ESTIMATION OF GUGGULSTERONE-Z IN GOKSHURADI GUGGULU USING REVERSED-PHASE HIGH-PERFORMANCE LIQUID CHROMATOGRAPHY

Objective: A study was aimed to estimate guggulsterone-Z (GZ) in Gokshuradi Guggulu (GG).Methods: An analytical method was developed and validated using Waters Alliance high-performance liquid chromatography system (Empower software), equipped with photodiode array detector. Separation was achieved using Phenomenex, C-18 (250 mm×4.6 mm, 5 μ) column. Mobile phase consisted of acetonitrile:water (70:30,v/v). Flow rate was set to 1 ml/min and detection was performed at 251 nm.Results and Discussion: Validation parameters such as linearity, precision, accuracy, limit of detection, limit of quantification, and robustness were performed. Amount of GZ was estimated using linearity equation.Conclusion: GG was found to contain 0.815±0.03 g% w/w GZ. Validated method may be used as one of the parameters to standardize the formulation

Persistence of Primary and Secondary Pollutants in Delhi : Concentrations and Composition from 2017 through the COVID Pandemic

We assess impacts of the 2020 COVID-19 lockdown on ambient air quality in Delhi, building on over three years of real-time measurements of black carbon (BC) and nonrefractory submicrometer aerosol (NR-PM1) composition from the Delhi Aerosol Supersite and public data from the regulatory monitoring network. We performed source apportionment of organic aerosol (OA) and robust statistical analyses to differentiate lockdown-related impacts from baseline seasonal and interannual variability. The primary pollutants NOx, CO, and BC were most reduced, primarily due to lower transportation emissions. Local and regional emissions such as agricultural burning decreased during the lockdown. PM2.5 declined but remained well above WHO guidelines. Despite the lockdown, NR-PM1 changed only moderately compared to prior years. Differences in the trends of hydrocarbon-like OA and BC suggest that some sources of primary aerosol may have increased. Despite notable reductions in some primary pollutants, the lockdown restrictions led to rather small perturbations in the primary fraction of NR-PM1, with secondary aerosol continuing to dominate. Overall, our results demonstrate the impact of secondary and primary pollution on Delhi's air quality and show that large changes in emissions within Delhi alone are insufficient to bring about needed improvements in air quality.Peer reviewe

Persistence of Primary and Secondary Pollutants in Delhi : Concentrations and Composition from 2017 through the COVID Pandemic

We assess impacts of the 2020 COVID-19 lockdown on ambient air quality in Delhi, building on over three years of real-time measurements of black carbon (BC) and nonrefractory submicrometer aerosol (NR-PM1) composition from the Delhi Aerosol Supersite and public data from the regulatory monitoring network. We performed source apportionment of organic aerosol (OA) and robust statistical analyses to differentiate lockdown-related impacts from baseline seasonal and interannual variability. The primary pollutants NOx, CO, and BC were most reduced, primarily due to lower transportation emissions. Local and regional emissions such as agricultural burning decreased during the lockdown. PM2.5 declined but remained well above WHO guidelines. Despite the lockdown, NR-PM1 changed only moderately compared to prior years. Differences in the trends of hydrocarbon-like OA and BC suggest that some sources of primary aerosol may have increased. Despite notable reductions in some primary pollutants, the lockdown restrictions led to rather small perturbations in the primary fraction of NR-PM1, with secondary aerosol continuing to dominate. Overall, our results demonstrate the impact of secondary and primary pollution on Delhi's air quality and show that large changes in emissions within Delhi alone are insufficient to bring about needed improvements in air quality.Peer reviewe

Higher Risk for Incident Heart Failure and Cardiovascular Mortality among Community-Dwelling Octogenarians without Pneumococcal Vaccination

AIMS: Octogenarians have the highest incidence of heart failure (HF) that is not fully explained by traditional risk factors. We explored whether lack of pneumococcal vaccination is associated with higher risk of incident HF among octogenarians. METHODS AND RESULTS: In the Cardiovascular Health Study (CHS), 5290 community-dwelling adults, ≥65 years of age, were free of baseline HF and had data on pneumococcal vaccination. Of these, 851 were octogenarians, of whom, 593 did not receive pneumococcal vaccination. Multivariable-adjusted hazard ratios (aHR) and 95% confidence intervals (CI) for associations of lack of pneumococcal vaccination with incident HF and other outcomes during 13 years of follow-up were estimated using Cox regression models, adjusting for demographics and other HF risk factors including influenza vaccination. Octogenarians had a mean (±SD) age of 83 (±3) years; 52% were women and 17% African American. Overall, 258 participants developed HF and 662 died. Lack of pneumococcal vaccination was associated with higher relative risk of incident HF (aHR, 1.37; 95% CI, 1.01-1.85; P = 0.044). There was also higher risk for all-cause mortality (aHR, 1.23; 95% CI, 1.02-1.49; P = 0.028), which was mostly driven by cardiovascular mortality (aHR, 1.45; 95% CI, 1.06-1.98; P = 0.019). Octogenarians without pneumococcal vaccination had a trend toward higher risk of hospitalization due to pneumonia (aHR, 1.34; 95% CI, 0.99-1.81; P = 0.059). These associations were not observed among those 65-79 years of age. CONCLUSIONS: Among community-dwelling octogenarians, lack of pneumococcal vaccination was associated with a significantly higher independent risk of incident HF and mortality, and trend for higher pneumonia hospitalization

Similar clinical benefits from below‐target and target dose enalapril in patients with heart failure in the SOLVD Treatment trial

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/142515/1/ejhf937.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/142515/2/ejhf937_am.pd

Understanding the electrochemistry of "water-in-salt" electrolytes: basal plane highly ordered pyrolytic graphite as a model system.

From Europe PMC via Jisc Publications RouterHistory: ppub 2020-06-01, epub 2020-06-08Publication status: PublishedFunder: Engineering and Physical Sciences Research Council; Grant(s): EP/R023034/1, EP/K005014/1A new approach to expand the accessible voltage window of electrochemical energy storage systems, based on so-called "water-in-salt" electrolytes, has been expounded recently. Although studies of transport in concentrated electrolytes date back over several decades, the recent demonstration that concentrated aqueous electrolyte systems can be used in the lithium ion battery context has rekindled interest in the electrochemical properties of highly concentrated aqueous electrolytes. The original aqueous lithium ion battery conception was based on the use of concentrated solutions of lithium bis(trifluoromethanesulfonyl)imide, although these electrolytes still possess some drawbacks including cost, toxicity, and safety. In this work we describe the electrochemical behavior of a simple 1 : 1 electrolyte based on highly concentrated aqueous solutions of potassium fluoride (KF). Highly ordered pyrolytic graphite (HOPG) is used as well-defined model carbon to study the electrochemical properties of the electrolyte, as well as its basal plane capacitance, from a microscopic perspective: the KF electrolyte exhibits an unusually wide potential window (up to 2.6 V). The faradaic response on HOPG is also reported using K3Fe(CN)6 as a model redox probe: the highly concentrated electrolyte provides good electrochemical reversibility and protects the HOPG surface from adsorption of contaminants. Moreover, this electrolyte was applied to symmetrical supercapacitors (using graphene and activated carbon as active materials) in order to quantify its performance in energy storage applications. It is found that the activated carbon and graphene supercapacitors demonstrate high gravimetric capacitance (221 F g-1 for activated carbon, and 56 F g-1 for graphene), a stable working voltage window of 2.0 V, which is significantly higher than the usual range of water-based capacitors, and excellent stability over 10 000 cycles. These results provide fundamental insight into the wider applicability of highly concentrated electrolytes, which should enable their application in future of energy storage technologies

Factors influencing ambient particulate matter : from Texas to New Delhi

Long term exposure to particulate matter (PM) has been linked to an increase in mortality and cardiorespiratory diseases. In addition, PM affects Earth’s radiative balance, and is one of the main sources of uncertainty in climate change predictions. Hence, it is imperative to understand PM composition and concentrations and the factors contributing to their variability. Different parts of the world experience different levels of air pollution, due to an interplay between various factors including sources, meteorological factors, and chemical transformations. PM can either be directly emitted into the atmosphere (primary) or can be generated as result of oxidation of gas-phase precursors leading to the formation and partitioning of low volatility products to the particle phase (secondary). The nature, sources and dynamics of PM can be estimated by combining ambient field measurements with receptor modeling, machine learning and statistical analysis tools. The objective of my thesis is to understand the factors influencing PM concentration and composition in different environments. In chapter 2, I have reported the results of the measurements in Austin, Texas, one of the fastest growing metropolitan cities in the U.S. I used several modeling and data analysis tools to understand the sources and formation of particulate matter in Austin including positive matrix factorization (PMF), the Extended Aerosol Thermodynamics Model (E-AIM) and air back trajectory analysis using HYSPLIT. Through my analysis, I demonstrated that photochemistry is an important factor in governing PM composition in Austin. We observed rapid photochemical processing of traffic emissions, H₂SO₄-driven new particle formation (NPF) events, production of organic nitrate, and daytime peaks in the locally formed oxidized organic aerosol during the summer period. My analysis also suggested that SO₂ emissions from cement kilns may be the main source of particulate sulfate observed at this receptor site, pointing toward the need for measurements at the source to investigate this further. This chapter has been published in ACS Earth and Space Chemistry. Meanwhile, Delhi (India) is the most polluted megacity in the world and routinely experiences extreme pollution episodes. Our group is one of the first in the world to measure long term PM composition at high time resolution in the city. As part of the Delhi Aerosol Supersite (DAS) study, we have recorded over five years of near-continuous PM composition to understand inter-seasonal as well as inter-annual variability in the PM concentrations and the factors influencing them. I have studied specific “special” events which have implications for policy decisions. In chapter 3, I have investigated the factors influencing high PM concentrations observed during the autumn (~Sep – Nov) season which experiences some of the most extreme pollution episodes observed anywhere in the world. I combined our measurements with data obtained from regulatory monitoring sites (CO, NOₓ, PM₂.₅) to gain insights from the temporal trends of the pollutants and to demonstrate the differences between autumn and winter, which also experiences high concentrations. I incorporated receptor models and non-parametric wind regression to understand the nature and sources of PM during this period. Further, I used meteorological data such as temperature, planetary boundary layer height, wind speed/direction and relative humidity to understand their impact on PM using statistical hypothesis testing. Using these tools, I demonstrated the influence of regional agricultural burning (from the neighboring states) and fireworks during the festival of Diwali on PM during this season. Overall, my analysis provided detailed insights into the sources and dynamics of PM during one of the most polluted seasons in Delhi (and in the world) and provided a direction for future studies in the region. This chapter has also been published in ACS Earth and Space Chemistry. In chapter 4, I have investigated the impact of COVID-19 lock-down on Delhi's air quality by combining PM and gas phase data of over four years with robust statistical analysis, including the method of “robust differences” to account for seasonal variability in the pollutant concentrations. My analysis suggests that future large-scale modification of activity restrictions in Delhi may impact the primary pollutants (NOₓ, CO, black carbon) more than the secondary pollutants, emphasizing the fundamental importance of secondary or regional pollutants on air quality in Delhi. I showed that overall, future strict activity reductions may lead to only a moderate reduction in PM₁, reflective of complex PM₁ chemistry and the need for integrative, multiscale, and multisectoral policies to address the major air pollution challenge in Delhi. This chapter has been published in ACS Environmental Science & Technology Letters. Because of the interplay between sources and meteorology in Delhi, in chapter 5 I have developed machine learning models incorporating random forest regression that estimate the concentrations of PM₁ and its constituents by using meteorology and emission proxies. I have demonstrated the applicability of these models to capture temporal variability of the PM₁ species, to understand the influence of individual factors via sensitivity analyses, and to separate impacts of the COVID-19 lockdowns and associated activity restrictions from impacts of other factors. Overall, these models provide new insights into the factors influencing ambient PM₁ in New Delhi, India, demonstrating the power of machine learning models in atmospheric science applications. This chapter will be submitted to Aerosol Science and Technology. My research has advanced our understanding about PM formation and processing in different environments. These novel measurements and analyses will help guide future studies aimed at understanding and improving ambient air quality in these regions. Furthermore, the results of my scientific analyses may help guide policy decisions aimed at reducing PM levels in the atmosphere, thus helping improve the lives of millions of people.Chemical Engineerin