Prediction of free imatinib concentrations based on total plasma concentrations in patients with gastrointestinal stromal tumours.

AIM: Total imatinib concentrations are currently measured for the therapeutic drug monitoring of imatinib, whereas only free drug equilibrates with cells for pharmacological action. Due to technical and cost limitations, routine measurement of free concentrations is generally not performed. In this study, free and total imatinib concentrations were measured to establish a model allowing the confident prediction of imatinib free concentrations based on total concentrations and plasma proteins measurements. METHODS: One hundred and fifty total and free plasma concentrations of imatinib were measured in 49 patients with gastrointestinal stromal tumours. A population pharmacokinetic model was built up to characterize mean total and free concentrations with inter-patient and intrapatient variability, while taking into account α1 -acid glycoprotein (AGP) and human serum albumin (HSA) concentrations, in addition to other demographic and environmental covariates. RESULTS: A one compartment model with first order absorption was used to characterize total and free imatinib concentrations. Only AGP influenced imatinib total clearance. Imatinib free concentrations were best predicted using a non-linear binding model to AGP, with a dissociation constant Kd of 319 ng ml(-1) , assuming a 1:1 molar binding ratio. The addition of HSA in the equation did not improve the prediction of imatinib unbound concentrations. CONCLUSION: Although free concentration monitoring is probably more appropriate than total concentrations, it requires an additional ultrafiltration step and sensitive analytical technology, not always available in clinical laboratories. The model proposed might represent a convenient approach to estimate imatinib free concentrations. However, therapeutic ranges for free imatinib concentrations remain to be established before it enters into routine practice.

Improving the prediction of the functional impact of cancer mutations by baseline tolerance transformation

High-throughput prioritization of cancer-causing mutations (drivers) is a key challenge of cancer genome projects, due to the number of somatic variants detected in tumors. One important step in this task is to assess the functional impact of tumor somatic mutations. A number of computational methods have been employed for that purpose, although most were originally developed to distinguish disease-related nonsynonymous single nucleotide variants (nsSNVs) from polymorphisms. Our new method, transformed Functional Impact score for Cancer (transFIC), improves the assessment of the functional impact of tumor nsSNVs by taking into account the baseline tolerance of genes to functional variants.

Prediction of cross-recognition of peptide-HLA A2 by Melan-A-specific cytotoxic T lymphocytes using three-dimensional quantitative structure-activity relationships.

The cross-recognition of peptides by cytotoxic T lymphocytes is a key element in immunology and in particular in peptide based immunotherapy. Here we develop three-dimensional (3D) quantitative structure-activity relationships (QSARs) to predict cross-recognition by Melan-A-specific cytotoxic T lymphocytes of peptides bound to HLA A*0201 (hereafter referred to as HLA A2). First, we predict the structure of a set of self- and pathogen-derived peptides bound to HLA A2 using a previously developed ab initio structure prediction approach [Fagerberg et al., J. Mol. Biol., 521-46 (2006)]. Second, shape and electrostatic energy calculations are performed on a 3D grid to produce similarity matrices which are combined with a genetic neural network method [So et al., J. Med. Chem., 4347-59 (1997)] to generate 3D-QSAR models. The models are extensively validated using several different approaches. During the model generation, the leave-one-out cross-validated correlation coefficient (q (2)) is used as the fitness criterion and all obtained models are evaluated based on their q (2) values. Moreover, the best model obtained for a partitioned data set is evaluated by its correlation coefficient (r = 0.92 for the external test set). The physical relevance of all models is tested using a functional dependence analysis and the robustness of the models obtained for the entire data set is confirmed using y-randomization. Finally, the validated models are tested for their utility in the setting of rational peptide design: their ability to discriminate between peptides that only contain side chain substitutions in a single secondary anchor position is evaluated. In addition, the predicted cross-recognition of the mono-substituted peptides is confirmed experimentally in chromium-release assays. These results underline the utility of 3D-QSARs in peptide mimetic design and suggest that the properties of the unbound epitope are sufficient to capture most of the information to determine the cross-recognition.

Histones from dying renal cells aggravate kidney injury via TLR2 and TLR4.

In AKI, dying renal cells release intracellular molecules that stimulate immune cells to secrete proinflammatory cytokines, which trigger leukocyte recruitment and renal inflammation. Whether the release of histones, specifically, from dying cells contributes to the inflammation of AKI is unknown. In this study, we found that dying tubular epithelial cells released histones into the extracellular space, which directly interacted with Toll-like receptor (TLR)-2 (TLR2) and TLR4 to induce MyD88, NF-κB, and mitogen activated protein kinase signaling. Extracellular histones also had directly toxic effects on renal endothelial cells and tubular epithelial cells in vitro. In addition, direct injection of histones into the renal arteries of mice demonstrated that histones induce leukocyte recruitment, microvascular vascular leakage, renal inflammation, and structural features of AKI in a TLR2/TLR4-dependent manner. Antihistone IgG, which neutralizes the immunostimulatory effects of histones, suppressed intrarenal inflammation, neutrophil infiltration, and tubular cell necrosis and improved excretory renal function. In summary, the release of histones from dying cells aggravates AKI via both its direct toxicity to renal cells and its proinflammatory effects. Because the induction of proinflammatory cytokines in dendritic cells requires TLR2 and TLR4, these results support the concept that renal damage triggers an innate immune response, which contributes to the pathogenesis of AKI.

Calibration of Highway Safety Manual Work Zone Crash Modification Factors, TPF-5(081), 2014

The Highway Safety Manual is the national safety manual that provides quantitative methods for analyzing highway safety. The HSM presents crash modification factors related to work zone characteristics such as work zone duration and length. These crash modification factors were based on high-impact work zones in California. Therefore there was a need to use work zone and safety data from the Midwest to calibrate these crash modification factors for use in the Midwest. Almost 11,000 Missouri freeway work zones were analyzed to derive a representative and stratified sample of 162 work zones. The 162 work zones was more than four times the number of work zones used in the HSM. This dataset was used for modeling and testing crash modification factors applicable to the Midwest. The dataset contained work zones ranging from 0.76 mile to 9.24 miles and with durations from 16 days to 590 days. A combined fatal/injury/non-injury model produced a R2 fit of 0.9079 and a prediction slope of 0.963. The resulting crash modification factors of 1.01 for duration and 0.58 for length were smaller than the values in the HSM. Two practical application examples illustrate the use of the crash modification factors for comparing alternate work zone setups.

Inhibition of inducible nitric oxide synthase protects against liver injury induced by mycobacterial infection and endotoxins.

BACKGROUND/AIMS: Bacillus Calmette Guerin (BCG) infection causes hepatic injury following granuloma formation and secretion of cytokines which render mice highly sensitive to endotoxin-mediated hepatotoxicity. This work investigates the role of inducible nitric oxide synthase (iNOS) in liver damage induced by BCG and endotoxins in BCG-infected mice. METHODS: Liver injury and cytokine activation induced by BCG and by LPS upon BCG infection (BCG/LPS) were compared in wild-type and iNOS-/- mice. RESULTS: iNOS-/- mice infected with living BCG are protected from hepatic injury when compared to wild-type mice which express iNOS protein in macrophages forming hepatic granulomas. In addition, iNOS-/- mice show a decrease in BCG-induced IFN-gamma serum levels. LPS challenge in BCG-infected mice strongly activates iNOS in the liver and spleen of wild-type mice which show important liver damage associated with a dramatic increase in TNF and IL-6 and also Th1 type cytokines. In contrast, iNOS-/- mice are protected from liver injury after BCG/LPS challenge and their TNF, IL-6 and Th1 type cytokine serum levels raise moderately. CONCLUSIONS: These results demonstrate that nitric oxide (NO) from iNOS is involved in hepatotoxicity induced by both mycobacterial infection and endotoxin effects upon BCG infection and that inhibition of NO from iNOS protects from liver injuries.

Gene Ontology Function prediction in Mollicutes using Protein-Protein Association Networks

Abstract Background: Many complex systems can be represented and analysed as networks. The recent availability of large-scale datasets, has made it possible to elucidate some of the organisational principles and rules that govern their function, robustness and evolution. However, one of the main limitations in using protein-protein interactions for function prediction is the availability of interaction data, especially for Mollicutes. If we could harness predicted interactions, such as those from a Protein-Protein Association Networks (PPAN), combining several protein-protein network function-inference methods with semantic similarity calculations, the use of protein-protein interactions for functional inference in this species would become more potentially useful. Results: In this work we show that using PPAN data combined with other approximations, such as functional module detection, orthology exploitation methods and Gene Ontology (GO)-based information measures helps to predict protein function in Mycoplasma genitalium. Conclusions: To our knowledge, the proposed method is the first that combines functional module detection among species, exploiting an orthology procedure and using information theory-based GO semantic similarity in PPAN of the Mycoplasma species. The results of an evaluation show a higher recall than previously reported methods that focused on only one organism network.

Early EEG correlates of neuronal injury after brain anoxia.

OBJECTIVES: EEG and serum neuron-specific enolase (NSE) are used for outcome prognostication in patients with postanoxic coma; however, it is unclear if EEG abnormalities reflect transient neuronal dysfunction or neuronal death. To assess this question, EEG abnormalities were correlated with NSE. Moreover, NSE cutoff values and hypothermic EEG features related with poor outcome were explored.¦METHODS: In a prospective cohort of 61 adults treated with therapeutic hypothermia (TH) after cardiac arrest (CA), multichannel EEG recorded during TH was assessed for background reactivity and continuity, presence of epileptiform transients, and correlated with serum NSE collected at 24-48 hours after CA. Demographic, clinical, and functional outcome data (at 3 months) were collected and integrated in the analyses.¦RESULTS: In-hospital mortality was 41%, and 82% of survivors had good neurologic outcome at 3 months. Serum NSE and EEG findings were strongly correlated (Spearman rho = 0.45; p < 0.001). Median NSE peak values were higher in patients with unreactive EEG background (p < 0.001) and discontinuous patterns (p = 0.001). While all subjects with nonreactive EEG died, 5 survivors (3 with good outcome) had NSE levels >33 μg/L.¦CONCLUSION: The correlation between EEG during TH and serum NSE levels supports the hypothesis that early EEG alterations reflect permanent neuronal damage. Furthermore, this study confirms that absent EEG background reactivity and presence of epileptiform transients are robust predictors of poor outcome after CA, and that survival with good neurologic recovery is possible despite serum NSE levels> 33 μg/L. This underscores the importance of multimodal assessments in this setting.

Symptomatic intracranial hemorrhage after stroke thrombolysis: comparison of prediction scores.

BACKGROUND AND PURPOSE: Several prognostic scores have been developed to predict the risk of symptomatic intracranial hemorrhage (sICH) after ischemic stroke thrombolysis. We compared the performance of these scores in a multicenter cohort. METHODS: We merged prospectively collected data of patients with consecutive ischemic stroke who received intravenous thrombolysis in 7 stroke centers. We identified and evaluated 6 scores that can provide an estimate of the risk of sICH in hyperacute settings: MSS (Multicenter Stroke Survey); HAT (Hemorrhage After Thrombolysis); SEDAN (blood sugar, early infarct signs, [hyper]dense cerebral artery sign, age, NIH Stroke Scale); GRASPS (glucose at presentation, race [Asian], age, sex [male], systolic blood pressure at presentation, and severity of stroke at presentation [NIH Stroke Scale]); SITS (Safe Implementation of Thrombolysis in Stroke); and SPAN (stroke prognostication using age and NIH Stroke Scale)-100 positive index. We included only patients with available variables for all scores. We calculated the area under the receiver operating characteristic curve (AUC-ROC) and also performed logistic regression and the Hosmer-Lemeshow test. RESULTS: The final cohort comprised 3012 eligible patients, of whom 221 (7.3%) had sICH per National Institute of Neurological Disorders and Stroke, 141 (4.7%) per European Cooperative Acute Stroke Study II, and 86 (2.9%) per Safe Implementation of Thrombolysis in Stroke criteria. The performance of the scores assessed with AUC-ROC for predicting European Cooperative Acute Stroke Study II sICH was: MSS, 0.63 (95% confidence interval, 0.58-0.68); HAT, 0.65 (0.60-0.70); SEDAN, 0.70 (0.66-0.73); GRASPS, 0.67 (0.62-0.72); SITS, 0.64 (0.59-0.69); and SPAN-100 positive index, 0.56 (0.50-0.61). SEDAN had significantly higher AUC-ROC values compared with all other scores, except for GRASPS where the difference was nonsignificant. SPAN-100 performed significantly worse compared with other scores. The discriminative ranking of the scores was the same for the National Institute of Neurological Disorders and Stroke, and Safe Implementation of Thrombolysis in Stroke definitions, with SEDAN performing best, GRASPS second, and SPAN-100 worst. CONCLUSIONS: SPAN-100 had the worst predictive power, and SEDAN constantly the highest predictive power. However, none of the scores had better than moderate performance.

Caveolin expression changes in the neurovascular unit after juvenile traumatic brain injury: signs of blood-brain barrier healing?

Traumatic brain injury (TBI) is one of the major causes of death and disability in pediatrics, and results in a complex cascade of events including the disruption of the blood-brain barrier (BBB). A controlled-cortical impact on post-natal 17 day-old rats induced BBB disruption by IgG extravasation from 1 to 3 days after injury and returned to normal at day 7. In parallel, we characterized the expression of three caveolin isoforms, cav-1, cav-2 and cav-3. While cav-1 and cav-2 are expressed on endothelial cells, both cav-1 and cav-3 were found to be present on reactive astrocytes, in vivo and in vitro. Following TBI, cav-1 expression was increased in blood vessels at 1 and 7 days in the perilesional cortex. An increase of vascular cav-2 expression was observed 7 days after TBI. In contrast, astrocytic cav-3 expression decreased 3 and 7 days after TBI. Activation of eNOS (via its phosphorylation) was detected 1 day after TBI and phospho-eNOS was detected both in association with blood vessels and with astrocytes. The molecular changes involving caveolins occurring in endothelial cells following juvenile-TBI might participate, independently of eNOS activation, to a mechanism of BBB repair while, they might subserve other undefined roles in astrocytes.

Prediction of Childhood Asthma Using Conditional Probability and Discrete Event Simulation

Abstract: Asthma prevalence in children and adolescents in Spain is 10-17%. It is the most common chronic illness during childhood. Prevalence has been increasing over the last 40 years and there is considerable evidence that, among other factors, continued exposure to cigarette smoke results in asthma in children. No statistical or simulation model exist to forecast the evolution of childhood asthma in Europe. Such a model needs to incorporate the main risk factors that can be managed by medical authorities, such as tobacco (OR = 1.44), to establish how they affect the present generation of children. A simulation model using conditional probability and discrete event simulation for childhood asthma was developed and validated by simulating realistic scenario. The parameters used for the model (input data) were those found in the bibliography, especially those related to the incidence of smoking in Spain. We also used data from a panel of experts from the Hospital del Mar (Barcelona) related to actual evolution and asthma phenotypes. The results obtained from the simulation established a threshold of a 15-20% smoking population for a reduction in the prevalence of asthma. This is still far from the current level in Spain, where 24% of people smoke. We conclude that more effort must be made to combat smoking and other childhood asthma risk factors, in order to significantly reduce the number of cases. Once completed, this simulation methodology can realistically be used to forecast the evolution of childhood asthma as a function of variation in different risk factors.

Investigation of Rapid Thermal Analysis Procedures for Prediction of the Service Life of PCCP Carbonate Coarse Aggregate, HR-337, 1993

The major objective of this research project was to use thermal analysis techniques in conjunction with x-ray analysis methods to identify and explain chemical reactions that promote aggregate related deterioration in portland cement concrete. Twenty-two different carbonate aggregate samples were subjected to a chemical testing scheme that included: • bulk chemistry (major, minor and selected trace elements) • bulk mineralogy (minor phases concentrated by acid extraction) • solid-solution in the major carbonate phases • crystallite size determinations for the major carbonate phases • a salt treatment study to evaluate the impact of deicer salts Test results from these different studies were then compared to information that had been obtained using thermogravimetric analysis techniques. Since many of the limestones and dolomites that were used in the study had extensive field service records it was possible to correlate many of the variables with service life. The results of this study have indicated that thermogravimetric analysis can play an important role in categorizing carbonate aggregates. In fact, with modern automated thermal analysis systems it should be possible to utilize such methods on a quality control basis. Strong correlations were found between several of the variables that were monitored in this study. In fact, several of the variables exhibited significant correlations to concrete service life. When the full data set was utilized (n = 18), the significant correlations to service life can be summarized as follows ( a = 5% level): • Correlation coefficient, r, = -0.73 for premature TG loss versus service life. • Correlation coefficient, r, = 0.74 for relative crystallite size versus service life. • Correlation coefficient, r, = 0.53 for ASTM C666 durability factor versus service life. • Correlation coefficient, r, = -0.52 for acid-insoluble residue versus service life. Separation of the carbonate aggregates into their mineralogical categories (i.e., calcites and dolomites) tended to increase the correlation coefficients for some specific variables (r sometimes approached 0.90); however, the reliability of such correlations was questionable because of the small number of samples that were present in this study.

Prediction of cottonseed longevity

The objective of this work was to determine the viability equation constants for cottonseed and to detect the occurrence and depletion of hardseededness. Three seedlots of Brazilian cultivars IAC-19 and IAC-20 were tested, using 12 moisture content levels, ranging from 2.2 to 21.7% and three storage temperatures, 40, 50 and 65ºC. Seed moisture content level was reached from the initial value (around 8.8%) either by rehydration, in a closed container, or by drying in desiccators containing silica gel, both at 20ºC. Twelve seed subsamples for each moisture content/temperature treatment were sealed in laminated aluminium-foil packets and stored in incubators at those temperatures, until complete survival curves were obtained. Seed equilibrium relative humidity was recorded. Hardseededness was detected at moisture content levels below 6% and its releasing was achieved either naturally, during storage period, or artificially through seed coat removal. The viability equation quantified the response of seed longevity to storage environment well with K E = 9.240, C W = 5.190, C H = 0.03965 and C Q = 0.000426. The lower limit estimated for application of this equation at 65ºC was 3.6% moisture content.