% after 0.071 mg/kg of l-sulpiride, -23.5% after 0.357 mg/kg and -28.5% after 1.428 mg/kg. The last two variations were significant at P < 0.01 and P < 0.01 respectively. These data suggest that a dose-dependent effect on the human retinal response to 4 c/deg stimuli exists, probably mediated by a coupling between l-sulpiride and D2 receptors. Lastly, our data suggest that D2 receptors may play an important role in the pathophysiology of visual dysfunction in Parkinson's disease, that has been described to be more significant at medium spatial frequency (2-5 c/deg).

Adult↗
PubMed1991

Identification of a new motif on nucleic acid sequence data using Kohonen's self-organizing map.

Here we present a performance test of a Kohonen features map applied to the fast extraction of uncommon sequences from the coding region of the human insulin receptor gene. We used a network with 30 neurons and with a variable input window. The program was aimed at detecting unique or uncommon DNA regions present in crude sequence data and was able to automatically detect the signal peptide coding regions of a set of human insulin receptor gene data. The testing of this program with HSIRPR cDNA release (EMBL data bank) indicated the presence of unique features in the signal peptide coding region. On the basis of our results this program can automatically detect 'singularity' from crude sequencing data and it does not require knowledge of the features to be found.

Algorithms↗
PubMed2002

Fungi, dendritic cells and receptors: a host perspective of fungal virulence.

An association between morphogenesis and virulence has long been presumed for dimorphic fungi that are pathogenic to humans, as one morphotype exists in the environment or during commensalism, and another within the host during the disease process. For Candida albicans, putative virulence factors include the ability to switch between saprophytic yeast and pathogenic, filamentous forms of the fungus. Dendritic cells sense either form in a specific way, resulting in distinct, T-helper-cell-dependent protective and non-protective immunities. Recent evidence suggests that the use of distinct recognition receptors contributes to the disparate patterns of reactivity observed locally in response to challenge with C. albicans. These findings offer new interpretive clues to the mechanisms of fungal virulence: rather than dimorphism per se, the engagement of different recognition receptors on dendritic cells might select the mode of fungal internalization and antigen presentation, condition the nature of the T-helper response and, ultimately, favor saprophytism or infection.

Candida albicans↗
PubMed2005

Fast fourier transform-based support vector machine for prediction of G-protein coupled receptor subfamilies.

Although the sequence information on G-protein coupled receptors (GPCRs) continues to grow, many GPCRs remain orphaned (i.e. ligand specificity unknown) or poorly characterized with little structural information available, so an automated and reliable method is badly needed to facilitate the identification of novel receptors. In this study, a method of fast Fourier transform-based support vector machine has been developed for predicting GPCR subfamilies according to protein's hydrophobicity. In classifying Class B, C, D and F subfamilies, the method achieved an overall Matthe's correlation coefficient and accuracy of 0.95 and 93.3%, respectively, when evaluated using the jackknife test. The method achieved an accuracy of 100% on the Class B independent dataset. The results show that this method can classify GPCR subfamilies as well as their functional classification with high accuracy. A web server implementing the prediction is available at http://chem.scu.edu.cn/blast/Pred-GPCR.

Algorithms↗
PubMedDate not supplied

Image processing for the rest of us: the potential utility of inexpensive computerized image analysis in clinical pathology and radiology.

Recent progress in computer technology in both hardware and software, combined with marked cost reductions, have placed quantitatively accurate video densitometry systems within the reach of the individual clinician, biomedical researcher, and community hospital. While much of the attention generated by advances in image processing has focussed on larger scale procedures, such as CAT, chemical shift, and positron emission tomography, important applications can be found for considerably more modest systems. In this article, we discuss three such applications of DUMAS, a personal computer-based imaging system developed by the Image Processing Center at Drexel University. A potential technique for quantifying numbers of estrogen receptors in tumorous breast tissue samples as a predictor of patient responsiveness to hormonal therapy is described first, along with possible sources of error. The second application, also related to clinical pathology and cancer, outlines methods for relating changes in nuclear and cell morphology to the diagnosis of Sezary Cell Syndrome. The utility of binary image filtering methods in the classification of cell types is discussed. The third application involves the development of a semi-automatic procedure for the determination of vessel diameter in arteriograms. A detailed description of the optimization and curve-fitting algorithms is provided along with preliminary test results comparing various approaches. The need for user demand to fuel research and development in small-scale imaging systems is also discussed.

Algorithms↗
PubMed2006

Predicting G-protein coupled receptors-G-protein coupling specificity based on autocross-covariance transform.

Determining G-protein coupled receptors (GPCRs) coupling specificity is very important for further understanding the functions of receptors. A successful method in this area will benefit both basic research and drug discovery practice. Previously published methods rely on the transmembrane topology prediction at training step, even at prediction step. However, the transmembrane topology predicted by even the best algorithm is not of high accuracy. In this study, we developed a new method, autocross-covariance (ACC) transform based support vector machine (SVM), to predict coupling specificity between GPCRs and G-proteins. The primary amino acid sequences are translated into vectors based on the principal physicochemical properties of the amino acids and the data are transformed into a uniform matrix by applying ACC transform. SVMs for nonpromiscuous coupled GPCRs and promiscuous coupled GPCRs were trained and validated by jackknife test and the results thus obtained are very promising. All classifiers were also evaluated by the test datasets with good performance. Besides the high prediction accuracy, the most important feature of this method is that it does not require any transmembrane topology prediction at either training or prediction step but only the primary sequences of proteins. The results indicate that this relatively simple method is applicable. Academic users can freely download the prediction program at http://www.scucic.net/group/database/Service.asp.

Algorithms↗
PubMed2005

Various members of the Toll-like receptor family contribute to the innate immune response of human epidermal keratinocytes.

Toll-like receptors (TLRs) are important pattern recognition molecules that activate the nuclear factor (NF)-kappaB pathway leading to the production of antimicrobial immune mediators. As keratinocytes represent the first barrier against exogenous pathogens in human skin, we investigated their complete functional TLR1-10 expression profile. First, reverse transcription-polymerase chain reaction (PCR) analysis revealed a very similar pattern of TLR mRNA expression when comparing freshly isolated human epidermis and cultured primary human keratinocytes. Thus, further experiments were carried out with primary keratinocytes in comparison with the spontaneously immortalized human keratinocyte cell line HaCaT. The quantitative expression of TLR1-10 mRNA in real-time PCR of primary human keratinocytes and HaCaT cells was analysed. Both cell types constitutively expressed TLR2, TLR3, TLR5, and to a lesser extent TLR10. TLR4 was only found in HaCaT cells, TLR1 to a higher degree in primary keratinocytes. In line with this, LPS induced mRNA expression of CD14 and TLR4 only in HaCaT cells. After stimulation with various TLR ligands, the NF-kappaB-activated chemokine interleukin-8 (IL-8) was measured. In primary keratinocytes and HaCaT cells the TLR3 ligand poly (I:C) was the most potent stimulator of IL-8 secretion. The TLR ligands peptidoglycan, Pam3Cys and flagellin which bind to TLR2, TLR1/TLR2 heterodimer, and TLR5, respectively, also induced IL-8 secretion, whereas no IL-8 was induced by LPS, R-848, loxoribine and cytosine guanine dinucleotide-containing oligodeoxynucleotide. A corresponding pattern was found in the RelA NF-kappaB translocation assay after ligand stimulation of primary keratinocytes. These studies provide substantial evidence for a functional TLR expression and signalling profile of normal human keratinocytes contributing to the antimicrobial defence barrier of human skin.

Biological Transport↗
PubMed1989

Dopamine and memory function in Parkinson's disease.

Response fluctuations in motor function, complicating long-term dopaminomimetic therapy of Parkinson's disease, may extend to the cognitive realm. To evaluate the effect of levodopa treatment both on attention as well as acquisition and retrieval of memory tasks, parkinsonian patients were examined neuropsychologically both while medicated with levodopa/carbidopa ("on") and when the medication's antiparkinsonian effect had worn off ("off"). Significant cognitive differences emerged only on the delayed recall of complex verbal materials, where patients when "on" performed better compared with their "off" state. Comparison of change scores across states (administration or withholding of levodopa/carbidopa between acquisition and retrieval, "off" to "on" or "on" to "off"), revealed no substantial differences as a function of dopaminomimetic therapy. These results support the view that slight changes in cognition are associated with dopaminomimetic therapy of Parkinson's disease, but that these changes may be task-specific.

Aged↗
PubMed1989

Pattern recognition display methods for the analysis of computed molecular properties.

Pattern recognition methods, particularly the 'unsupervised learning' techniques, are well suited for the preliminary analysis of the large data sets produced by computer chemistry. The use of linear and non-linear display methods for such exploratory analysis are exemplified with the aid of two data sets of biologically active molecules. Advantages and disadvantages of these techniques are discussed.

Computer Simulation↗
PubMed2001

Recognition of double-stranded RNA and activation of NF-kappaB by Toll-like receptor 3.

Toll-like receptors (TLRs) are a family of innate immune-recognition receptors that recognize molecular patterns associated with microbial pathogens, and induce antimicrobial immune responses. Double-stranded RNA (dsRNA) is a molecular pattern associated with viral infection, because it is produced by most viruses at some point during their replication. Here we show that mammalian TLR3 recognizes dsRNA, and that activation of the receptor induces the activation of NF-kappaB and the production of type I interferons (IFNs). TLR3-deficient (TLR3-/-) mice showed reduced responses to polyinosine-polycytidylic acid (poly(I:C)), resistance to the lethal effect of poly(I:C) when sensitized with d-galactosamine (d-GalN), and reduced production of inflammatory cytokines. MyD88 is an adaptor protein that is shared by all the known TLRs. When activated by poly(I:C), TLR3 induces cytokine production through a signalling pathway dependent on MyD88. Moreover, poly(I:C) can induce activation of NF-kappaB and mitogen-activated protein (MAP) kinases independently of MyD88, and cause dendritic cells to mature.

Adaptor Proteins, Signal Transducing↗
PubMed2004

Activation and proteasomal degradation of rho GTPases by cytotoxic necrotizing factor-1 elicit a controlled inflammatory response.

The CNF1 toxin is produced by uropathogenic and meningitis-causing Escherichia coli. CNF1 penetrates autonomously into cells and confers phagocytic properties to epithelial and endothelial cells. CNF1 acts at the molecular level by constitutively activating Rho GTPases attenuated by their cellular ubiquitin-mediated proteasomal degradation. Here we report the relationship between the ubiquitin-mediated proteasomal degradation of activated Rho and the endothelial cell response to the toxin. The type of cellular response to CNF1 intoxication, first screened by DNA microarray analysis, revealed the launching of a program oriented toward an inflammatory response. Parallel to Rho protein activation by CNF1, we also established the kinetics of production of monocyte chemotactic protein-1 (MCP-1), interleukin-8 (IL-8), IL-6, monocyte inflammatory protein-3alpha (MIP-3alpha) and E-selectin. Both the mutation of the catalytic domain of the toxin (CNF1-C866S) and the inhibition of Rho proteins abrogate the CNF1-induced production of the immunomodulators MIP-3alpha, MCP-1, and IL-8. These immunomodulators are also produced upon activation of Cdc42 and Rac preferentially. Our results indicate that, in addition to pathogen molecular pattern recognition by host-receptors, a direct activation of Rho proteins by the CNF1 virulence factor efficiently triggers a cellular reaction of host alert. Consistently, we assume that the CNF1-induced ubiquitin-mediated proteasomal degradation of activated Rho proteins may limit the amplitude of the host cell immune responses.

Bacterial Toxins↗
PubMed2005

A hybrid machine-learning approach for segmentation of protein localization data.

MOTIVATION: Subcellular protein localization data are critical to the quantitative understanding of cellular function and regulation. Such data are acquired via observation and quantitative analysis of fluorescently labeled proteins in living cells. Differentiation of labeled protein from cellular artifacts remains an obstacle to accurate quantification. We have developed a novel hybrid machine-learning-based method to differentiate signal from artifact in membrane protein localization data by deriving positional information via surface fitting and combining this with fluorescence-intensity-based data to generate input for a support vector machine. RESULTS: We have employed this classifier to analyze signaling protein localization in T-cell activation. Our classifier displayed increased performance over previously available techniques, exhibiting both flexibility and adaptability: training on heterogeneous data yielded a general classifier with good overall performance; training on more specific data yielded an extremely high-performance specific classifier. We also demonstrate accurate automated learning utilizing additional experimental data.

Animals↗