Immunocytochemical assessment of bone marrow aspirates for monitoring response to chemotherapy in small-cell lung cancer patients

Recent reports have suggested that tumour cell immunodetection in bone marrow of small-cell lung cancer patients is by far more frequent than found cytohistologically and may have clinical relevance. This study evaluates primarily the efficacy of chemotherapy as method of in vivo purging, but also the relationship of marrow involvement with survival. A total of 112 bone marrow aspirates from 30 chemo-naïve patients were stained twice using anti-NCAM antibodies, first at diagnosis and then after chemotherapy (24 patients) or at disease progression (six patients). Marrow contamination was associated with lower survival (P = 0.002), and was also detected in 7/17 patients conventionally staged as having limited disease. At multivariate analysis, marrow involvement was an independent factor of unfavourable prognosis (P = 0.033). The amount of tumour contamination, before and after chemotherapy, remained unchanged also in responders and even in the subset of patients with apparent limited disease. Following chemotherapy, bone marrow became tumour negative only in 25% of initially positive responders and in none of non-responders. Our results indicate that (i) chemotherapy is not effective in purging bone marrow even in chemo-responsive patients and (ii) a subset of patients with limited disease and negative bone marrow aspirates might have a more favourable prognosis. © 1999 Cancer Research Campaig

Selecting high-dimensional mixed graphical models using minimal AIC or BIC forests

<p>Abstract</p> <p>Background</p> <p>Chow and Liu showed that the maximum likelihood tree for multivariate discrete distributions may be found using a maximum weight spanning tree algorithm, for example Kruskal's algorithm. The efficiency of the algorithm makes it tractable for high-dimensional problems.</p> <p>Results</p> <p>We extend Chow and Liu's approach in two ways: first, to find the forest optimizing a penalized likelihood criterion, for example AIC or BIC, and second, to handle data with both discrete and Gaussian variables. We apply the approach to three datasets: two from gene expression studies and the third from a genetics of gene expression study. The minimal BIC forest supplements a conventional analysis of differential expression by providing a tentative network for the differentially expressed genes. In the genetics of gene expression context the method identifies a network approximating the joint distribution of the DNA markers and the gene expression levels.</p> <p>Conclusions</p> <p>The approach is generally useful as a preliminary step towards understanding the overall dependence structure of high-dimensional discrete and/or continuous data. Trees and forests are unrealistically simple models for biological systems, but can provide useful insights. Uses include the following: identification of distinct connected components, which can be analysed separately (dimension reduction); identification of neighbourhoods for more detailed analyses; as initial models for search algorithms with a larger search space, for example decomposable models or Bayesian networks; and identification of interesting features, such as hub nodes.</p

Hypoglycemic effect of <it>Carica papaya</it> leaves in streptozotocin-induced diabetic rats

<p>Abstract</p> <p>Background</p> <p>Traditional plant treatment for diabetes has shown a surging interest in the last few decades. Therefore, the purpose of this study was to assess the hypoglycemic effect of the aqueous extract of <it>C. papaya</it> leaves in diabetic rats. Several studies have reported that some parts of the <it>C. papaya</it> plant exert hypoglycemic effects in both animals and humans.</p> <p>Methods</p> <p>Diabetes was induced in rats by intraperitoneal administration of 60 mg/kg of streptozotocin (STZ). The aqueous extract of <it>C. papaya</it> was administered in three different doses (0.75, 1.5 and 3 g/100 mL) as drinking water to both diabetic and non-diabetic animals during 4 weeks.</p> <p>Results</p> <p>The aqueous extract of <it>Carica papaya</it> (0.75 g and 1.5 g/100 mL) significantly decreased blood glucose levels (p<0.05) in diabetic rats. It also decreased cholesterol, triacylglycerol and amino-transferases blood levels. Low plasma insulin levels did not change after treatment in diabetic rats, but they significantly increased in non-diabetic animals. Pancreatic islet cells were normal in non-diabetic treated animals, whereas in diabetic treated rats, <it>C. papaya</it> could help islet regeneration manifested as preservation of cell size. In the liver of diabetic treated rats, <it>C. papaya</it> prevented hepatocyte disruption, as well as accumulation of glycogen and lipids. Finally, an antioxidant effect of <it>C. papaya</it> extract was also detected in diabetic rats.</p> <p>Conclusions</p> <p>This study showed that the aqueous extract of <it>C. papaya</it> exerted a hypoglycemic and antioxidant effect; it also improved the lipid profile in diabetic rats. In addition, the leaf extract positively affected integrity and function of both liver and pancreas.</p

Coherent and Squeezed States: Introductory Review of Basic Notions, Properties, and Generalizations

A short review of the main properties of coherent and squeezed states is given in introductory form. The efforts are addressed to clarify concepts and notions, including some passages of the history of science, with the aim of facilitating the subject for nonspecialists. In this sense, the present work is intended to be complementary to other papers of the same nature and subject in current circulation.Comment: 50 pages, misprints corrected, some new references included. To appear in "Integrability, Supersymmetry and Coherent States. A Volume in Honor of Professor Veronique Hussin