From Staphylococcus aureus gene regulation to its pattern formation.

The focus of this paper is to develop a new partial differential equation model for the pattern formation of the human pathogen Staphylococcus aureus, starting from a newly developed model of selected gene regulation mechanisms. In our model, we do not only account for the bacteria densities and nutrient concentrations, but also for the quorum sensing and biofilm components, since they enable bacteria to coordinate their behavior and provide the environment in which the colony grows. To this end, we model the relevant gene regulation systems using ordinary differential equations and therefrom derive our evolution equations for quorum sensing and biofilm environment by time-scale arguments. Furthermore, we compare and validate our model and the corresponding simulation results with biological real data observations of Staphylococcus aureus mutant colony growth in the laboratory. We show that we are able to adequately display the qualitative biological features of pattern formation in selected mutants, using the parameter changes indicated by the gene regulation mechanisms.

Selection and Validation of Predictive Models of Radiation Effects on Tumor Growth Based on Noninvasive Imaging Data.

The use of mathematical and computational models for reliable predictions of tumor growth and decline in living organisms is one of the foremost challenges in modern predictive science, as it must cope with uncertainties in observational data, model selection, model parameters, and model inadequacy, all for very complex physical and biological systems. In this paper, large classes of parametric models of tumor growth in vascular tissue are discussed including models for radiation therapy. Observational data is obtained from MRI of a murine model of glioma and observed over a period of about three weeks, with X-ray radiation administered 14.5 days into the experimental program. Parametric models of tumor proliferation and decline are presented based on the balance laws of continuum mixture theory, particularly mass balance, and from accepted biological hypotheses on tumor growth. Among these are new model classes that include characterizations of effects of radiation and simple models of mechanical deformation of tumors. The Occam Plausibility Algorithm (OPAL) is implemented to provide a Bayesian statistical calibration of the model classes, 39 models in all, as well as the determination of the most plausible models in these classes relative to the observational data, and to assess model inadequacy through statistical validation processes. Discussions of the numerical analysis of finite element approximations of the system of stochastic, nonlinear partial differential equations characterizing the model classes, as well as the sampling algorithms for Monte Carlo and Markov chain Monte Carlo (MCMC) methods employed in solving the forward stochastic problem, and in computing posterior distributions of parameters and model plausibilities are provided. The results of the analyses described suggest that the general framework developed can provide a useful approach for predicting tumor growth and the effects of radiation.

Assessment of the nature of residual masses at end of treatment in lymphoma patients using volume perfusion computed tomography.

OBJECTIVES: To determine the diagnostic benefit of volume perfusion computed tomography (VPCT) at end of treatment for response assessment in lymphoma patients. METHODS: Seventy-five patients with different lymphoma subtypes were included: 50/75 patients had residual masses at end of treatment, 26/50 patients underwent VPCT at baseline and at end of treatment, and 24/50 patients only had end-of-treatment VPCTs. We evaluated the size of the main lymphoma mass, its blood flow (BF), blood volume (BV) and k-trans, calculated ratios (baseline and end of treatment) as well as sensitivity/specificity/negative (NPV)/positive predictive values (PPV). For VPCT at end of treatment, a cutoff threshold between responders and non-responders was calculated. RESULTS: For patients undergoing VPCT at baseline and end of treatment, reduction in size, BF, BV and k-trans was significant (P < 0.001). Identification of non-response was reached at: <53% reduction in size (sensitivity/specificity/accuracy/PPV/NPV of 88.89%/62.5%/80.77%/84.21%/71.43%), <15% reduction of BF (sensitivity/specificity/accuracy/PPV/NPV of 100%/37.5%/80.77%/0.26%/100%), or <45% reduction of k-trans (sensitivity/specificity/accuracy/PPV/NPV of 88.89%/75%/84.62%/88.89%/75%). In the subgroup undergoing VPCT at end of treatment, BF >18.51 ml/100 ml indicated non-responsiveness (sensitivity 92.86%, specificity 72.73%, accuracy 84%, PPV 81.25%, NPV 88.89%). CONCLUSIONS: VPCT seems adequate for assessment of lymphoma response at end of treatment. The degree of residual lymphoma perfusion at end of treatment helps to identify patients likely to remain in remission 1 year after completion of therapy. KEY POINTS: • Volume perfusion computed tomography (VPCT) offers measurements for assessing tumour response. • Perfusion parameter changes measured by VPCT correlate with antitumour therapy response. • In lymphoma, baseline and end-of-treatment perfusion parameter ratios can predict response. • Perfusion measurements after treatment identify patients likely to remain in remission.

Characterization of hepatocellular carcinoma (HCC) lesions using a novel CT-based volume perfusion (VPCT) technique.

OBJECTIVE: To characterize hepatocellular carcinoma (HCC) in terms of perfusion parameters using volume perfusion CT (VPCT) and two different calculation methods, compare their results, look for interobserver agreement of measurements and correlation between tumor arterialization and lesion size. MATERIAL AND METHODS: This study was part of a prospective monitoring study in patients with HCC undergoing TACE, which was approved by the local Institutional Review Board. 79 HCC-patients (mean age, 64.7) with liver cirrhosis were enrolled. VPCT was performed for 40s covering the involved liver (80 kV, 100/120 mAs) using 64 mm × 0.6 mm collimation, 26 consecutive volume measurements, 50 mL iodinated contrast IV and 5 mL/s flow rate. Mean/maximum blood flow (BF; ml/100mL/min), blood volume (BV) and k-trans were determined both with the maximum slope+Patlak vs. deconvolution method. Additionally, the portal venous liver perfusion (PVP), the arterial liver perfusion (ALP) and the hepatic perfusion index (HPI) were determined for each tumor including size measurements. Interobserver agreement for all perfusion parameters was calculated using intraclass correlation coefficients (ICC). RESULTS: The max. slope+Patlak method yielded: BFmean/max=37.8/57 mL/100g-tissue/', BVmean/max=9.8/11.1 mL/100g-tissue, k-trans-mean/max=34.4/44.5 mL/100g-tissue/'. For the deconvolution method BFmean/max, BVmean/max and, k-trans-mean/max were 68.3/106.1 mL/100g-tissue/', 12.6/15.5 mL/100g-tissue and 24/33.8 mL/100g-tissue/'. Mean ALP, PVP, HPI and size were 53.7 mL/100g-tissue/', 2.4 mL/100g-tissue/', 96.4 and 3.5 cm, respectively. Interobserver agreement measured with intraclass coefficient correlation (ICC) was very good for all perfusion parameters (≥ 0.99). Best correlation between calculation methods was achieved for measurements of BF, while BV and k-trans values were less correlated. There was no relationship between HPI and lesion size. CONCLUSION: VPCT can measure tumor volume perfusion non-invasively and enables quantification of the degree of HCC arterialization. Results are dependent on the technique used with best inter-method correlation for BF. Tumor HPI did not proved size-dependent.

Volume perfusion computed tomography (VPCT)-based evaluation of response to TACE using two different sized drug eluting beads in patients with nonresectable hepatocellular carcinoma: Impact on tumor and liver parenchymal vascularisation.

OBJECTIVE: Response monitoring of transarterial chemoembolization (TACE) with the help of volume perfusion computed tomography (VPCT) at day one post-TACE and analysis of TACE-impact on tumor and uninvolved liver parenchymal perfusion by using different particles sizes and epirubicin dose. MATERIALS AND METHODS: Institutional review board approved this prospective study. VPCT was performed in the baseline, post-interventional (FU1; 24 h post-TACE) and at follow-up (FU2; median, 81 days) in 45 consecutive patients. 100-300 µm (n=17) and 300-500 µm (n=28) drug eluting beads (DEB) using an epirubicin dose of (<=25 vs. >25) were administered. VPCT was performed for 40-s using 80 kV, 100/120 mAs, 64×0.6 mm collimation, 26 consecutive measurements, IV injection (50 ml iodinated contrast), flow rate (5 ml/s). Blood flow (BF), blood volume (BV) and k-trans were registered as average and max values in the tumor. Arterial liver perfusion (ALP), portal-venous perfusion (PVP) and the hepatic perfusion index (HPI) were registered both in tumor and non-involved liver parenchyma. Response to TACE was classified by VPCT as complete (CR), partial (PR) or no response (NR). RESULTS: A significant reduction of viable tumor tissue was found in all patients between baseline and FU1 (p<0.001) being independent on particle size and epirubicin dose (p>0.05). PPV/NPV/sensitivity/specificity of post-interventional VPCT (FU1) results for prediction of the mid-term tumor course (FU2) were 100%/70%/76%/100%. There was generally a significant increase of the ALP between baseline and FU1 in the liver parenchyma coupled by a significant subsequent decrease (normalization) of ALP and HPI between FU1 and FU2. CONCLUSION: VPCT accurately measures impact of TACE on liver tumor and hepatic parenchymal perfusion. The former proved not to be significantly dependent on particle size and epirubicin dose. There was no persistent perfusion deficit in the liver after TACE.

Neutrophil elastase increases MUC5AC mRNA and protein expression in respiratory epithelial cells.

Chronic neutrophil-predominant inflammation and hypersecretion of mucus are common pathophysiological features of cystic fibrosis, chronic bronchitis, and viral- or pollution-triggered asthma. Neutrophils release elastase, a serine protease, that causes increased mucin production and secretion. The molecular mechanisms of elastase-induced mucin production are unknown. We hypothesized that as part of this mechanism, elastase upregulates expression of a major respiratory mucin gene, MUC5AC. A549, a human lung carcinoma cell line that expresses MUC5AC mRNA and protein, and normal human bronchial epithelial cells in an air-liquid interface culture were stimulated with neutrophil elastase. Neutrophil elastase increased MUC5AC mRNA levels in a time-dependent manner in both cell culture systems. Neutrophil elastase treatment also increased MUC5AC protein levels in A549 cells. The mechanism of MUC5AC gene regulation by elastase was determined in A549 cells. The induction of MUC5AC gene expression required serine protease activity; other classes of proteases had no effect on MUC5AC gene expression. Neutrophil elastase increased MUC5AC mRNA levels by enhancing mRNA stability. This is the first report of mucin gene regulation by this mechanism.