Peptide amidating activity in human bronchoalveolar lavage fluid

Monitoring respiratory epithelial biology may reveal individuals with incipient lung cancer. The expression of neuroendocrine (NE) markers in pulmonary epithelium is thought to be central to lung development, repair of injury and may contribute to carcinogenesis. In this study, we evaluate several candidate NE markers to determine the feasibility of prospective analysis of clinical specimens. The potential NE markers include the enzyme L-DOPA decarboxylase (DDC), the neuropeptide gastrin releasing peptide (GRP), and peptidyl-glycine alpha-amidating monooxygenase (PAM), the bifunctional enzyme responsible for the final bioactivation step of many neuropeptides. A comparison of PAM activity and DDC levels in 30 lung cancer cell lines indicated that peptide amidating activity may be an indicator of NE status. Bronchoalveolar lavage (BAL) fluid from subjects at risk of developing second primary lung cancer and from volunteers was obtained. The activity of the first PAM enzyme, peptidylglycine alpha-hydroxylating monooxygenase (PHM), ranged from not detectable to 507 pmol/h/mg protein in 57 specimens. The second PAM enzyme, peptidylamidoglycolate lyase (PAL), ranged from not detectable to 414 pmol/h/mg protein in 56 specimens. Using cluster analysis by the average linkage method, a group of enzyme values with PHM greater than 230 pmol/h/mg protein was determined. Long-term follow-up of these patients for new second primary lung cancers may help to determine the potential predictive value of PAM detected in the BAL fluid.     

Tree-structured piecewise linear adaptive equalization

The use of a tree-structured piecewise linear filter as an adaptive equalizer is proposed. In the tree equalizer, each node in a tree is associated with a linear filter restricted to a polygonal domain, and each subtree is associated with a piecewise linear filter. A training sequence is used to adaptively update the filter coefficients and domains at each node, and to select the best subtree and corresponding piecewise linear filter. The tree-structured approach offers several advantages. First, it makes use of standard linear adaptive filtering techniques at each node to find the corresponding conditional linear filter. Second, it allows for efficient selection of the subtree and corresponding piecewise linear filter of appropriate complexity. Overall, the approach is computationally efficient and conceptually simple. Numerical experiments are performed to show the advantages of tree-structured piecewise linear and piecewise decision feedback equalizers over linear, polynomial, and decision feedback equalizers for the equalization of channels with severe intersymbol interference     

A neural network model for the wire bonding process

A crucial step in manufacturing microcircuits is the wire bonding process in which a very thin gold wire must be formed to connect two surfaces in the microcircuit. The quality of the wire bond can be measured by visual inspection and a pull test—both of which are high-reliability, high-cost approaches to statistical process control. Westinghouse wanted to develop a high-reliability, low-cost quality assurance system. In this paper, we report on a year-long study to construct a neural network model that is capable of predicting the quality of wire bonds. The results of our modeling efforts reveal that neural networks are useful tools for statistical process control problems.     

Environment-assisted cracking in austenitic components

Stress corrosion cracking and corrosion fatigue have been responsible for some costly generic material failures in water cooled power reactors. This paper reviews the main features of two of the most widespread problems, namely intergranular stress corrosion cracking of sensitized stainless steel piping in boiling water reactors (BWR) and of nickel alloy steam generator tubes in pressurized water reactors (PWR). Mechanisms, in so far as they are known, are described together with remedial measures and crack growth models applicable to in-plant components.