4,210 research outputs found
Complications of nephrotic syndrome
Nephrotic syndrome (NS) is one of the most common glomerular diseases that affect children. Renal histology reveals the presence of minimal change nephrotic syndrome (MCNS) in more than 80% of these patients. Most patients with MCNS have favorable outcomes without complications. However, a few of these children have lesions of focal segmental glomerulosclerosis, suffer from severe and prolonged proteinuria, and are at high risk for complications. Complications of NS are divided into two categories: disease-associated and drug-related complications. Disease-associated complications include infections (e.g., peritonitis, sepsis, cellulitis, and chicken pox), thromboembolism (e.g., venous thromboembolism and pulmonary embolism), hypovolemic crisis (e.g., abdominal pain, tachycardia, and hypotension), cardiovascular problems (e.g., hyperlipidemia), acute renal failure, anemia, and others (e.g., hypothyroidism, hypocalcemia, bone disease, and intussusception). The main pathomechanism of disease-associated complications originates from the large loss of plasma proteins in the urine of nephrotic children. The majority of children with MCNS who respond to treatment with corticosteroids or cytotoxic agents have smaller and milder complications than those with steroid-resistant NS. Corticosteroids, alkylating agents, cyclosporin A, and mycophenolate mofetil have often been used to treat NS, and these drugs have treatment-related complications. Early detection and appropriate treatment of these complications will improve outcomes for patients with NS
Anti-Photoagaing and Photo-Protective Compounds from Marine Organisms
This Special Issue Book ""Anti-Photoagaing and Photo-Protective Compounds from Marine Organisms"" is aimed at collecting literature on the below-mentioned keyword topics, which can significantly increase our basic understanding of marine-derived compounds in cosmeceutical product development and increases the value of marine products at the industrial level
Contextual Linear Bandits under Noisy Features: Towards Bayesian Oracles
We study contextual linear bandit problems under uncertainty on features;
they are noisy with missing entries. To address the challenges from the noise,
we analyze Bayesian oracles given observed noisy features. Our Bayesian
analysis finds that the optimal hypothesis can be far from the underlying
realizability function, depending on noise characteristics, which is highly
non-intuitive and does not occur for classical noiseless setups. This implies
that classical approaches cannot guarantee a non-trivial regret bound. We thus
propose an algorithm aiming at the Bayesian oracle from observed information
under this model, achieving regret bound with respect to
feature dimension and time horizon . We demonstrate the proposed
algorithm using synthetic and real-world datasets.Comment: 30 page
- …