Plastic pyrolytic oils as renewable fuel: improving its physical properties and ignition patterns by waste renewable source-an experimental analysis.

The increase in plastic products and disposal poses a severe environmental challenge because of their poor biodegradability and undesirable disposal by landfilling. Recycling is the best possible solution to the environmental challenges implemented by the plastic industry. Pyrolysis is a process that converts waste plastics into pyrolytic oil, and it can be used as fuel in a blended form. The viscosity and lubricity of the LDWP (low-density waste polyethylene) pyrolytic oil were lower than standard diesel. Capparis spinosa methyl ester (CME) is blended and experimented with to overcome the lubricity issue of pyrolytic oil. In this investigation, 5%, 10%, and 15% CME were blended with PD20 (20% LDWP oil + 80% diesel) blend on a volume basis. Experiments were conducted to examine the effects of CME on combustion, performance, and emissions using the combination of CME and PD20 blend tested at 0%, 25%, 50%, 75%, and 100% loading conditions. All three ternary mixtures showed enhanced combustion performance and increased NOx and smoke emissions. Due to better combustion, the efficiency of the blend PCD10 (10% CME + 20% LDWP oil + 70% diesel) was higher than the PD20 blend and significantly closer to diesel. Hence, PCD10 is suggested as an alternative to diesel fuel.

A methodology employing retention modeling for achieving control space in liquid chromatography method development using quality by design approach.

This study reports the application of retention modeling and quality by design practices for reverse-phase liquid chromatographic method development of a new chemical entity. Prior to the retention modeling, preliminary screening experiments were performed for the selection of stationary phase, organic modifiers, and method parameters. Based on the results of preliminary method conditions, tG-T (gradient time - temperature) 2-D modeling with 4 input runs, and tG-T-tc (gradient time-temperature-ternary composition) 3-D modeling with 12 input runs were designed to build a model for achieving the optimized separation. Modeling of reverse phase separations was based on the measurement of both retention times and peak areas. A design space with appropriate input variables and control strategy was established prior to optimization and robustness evaluation following the quality by design framework. DryLabⓇ was used to predict the optimized gradient profile and separation temperature. The robustness evaluation was carried out using the multiple factors at a time approach and the control space was established. The interdependence of control space and the control strategy was demonstrated by evaluating method robustness using two levels of system suitability criteria. The predictive accuracy of the retention modeling was established through experimental verification of the in-silico predictions. The quality by design based method development approach demonstrated the in-silico optimization as an integral component of reverse-phase chromatographic method development to evaluate the interplay of factors such as organic modifiers, separation temperature and gradient time, which greatly integrated and enhanced method robustness during method development.

Clinical Profile of Elderly Patients (Over 90 Years) with Type 2 Diabetes Seen at a Diabetes Center in South India.

Background: The current life expectancy in India is <70 years. Type 2 diabetes mellitus (T2DM) is known to reduce life expectancy by 6-8 years. Hence elderly people with T2DM in India would be rare. We report on the clinical profile of Asian Indian patients with T2DM who lived beyond 90 years of age and compared them with T2DM patients aged 50 to 60 years. Methods: From the diabetes electronic medical records of >470,000 diabetes patients, we identified T2DM patients who had lived ≥90 years and compared them with those in the 50-60 years age group, matched for gender and duration of diabetes. Clinical data included age at last visit, age at diagnosis, duration of diabetes, family history, smoking and alcohol, details of medications, body mass index (BMI), and blood pressure. Biochemical data included fasting and postprandial plasma glucose, glycated hemoglobin, fasting and stimulated C-peptide levels, lipid profile, and renal function studies. Assessment of retinopathy, nephropathy, neuropathy, coronary artery disease (CAD), and peripheral vascular disease (PVD) was also done. Results: A total of 325 T2DM patients aged ≥90 years and 278 T2DM patients aged between 50 and 60 years were selected for the study. Patients aged ≥90 years had higher systolic blood pressure (P < 0.001) and lower BMI (P < 0.001) than those between 50 and 60 years. Prevalence of retinopathy (29.7% vs. 53.5%) and macroalbuminuria (3.7% vs. 16.0%) was lower in the ≥90 years T2DM patients than in the 50-60 years age group. However, prevalence of neuropathy (89.8% vs. 50.8%), PVD (13.5% vs. 2.0%), and CAD (60.3% vs. 32.0%) was higher among the ≥90 years patients. Eighty-five percent of the T2DM aged ≥90 years were on oral hypoglycemic agents (OHAs), (of whom 64.9% were on sulfonylurea), 12% were on insulin, and 3% on diet alone. Among the 50-60 years old, 87.8% were on OHAs and 12.2% on insulin. Conclusions: This is the first report on the clinical profile of Asian Indians with T2DM aged ≥90 years, and significant differences are seen in their clinical profile compared with younger T2DM patients.