Extracellular enzymes of mycobacteria

Abstract Extracellular enzymes were studied in different mycobacteria using a plate substrate assay. All the pathogenic mycobacteria included in the study showed the presence of protease, while lipase, ribonuclease, mucinase and β-lactamase could also be detected in some strains. In contrast, no protease was detected in the 3 saprophytic mycobacteria studied. DNase was not detected in any of the species studied. Thus, the demonstration of extracellular enzymes, in particular of protease, in mycobacteria may be relevant in understanding their role in pathogenicity.     

Hydrogen peroxide formation and lipid peroxidation in rat uterus—effect of hormones and vitamin E

The effect of estradiol-17β and progesterone given separately as well as in combination on the rate of hydrogen peroxide formation and lipid peroxidation in the uteri of ovariectomized rats was studied. Estradiol in 3μg dose per day per animal elicited maximum stimulatory response and progesterone (100μg), on the other hand, was without any such effect. However, progesterone given along with estradiol completely prevented the effect due to the latter. In the same way, vitamin E, a well known antioxidant was found to be extremelv effective in protecting the uterus from the highly peroxidative action of estradiol-17β.     

Pathogenesis of SIVmac251 after atraumatic inoculation of the rectal mucosa in rhesus monkeys

Intrarectal inoculation of rhesus monkeys with low doses of SIV_mac led to a prolonged clinical and virological latency that was not observed for high intrarectal doses or for intravenous inoculation. Animals infected intrarectally with low virus doses remained negative for serum antibody responses to SIV for at least one year even though they readily transferred SIV to naive recipients via transfusion of whole blood.     

Comparison of SSR and cytochrome P-450 markers for estimating genetic diversity in Picrorhiza kurrooa L.

Picrorhiza kurrooa L., a high altitude medicinal plant, is known for its drug content called Kutkin. In the present study, DNA-based molecular marker techniques, viz. simple sequence repeats (SSR) and cytochrome P-450 markers were used to estimate genetic diversity in Picrorhiza kurrooa. Twenty five accessions of Picrorhiza kurrooa, collected from ten different eco-geographical locations were subjected to 22 SSR and eight cytochrome P-450 primer pairs, out of which 13 SSR markers detected mean 5.037 alleles with a mean polymorphic information content (PIC) of 0.7718, whereas eight cytochrome P-450 markers detected mean 5.0 alleles with a mean PIC of 0.7596. Genetic relationship among the accessions was estimated by constructing the dendrograms using SSR and cytochrome P-450 data. There was a clear consistency between SSR and cytochrome P-450 trees in terms of positioning of most Picrorhiza accessions. SSR markers could cluster various Picrorhiza kurrooa accessions based on their geographical locations whereas cytochrome P-450 markers could cluster few accessions as per their geographical locations. The Mantel test between SSR and cytochrome P-450 markers revealed a good fit correlation (r = 0.6405). The dendrogram constructed using the combined data of SSR and cytochrome P-450s depicted two clusters of accessions based on its eco-geographical locations whereas two clusters contained the accessions from mixed eco-geographical locations. Overall, the results of the present study point towards quiet high degree of genetic variation among the accessions of each eco-geographic region.     

Revisiting the notion of deleterious sweeps

It has previously been shown that, conditional on its fixation, the time to fixation of a semi-dominant deleterious autosomal mutation in a randomly mating population is the same as that of an advantageous mutation. This result implies that deleterious mutations could generate selective sweep-like effects. Although their fixation probabilities greatly differ, the much larger input of deleterious relative to beneficial mutations suggests that this phenomenon could be important. We here examine how the fixation of mildly deleterious mutations affects levels and patterns of polymorphism at linked sites—both in the presence and absence of interference amongst deleterious mutations—and how this class of sites may contribute to divergence between-populations and species. We find that, while deleterious fixations are unlikely to represent a significant proportion of outliers in polymorphism-based genomic scans within populations, minor shifts in the frequencies of deleterious mutations can influence the proportions of private variants and the value of F_ST after a recent population split. As sites subject to deleterious mutations are necessarily found in functional genomic regions, interpretations in terms of recurrent positive selection may require reconsideration.     

A novel steroidal spin label for membrane structure studies: synthesis and applications

2,2,6,6-Tetramethyl piperidine-N-oxyl nitroxyls are known to partition between aqueous and lipid phases, thus serving as probes to study membrane dynamics. The synthesis of a novel steroidal spin label, 3alpha-hydroxycholan-24-yl-(2",2",6",6"-tetramethyl-N-oxyl)p iperidyl butan-1',4'-dioate, containing 2,2,6,6-tetramethylpiperidine-N-oxyl moiety covalently bonded to the side chain in 3,24-caprostan-diol has been described. The localization of this spin label in model biomembranes has been studied by using electron spin resonance, differential scanning calorimetry, and 1H and 31P NMR spectroscopic techniques. Its applicability in studying the phase transition properties of model membrane L-alpha-dipalmitoyl phosphatidyl choline in the presence and absence of drugs has been described by using electron spin resonance. The label has also been used to study the permeability of epinephrine into membrane. The results have shown the applicability of the spin label as a potential spin probe in the study of biomembranes.     

Discrimination models using variance-stabilizing transformation of metabolomic NMR data

After the extensive work that is being done in the areas of genomics, proteomics, and metabolomics, the study of metabolites has come of interest in its own right. Metabolites in biological systems give an understanding of the state of the system and provide a powerful tool for the study of disease and other maladies. Several analytical techniques such as mass spectrometry and high-resolution NMR spectroscopy have been used to study metabolites. The data, however, from these techniques remains quite complex. Traditionally, multivariate analyses have been used for such data. These methods however have an underlying assumption that the data is multivariate normal with a constant variance. This is not necessarily the case. It has been shown that a generalized log transformation renders the variance of the data constant effectively making the data more suitable for multivariate analysis. We demonstrate the effectiveness of these transformations on NMR data taken on a set of 18 abalone that were categorized as either being healthy, stunted, or diseased. We show how the transformation makes multivariate classification of the abalone into the healthy, stunted and diseased categories much more effective and gives a tool for identifying potential metabolic biomarkers for disease.     

Discriminant models for high-throughput proteomics mass spectrometer data

We use several different multivariate analysis methods to discriminate between diseased and healthy patients using protein mass spectrometer data provided by Duke University. Two problems were presented by the university; one in which the responses (diseased or healthy) of the patients were not known and second, when the responses were known. In the latter case, the data can be used as a 'training' set. We attempted both problems. In particular, we use principle component analysis along with clustering methods to discriminate for the first problem set and partial least squares coupled with logistic and discriminant methods when the responses were known. In addition, we were able to detect regions of interest in the spectrum where there were differences in the protein patterns between healthy and diseased patients. There was considerable effort involved in the preprocessing of the data. We used a binning approach to reduce the number of variables rather than peak heights or peak areas. We performed a square root transformation on the data to help stabilize the variance; this in turn made a significant improvement in clustering results.     

Food Choices and Consequences for the Nutritional Status: Insights into Nutrition Transition in an Hospital Community

Introduction

Although economic development is generally accompanied by improvements in the overall nutritional status of the country’s population the ‘nutritional transition’ often involves a shift to high energy diets and less exercise with negative consequences. This pilot study was done to examine if education of parents operates at the household level to influence dietary choices and the nutritional status of children in a small community of hospital workers.

Material and Methods

3 groups of persons with varying skill and education levels participated. Weighed food logs were used in all households to calculate ‘adult equivalent’ per-capita-consumption. Nutrients were calculated using nutrients calculator software. BMI was used to classify children as underweight, normal weight and overweight.

Results

128 individuals participated from 30 families included 47 children. 10 children (21%) were underweight, 29 (62%) were normal and 8 (17%) were overweight. Energy consumption was highest in families with overweight children 2692 +/-502 compared to 2259 +/-359 in families with normal weight and 2031+/-354 in the family of underweight children. These differences were statistically significant. 42% underweight children belonged to Class 1 at the lowest skill level and there were no overweight children in this group. Most of the overweight children belonged to Class 2. In Class 3 there were no underweight children and the majority was normal weight children.

Conclusion

Underweight children came from the poorer households. Per capita intake of the family as a whole correlated well with BMI in the children. There was increased obesity in middle income families belonging to Class 2—probably in families who move up the scale from deprivation. Nutritional status in children correlated mostly with maternal education status.