Objective: To predict the role of clinical risk factors and urinary β2-microglobulin levels as a biomarker for steroid-resistant nephrotic syndrome. Study Design: Quasi-experimental study. Place and Duration of Study: Paediatric Nephrology Department, Sindh Institute of Urology and Transplantation, Karachi Pakistan, from Jun 2019 to Nov 2020. Methodology: All children (3 months to 12 years) with either first episode or relapse of the nephrotic syndrome were included. A stored urine sample was used on 100 patients with steroid-sensitive (group-1) and 35 patients with steroid-resistant nephrotic syndrome (group-2). In addition, histopathology of all patients with steroid-resistant nephrotic syndrome was recorded. Results: Both groups and those who had focal segmental glomerulosclerosis were compared and analysed to evaluate the predictability of steroid response. There was a significant association in both groups for microscopic haematuria, hypertension, heavy proteinuria (urine spot protein to creatinine ratio >10 g/g) and increased β2-microglobulin levels (> 3× normal) as individual risk factors (p<0.01). The sensitivity of β2-microglobulin levels was 78% and a positive predictive value of 80%. Multivariate regression analysis on steroid-resistant nephrotic syndrome as a group did not confer a higher risk; however, for children with focal segmental glomerulosclerosis, the likelihood of steroid unresponsiveness was significantly higher for the same parameters. Conclusion: The addition of biomarker measurement and known clinical risk factors helped predict steroid-resistant focal segmental glomerulosclerosis. However, further studies are warranted before these results can be generalized.
Biodiesel is being considered a possible alternative fuel due to its similarity with diesel and environmental benefits. This current work involves a numerical investigation of CI engine characteristics operating on D100 (diesel) and Dunaliella tertiolecta (DMB20), Scenedesmus obliquus (SOMB20), Scenedesmus dimorphu (SDMB20), and Chlorella protothecoides (CMB20) microalgae biodiesel blend. A diesel engine of 3.7 kW was used with variable compression ratios (CRs) (15.5, 16.5, 17.5, and 18.5) and constant speed (1500 rpm). Comparative analysis was performed for engine characteristics, including emission, combustion, and performance. Cylinder pressure, heat release rate, brake thermal efficiency, specific fuel consumption, particulate matter, oxide of nitrogen, carbon dioxide, etc., were evaluated using the blended fuel. The results show that the maximum cylinder pressure falls, SFC increases, and EGT and BTE were reduced for all blends at full load. In terms of emission characteristics, PM and smoke were lowered when compared to diesel, but a slight increment in NOx and CO2 was observed. Among all the blends, SOMB20 shows the most decrement in PM and smoke emissions by 14.16% and 11.6%, respectively, at CR 16.5. CMB20 shows a maximum increment in SFC by 3.22% at CR 17.5. A minimum reduction in CP and HRR was shown by DMB20 irrespective of CRs.
Objective: The aim of this study is to determine the zinc levels in children with upper respiratory tract infection in the age of 2-12 years in Pakistan. Study Design: A prospective observational Place and Duration: Conducted at department of Paediatrics Hamdard University hospital, Karachi and PIMS Children Hospital, Islamabad for four months duration from October, 2020 to January, 2021. Methods: Total 90 children of both genders were presented in this study. Patients’ detailed demographics including age, sex, socio-economic class and maternal education were recorded after taking informed written consent from the authorities. Patients with upper respiratory tract infection were included. Mean serum zinc among children was calculated as 55.14±17.68 μg/dl. Outcomes were measured in terms of risk factors associated with URT and lower level of serum zinc among patients. Complete data was analyzed by SPSS 24.0 version. Results: There were 60 (66.7%) males and 30 (33.3%) were females. Mean age of the cases were 08.44±7.65 years. 62 (68.9%) patients were from lower socio economic status and literacy rate of mothers were 35 (38.9%).Symptoms of URTI were cough, sore throat, runny nose and headache. Previous family history of URTI found in 55 (61.1%) cases. Rhinovirus was the most common cause of URTI found in 70(77.8%) cases. Severity of cold was found among 18 (20%) children. Meanserum zinc was38.76±6.88 μg/dl and found among 87 (96%) cases. Conclusion: We concluded in this study that the zinc level was significantly lower among children who had rhinovirus due to severe cold. Keywords: Serum Zinc Level, Children, Upper Respiratory Tract Infection
Creating reservoir model that is accurate requires extensive data and enormous computing resources. As these resources are often not available, this study proposes a workflow (& corresponding case study) to generate box reservoir models that require minimum data yet yield reasonable results. Field Lima has two wells Lima-1 & Lima-2 (down-dip well) that produces gas from Sand-B which is a moderate water drive reservoir. After producing gas naturally, Lima-2 watered-out while Lima-1 still produced gas. To curtail the increase of Water Gas Ratio (WGR) in Lima-1, a coproduction technique was evaluated. The intent was to produce water from Lima-2 at high rates to reduce WGR increase in Lima-1. This required reservoir simulation to predict if producing water from Lima-2 will limit aquifer encroachment at Lima-1 and justify the additional CAPEX required to install water handling facility at Lima-2. As Lima is a marginal field, available dataset only included; initial reservoir pressure, production history and standard open-hole logs. No permeability, aquifer or pressure history data was available. Therefore, a workflow was formulated to create a reservoir model that can predict production rates of Lima-1 using available data within engineering accuracy. Firstly, the pressure history was created using recorded flowing wellhead pressures and wellbore hydraulics model. Further, a tank model was created for the reservoir using material balance software and cumulative productions of both wells were used as unique data to calibrate the model. This was used to calculate the aquifer properties. Fractional flow models & Corey correlations were used to estimate relative permeability data. All this derived data was then used as input in the reservoir simulator, where a localized block grid was created using depth-structure maps of Sand-B. The model was history matched using production data of Lima-1 & Lima-2 and aquifer movement was calibrated using water breakthrough in Lima-2. Finally, the model was run to predict production rates of Lima-1 with & without keeping Lima-2 on production to evaluate if co-production technique was effective. The model predicted that Lima-1 will be able to deliver its production targets even without keeping Lima-2 on production suggesting that extra CAPEX required for co-production was not justified. Forecasted gas rates for Lima-1 matched the actual gas rates with around 10% error. The accuracy of forecasted results endorses the use of box reservoir models to undertake economic decisions, in scenarios where lack of time & data doesn’t allow creation of detailed dynamic reservoir models.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.