Time filter

Source Type

Martin F.,Philip Morris Products S.A. | Thomson T.M.,Selventa | Sewer A.,Philip Morris Products S.A. | Drubin D.A.,Selventa | And 5 more authors.
BMC Systems Biology | Year: 2012

Background: High-throughput measurement technologies produce data sets that have the potential to elucidate the biological impact of disease, drug treatment, and environmental agents on humans. The scientific community faces an ongoing challenge in the analysis of these rich data sources to more accurately characterize biological processes that have been perturbed at the mechanistic level. Here, a new approach is built on previous methodologies in which high-throughput data was interpreted using prior biological knowledge of cause and effect relationships. These relationships are structured into network models that describe specific biological processes, such as inflammatory signaling or cell cycle progression. This enables quantitative assessment of network perturbation in response to a given stimulus.Results: Four complementary methods were devised to quantify treatment-induced activity changes in processes described by network models. In addition, companion statistics were developed to qualify significance and specificity of the results. This approach is called Network Perturbation Amplitude (NPA) scoring because the amplitudes of treatment-induced perturbations are computed for biological network models. The NPA methods were tested on two transcriptomic data sets: normal human bronchial epithelial (NHBE) cells treated with the pro-inflammatory signaling mediator TNFα, and HCT116 colon cancer cells treated with the CDK cell cycle inhibitor R547. Each data set was scored against network models representing different aspects of inflammatory signaling and cell cycle progression, and these scores were compared with independent measures of pathway activity in NHBE cells to verify the approach. The NPA scoring method successfully quantified the amplitude of TNFα-induced perturbation for each network model when compared against NF-κB nuclear localization and cell number. In addition, the degree and specificity to which CDK-inhibition affected cell cycle and inflammatory signaling were meaningfully determined.Conclusions: The NPA scoring method leverages high-throughput measurements and a priori literature-derived knowledge in the form of network models to characterize the activity change for a broad collection of biological processes at high-resolution. Applications of this framework include comparative assessment of the biological impact caused by environmental factors, toxic substances, or drug treatments. © 2012 Martin et al.; licensee BioMed Central Ltd.

Piade J.-J.,Philip Morris Products S.A. | Roemer E.,Philip Morris Products S.A. | Dempsey R.,Philip Morris Products S.A. | Weiler H.,Philip Morris Research Laboratories GmbH | And 4 more authors.
Regulatory Toxicology and Pharmacology | Year: 2014

A typical Indonesian kretek cigarette brand and an experimental kretek reference cigarette were compared to the reference cigarette 2R4F in two 90-day inhalation studies. Male and female rats were exposed nose-only to mainstream smoke for 6 hours daily, for 90 consecutive days. Biological endpoints were assessed according to OECD guideline 413, with special emphasis on respiratory tract histopathology and on lung inflammation (broncho-alveolar lavage fluid levels of neutrophils, macrophages and lymphocytes). Histopathological alterations included: in the nose, hyperplasia and squamous metaplasia of the respiratory epithelium and squamous metaplasia and atrophy of the olfactory epithelium; in the larynx, epithelial squamous metaplasia and hyperplasia; in the lungs, accumulation of macrophages in alveoli and goblet cell hyperplasia in bronchial epithelium. The findings were qualitatively consistent with observations from previous similar studies on conventional cigarettes. Compared to 2R4F cigarette, however, kretek smoke exposure was associated with a pronounced attenuation of pulmonary inflammation and less severe histopathological changes in the respiratory tract. Neutrophilic inflammation was also significantly lower (>70%). These results are consistent with the observations made on smoke chemistry and in vitro toxicology. They do not support any increased toxicity of the smoke of kretek cigarettes compared to conventional American-blended cigarettes. © 2014 Elsevier Inc.

Friedrichs B.,Philip Morris Research Laboratories GmbH | Neumann U.,Philip Morris Research Laboratories GmbH | Schuller J.,Philip Morris Research Laboratories GmbH | Peck M.J.,Philip Morris Products S.A.
Toxicology in Vitro | Year: 2014

In vitro treatment of human peripheral blood neutrophils from smokers and non-smokers with an aqueous cigarette smoke (CS) extract resulted in a concentration-dependent increase in surface expression of CD11b and CD66b and a corresponding decrease of CD62L, together with a concentration-dependent release of MMP-8, MMP-9, and lactoferrin, indicating considerable activation and degranulation. However, the burst response to N-formyl-methionyl-leucyl-phenylalanine (fMLP) was unchanged in CS-stimulated neutrophils from both smokers and non-smokers. When supernatants from CS-treated monocytic MonoMac-6 (MM6) cells were used for activation of neutrophils, concentration-dependent changes in surface marker expression, granule protein release, and the oxidative burst response to fMLP were observed, again with no major differences between smokers and non-smokers. CS-treated MM6 cells released significant amounts of IL-8 and TNF-α into the culture supernatant. However, antibody blocking experiments showed that only TNF-α mediated the increased burst response in neutrophils. These data show that, in the presence of secondary cells, CS is able to prime neutrophils for an increased burst response to fMLP which is mediated by TNF-α, released from the secondary cells in response to CS. Following stimulation with priming agents, peripheral blood neutrophils from healthy smokers show an equal burst response compared to those from non-smokers. © 2014.

Roemer E.,Philip Morris Products S.A. | Dempsey R.,Philip Morris Products S.A. | Lawless-Pyne J.,PT HM Sampoerna Tbk | Lukman S.,PT HM Sampoerna Tbk | And 4 more authors.
Regulatory Toxicology and Pharmacology | Year: 2014

The smoke chemistry and in vitro toxicity of mainstream smoke (MS) was investigated in American-blended cigarettes with or without the addition of 2.5%, 5% or 10% eugenol to the tobacco and in Indonesian-blended cigarettes with and without the addition of cloves, cloves extracted with hot ethanol, and extracted cloves replenished with eugenol or clove oil. The addition of eugenol reduced the concentration of nearly all toxicants measured in MS as well as the in vitro cytotoxicity of the gas/vapor phase. Reductions were also seen in bacterial mutagenicity of the total particulate matter (TPM) assessed by the Ames Assay. The addition of extracted cloves led to increases and decreases of toxicant concentrations in MS. Replenishment with eugenol or clove oil decreased the toxicant concentrations; with most smoke constituent concentrations reduced below the concentration found in tobacco-only cigarettes. Cytotoxicity of the TPM was not affected by the clove preparations. However, GVP cytotoxicity was reduced (untreated cloves showing the highest reductions). Mutagenicity of TPM was decreased by the clove preparations. Mechanisms for the reductions, (up to 40%), are most likely due to dilution effects by eugenol, changed burning characteristics of the tobacco, and free radical scavenging by eugenol. © 2014 Elsevier Inc.

Knorr A.,Philip Morris Products S.A. | Monge A.,Philip Morris Products S.A. | Stueber M.,Philip Morris Research Laboratories GmbH | Stratmann A.,Philip Morris Research Laboratories GmbH | And 3 more authors.
Analytical Chemistry | Year: 2013

Compound identification is widely recognized as a major bottleneck for modern metabolomic approaches and high-throughput nontargeted characterization of complex matrices. To tackle this challenge, an automated platform entitled computer-assisted structure identification (CASI) was designed and developed in order to accelerate and standardize the identification of compound structures. In the first step of the process, CASI automatically searches mass spectral libraries for matches using a NIST MS Search algorithm, which proposes structural candidates for experimental spectra from two-dimensional gas chromatography with time-of-flight mass spectrometry (GC × GC-TOF-MS) measurements, each with an associated match factor. Next, quantitative structure-property relationship (QSPR) models implemented in CASI predict three specific parameters to enhance the confidence for correct compound identification, which were Kovats Index (KI) for the first dimension (1D) separation, relative retention time for the second dimension separation (2DrelRT) and boiling point (BP). In order to reduce the impact of chromatographic variability on the second dimension retention time, a concept based upon hypothetical reference points from linear regressions of a deuterated n-alkanes reference system was introduced, providing a more stable relative retention time measurement. Predicted values for KI and 2DrelRT were calculated and matched with experimentally derived values. Boiling points derived from 1D separations were matched with predicted boiling points, calculated from the chemical structures of the candidates. As a last step, CASI combines the NIST MS Search match factors (NIST MF) with up to three predicted parameter matches from the QSPR models to generate a combined CASI Score representing the measure of confidence for the identification. Threshold values were applied to the CASI Scores assigned to proposed structures, which improved the accuracy for the classification of true/false positives and true/false negatives. Results for the identification of compounds have been validated, and it has been demonstrated that identification using CASI is more accurate than using NIST MS Search alone. CASI is an easily accessible web-interfaced software platform which represents an innovative, high-throughput system that allows fast and accurate identification of constituents in complex matrices, such as those requiring 2D separation techniques. © 2013 American Chemical Society.

Discover hidden collaborations