Use of Hypertonic Continuous Venovenous Hemodiafiltration to Control Intracranial Hypertension in an End-Stage Renal Disease Patient

Continuous venovenous hemodiafiltration (CVVHDF) using solutions designed to maintain hypernatremia is described in an end-stage renal disease (ESRD) patient with cerebral edema (CE) due to an intracerebral hemorrhage (ICH). Hypernatremia was readily achieved and maintained without complication. CVVHDF should be considered as an alternative treatment option in ESRD patients with cerebral edema who require hypertonic saline therapy

Plasminogen Activator in Differentiating Mouse Keratinocytes

The activity of the serine protease plasminogen activator (PA) was measured in cell lysates from primary mouse keratinocyte cultures as well as from a number of established mouse keratinocyte lines. Enzyme activity was generally higher in the transformed lines than in the primary cultures; however, among the lines tested, those that expressed the highest degree of morphologic differentiation had the highest levels of cell-associated PA. In both the normal (primary) and transformed (established) keratinocyte cultures, PA activity increased when cultures reached confluence and morphologic evidence of differentiation was noted. The highest specific activity of the enzyme was found in cells shed from differentiating cultures, which consisted predominantly of detergent-resistant cornified envelopes. As the cultures differentiated and these cells were shed from the culture surface, the total cell-associated PA activity of the culture decreased accordingly. In both the normal and transformed keratinocyte cultures, peak PA activity occurred at a time when DNA synthesis was declining. These findings indicate that as keratinocytes differentiate, their intracellular levels of PA increase. The modulation of this endogenous keratinocyte enzyme may play an important, although as yet undefined, role in the normal maturation and terminal differentiation of these cells

ACA Implementation Monitoring and Tracking: New York Site Visit Report

Examines New York's progress in implementing the 2010 federal healthcare reform, including an executive order to establish a health insurance exchange, legislation to enact insurance reforms, and the debate over implementing the Basic Health Program

Puromycin Sensitivity of Ribosomal Label after Incorporation of 14C-Labelled Amino Acids into Isolated Mitochondria from Neurospora crassa

Radioactive amino acids were incorporated into isolated mitochondria from Neurospora crassa. Then the mitochondrial ribosomes were isolated and submitted to density gradient centrifugation. A preferential labelling of polysomes was observed. However, when the mitochondrial suspension was treated with puromycin after amino acid incorporation, no radioactivity could be detected in either the monosomes or the polysomes. The conclusion is drawn that isolated mitochondria under these conditions do not incorporate significant amounts of amino acids into proteins of their ribosomes

Implicitly Constrained Semi-Supervised Least Squares Classification

We introduce a novel semi-supervised version of the least squares classifier. This implicitly constrained least squares (ICLS) classifier minimizes the squared loss on the labeled data among the set of parameters implied by all possible labelings of the unlabeled data. Unlike other discriminative semi-supervised methods, our approach does not introduce explicit additional assumptions into the objective function, but leverages implicit assumptions already present in the choice of the supervised least squares classifier. We show this approach can be formulated as a quadratic programming problem and its solution can be found using a simple gradient descent procedure. We prove that, in a certain way, our method never leads to performance worse than the supervised classifier. Experimental results corroborate this theoretical result in the multidimensional case on benchmark datasets, also in terms of the error rate.Comment: 12 pages, 2 figures, 1 table. The Fourteenth International Symposium on Intelligent Data Analysis (2015), Saint-Etienne, Franc

A Unifying View of Multiple Kernel Learning

Recent research on multiple kernel learning has lead to a number of approaches for combining kernels in regularized risk minimization. The proposed approaches include different formulations of objectives and varying regularization strategies. In this paper we present a unifying general optimization criterion for multiple kernel learning and show how existing formulations are subsumed as special cases. We also derive the criterion's dual representation, which is suitable for general smooth optimization algorithms. Finally, we evaluate multiple kernel learning in this framework analytically using a Rademacher complexity bound on the generalization error and empirically in a set of experiments