No abstract

Background:Major international studies on course and outcome of schizophrenia suggest a better prognosis in the rural world and in low-income nations. Industrialization is thought to result in increased stigma for mental illness, which in turn is thought to worsen prognosis. The lack of an ethnographically derived and cross-culturally valid measure of stigma has hampered investigation. The present study deploys such a scale and examines stigmatizing attitudes towards the severely mentally ill among rural and urban community dwellers in India.Aim:To test the hypothesis that there are fewer stigmatizing attitudes towards the mentally ill amongst rural compared to urban community dwellers in India.Materials and Methods:An ethnographically derived and vignette-based stigmatization scale was administered to a general community sample comprising two rural and one urban site in India. Responses were analyzed using univariate and multivariate statistical methods.Result:Rural Indians showed significantly higher stigma scores, especially those with a manual occupation. The overall pattern of differences between rural and urban samples suggests that the former deploy a punitive model towards the severely mentally ill, while the urban group expressed a liberal view of severe mental illness. Urban Indians showed a strong link between stigma and not wishing to work with a mentally ill individual, whereas no such link existed for rural Indians.Conclusion:This is the first study, using an ethnographically derived stigmatization scale, to report increased stigma amongst a rural Indian population. Findings from this study do not fully support the industrialization hypothesis to explain better outcome of severe mental illness in low-income nations. The lack of a link between stigma and work attitudes may partly explain this phenomenon.

The influence of temporal and spatial variations on the microbial community composition was assessed in the unique coastal mangrove of Sundarbans using parallel 16S rRNA gene pyrosequencing. The total sediment DNA was extracted and subjected to the 16S rRNA gene pyrosequencing, which resulted in 117 Mbp of data from three experimental stations. The taxonomic analysis of the pyrosequencing data was grouped into 24 different phyla. In general, Proteobacteria were the most dominant phyla with predominance of Deltaproteobacteria, Alphaproteobacteria, and Gammaproteobacteria within the sediments. Besides Proteobacteria, there are a number of sequences affiliated to the following major phyla detected in all three stations in both the sampling seasons: Actinobacteria, Bacteroidetes, Planctomycetes, Acidobacteria, Chloroflexi, Cyanobacteria, Nitrospira, and Firmicutes. Further taxonomic analysis revealed abundance of micro-aerophilic and anaerobic microbial population in the surface layers, suggesting anaerobic nature of the sediments in Sundarbans. The results of this study add valuable information about the composition of microbial communities in Sundarbans mangrove and shed light on possible transformations promoted by bacterial communities in the sediments.

Carbonic anhydrase (CA), a well-characterized metalloenzyme, is associated with oxygen-18 ( 18O)-isotopic fractionations of CO2. To investigate how CA activity links the 18O of breath CO2 to pre-diabetes (PD) and type 2 diabetes (T2D) during metabolism, we studied pre- and post-dose CA activities in erythrocytes with simultaneous monitoring of 18O/ 16O-isotope ratios of breath CO2 and thereafter elucidated potential metabolic pathways underlying CA alteration in the pathogenesis of T2D. Here we show that the post-dose CA activity in both T2D and PD was markedly enhanced, whereas the non-diabetic controls (NDC) exhibited a considerable reduction in post-dose CA activity when compared with their basal CA activities. However, T2D and PD exhibited isotopic enrichments of 18O in breath CO2, while a marked depletion of 18O in CO2 was manifested in NDC. Thus, the isotopic enrichments and depletions of 18O in breath CO2 were well correlated with the changes in CA activities for controls, PD and T2D. Our findings suggest the changes in CA activities in erythrocytes may contribute to the pathogenesis of T2D and the breath C 18O 16O regulated by the CA activity as a potential biomarker for non-invasive assessment of T2D, and thus may open a new method for treating T2D.

We report, for the first time, the clinical feasibility of a novel residual gas analyzer mass spectrometry (RGA-MS) method for accurate evaluation of the (13)C-glucose breath test ((13)C-GBT) in the diagnosis of pre-diabetes (PD) and type 2 diabetes mellitus (T2D). In T2D or PD, glucose uptake is impaired and results in blunted isotope enriched (13)CO2 production in exhaled breath samples. Using the Receiver operating characteristics (ROC) curve analysis, an optimal diagnostic cut-off point of the (13)CO2/(12)CO2 isotope ratios expressed as the delta-over-baseline (DOB) value, was determined to be δDOB(13)C‰ = 28.81‰ for screening individuals with non-diabetes controls (NDC) and pre-diabetes (PD), corresponding to a sensitivity of 100% and specificity of 94.4%. We also determined another optimal diagnostic cut-off point of δDOB(13)C‰ = 19.88‰ between individuals with PD and T2D, which exhibited 100% sensitivity and 95.5% specificity. Our RGA-MS methodology for the (13)C-GBT also manifested a typical diagnostic positive and negative predictive value of 96% and 100%, respectively. The diagnostic accuracy, precision and validity of the results were also confirmed by high-resolution optical cavity enhanced integrated cavity output spectroscopy (ICOS) measurements. The δDOB(13)C‰ values measured with RGA-MS method, correlated favourably (R(2) = 0.979) with those determined by the laser based ICOS method. Moreover, we observed that the effects of endogenous CO2 production related to basal metabolic rates in individuals were statistically insignificant (p = 0.37 and 0.73) on the diagnostic accuracy. Our findings suggest that the RGA-MS is a valid and sufficiently robust method for the (13)C-GBT which may serve as an alternative non-invasive point-of-care diagnostic tool for routine clinical practices as well as for large-scale diabetes screening purposes in real-time.

Mangrove microbial communities and their associated activities have profound impact on biogeochemical cycles. Although microbial composition and structure are known to be influenced by biotic and abiotic factors in the mangrove sediments, finding direct correlations between them remains a challenge. In this study we have explored sediment bacterial diversity of the Sundarbans, a world heritage site using a culture-independent molecular approach. Bacterial diversity was analyzed from three different locations with a history of exposure to differential anthropogenic activities. 16S rRNA gene libraries were constructed and partial sequencing of the clones was performed to identify the microbial strains. We identified bacterial strains known to be involved in a variety of biodegradation/biotransformation processes including hydrocarbon degradation, and heavy metal resistance. Canonical Correspondence Analysis of the environmental and exploratory datasets revealed correlations between the ecological indices associated with pollutant levels and bacterial diversity across the sites. Our results indicate that sites with similar exposure of anthropogenic intervention reflect similar patterns of microbial diversity besides spatial commonalities.

The magnitude of type 2 diabetes mellitus (T2DM) is ever-increasing in India, and at present, ~77 million people live with diabetes. Studies have established that T2DM increases the risk of neurodegenerative disorders. This study aimed to determine the age-related prevalence of mild cognitive impairment (MCI) in T2DM patients in the Indian population and to identify link between cognitive dysfunction in T2DM patients and serum lipid composition through untargeted and targeted lipidomic studies. Using a cross-sectional study, we evaluated 1278 T2DM patients with Montreal cognitive assessment test (MoCA) and digit symbol substitution test (DSST) for cognitive functions. As per MoCA, the prevalences of MCI in T2DM patients in age groups below 40, 41-50, 51-60, 61-70, 71-80 and 81-90 years were 13.7, 20.5, 33.5, 43.7, 57.1 and 75% with DSST scores of 45.8, 41.7, 34.4, 30.5, 24.2 and 18.8% respectively. Binomial logistic regression analysis revealed serum HbA1c ≥ 7.51, duration of T2DM over 20 years, age above 41 years, and females were independent contributors for cognitive dysfunction in T2DM patients. Preliminary studies with untargeted lipidomics of the serum from 20 T2DM patients, including MCI and normal cognition (NC) group, identified a total of 646 lipids. Among the identified lipids, 33 lipids were significantly different between MCI and NC group, which comprised of triglycerides (TGs, 14), sphingolipids (SL, 11), and phosphatidylcholines (PC, 5). Importantly, 10 TGs and 3 PCs containing long-chain polyunsaturated fatty acids (PUFA) were lower, while 8 sphingolipids were increased in the MCI group. Since brain-derived sphingolipids are known to get enriched in the serum, we further quantified sphingolipids from the same 20 serum samples through targeted lipidomic analysis, which identified a total of 173 lipids. Quantitation revealed elevation of 3 species of ceramides, namely Cer (d18:1_24:1), Hex1Cer (d16:0_22:6), and Hex2Cer (d28:1) in the MCI group compared to the NC group of T2DM patients. Overall, this study demonstrated an age-related prevalence of MCI in T2DM patients and highlighted reduced levels of several species of PUFA containing TGs and PCs and increased levels of specific ceramides in T2DM patients exhibiting MCI. Large-scale lipidomic studies in future could help understand the cognitive dysfunction domain in T2DM patients, while studies with preclinical models are required to understand the functional significance of the identified lipids.

No abstract