Serum IgG2 level, Gm(23) allotype and FcgammaRIIa and FcgammaRIIIb receptors in refractory periodontal disease

The purpose of this investigation was to compare the levels of serum IgG2, the frequency of detection of Gm(23)-negative allotype and frequency of detection of FcgammaRIIa and FcgammaRIIIb receptor haplotypes in 32 refractory, 54 successfully treated and 27 periodontally healthy individuals. Refractory subjects showed mean full mouth attachment loss and/or >3 sites with attachment loss >2.5 mm within 1 year after both scaling and root planing, and surgery plus systemically administered tetracycline. Successfully treated subjects showed mean attachment level gain and no sites with attachment loss >2.5 mm 1 year post-therapy. Periodontally healthy subjects exhibited no pocket depth or attachment level >3 mm, and no evidence of progressing disease during 1 year of monitoring. Blood was obtained from each subject at baseline. Serum IgG2 and Gm(23) allotype were determined using radial immunodiffusion. DNA was extracted from whole blood and the FcgammaR genotypes determined using PCR and allele specific oligonucleotide probes. Significance of differences among clinical groups were sought using the Kruskal-Wallis or chi-square tests. Associations between 2 or more variables were tested using regression analysis. Refractory subjects exhibited higher mean attachment loss and pocket depth than successfully treated or periodontally healthy subjects. Smoking status did not differ significantly among groups. No significant differences in serum IgG2 levels and frequency of detection of Gm(23)-negative allotype were observed among the clinical groups. Serum IgG2 level was positively associated with the number of serum antibody responses to subgingival species (r=0.51, p<0.001). Subjects with the Gm(23)-negative allotype exhibited lower mean levels of serum IgG2 (3.06+/-0.3 versus 3.9+/-0.2, p<0.01) and mean number of serum antibodies to subgingival species (17.7+/-1.7 versus 23.3+/-1.4, p<0.05) than allotype positive individuals. No significant differences in FcgammaR haplotype distribution were observed among the 3 clinical groups. Associations of serum IgG2 level, Gm(23) allotype, FcgammaRIIa and FcgammaRIIIb receptor haplotypes and smoking status were weakly related or not related to clinical status. This lack of relationship may have been due to a reality of no relationship, or the inadvertent pooling of subjects where these factors were of primary importance with subjects in whom these factors played a less important role.     

Comparative evaluation of FUNGITEST and broth microdilution methods for antifungal drug susceptibility testing of Candida species and Cryptococcus neoformans

The FUNGITEST method (Sanofi Diagnostics Pasteur, Paris, France) is a microplate-based procedure for the breakpoint testing of six antifungal agents (amphotericin B, flucytosine, fluconazole, itraconazole, ketoconazole, and miconazole). We compared the FUNGITEST method with a broth microdilution test, performed according to National Committee for Clinical Laboratory Standards document M27-A guidelines, for determining the in vitro susceptibilities of 180 isolates of Candida spp. (50 C. albicans, 50 C. glabrata, 10 C. kefyr, 20 C. krusei, 10 C. lusitaniae, 20 C. parapsilosis, and 20 C. tropicalis isolates) and 20 isolates of Cryptococcus neoformans. Overall, there was 100% agreement between the methods for amphotericin B, 95% agreement for flucytosine, 84% agreement for miconazole, 83% agreement for itraconazole, 77% agreement for ketoconazole, and 76% agreement for fluconazole. The overall agreement between the methods exceeded 80% for all species tested with the exception of C. glabrata (71% agreement). The poorest agreement between the results for individual agents was seen with C. glabrata (38% for fluconazole, 44% for ketoconazole, and 56% for itraconazole) and C. tropicalis (50% for miconazole). The FUNGITEST method misclassified as susceptible 2 of 12 (16.6%) fluconazole-resistant isolates, 2 of 10 (20%) itraconazole-resistant isolates, and 4 of 8 (50%) ketoconazole-resistant isolates of several Candida spp. Further development of the FUNGITEST procedure will be required before it can be recommended as an alternative method for the susceptibility testing of Candida spp. or C. neoformans.     

Screening for diabetic retinopathy: the utility of nonmydriatic retinal photography in Egyptian adults

BACKGROUND AND OBJECTIVE: Drug resistance has become a major cause of treatment failure in patients with acute leukemia. P-glycoprotein (Pgp), which is associated with the multidrug resistance (MDR) phenotype, has been reported to be an important predictor of treatment outcome. The aim of this study was to analyze the value of Pgp expression in bone marrow or peripheral blood as a predictor of the response to remission induction chemotherapy as well as the duration of remission in patients with de novo acute myeloid leukemia (AML). DESIGN AND METHODS: We examined the expression of Pgp in 82 patients with de novo AML using an immunocytochemical assay with the C219 monoclonal antibody. RESULTS: Twenty-seven of the 82 patients (33%) were C219-positive in from 1% to 100% of their cells. Thirteen cases (16%) showed a positive reaction in more than 50% of the leukemic cells. Only hyperleukocytosis was significantly associated with higher expression of Pgp. Although 8 of the 13 cases (62%) with more than 50% of cells having Pgp expression were CD34-positive, this association was not statistically significant. A univariate analysis of resistance to induction therapy showed a significantly higher resistance rate in patients with increased Pgp expression (P = 0.01) as well as in those patients with decreased reactivity to myeloperoxidase. The multivariate analysis revealed the independent prognostic value of Pgp expression. C219 reactivity did not have an influence on remission duration. INTERPRETATION AND CONCLUSIONS: Our data indicate that P-glycoprotein expression is a reliable marker of resistance to induction treatment in patients with de novo AML.     

From ethnographic record to system design

This paper explores the issues involved in moving from ethnographic explorations of work in context to a practical contribution to system design. It does so using the example of an interdisciplinary research project involving sociologists and computer scientists in the domain of air traffic control systems. It forms a pair with another paper (Sommerville et al., 1992) exploring these questions from the perspective of our computer science partners. We characterise ethnography as a research method, and consider the differences between undertaking it for strictly sociological or anthropological purposes by contrast with interdisciplinary and design purposes. We summarise some of our results in ethnographic explications of the work of air traffic controllers, and the sociality which it manifests. We describe the dialogues involved in rendering these observations informative for systems design, and the mutual translations implied in attempting to reconcile sociological with software engineering questions about supporting the work. We conclude by specifying some features of cooperative work which an engineering approach is in danger of overlooking; the ways, and limits, in which ethnographers can form a bridge between users and designers; and some of the conflicts of interest entrained in generating technical change.The research is funded by the UK MRC/SERC/ESRC Cognitive Science/HCI Initiative with the title Social Analysis of Control Systems for HCI Design, grant number SPG 8931598. The computer science partners are Professor Ian Sommerville, Dr Tom Rodden, Dr Pete Sawyer and Mr Richard Bentley. Thanks are due to Val King, Kjeldt Schmidt, Ian Sommerville and Tom Rodden for very helpful comments on earlier drafts of this paper.     

A comparative study of iterative and non-iterative feature selection techniques for software defect prediction

Two important problems which can affect the performance of classification models are high-dimensionality (an overabundance of independent features in the dataset) and imbalanced data (a skewed class distribution which creates at least one class with many fewer instances than other classes). To resolve these problems concurrently, we propose an iterative feature selection approach, which repeated applies data sampling (in order to address class imbalance) followed by feature selection (in order to address high-dimensionality), and finally we perform an aggregation step which combines the ranked feature lists from the separate iterations of sampling. This approach is designed to find a ranked feature list which is particularly effective on the more balanced dataset resulting from sampling while minimizing the risk of losing data through the sampling step and missing important features. To demonstrate this technique, we employ 18 different feature selection algorithms and Random Undersampling with two post-sampling class distributions. We also investigate the use of sampling and feature selection without the iterative step (e.g., using the ranked list from a single iteration, rather than combining the lists from multiple iterations), and compare these results from the version which uses iteration. Our study is carried out using three groups of datasets with different levels of class balance, all of which were collected from a real-world software system. All of our experiments use four different learners and one feature subset size. We find that our proposed iterative feature selection approach outperforms the non-iterative approach.     

Root growth and phosphorus and potassium uptake by two corn genotypes in the field

In a field study P and K uptake by two corn (Zea mays L.) genotypes which differed in root growth was investigated. The effect of differences in root growth on P and K uptake was assessed using a mechanistic-mathematical model which describes nutrient uptake by growing plant roots in soil. Nitrogen was applied at 0 and 227 kg ha^–1 to Pioneer 3732 and B73xMo17 corn grown on Raub silt loam (fine-silty, mixed, mesic Aquic Argiudoll) and at 227 kg N ha^–1 to these two genotypes on Chalmers silt loam (finesilty, mixed, mesic, Typic Haplaquoll). Root growth and P and K uptake by the two corn genotypes was measured 31, 47, 75 and 91 d after planting on the Raub and 31, 47, 61 and 75 d after planting on the Chalmers soil.Root growth and P and K uptake by B73xMo17 was greater than that of Pioneer 3732 on N-fertilized Raub soil. On Chalmers soil the difference in root growth between the two genotypes resulted in an increase in K but not P uptake. The higher soil P level of the Chalmers appears to have offset possible differences in P uptake due to root size. There were no differences between the two genotypes in either the percentage of roots with root hairs, or the density or length of root hairs. Phosphorus and K uptake calculated with the simulation models for both corn genotypes on both soils over each of three growth periods agreed with observed P (Y = 0.68X + 1.71; r = 0.944^**) and K (Y = 0.88X + 15.52; r = 0.928^**) uptake. Differences in P and K uptake between B73xMo17 and Pioneer 3732 resulted primarily from the difference in root growth in the topsoil. A high correlation was found between root surface area and P (r = 0.893^**) and K (r = 0.928^**) uptake by both corn genotypes on both the soils.Journal paper No. 10,316 Purdue Univ. Agric. Exp. Stn., W. Lafayette, In 47906. Contribution from the Dep. of Agron. This paper was supported in part by a grant from the Tennessee Valley Authority.     

Information Systems Offshore Outsourcing: An Exploratory Study of Motivations and Risks in Large Spanish Firms

Prior research has documented that IT investment increases market returns. Economic theories predict such returns to be recognized in accounting profitability; this relationship remains ambiguous in prior literature. We reexamine the relationship between IT investment and firm profitability. Our approach is unique in that we examine complementarities between distinct IT components. We document that a firm’s investments in IT components exhibit different impacts on its profitability conditional on the level of investments in complementary components.     

Random Bichromatic Matchings

Given a graph with edges colored Red and Blue, we study the problem of sampling and approximately counting the number of matchings with exactly k Red edges. We solve the problem of estimating the number of perfect matchings with exactly k Red edges for dense graphs. We study a Markov chain on the space of all matchings of a graph that favors matchings with k Red edges. We show that it is rapidly mixing using non-traditional canonical paths that can backtrack. We show that this chain can be used to sample matchings in the 2-dimensional toroidal lattice of any fixed size ℓ with k Red edges, where the horizontal edges are Red and the vertical edges are Blue. An extended abstract appeared in J.R. Correa, A. Hevia and M.A. Kiwi (eds.) Proceedings of the 7th Latin American Theoretical Informatics Symposium, LNCS 3887, pp. 190–201, Springer, 2006. N. Bhatnagar’s and D. Randall’s research was supported in part by NSF grants CCR-0515105 and DMS-0505505. V.V. Vazirani’s research was supported in part by NSF grants 0311541, 0220343 and CCR-0515186. N. Bhatnagar’s and E. Vigoda’s research was supported in part by NSF grant CCR-0455666.