Alteration of the immune response to Mycobacterium bovis BCG in mice exposed chronically to low doses of UV radiation

BALB/c mice were exposed on shaved dorsal skin to 1 minimal erythemal dose (MED) of UVB radiation (2.25 kJ/m2) from a bank of six FS-40 sunlamps three times per week. The total number of irradiations ranged from 1 to 27. At regular intervals, groups of mice were injected in the left hind foot pad with 1 x 10(6) live mycobacteria (Mycobacterium bovis BCG) 3 days after the last UVB exposure. The mice were tested 21 and 42 days after infection for a delayed type hypersensitivity (DTH) response to the purified protein derivative (PPD) of tubercle bacilli by injecting PPD into the right hind foot pad and measuring the foot pad swelling 24 hr later. The course of infection was followed by assessing the number of bacterial colony forming units in the lymph node draining the site of BCG infection and the spleen. Mice exposed from 1 to 15 times to 1 MED of UV radiation showed a significant suppression in their DTH response to PPD compared with the unirradiated mice. At the same time, the number of bacterial colony-forming units in the lymph node and spleen of the UV-irradiated mice was greater than in control mice. With continued exposure to UVB, however, the DTH response recovered to a normal level, and there was no longer an increase in the number of viable bacteria in the lymphoid organs. These results indicate that early in the course of chronic UV irradiation, mice were impaired in their ability to mount a DTH response to BCG and to clear these bacteria from their lymphoid organs; later the mice recovered from these effects of UV, with continued treatment. A dose-response study using single doses of UV radiation indicated that a dose of 2.7 kJ/m2 suppressed the DTH response by 50%. Thus, exposure of mice to a single or multiple low doses of UV radiation prior to infection can interfere with systemic immunity to mycobacteria.     

Recognition of viral RNA stem–loops by the tandem double-stranded RNA binding domains of PKR

In humans, the double-stranded RNA (dsRNA)-activated protein kinase (PKR) is expressed in late stages of the innate immune response to viral infection by the interferon pathway. PKR consists of tandem dsRNA binding motifs (dsRBMs) connected via a flexible linker to a Ser/Thr kinase domain. Upon interaction with viral dsRNA, PKR is converted into a catalytically active enzyme capable of phosphorylating a number of target proteins that often results in host cell translational repression. A number of high-resolution structural studies involving individual dsRBMs from proteins other than PKR have highlighted the key features required for interaction with perfectly duplexed RNA substrates. However, viral dsRNA molecules are highly structured and often contain deviations from perfect A-form RNA helices. By use of small-angle X-ray scattering (SAXS), we present solution conformations of the tandem dsRBMs of PKR in complex with two imperfectly base-paired viral dsRNA stem–loops; HIV-1 TAR and adenovirus VA_I-AS. Both individual components and complexes were purified by size exclusion chromatography and characterized by dynamic light scattering at multiple concentrations to ensure monodispersity. SAXS ab initio solution conformations of the individual components and RNA–protein complexes were determined and highlight the potential of PKR to interact with both stem and loop regions of the RNA. Excellent agreement between experimental and model-based hydrodynamic parameter determination heightens our confidence in the obtained models. Taken together, these data support and provide a framework for the existing biochemical data regarding the tolerance of imperfectly base-paired viral dsRNA by PKR.     

Exchangeability of the flagellin (FliC) and the cap protein (FliD) among different species in flagellar assembly

Flagellar filament self‐assembles from the component protein, flagellin or FliC, with the aid of the capping protein, HAP2 or FliD. Depending on the helical parameters of filaments, flagella from various species are divided into three groups, family I, II, and III. Each family coincides with the traditional classification of flagella, peritrichous flagella, polar flagella, and lateral flagella, respectively. To elucidate the physico‐chemical properties of flagellin to separate families, we chose family I flagella and family II flagella and examined how well the exchangeability of a combination of FliC and/or FliD from different families is kept in filament formation. FliC or FliD of Salmonella enterica serovar Typhimurium (Salty; family I) were exchanged with those of Escherichia coli (Escco; family I) or Pseudomonas aeruginosa (Pseae; family II). In a Salty fliC deletion mutant, Escco FliC formed short filaments, but Pseae FliC did not form filaments. In a Salty fliD deletion mutant, both Escco FliD and Pseae FliD allowed Salty FliC to polymerize into short filaments. In conclusion, FliC can be exchanged among the same family but not between different families, while FliD serves as the cap protein even in different families, confirming that FliC is essential for determining families, but FliD plays a subsidiary role in filament formation. © 2012 Wiley Periodicals, Inc.     

Dynamic light scattering: a practical guide and applications in biomedical sciences

Dynamic light scattering (DLS), also known as photon correlation spectroscopy (PCS), is a very powerful tool for studying the diffusion behaviour of macromolecules in solution. The diffusion coefficient, and hence the hydrodynamic radii calculated from it, depends on the size and shape of macromolecules. In this review, we provide evidence of the usefulness of DLS to study the homogeneity of proteins, nucleic acids, and complexes of protein–protein or protein–nucleic acid preparations, as well as to study protein–small molecule interactions. Further, we provide examples of DLS’s application both as a complementary method to analytical ultracentrifugation studies and as a screening tool to validate solution scattering models using determined hydrodynamic radii.     

Solution Structure of C. elegans UNC-6: A Nematode Paralogue of the Axon Guidance Protein Netrin-1

UNCoordinated-6 (UNC-6) was the first member of the netrin family to be discovered in Caenorhabditis elegans. With homology to human netrin-1, it is a key signaling molecule involved in directing axon migration in nematodes. Similar to netrin-1, UNC-6 interacts with multiple receptors (UNC-5 and UNC-40, specifically) to guide axon migration in development. As a result of the distinct evolutionary path of UNC-6 compared to vertebrate netrins, we decided to employ an integrated approach to study its solution behavior and compare it to the high-resolution structure we previously published on vertebrate netrins. Dynamic light scattering and analytical ultracentrifugation on UNC-6 (with and without its C-domain) solubilized in a low-ionic strength buffer suggested that UNC-6 forms high-order oligomers. An increase in the buffer ionic strength resulted in a more homogeneous preparation of UNC-6, that was used for subsequent solution x-ray scattering experiments. Our biophysical analysis of UNC-6 ΔC solubilized in a high-ionic strength buffer suggested that it maintains a similar head-to-stalk arrangement as netrins ?1 and ?4. This phenomenon is thought to play a role in the signaling behavior of UNC-6 and its ability to move throughout the extracellular matrix.     

Mapping of lymphatic filariasis in Nepal

BACKGROUND: Human infection with Wuchereria bancrofti causes a disabling parasitic disease known as lymphatic filariasis, which is a major public health and socio-economic problem in many parts of the world. At the onset of the study, little was known of the distribution of filariasis and its current importance as a public health problem in Nepal. METHODS: Epidemiological mapping was undertaken to determine the prevalence of infection by Wuchereria bancrofti in 37 districts of Nepal between July to December 2001. The study population above 15 years of age was selected, and the immunochromatographic test (ICT Filariasis) was used to screen for circulating filarial antigen (CFA). RESULTS: The overall prevalence of lymphatic filariasis from a 4,488-sample population was 13% and 33/37 districts were found to be endemic. On the basis of geographical data, the highest number of cases was found at altitudes between 500-700 m; however, a substantial number of infected individuals were found in the highly populated Kathmandu valley, at altitudes between 900-1,500 metres where transmission appears to take place. Prevalence rates above 20% were found in 11 districts (with the highest rate of 40%), 6-19% were found in 15 districts, and 0.1-5% were in 7 districts.Information on people's knowledge, attitudes and behaviour towards filariasis was also collected by means of a structured questionnaire, which is presented and discussed in the study. CONCLUSIONS: This is the most extensive study of lymphatic filariasis undertaken to date in Nepal. The study indicates that the prevalence of infection is far greater that was previously reported and that lymphatic filariasis should be a much higher health priority than currently given.     

Tissue distribution of puerarin and its conjugated metabolites in rats assessed by liquid chromatography–tandem mass spectrometry

Puerarin (an isoflavone C-glucoside from kudzu root) has been the focus of several studies investigating its potential effects on health benefits. In this study, we determined single dose tissue distribution of puerarin and its metabolites in order to examine whether they undergo selective uptake by specific organs. Puerarin was administered orally (50 mg/kg) to rats and the concentration of puerarin in tissue compartments was determined using liquid chromatography–tandem mass spectrometry (LC–MS/MS). Puerarin was widely distributed in rat tissues with highest concentrations in lungs (799±411.6 ng/g wet tissues). In addition, we examined the excretion of puerarin into the bile. LC–MS/MS analysis of bile samples collected after infusing puerarin directly into the portal vein indicated that puerarin was excreted into the bile predominantly in the form of unconjugated puerarin. This report identifying puerarin in several organs including kidney and pancreas may explain its beneficial effects in diabetes.     

An Automated and Intelligent Medical Decision Support System for Brain MRI Scans Classification

A wide interest has been observed in the medical health care applications that interpret neuroimaging scans by machine learning systems. This research proposes an intelligent, automatic, accurate, and robust classification technique to classify the human brain magnetic resonance image (MRI) as normal or abnormal, to cater down the human error during identifying the diseases in brain MRIs. In this study, fast discrete wavelet transform (DWT), principal component analysis (PCA), and least squares support vector machine (LS-SVM) are used as basic components. Firstly, fast DWT is employed to extract the salient features of brain MRI, followed by PCA, which reduces the dimensions of the features. These reduced feature vectors also shrink the memory storage consumption by 99.5%. At last, an advanced classification technique based on LS-SVM is applied to brain MR image classification using reduced features. For improving the efficiency, LS-SVM is used with non-linear radial basis function (RBF) kernel. The proposed algorithm intelligently determines the optimized values of the hyper-parameters of the RBF kernel and also applied k-fold stratified cross validation to enhance the generalization of the system. The method was tested by 340 patients’ benchmark datasets of T1-weighted and T2-weighted scans. From the analysis of experimental results and performance comparisons, it is observed that the proposed medical decision support system outperformed all other modern classifiers and achieves 100% accuracy rate (specificity/sensitivity 100%/100%). Furthermore, in terms of computation time, the proposed technique is significantly faster than the recent well-known methods, and it improves the efficiency by 71%, 3%, and 4% on feature extraction stage, feature reduction stage, and classification stage, respectively. These results indicate that the proposed well-trained machine learning system has the potential to make accurate predictions about brain abnormalities from the individual subjects, therefore, it can be used as a significant tool in clinical practice.