Scleroderma with crescentic glomerulonephritis: a case report

<p>Abstract</p> <p>Introduction</p> <p>Systemic sclerosis or scleroderma is an autoimmune rheumatic disease characterized by organ-based fibrosis. Renal involvement in scleroderma occurs mainly in the form of scleroderma renal crisis, affecting 5 to 10% of patients. It remains one of the most important and immediately life-threatening complications of scleroderma, but the prognosis improves considerably after treatment with angiotensin-converting enzyme inhibitors. Other renal pathologies can occur in scleroderma. These include scleroderma overlap syndromes with associated features of lupus nephritis, myeloperoxidase anti-neutrophil cytoplasmic antibodies (ANCA) or proteinase 3 ANCA-associated glomerulonephritis, or crescentic glomerulonephritis. These alternative pathologies should be suspected in any individual patient with a differing clinical picture and the patient should be appropriately investigated. Crescentic glomerulonephritis occurs very rarely in scleroderma. This report describes a patient with scleroderma and crescentic glomerulonephritis.</p> <p>Case presentation</p> <p>A 52-year-old woman with a known history of scleroderma and hypertension on angiotensin-converting enzyme inhibitors was referred to the nephrologist because of a rapid decline in renal function. Kidney biopsy was performed which revealed immune complex type crescentic glomrulonephritis. Cytoplasmic-staining ANCA was negative. Despite immunosuppressive treatment the patient rapidly went into end-stage renal failure and is still on hemodialysis.</p> <p>Conclusion</p> <p>Scleroderma is a complex disease, and the best characterized renal involvement in scleroderma is scleroderma renal crisis. However, other renal pathologies can occur in scleroderma. These alternative pathologies should be suspected in any patient with a differing clinical picture and the patient should be appropriately investigated, as the clinical course and treatment are different from the more common scleroderma renal crisis.</p

Studies on the characteristics of water soluble acrylic resins used for electrodeposition

Electrodeposition of paint has become a widely accepted technique for application of paint coating and is being adopted for coating a variety of metal articles for corrosion protection as well as for decoration. Several resin systems have been used for this purpose depending on the specific application for which the coating is used. For example for excellent corrosion protection, primer coatings based on epoxies and polybutadiene are used. Acrylic coatings have not very good fade resistance properties and can be used for decorative applications over different metallic substrates. This paper deals with some of the studies made mainly on the bath characteristics of the acrylic system. The main parameters studied include the effect of conductivity of the solution on deposition characteristics, the throwing power at different operating parameters and columbic efficiency with and without pigmentation. Some of the physical properties like bond strength of cured coatings, hardness, abrasion resistance and also corrosion resistance are also reported in this pape

Minimizing Energy Depletion Using Extended Lifespan: QoS Satisfied Multiple Learned Rate (ELQSSM-ML) for Increased Lifespan of Mobile Adhoc Networks (MANET)

Mobile Adhoc Networks (MANETs) typically employ with the aid of new technology to increase Quality-of-Service (QoS) when forwarding multiple data rates. This kind of network causes high forwarding delays and improper data transfer rates because of the changes in the node’s vicinity. Although an optimized routing technique to transfer energy has been used to lessen the delay and improve the throughput by assigning a proper data rate, it does not consider the objective of minimizing the energy use, which results in less network lifetime. The goal of the proposed work is to minimize the energy depletion in a MANET, which results in an extended Lifespan of the network. In this research paper, an Extended Life span and QSSM-ML routing algorithm is proposed, which minimizes energy use and enhances the network lifetime. First, an optimization problem is formulated with the purpose of increasing the network’s lifetime while limiting the energy utilization and stability of the path along with residual. Second, an adaptive policy is applied for the asymmetric distribution of energy at both origin and intermediate nodes. In order to achieve maximum network lifespan and minimal energy depletion, the optimization problem was framed when power usage is a constraint by allowing the network to make use of the leftover power. An asymmetric energy transmission strategy was also designed for the adaptive allocation of maximum transmission energy in the origin. This made the network lifespan extended with the help of reducing the node’s energy use for broadcasting the data from the origin to the target. Moreover, the node’s energy use during packet forwarding is reduced to recover the network lifetime. The overall benefit of the proposed work is that it can achieve both minimal energy depletion and maximizes the lifetime of the network. Finally, the simulation findings reveal that the ELQSSM-ML algorithm accomplishes a better network performance than the classical algorithms

Basic life support through early clinical exposure: Students’ perspective

In this study, an attempt is made to analyse the students’ perspective on ECE. The effectiveness of this program and the extent to which the students are benefitted is being evaluated

Peristaltic transport of Sutterby nanofluid flow in an inclined tapered channel with an artificial neural network model and biomedical engineering application

Abstract Modern energy systems are finding new applications for magnetohydrodynamic rheological bio-inspired pumping systems. The incorporation of the electrically conductive qualities of flowing liquids into the biological geometries, rheological behavior, and propulsion processes of these systems was a significant effort. Additional enhancements to transport properties are possible with the use of nanofluids. Due to their several applications in physiology and industry, including urine dynamics, chyme migration in the gastrointestinal system, and the hemodynamics of tiny blood arteries. Peristaltic processes also move spermatozoa in the human reproductive system and embryos in the uterus. The present research examines heat transport in a two-dimensional deformable channel containing magnetic viscoelastic nanofluids by considering all of these factors concurrently, which is vulnerable to peristaltic waves and hall current under ion slip and other situations. Nanofluid rheology makes use of the Sutterby fluid model, while nanoscale effects are modeled using the Buongiorno model. The current study introduces an innovative numerical computing solver utilizing a Multilayer Perceptron feed-forward back-propagation artificial neural network (ANN) with the Levenberg–Marquardt algorithm. Data were collected for testing, certifying, and training the ANN model. In order to make the dimensional PDEs dimensionless, the non-similar variables are employed and calculated by the Homotopy perturbation technique. The effects of developing parameters such as Sutterby fluid parameter, Froude number, thermophoresis, ion-slip parameter, Brownian motion, radiation, Eckert number, and Hall parameter on velocity, temperature, and concentration are demonstrated. The machine learning model chooses data, builds and trains a network, and subsequently assesses its performance using the mean square error metric. Current results declare that the improving Reynolds number tends to increase the pressure rise. Improving the Hall parameter is shown to result in a decrease in velocity. When raising a fluid's parameter, the temperature profile rises