Knowledge-Based Design of a Biosensor to Quantify Localized ERK Activation in Living Cells

1. Download : Download high-res image (394KB)
2. Download : Download full-size image

     

Crystal Structures of Sirt3 Complexes with 4′-Bromo-Resveratrol Reveal Binding Sites and Inhibition Mechanism

1. Download : Download high-res image (246KB)
2. Download : Download full-size image

     

Detection and identification of the designer benzodiazepine flubromazepam and preliminary data on its metabolism and pharmacokinetics

The appearance of pyrazolam in Internet shops selling ‘research chemicals’ in 2012 marked the beginning of designer benzodiazepines being sold as recreational drugs or ‘self medication’. With recent changes in national narcotics laws in many countries, where two uncontrolled benzodiazepines (phenazepam and etizolam), which were marketed by pharmaceutical companies in some countries, were scheduled, clandestine laboratories seem to turn to poorly characterized research drug candidates as legal substitutes. Following the appearance of pyrazolam, it comes with no surprise that recently, flubromazepam (7‐bromo‐5‐(2‐fluorophenyl)‐1,3‐dihydro‐2H‐1,4‐benzodiazepin‐2‐one), a second designer benzodiazepine, was offered on the market. In this article, this new compound was characterized using nuclear magnetic resonance, gas chromatography‐mass spectrometry (GC–MS), liquid chromatography–mass spectrometry (LC–MS/MS) and liquid chromatography quadrupole time‐of‐flight MS (LC–Q–ToF–MS). Additionally, a study was carried out, in which one of the authors consumed 4 mg of flubromazepam to gain preliminary data on the pharmacokinetic properties and the metabolism of this compound. For this purpose, serum as well as urine samples were collected for up to 31 days post‐ingestion and analyzed applying LC–MS/MS and LC–Q‐ToF‐MS techniques. On the basis of this study, flubromazepam appears to have an extremely long elimination half‐life of more than 100 h. One monohydroxylated compound and the debrominated compound could be identified as the predominant metabolites, the first allowing a detection of a consumption for up to 28 days post‐ingestion when analyzing urine samples in our case. Additionally, various immunochemical assays were evaluated, showing that the cross‐reactivity of the used assay seems not to be sufficient for safe detection of the applied dose in urine samples, bearing the risk that it could be misused in drug‐withdrawal settings or in other circumstances requiring regular drug testing. Furthermore, it may be used in drug‐facilitated crimes without being detected. Copyright © 2013 John Wiley & Sons, Ltd.     

Size does matter! Label-free detection of small molecule–protein interaction

This review is focused on methods for detecting small molecules and, in particular, the characterisation of their interaction with natural proteins (e.g. receptors, ion channels). Because there are intrinsic advantages to using label-free methods over labelled methods (e.g. fluorescence, radioactivity), this review only covers label-free techniques. We briefly discuss available techniques and their advantages and disadvantages, especially as related to investigating the interaction between small molecules and proteins. The reviewed techniques include well-known and widely used standard analytical methods (e.g. HPLC-MS, NMR, calorimetry, and X-ray diffraction), newer and more specialised analytical methods (e.g. biosensors), biological systems (e.g. cell lines and animal models), and in-silico approaches.     

Common Trends and Differences in Antioxidant Activity Analysis of Phenolic Substances Using Single Electron Transfer Based Assays

Numerous assays were developed to measure the antioxidant activity, but each has limitations and the results obtained by different methods are not always comparable. Popular examples are the DPPH and ABTS assay. Our aim was to study similarities and differences of these two assay regarding the measured antioxidant potentials of 24 phenolic compounds using the same measurement and evaluation methods. This should allow conclusions to be drawn as to whether one of the assays is more suitable for measuring specific subgroups like phenolic acids, flavonols, flavanones, dihydrochalcones or flavanols. The assays showed common trends for the mean values of most of the subgroups. Some dihydrochalcones and flavanones did not react with the DPPH radical in contrast to the ABTS radical, leading to significant differences. Therefore, to determine the antioxidant potential of dihydrochalcone or flavanone-rich extracts, the ABTS assay should be preferred. We found that the results of the flavonoids in the DPPH assay were dependent on the Bors criteria, whereas the structure–activity relationship in the ABTS assay was not clear. For the phenolic acids, the results in the ABTS assay were only high for pyrogallol structures, while the DPPH assay was mainly determined by the number of OH groups.     

Diffusion changes in patients with systemic lupus erythematosus

BACKGROUND AND PURPOSE: Systemic lupus erythematosus (SLE) is an autoimmune disease in which almost all the organs are involved. Neuropsychiatric SLE is of one of the major concerns in the clinical evaluation of this disease. Routine magnetic resonance imaging (MRI) findings are often nonspecific or negative. In this study, we explored the use of diffusion tensor imaging in assisting with the diagnosis of SLE. METHODS: Data from 34 SLE patients (age range, 18-73 years) and 29 age-matched volunteers (age range, 29-64 years) were analyzed. MRI was performed on a 1.5-T clinical MR scanner with a quadrature head coil. The average diffusion constant (D(av)) and diffusion anisotropy maps [fractional anisotropy (FA)] were determined on a pixel-by-pixel basis. Regional diffusion measurements were made by region of interest in the genu and splenium of the corpus callosum (CC), anterior and posterior limb of the internal capsule (IC) and frontal lobe and thalamus. The diffusion distribution was fitted to a triple-Gaussian model. The mean of the brain tissue distribution was determined as a mean diffusion constant for the whole brain (BD(av)). Student's t test was used to determine the diffusion difference between SLE patients and control subjects. The SLE patients were separated into two groups according to their MRI results. A P value lower than .05 was considered to be statistically significant. RESULTS: Twenty of the 34 SLE patients with abnormal MRI results showed findings dominated by nonspecific white matter disease. The BD(av) and D(av) values of the frontal lobe, splenium CC and anterior IC were significantly higher in all SLE patients as compared with the control subjects. The SLE patients with normal MRI results also showed higher BD(av) and D(av) values in the frontal lobe, splenium and anterior and posterior limbs of the IC as compared with the control subjects. There was no significant difference in the D(av) values of the thalamus between the SLE patients and the control subjects. The BD(av) value in the SLE patient group was robustly correlated with the D(av) values of the frontal lobe, splenium and thalamus. These correlations were found to be similarly significant for the SLE patients with normal MRI findings. The diffusion anisotropy measurements showed that splenium CC had the highest FA value in both the control subjects and SLE patients. Overall, SLE patients had lower FA values in the genu and splenium CC as compared with the control subjects. In the group of patients with normal MRI findings, the FA values of the genu and splenium CC as well as the anterior IC were also lower than those in the control subjects. Pearson's correlation statistics revealed robust correlations between the measurements of D(av) and FA values in the SLE patient group. CONCLUSION: Quantitative diffusion imaging and diffusion anisotropy showed early changes in the brains of the SLE patients. Increased BD(av) and D(av) values of the frontal lobe as well as decreased anisotropy in the genu CC and anterior IC may represent preclinical signs of central nervous system involvement of SLE even when the routine MRI findings are negative or nonspecific. Quantitative diffusion analysis may prove to be useful in detecting the initial brain involvement of SLE and may enable monitoring of early disease progression and treatment efficacy.