Protein and lipid binding parameters in rainbow trout (Oncorhynchus mykiss) blood and liver fractions to extrapolate from an in vitro metabolic degradation assay to in vivo bioaccumulation potential of hydrophobic organic chemicals

Binding of hydrophobic chemicals to colloids such as proteins or lipids is difficult to measure using classical microdialysis methods due to low aqueous concentrations, adsorption to dialysis membranes and test vessels, and slow kinetics of equilibration. Here, we employed a three-phase partitioning system where silicone (polydimethylsiloxane, PDMS) serves as a third phase to determine partitioning between water and colloids and acts at the same time as a dosing device for hydrophobic chemicals. The applicability of this method was demonstrated with bovine serum albumin (BSA). Measured binding constants (K(BSAw)) for chlorpyrifos, methoxychlor, nonylphenol, and pyrene were in good agreement with an established quantitative structure-activity relationship (QSAR). A fifth compound, fluoxypyr-methyl-heptyl ester, was excluded from the analysis because of apparent abiotic degradation. The PDMS depletion method was then used to determine partition coefficients for test chemicals in rainbow trout (Oncorhynchus mykiss) liver S9 fractions (K(S9w)) and blood plasma (K(bloodw)). Measured K(S9w) and K(bloodw) values were consistent with predictions obtained using a mass-balance model that employs the octanol-water partition coefficient (K(ow)) as a surrogate for lipid partitioning and K(BSAw) to represent protein binding. For each compound, K(bloodw) was substantially greater than K(S9w), primarily because blood contains more lipid than liver S9 fractions (1.84% of wet weight vs 0.051%). Measured liver S9 and blood plasma binding parameters were subsequently implemented in an in vitro to in vivo extrapolation model to link the in vitro liver S9 metabolic degradation assay to in vivo metabolism in fish. Apparent volumes of distribution (V(d)) calculated from the experimental data were similar to literature estimates. However, the calculated binding ratios (f(u)) used to relate in vitro metabolic clearance to clearance by the intact liver were 10 to 100 times lower than values used in previous modeling efforts. Bioconcentration factors (BCF) predicted using the experimental binding data were substantially higher than the predicted values obtained in earlier studies and correlated poorly with measured BCF values in fish. One possible explanation for this finding is that chemicals bound to proteins can desorb rapidly and thus contribute to metabolic turnover of the chemicals. This hypothesis remains to be investigated in future studies, ideally with chemicals of higher hydrophobicity.

Influence of different spacers on the biological profile of a DOTA-somatostatin analogue

Radiolabeled somatostatin analogues have been successfully used for targeted radiotherapy and for imaging of somatostatin receptor (sst1-5)-positive tumors. Nevertheless, these analogues are subject to improving their tumor-to-nontarget ratio to enhance their diagnostic or therapeutic properties, preventing nephrotoxicity. In order to understand the influence of lipophilicity and charge on the pharmacokinetic profile of [1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid (DOTA)]-somatostatin-based radioligands such as [DOTA,1-Nal3]-octreotide (DOTA-NOC), different spacers (X) based on 8-amino-3,6-dioxaoctanoic acid (PEG2), 15-amino-4,7,10,13-tetraoxapentadecanoic acid (PEG4), N-acetyl glucosamine (GlcNAc), triglycine, beta-alanine, aspartic acid, and lysine were introduced between the chelator DOTA and the peptide NOC. All DOTA-X-NOC conjugates were synthesized by Fmoc solid-phase synthesis. The partition coefficient (log D) at pH = 7.4 indicated that higher hydrophilicity than [111In-DOTA]-NOC was achieved with the introduction of the mentioned spacers, except with triglycine and beta-alanine. The high affinity of [InIII-DOTA]-NOC for human sst2 (hsst2) was preserved with the structural modifications, while an overall drop for hsst3 affinity was observed, except in the case of [InIII-DOTA]-beta-Ala-NOC. The new conjugates preserved the good affinity for hsst5, except for [InIII-DOTA]-Asn(GlcNAc)-NOC, which showed decreased affinity. A significant 1.2-fold improvement in the specific internalization rate in AR4-2J rat pancreatic tumor cells (sst2 receptor expression) at 4 h was achieved with the introduction of Asp as a spacer in the parent compound. In sst3-expressing HEK cells, the specific internalization rate at 4 h for [111In-DOTA]-NOC (13.1% +/- 0.3%) was maintained with [111In-DOTA]-beta-Ala-NOC (14.0% +/- 1.8%), but the remaining derivatives showed <2% specific internalization. Biodistribution studies were performed with Lewis rats bearing the AR4-2J rat pancreatic tumor. In comparison to [111In-DOTA]-NOC (2.96% +/- 0.48% IA/g), the specific uptake in the tumor at 4 h p.i. was significantly improved for the 111In-labeled sugar analogue (4.17% +/- 0.46% IA/g), which among all the new derivatives presented the best tumor-to-kidney ratio (1.9).

Oxygenated polycyclic aromatic hydrocarbons and azaarenes in urban soils: A comparison of a tropical city (Bangkok) with two temperate cities (Bratislava and Gothenburg)

Environmental conditions in the tropics favor the formation of polar polycyclic aromatic compound (polar PACs, such as oxygenated PAHs [OPAHs] and azaarenes [AZAs]), but little is known about these hazardous compounds in tropical soils. The objectives of this work were to determine (i) the level of contamination of soils (0–5 and 5–10 cm layers) from the tropical metropolis of Bangkok (Thailand) with OPAHs and AZAs and (ii) the influence of urban emission sources and soil properties on the distribution of PACs. We hypothesized that the higher solar insolation and microbial activity in the tropics than in the temperate zone will lead to enhanced secondary formation of OPAHs. Hence, OPAH to related parent-PAH ratios will be higher in the tropical soils of Bangkok than in temperate soils of Bratislava and Gothenburg. The concentrations of ∑15OPAHs (range: 12–269 ng g−1) and ∑4AZAs (0.1–31 ng g−1) measured in soils of Bangkok were lower than those in several cities of the industrialized temperate zone. The ∑15OPAHs (r = 0.86, p < 0.01) and ∑4AZAs (r = 0.67, p < 0.01) correlated significantly with those of ∑20PAHs highlighting similar sources and related fate. The octanol–water partition coefficient did not explain the transport to the subsoil, indicating soil mixing as the reason for the polar PAC load of the lower soil layer. Data on PAC concentrations in soils of Bratislava and Gothenburg were taken from published literature. The individual OPAH to parent-PAH ratios in soils of Bangkok were mostly higher than those of Bratislava and Gothenburg (e.g. 9-fluorenone/fluorene concentration ratio was 12.2 ± 6.7, 5.6 ± 2.4, and 0.7 ± 02 in Bangkok, Bratislava and Gothenburg soils, respectively) supporting the view that tropical environmental conditions and higher microbial activity likely lead to higher OPAH to parent-PAH ratios in tropical than in temperate soils.

Determination of Δ9-tetrahydrocannabinolic acid A (Δ9-THCA-A) in whole blood and plasma by LC–MS/MS and application in authentic samples from drivers suspected of driving under the influence of cannabis

Delta-9-tetrahydrocannabinolic acid A (THCA-A) is the biosynthetic precursor of delta-9-tetrahydrocannabinol (THC) in cannabis plants, and has no psychotropic effects. THCA-A can be detected in blood and urine, and several metabolites have been identified. THCA-A was also shown to be incorporated in hair by side stream smoke to a minor extent, but incorporation via blood stream or sweat seems unlikely. The detection of THCA-A in biological fluids may serve as a marker for differentiating between the intake of prescribed THC medication – containing only pure THC – and cannabis products containing THC besides THC-acid A and other cannabinoids. However, the knowledge about its usefulness in forensic cases is very limited. The aim of the present work was the development of a reliable method for THCA-A determination in human blood or plasma using LC–MS/MS and application to cases of driving under the influence of drugs. Fifty eight (58) authentic whole blood and the respective plasma samples were collected from drivers suspected of driving under the influence of cannabis from the region of Bern (Switzerland). Samples were first tested for THC, 11-OH-THC and THC-COOH, and then additionally for THCA-A. For this purpose, the existing LC–MS/MS method was modified and validated, and found to be selective and linear over a range of 1.0 to 200 ng/mL (the correlation coefficients were above 0.9980 in all validation runs). Limit of detection (LOD) and limit of quantification (LOQ) were 0.3 ng/mL and 1.0 ng/mL respectively. Intra- and inter-assay accuracy were equal or better than 90% and intra- and inter-assay precision were equal or better than 11.1%. The mean extraction efficiencies were satisfactory being equal or higher than 85.4%. THCA-A was stable in whole blood samples after 3 freeze/thaw cycles and storage at 4 °C for 7 days. Re-injection (autosampler) stability was also satisfactory. THC was present in all blood samples with levels ranging from 0.7 to 51 ng/mL. THCA-A concentrations ranged from 1.0 to 496 ng/mL in blood samples and from 1.4 to 824 ng/mL in plasma samples. The plasma:blood partition coefficient had a mean value of 1.7 (±0.21, SD). No correlation was found between the degree of intoxication or impairment stated in the police protocols or reports of medical examinations and the detected THCA-A-concentration in blood.

Apparent diffusion coefficient in the aging mouse brain: a magnetic resonance imaging study

Novel magnetic resonance imaging sequences have and still continue to play an increasing role in neuroimaging and neuroscience. Among these techniques, diffusion-weighted imaging (DWI) has revolutionized the diagnosis and management of diseases such as stroke, neoplastic disease and inflammation. However, the effects of aging on diffusion are yet to be determined. To establish reference values for future experimental mouse studies we tested the hypothesis that absolute apparent diffusion coefficients (ADC) of the normal brain change with age. A total of 41 healthy mice were examined by T2-weighted imaging and DWI. For each animal ADC frequency histograms (i) of the whole brain were calculated on a voxel-by-voxel basis and region-of-interest (ROI) measurements (ii) performed and related to the animals' age. The mean entire brain ADC of mice <3 months was 0.715(+/-0.016) x 10(-3) mm2/s, no significant difference to mice aged 4 to 5 months (0.736(+/-0.040) x 10(-3) mm2/s) or animals older than 9 months 0.736(+/-0.020) x 10(-3) mm2/s. Mean whole brain ADCs showed a trend towards lower values with aging but both methods (i + ii) did not reveal a significant correlation with age. ROI measurements in predefined areas: 0.723(+/-0.057) x 10(-3) mm2/s in the parietal lobe, 0.659(+/-0.037) x 10(-3) mm2/s in the striatum and 0.679(+/-0.056) x 10(-3) mm2/s in the temporal lobe. With advancing age, we observed minimal diffusion changes in the whole mouse brain as well as in three ROIs by determination of ADCs. According to our data ADCs remain nearly constant during the aging process of the brain with a small but statistically non-significant trend towards a decreased diffusion in older animals.

Contribution of the apparent diffusion coefficient in perilesional edema for the assessment of brain tumors

OBJECTIVES: Diffusion-weighted MRI is sensitive to molecular motion and has been applied to the diagnosis of stroke. Our intention was to investigate its usefulness in patients with brain tumor and, in particular, in the perilesional edema. METHODS: We performed MRI of the brain, including diffusion-weighted imaging and mapping of the apparent diffusion coefficient (ADC), in 16 patients with brain tumors (glioblastomas, low-grade gliomas and metastases). ADC values were determined by the use of regions of interest positioned in areas of high signal intensities as seen on T2-weighted images and ADC maps. Measurements were taken in the tumor itself, in the area of perilesional edema and in the healthy contralateral brain. RESULTS: ADC mapping showed higher values of peritumoral edema in patients with glioblastoma (1.75 x 10(-3)mm(2)/s) and metastatic lesions (1.61 x 10(-3)mm(2)/s) compared with those who had low-grade glioma (1.40 x10(-3)mm(2)/s). The higher ADC values in the peritumoral zone were associated with lower ADC values in the tumor itself. CONCLUSIONS: The higher ADC values in the more malignant tumors probably reflect vasogenic edema, thereby allowing their differentiation from other lesions.

Diffusion-weighted imaging of the parotid gland: Influence of the choice of b-values on the apparent diffusion coefficient value

PURPOSE: To determine how the ADC value of parotid glands is influenced by the choice of b-values. MATERIALS AND METHODS: In eight healthy volunteers, diffusion-weighted echo-planar imaging (DW-EPI) was performed on a 1.5 T system, with b-values (in seconds/mm2) of 0, 50, 100, 150, 200, 250, 300, 500, 750, and 1000. ADC values were calculated by two alternative methods (exponential vs. logarithmic fit) from five different sets of b-values: (A) all b-values; (B) b=0, 50, and 100; (C) b=0 and 750; (D) b=0, 500, and 1000; and (E) b=500, 750, and 1000. RESULTS: The mean ADC values for the different settings were (in 10(-3) mm2/second, exponential fit): (A) 0.732+/-0.019, (B) 2.074+/-0.084, (C) 0.947+/-0.020, (D) 0.890+/-0.023, and (E) 0.581+/-0.021. ADC values were significantly (P <0.001) different for all pairwise comparisons of settings (A-E) of b-values, except for A vs. D (P=0.172) and C vs. D (P=0.380). The ADC(B) was significantly higher than ADC(C) or ADC(D), which was significantly higher than ADC(E). ADC values from exponential vs. logarithmic fit (P=0.542), as well as left vs. right parotid gland (P=0.962), were indistinguishable. CONCLUSION: The ADC values calculated from low b-value settings were significantly higher than those calculated from high b-value settings. These results suggest that not only true diffusion but also perfusion and saliva flow may contribute to the ADC.

Comparative Analysis of Evolving Software Systems Using the Gini Coefficient

Software metrics offer us the promise of distilling useful information from vast amounts of software in order to track development progress, to gain insights into the nature of the software, and to identify potential problems. Unfortunately, however, many software metrics exhibit highly skewed, non-Gaussian distributions. As a consequence, usual ways of interpreting these metrics --- for example, in terms of "average" values --- can be highly misleading. Many metrics, it turns out, are distributed like wealth --- with high concentrations of values in selected locations. We propose to analyze software metrics using the Gini coefficient, a higher-order statistic widely used in economics to study the distribution of wealth. Our approach allows us not only to observe changes in software systems efficiently, but also to assess project risks and monitor the development process itself. We apply the Gini coefficient to numerous metrics over a range of software projects, and we show that many metrics not only display remarkably high Gini values, but that these values are remarkably consistent as a project evolves over time.