Cell lysis is a process in which the outer cell membrane is broken to release intracellular constituents in a way that important information about the DNA or RNA of an organism can be obtained. This article is a thorough review of reported methods for the achievement of effective cellular boundaries disintegration, together with their technological peculiarities and instrumental requirements. The different approaches are summarized in six categories: chemical, mechanical, electrical methods, thermal, laser, and other lysis methods. Based on the results derived from each of the investigated reports, we outline the advantages and disadvantages of those techniques. Although the choice of a suitable method is highly dependent on the particular requirements of the specific scientific problem, we conclude with a concise table where the benefits of every approach are compared, based on criteria such as cost, efficiency, and difficulty.
This article presents counter evidence against Smolensky's theory that human intuitive/nonconscious congnitive processes can only be accurately explained in terms of subsymbolic computations carried out in artificial neural networks. We present symbolic learning models of two well‐studied, complicated cognitive tasks involving nonconscious acquisition of information: learning production rules and artificial finite state grammars. Our results demonstrate that intuitive learning does not imply subsymbolic computation, and that the already well‐established, perceived correlation between “conscious” and “symbolic” on the one hand, and between “nonconscious” and “subsymbolic” on the other, does not exist.
As the focus of genome-wide scans for disease loci have shifted from simple Mendelian traits to genetically complex traits, researchers have begun to consider new alternative ways to detect linkage that will consider more than the marginal effects of a single disease locus at a time. One interesting new method is to train a neural network on a genome-wide data set in order to search for the best non-linear relationship between identity-by-descent sharing among affected siblings at markers and their disease status. We investigate here the repeatability of the neural network results from run to run, and show that the results obtained by multiple runs of the neural network method may differ quite a bit. This is most likely due to the fact that training a neural network involves minimizing an error function with a multitude of local minima.
The division of the hepatic duct is one of the most challenging passages of the donor hepatectomy. We report our experience with the early division, prior to the liver parenchyma resection, of the hepatic duct and the definition of the biliary anatomy with a probe inserted in the proper hepatic duct. From February 2002 to December 2004, 40 donors (25 male, 15 female; mean age 34, range 20-57) underwent right hepatectomy. The yield was a single duct in 24 donors (60%), two ducts in 12 donors (30%), and three ducts in one donor (2.5%), and three donors had aberrant anatomy yielding two ducts (7.5%). By means of a ductoplasty, a single orifice for the recipient biliary anastomosis was obtained in 77.5% of the cases. Three donors (7.5%) suffered a resection surface bile leak. The technique of hepatic duct probing and early division provides a precise definition of the biliary anatomy and facilitates one of the most challenging passages of the donor hepatectomy. This technique should also contribute to maximizing the preservation of the vascular supply of the hepatic duct and the yield of a single orifice for the recipient anastomosis. At a median follow-up of 21 months (range 10-44), neither short-nor long-term complications had been caused by the small donor choledochotomy.
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.