Interpreting cerebrospinal fluid pleocytosis in HIV in the era of potent antiretroviral therapy

Background: Cerebrospinal fluid (CSF) pleocytosis may be seen in asymptomatic HIV-infected individuals. This finding complicates interpretation of CSF abnormalities when such individuals are evaluated for other central nervous system infections. The goal of this study was to determine the relationship between CSF pleocytosis, central nervous system (CNS) antiretroviral penetration, adherence to antiretroviral medication regimens, neurological symptoms and performance on neuropsychological tests. Methods: Clinically stable HIV-infected individuals at any peripheral blood CD4+ T cell count or any plasma viral load were asked to attend study visits at entry and every 6 months thereafter for at least one year. At each visit, they underwent a standardized neurological and medication history; neurological examination; a brief neuropsychological test battery: venipuncture; lumbar puncture; and assessment of medication adherence. Generalized estimating equations (GEE) were used to assess the relationships between CSF pleocytosis and other variables. Results: CSF pleocytosis was independently and significantly related to lack of current antiretroviral use (OR 5.9, 95% CI 1.8-18.6, p = 0.003), CD4 count >200/ul (OR 23.4, 95% CI 3.1-177.3, p = 0.002) and detectable plasma HIV RNA (OR 3.3, 95% CI 1.1-9.4, p = 0.03). At visits where antiretrovirals were used, and taking into account detectable plasma HIV RNA, an antiretroviral regimen that contained two or more agents with good CNS penetration conferred a trend toward lower odds of CSF pleocytosis (OR 0.45, 95% CI 0.18-1.12, p = 0.087). Conclusion: CSF pleocytosis is a characteristic of HIV disease that varies significantly with easily identifiable clinical and laboratory features. Use of antiretroviral agents decreases the odds of pleocytosis. This association may be stronger when the regimen contains two or more agents with good CNS penetration.This work was supported by National Institutes of Health grant U54 NS 39406 (AI and CMM)

Neutrophil elastase reduces secretion of secretory leukoproteinase inhibitor (SLPI) by lung epithelial cells: role of charge of the proteinase-inhibitor complex

<p>Abstract</p> <p>Background</p> <p>Secretory leukoproteinase inhibitor (SLPI) is an important inhibitor of neutrophil elastase (NE), a proteinase implicated in the pathogenesis of lung diseases such as COPD. SLPI also has antimicrobial and anti-inflammatory properties, but the concentration of SLPI in lung secretions in COPD varies inversely with infection and the concentration of NE. A fall in SLPI concentration is also seen in culture supernatants of respiratory cells exposed to NE, for unknown reasons. We investigated the hypothesis that SLPI complexed with NE associates with cell membranes <it>in vitro</it>.</p> <p>Methods</p> <p>Respiratory epithelial cells were cultured in the presence of SLPI, varying doses of proteinases over time, and in different experimental conditions. The likely predicted charge of the complex between SLPI and proteinases was assessed by theoretical molecular modelling.</p> <p>Results</p> <p>We observed a rapid, linear decrease in SLPI concentration in culture supernatants with increasing concentration of NE and cathepsin G, but not with other serine proteinases. The effect of NE was inhibited fully by a synthetic NE inhibitor only when added at the same time as NE. Direct contact between NE and SLPI was required for a fall in SLPI concentration. Passive binding to cell culture plate materials was able to remove a substantial amount of SLPI both with and without NE. Theoretical molecular modelling of the structure of SLPI in complex with various proteinases showed a greater positive charge for the complex with NE and cathepsin G than for other proteinases, such as trypsin and mast cell tryptase, that also bind SLPI but without reducing its concentration.</p> <p>Conclusion</p> <p>These data suggest that NE-mediated decrease in SLPI is a passive, charge-dependent phenomenon <it>in vitro</it>, which may correlate with changes observed <it>in vivo</it>.</p

Kinome-wide interaction modelling using alignment-based and alignment-independent approaches for kinase description and linear and non-linear data analysis techniques

<p>Abstract</p> <p>Background</p> <p>Protein kinases play crucial roles in cell growth, differentiation, and apoptosis. Abnormal function of protein kinases can lead to many serious diseases, such as cancer. Kinase inhibitors have potential for treatment of these diseases. However, current inhibitors interact with a broad variety of kinases and interfere with multiple vital cellular processes, which causes toxic effects. Bioinformatics approaches that can predict inhibitor-kinase interactions from the chemical properties of the inhibitors and the kinase macromolecules might aid in design of more selective therapeutic agents, that show better efficacy and lower toxicity.</p> <p>Results</p> <p>We applied proteochemometric modelling to correlate the properties of 317 wild-type and mutated kinases and 38 inhibitors (12,046 inhibitor-kinase combinations) to the respective combination's interaction dissociation constant (K_d). We compared six approaches for description of protein kinases and several linear and non-linear correlation methods. The best performing models encoded kinase sequences with amino acid physico-chemical z-scale descriptors and used support vector machines or partial least- squares projections to latent structures for the correlations. Modelling performance was estimated by double cross-validation. The best models showed high predictive ability; the squared correlation coefficient for new kinase-inhibitor pairs ranging P²= 0.67-0.73; for new kinases it ranged P²_kin= 0.65-0.70. Models could also separate interacting from non-interacting inhibitor-kinase pairs with high sensitivity and specificity; the areas under the ROC curves ranging AUC = 0.92-0.93. We also investigated the relationship between the number of protein kinases in the dataset and the modelling results. Using only 10% of all data still a valid model was obtained with P²= 0.47, P²_kin= 0.42 and AUC = 0.83.</p> <p>Conclusions</p> <p>Our results strongly support the applicability of proteochemometrics for kinome-wide interaction modelling. Proteochemometrics might be used to speed-up identification and optimization of protein kinase targeted and multi-targeted inhibitors.</p

Computational approaches for modeling human intestinal absorption and permeability

Human intestinal absorption (HIA) is an important roadblock in the formulation of new drug substances. Computational models are needed for the rapid estimation of this property. The measurements are determined via in vivo experiments or in vitro permeability studies. We present several computational models that are able to predict the absorption of drugs by the human intestine and the permeability through human Caco-2 cells. The training and prediction sets were derived from literature sources and carefully examined to eliminate compounds that are actively transported. We compare our results to models derived by other methods and find that the statistical quality is similar. We believe that models derived from both sources of experimental data would provide greater consistency in predictions. The performance of several QSPR models that we investigated to predict outside the training set for either experimental property clearly indicates that caution should be exercised while applying any of the models for quantitative predictions. However, we are able to show that the qualitative predictions can be obtained with close to a 70% success rate

HIV-1 Tat Co-Operates with IFN-γ and TNF-α to Increase CXCL10 in Human Astrocytes

HIV-associated neurological disorders (HAND) are estimated to affect 60% of the HIV infected population. HIV-encephalitis (HIVE), the pathological correlate of the most severe form of HAND is often characterized by glial activation, cytokine/chemokine dysregulation, and neuronal damage and loss. However, the severity of HIVE correlates better with glial activation rather than viral load. One of the characteristic features of HIVE is the increased amount of the neurotoxic chemokine, CXCL10. This chemokine can be released from astroglia activated with the pro-inflammatory cytokines IFN-γ and TNF-α, in conjunction with HIV-1 Tat, all of which are elevated in HIVE. In an effort to understand the pathogenesis of HAND, this study was aimed at exploring the regulation of CXCL10 by cellular and viral factors during astrocyte activation. Specifically, the data herein demonstrate that the combined actions of HIV-1 Tat and the pro-inflammatory cytokines, IFN-γ and TNF-α, result in the induction of CXCL10 at both the RNA and protein level. Furthermore, CXCL10 induction was found to be regulated transcriptionally by the activation of the p38, Jnk, and Akt signaling pathways and their downstream transcription factors, NF-κB and STAT-1α. Since CXCL10 levels are linked to disease severity, understanding its regulation could aid in the development of therapeutic intervention strategies for HAND

Cognitive Neuropsychology of HIV-Associated Neurocognitive Disorders

Advances in the treatment of the human immunodeficiency virus (HIV) have dramatically improved survival rates over the past 10 years, but HIV-associated neurocognitive disorders (HAND) remain highly prevalent and continue to represent a significant public health problem. This review provides an update on the nature, extent, and diagnosis of HAND. Particular emphasis is placed on critically evaluating research within the realm of cognitive neuropsychology that aims to elucidate the component processes of HAND across the domains of executive functions, motor skills, speeded information processing, episodic memory, attention/working memory, language, and visuoperception. In addition to clarifying the cognitive mechanisms of HAND (e.g., impaired cognitive control), the cognitive neuropsychology approach may enhance the ecological validity of neuroAIDS research and inform the development of much needed novel, targeted cognitive and behavioral therapies