Circulating micrornas associated with glycemic impairment and progression in Asian Indians.

Aims/hypothesisAsian Indians have a high incidence of type 2 diabetes, but factors associated with glycemic progression in this population are not understood. MicroRNAs are emerging as important mediators of glucose homeostasis and have not been previously studied in Asian Indians. We examined microRNA (miR) expression associated with glycemic impairment and progression in Asian Indians from the San Francisco Bay Area. We studied 128 Asian Indians age 45-84 years without known cardiovascular disease and not taking diabetes medications. Oral glucose tolerance tests were performed at baseline and after 2.5 years. We quantified circulating miRs from plasma collected during the enrollment visit using a flow cytometry-based assay.ResultsGlycemic impairment was present in 57 % (n = 73) at baseline. MiR-191 was positively associated with glycemic impairment (odds ratio (OR) 1.7 (95 % CI 1.2, 2.4), p < 0.01). The prevalence of glycemic progression after 2.5 years was 24 % (n = 23). Six miRs were negatively associated with glycemic progression: miR-122 (OR 0.5 (0.2, 0.8), p < 0.01), miR-15a (OR 0.6 (0.4, 0.9), p < 0.01), miR-197 (OR 0.6 (0.4, 0.9), p < 0.01), miR-320a (OR 0.6 (0.4, 0.9), p < 0.01), miR-423 (OR 0.6 (0.4, 0.9), p < 0.01), and miR-486 (OR 0.5 (0.3, 0.8), p < 0.01). Further multivariate adjustment did not attenuate these results.Conclusions/interpretationThis is the first study to investigate circulating miRs associated with glycemic status among this high-risk ethnic group. Individual miRs were significantly associated with both glycemic impairment and glycemic progression. Further studies are needed to determine whether miR (s) might be useful clinical biomarkers for incident T2D in the Asian Indian population

Long-term electrode behavior during treatment of arsenic contaminated groundwater by a pilot-scale iron electrocoagulation system.

Iron electrocoagulation (Fe-EC) is an effective technology to remove arsenic (As) from groundwater used for drinking. A commonly noted limitation of Fe-EC is fouling or passivation of electrode surfaces via rust accumulation over long-term use. In this study, we examined the effect of removing electrode surface layers on the performance of a large-scale (10,000 L/d capacity) Fe-EC plant in West Bengal, India. We also characterized the layers formed on the electrodes in active use for over 2 years at this plant. The electrode surfaces developed three distinct horizontal sections of layers that consisted of different minerals: calcite, Fe(III) precipitates and magnetite near the top, magnetite in the middle, and Fe(III) precipitates and magnetite near the bottom. The interior of all surface layers adjacent to the Fe(0) metal was dominated by magnetite. We determined the impact of surface layer removal by mechanical abrasion on Fe-EC performance by measuring solution composition (As, Fe, P, Si, Mn, Ca, pH, DO) and electrochemical parameters (total cell voltage and electrode interface potentials) during electrolysis. After electrode cleaning, the Fe concentration in the bulk solution increased substantially from 15.2 to 41.5 mg/L. This higher Fe concentration led to increased removal of a number of solutes. For As, the concentration reached below the 10 μg/L WHO MCL more rapidly and with less total Fe consumed (i.e. less electrical energy) after cleaning (128.4 μg/L As removed per kWh) compared to before cleaning (72.9 μg/L As removed per kWh). Similarly, the removal of P and Si improved after cleaning by 0.3 mg/L/kWh and 1.1 mg/L/kWh, respectively. Our results show that mechanically removing the surface layers that accumulate on electrodes over extended periods of Fe-EC operation can restore Fe-EC system efficiency (concentration of solute removed/kWh delivered). Since Fe release into the bulk solution substantially increased upon electrode cleaning, our results also suggest that routine electrode maintenance can ensure robust and reliable Fe-EC performance over year-long timescales

Monsoon prediction - Why yet another failure?

The country experienced a deficit of 13 in the summer monsoon of 2004. As in 2002, this deficit was not predicted either by the operational empirical models at India Meteorological Department (IMD) or by the dynamical models at national and international centres. Our analysis of the predictions generated by the operational models at IMD from 1932 onwards suggests that the forecast skill has not improved over the seven decades despite continued changes in the operational models. Clearly, new approaches need to be explored with empirical models. The simulation of year-to-year variation of the monsoon is still a challenging problem for models of the atmosphere as well as the coupled ocean-atmosphere system. We expect dynamical models to generate better prediction only after this problem is successfully addressed

Parking and the visual perception of space

Using measured data we demonstrate that there is an amazing correspondence among the statistical properties of spacings between parked cars and the distances between birds perching on a power line. We show that this observation is easily explained by the fact that birds and human use the same mechanism of distance estimation. We give a simple mathematical model of this phenomenon and prove its validity using measured data

Monsoon variability: Links to major oscillations over the equatorial Pacific and Indian oceans

In this article, we first discuss our perception of the factors which are critical for inter-annual variation of the Indian summer monsoon rainfall and the major milestones leading to this understanding. The nature of the two critical modes for monsoon variability, viz. El Nino Southern Oscillation and equatorial Indian Ocean Oscillation is considered and their links to the monsoon elucidated. We suggest possible reasons for the rather poor skill of simulation of the interannual variation of the Indian summer monsoon rainfall by atmospheric general circulation models, run with the observed sea surface temperature as boundary condition. We discuss implications of what we have learned for the monsoon of 2006, and possible use of information on the two important modes for prediction of the rainfall in all or part of the summer monsoon season. We conclude with our view of what the focus of research and development should be for achieving a substantial improvement in the skill of simulation and prediction of the Indian summer monsoon rainfall in the near future

Predicting the extremes of Indian summer monsoon rainfall with coupled ocean-atmosphere models

An analysis of the retrospective predictions by seven coupled ocean-atmosphere models from major forecasting centres of Europe and USA, aimed at assessing their ability in predicting the interannual variation of the Indian summer monsoon rainfall (ISMR), particularly the extremes (i.e. droughts and excess rainfall seasons) is presented in this article. On the whole, the skill in prediction of extremes is not bad since most of the models are able to predict the sign of the ISMR anomaly for a majority of the extremes. There is a remarkable coherence between the models in successes and failures of the predictions, with all the models generating loud false alarms for the normal monsoon season of 1997 and the excess monsoon season of 1983. It is well known that the El Niño and Southern Oscillation (ENSO) and the Equatorial Indian Ocean Oscillation (EQUINOO) play an important role in the interannual variation of ISMR and particularly the extremes. The prediction of the phases of these modes and their link with the monsoon has also been assessed. It is found that models are able to simulate ENSO-monsoon link realistically, whereas the EQUINOO-ISMR link is simulated realistically by only one model-the ECMWF model. Furthermore, it is found that in most models this link is opposite to the observed, with the predicted ISMR being negatively (instead of positively) correlated with the rainfall over the western equatorial Indian Ocean and positively (instead of negatively) correlated with the rainfall over the eastern equatorial Indian Ocean. Analysis of the seasons for which the predictions of almost all the models have large errors has suggested the facets of ENSO and EQUINOO and the links with the monsoon that need to be improved for improving monsoon predictions by these models

Prediction of Indian rainfall during the summer monsoon season on the basis of links with equatorial Pacific and Indian Ocean climate indices

Interannual variation of Indian summer monsoon rainfall (ISMR) is linked to El Niño-Southern oscillation (ENSO) as well as the Equatorial Indian Ocean oscillation (EQUINOO) with the link with the seasonal value of the ENSO index being stronger than that with the EQUINOO index. We show that the variation of a composite index determined through bivariate analysis, explains 54% of ISMR variance, suggesting a strong dependence of the skill of monsoon prediction on the skill of prediction of ENSO and EQUINOO. We explored the possibility of prediction of the Indian rainfall during the summer monsoon season on the basis of prior values of the indices. We find that such predictions are possible for July–September rainfall on the basis of June indices and for August–September rainfall based on the July indices. This will be a useful input for second and later stage forecasts made after the commencement of the monsoon seaso

Realization of 2-dimensional air-bridge silicon photonic crystals by focused ion beam milling and nanopolishing

We report the design and fabrication of small photonic crystal structures which are combined with conventional dielectric ridge waveguides. We describe in details the fabrication of both rough and smooth membranes, which are used as host for photonic crystals. Two Focused Ion Beam milling experiments are highlighted: the first one shows how photonic crystals can be fast and accurate milled into a Si membrane, whereas the second experiment demonstrates how focused ion beam milling can turn a rough surface into a well-patterned nano-smooth surface. The previously ultra rough surface showed no detectable roughness after milling due to the nanopolishing effect of the focused ion beam milling

Alignment issues in photonic crystal device fabrication

An important requirement in the fabrication of photonic crystal structures is the correct relative alignment of structural elements. Accuracy should be in the order of some tens of nanometres. Some of the options for providing such accuracy are discussed. Examples are given of aligning defects with respect to a predefined 2D lattice, aligning access waveguides with respect to a small local photonic crystal structure, and the alignment of successive periodically structured layers in a 3D "woodpile" structure

Rapid and Efficient Arsenic Removal by Iron Electrocoagulation Enabled with in Situ Generation of Hydrogen Peroxide.

Millions of people are exposed to toxic levels of dissolved arsenic in groundwater used for drinking. Iron electrocoagulation (FeEC) has been demonstrated as an effective technology to remove arsenic at an affordable price. However, FeEC requires long operating times (∼hours) to remove dissolved arsenic due to inherent kinetics limitations. Air cathode Assisted Iron Electrocoagulation (ACAIE) overcomes this limitation by cathodically generating H2O2 in situ. In ACAIE operation, rapid oxidation of Fe(II) and complete oxidation and removal of As(III) are achieved. We compare FeEC and ACAIE for removing As(III) from an initial concentration of 1464 μg/L, aiming for a final concentration of less than 4 μg/L. We demonstrate that at short electrolysis times (0.5 min), i.e., high charge dosage rates (1200 C/L/min), ACAIE consistently outperformed FeEC in bringing arsenic levels to less than WHO-MCL of 10 μg/L. Using XRD and XAS data, we conclusively show that poor arsenic removal in FeEC arises from incomplete As(III) oxidation, ineffective Fe(II) oxidation and the formation of Fe(II-III) (hydr)oxides at short electrolysis times (<20 min). Finally, we report successful ACAIE performance (retention time 19 s) in removing dissolved arsenic from contaminated groundwater in rural California