Formulation and Evaluation of Bilayer Tablet by Wet Granulation

ABSTRACT: The objective of this present study was to design bilayer tablet of two different drugs for separate release, evaluation of the same and comparison dry granulation formulation with minor changes in components. Both layer of bilayer tablets comprised control release. In wet granulation different type and amount of polymer were used for each layer. The formulated bilayer tablets were evaluated for pre compression as well as post compression parameters including invitro_dissolution_study were carried out. The results showed that wet granulation of formulated bilayer tablet carried out with different polymers viz. Gum acacia, Guar gum, Acrypol -971, HPMC_ K100M, eudragit_RSPO was carried out and based on its release retarding properties. Based on drug release and release kinetics study final formulation was selected that was further analysed for stability study. The accelerated stability study for 6 month showed affirmative result

An unexpected supraclavicular swelling

<p>Abstract</p> <p>Background</p> <p>Colorectal cancer is the third commonest cause of cancer death in UK. It commonly metastasises to the liver but rarely to small bones.</p> <p>Case presentation</p> <p>We describe a case of a patient with adenocarcinoma of the descending colon who presented preoperatively with a right supraclavicular swelling. Subsequent imaging and cytology of the lesion revealed this to be a metastasis to the right clavicle resulting in a pathological fracture.</p> <p>Conclusion</p> <p>This report describes the rare occurrence of a colorectal metastasis to the clavicle. It emphasises that although bone metastases from primary colorectal tumours are rare events, they tend to metastasise to small, non-weight bearing bones. It also discusses the utility of isotope bone scanning and that on certain occasions this imaging method may prove to be equivocal. In such circumstances, biopsy or magnetic resonance imaging is more sensitive for the detection of bone metastases.</p

Design and Application of Distributed Economic Model Predictive Control for Large-Scale Building Temperature Regulation

Although recent research has suggested model predictive control as a promising solution for minimizing energy costs of commercial buildings, advanced control systems have not been widely deployed in practice. Large-scale implementations, including industrial complexes and university campuses, may contain thousands of air handler units each serving a multiplicity of zones. A single centralized control system for these applications is not desirable. In this paper, we propose a distributed control system to economically optimize temperature regulation for large-scale commercial building applications. The decomposition strategy considers the complexities of thermal energy storage, zone interactions, and chiller plant equipment while remaining computationally tractable. One of the primary benefits of the proposed formulation is that the low-level airside problem can be decoupled and solved in a distributed manner; hence, it can be easily extended to handle large applications. Peak demand charges, a major source of coupling, are included. The interactions of the airside system with the waterside system are also considered, including discrete decisions, such as turning chillers on and off. To deploy such a control scheme, a system model is required. Since using physical knowledge about building models can greatly reduce the number of parameters that must be identified, grey-box models are recommended to reduce the length of expensive identification testing. We demonstrate the effectiveness of this control system architecture and identification procedure via simulation studies

Changes in renal medulla gene expression in a pre-clinical model of post cardiopulmonary bypass acute kidney injury

BACKGROUND: Acute kidney injury (AKI) is a common and serious complication of cardiac surgery using cardiopulmonary bypass (CPB). The pathogenesis is poorly understood and the study of AKI in rodent models has not led to improvements in clinical outcomes. We sought to determine the changes in renal medullary gene expression in a novel and clinically relevant porcine model of CPB-induced AKI. RESULTS: Adult pigs (n = 12 per group) were randomised to undergo sham procedure, or 2.5 hours CPB. AKI was determined using biochemical (Cr51 EDTA clearance, CrCl, urinary IL-18 release) and histological measures. Transcriptomic analyses were performed on renal medulla biopsies obtained 24 hours post intervention or from sham group. Microarray results were validated with real-time polymerase chain reaction and Western Blotting. Of the transcripts examined, 66 were identified as differentially expressed in CPB versus Sham pig’s kidney samples, with 19 (29%) upregulated and 47 (71%) down-regulated. Out of the upregulated and downregulated transcripts 4 and 16 respectively were expression sequence tags (EST). The regulated genes clustered into three classes; Immune response, Cell adhesion/extracellular matrix and metabolic process. Upregulated genes included Factor V, SLC16A3 and CKMT2 whereas downregulated genes included GST, CPE, MMP7 and SELL. CONCLUSION: Post CPB AKI, as defined by clinical criteria, is characterised by molecular changes in renal medulla that are associated with both injury and survival programmes. Our observations highlight the value of large animal models in AKI research and provide insights into the failure of findings in rodent models to translate into clinical progress. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1471-2164-15-916) contains supplementary material, which is available to authorized users

Livestock Depredation by Leopards, Associated Economic Losses, and Financial Compensation to Communities in Chhota Udepur District of Central Gujarat, India

Livestock depredation by large carnivores has been documented across the entire Indian subcontinent. The failure of managers to mitigate livestock losses in landscapes dependent on subsistence agriculture poses a threat to the conservation of carnivores. For much of Gujarat, a western Indian state characterized by extensive semi-arid habitats, the Indian leopard (Panthera pardus fusca) is considered an apex predator. Increasing regional leopard populations in response to protection efforts has led to more attacks on humans, along with an increase in rates of livestock depredation. In many cases, the regional forest department financially compensates livestock owners for depredation caused by leopards. Herein, we report on data we collected on leopard-caused livestock depredations in the Chhota Udepur district of Gujarat for 2019–2020. Between November 2020 and March 2021, we recorded 104 distinct cases of leopard depredations that resulted in 134 livestock mortalities. Most attacks occurred in the middle of the night, with the greatest frequency occurring between 2100 and 0400 hours (n = 53). Interestingly, livestock depredations by leopards appeared to occur more in the monsoon season (66%) than during the drier seasons (Fisher’s least significant difference [LSD], P \u3c 0.05). We also found that not everyone enduring losses to leopards received full compensation for the value of their animals. Livestock kept in corrals at night were more vulnerable to leopard attack (R2 = 38.6, P = 0.01) compared to free-ranging livestock foraging by day in farms and forests. We recommend that livestock compensation claims filed by communities be investigated and processed quickly and that compensation be based on fair value for domestic animals lost. To better understand the drivers of human–leopard conflict, we also encourage rigorous surveys of potential leopard prey species in forested areas adjacent to conflict hotspots as well as research to identify the most effective methods communities might use to safeguard their livestock

An Economic Model Predictive Control Framework for Distributed Embedded Battery Applications

Since building heating, ventilation, and air conditioning (HVAC) systems are significant consumers of primary energy, considerable efforts are being made to improve energy efficiency and decrease energy costs in these applications. Notably, substantial opportunities in the area of HVAC control exist for decreasing energy costs by shifting loads from peak periods to off-peak periods in the presence of time-varying utility prices. This load shifting is also beneficial for power companies since it results in a more constant total load allowing them to operate more efficiently. Economic model predictive control (MPC) has been shown to significantly decrease the energy costs of commercial HVAC systems via load shifting. Typically, thermal energy storage (TES) is used for this purpose by running HVAC equipment at higher rates during periods of low power prices to charge TES and at lower rates during periods of higher prices while discharging TES to meet building demand loads. However, with batteries becoming less expensive to manufacture, electrical energy storage in batteries is becoming a viable option for load shifting. Batteries can be used for both load shifting to decrease costs and revenue generation if the incentives on the electricity market are appropriate. In this work, embedded battery applications are considered. In embedded battery applications, the batteries are directly packaged with airside equipment such as air handler units (AHUs), roof-top units (RTUs), and variable refrigerant flow systems (VRFs). In this arrangement, the batteries are accessible only to the local unit and not to other units. In this paper, we propose a hierarchical control system framework for the economic optimization of distributed embedded battery units. The architecture considers both building mass storage as well as the electrical energy storage of the battery units. A high-level problem performs an economic optimization over the entire system using aggregate models. The low-level layer is broken into subsystems, each optimizing its local decisions with higher fidelity models. Advantages of this framework include no iterative communication required between subsystems, decreased computational complexity in the high-level problem allowing for real-time online implementation, and management of total demand across the entire system to reduce peak demand charges. We conclude with a simulation study demonstrating the benefits of the proposed control architecture

A Case Study of Economic Optimization of HVAC Systems based on the Stanford University Campus Airside and Waterside Systems

Commercial buildings account for $200 billion per year in energy expenditures, with heating, ventilation, and air conditioning (HVAC) systems accounting for most of these costs. In energy markets with time-varying prices and peak demand charges, a significant potential for cost savings is provided by using thermal energy storage to shift energy loads. Since most implementations of HVAC control systems do not optimize energy costs, they have become a primary focus for new strategies aimed at economic optimization. Model predictive control (MPC) has emerged as one popular method to achieve this load shifting, while respecting system constraints. MPC uses a model of the system to make predictions and to solve an optimization problem. Much research has shown the benefits of MPC over alternative strategies for HVAC control [1]. However, some industrial applications, such as large research centers or university campuses, are too large to be solved in a single MPC instance. Decompositions have been proposed in the literature, but it is difficult to evaluate and to compare decompositions against one another when using different systems. In this paper, we present a large-scale relevant case study where solving a single MPC optimization problem is neither desirable nor feasible for real-time implementations. The study is modeled after the Stanford University campus, consisting of both an airside and waterside system [2]. The airside system includes 500 zones spread throughout 25 campus buildings along with the air handler units and regulatory building automation system used for temperature regulation. The waterside system includes the central plant equipment, such as chillers, that is used to meet the load from the buildings. Active thermal energy storage is available to the campus in addition to the passive thermal energy storage present in the form of building mass. The airside models describe the temperature dynamics in each of the 500 zones, and the waterside models describe the power consumption of the central plant equipment. The aim of the control system is to minimize costs in the presence of time-varying electricity prices and a peak demand charge as well as environmental disturbances such as weather while meeting constraints on comfort and equipment. We perform an economic optimization of the entire campus using a hierarchical system with distributed airside controllers to demonstrate the potential savings. The models from this case study are made publicly available for other researchers interested in designing alternative control strategies for managing chilled water production to meet airside loads. The aim of the case study release is to provide a standardized problem for the research community. A benchmark is provided for evaluating performance. References [1] A. Afram and F. Janabi-Sharifi. Theory and applications of HVAC control systems—A review of model predictive control (MPC). Building and Environment, 72:343–355, February 2014. [2] J. B. Rawlings, N. R. Patel, M. J. Risbeck, C. T. Maravelias, M. J. Wenzel, and R. D. Turney. Economic MPC and real-time decision making with application to large-scale HVAC energy systems. Computers & Chemical Engineering, 2017. In Press

Long-term survival after surgical aortic valve replacement among patients over 65 years of age

Surgical aortic valve replacement (AVR) remains the gold standard therapy for severe aortic stenosis. Long-term survival data following AVR is required. Our objective was to provide a detailed contemporary benchmark of long-term survival following AVR among elderly patients (≥65 years) in the UK.We conducted a retrospective cohort study of 1815 adult patients undergoing surgical AVR± coronary artery bypass graft (CABG) surgery at a single UK centre between 1996 and 2011. Our main outcome was patient survival, which was assessed by linkage to census records at the Office for National Statistics.The mean age of the cohort was 75 (±5.6) years. Patients in the AVR alone group had a slightly higher median survival of 10.9 (95% CI 10.5 to 11.8) years than the AVR+CABG group which had a median survival of 9.6 (95% CI 8.7 to 10.1) years (p=0.001 of log-rank test (LRT) for equality of survivor functions). The presence of chronic kidney disease, severely impaired left ventricular function or being a current smoker were each associated with a ≥50% increased risk of long-term mortality. Comparison of our study cohort patients and the reference (operation year, age and gender matched) UK population suggested no difference in survival probability up to 8 years (p=0.55). However, for longer periods of follow-up, the difference became increasingly significant (p<0.0001).Long-term survival following surgical AVR in patients over 65 years of age is excellent and up to 8 years is comparable to the matched general population