Conformational Studies of Ortho- and Meto-Isomers and Methyl, Dimethyl, and Chloro Ortho-Substituted Analogues of Dantrolene Using Ab Initio SCF-MO Procedures

The conformation of the nitro group of nitroaromatic compounds relative to the aromatic ringsystem is suggested to affect their metabolic activation and mutagenicity. We have recently showed the nitrophenylfuran skeletal muscle relaxant, dantrolene, tobe a potent mutagen inSalmonella. Synthesis of or^o-substituted analogues of dantrolene was achieved in an effort to alter the conformation of the nitro group ina manner that willdecrease the mutagenicity. Using ab initio techniques we investigated the minimum energy conformation of the nitro group of dantrolene (/mitro) and its o-and mnitro isomers as well as the nitro group conformation of dantrolene\u27s ortho- mono- and di- substituted analogues. The most stable conformer for each isomer and analogue was found by optimizing the bond lengths and bond angles for each molecule and rotating about bonds ofinterest using the STO-3G basis set in the Gaussian-92 program at the Hartree-Fock level

A review of the methodological features of systematic reviews in maternal medicine

Background In maternal medicine, research evidence is scattered making it difficult to access information for clinical decision making. Systematic reviews of good methodological quality are essential to provide valid inferences and to produce usable evidence summaries to guide management. This review assesses the methodological features of existing systematic reviews in maternal medicine, comparing Cochrane and non-Cochrane reviews in maternal medicine. Methods Medline, Embase, Database of Reviews of Effectiveness (DARE) and Cochrane Database of Systematic Reviews (CDSR) were searched for relevant reviews published between 2001 and 2006. We selected those reviews in which a minimum of two databases were searched and the primary outcome was related to the maternal condition. The selected reviews were assessed for information on framing of question, literature search and methods of review. Results Out of 2846 citations, 68 reviews were selected. Among these, 39 (57%) were Cochrane reviews. Most of the reviews (50/68, 74%) evaluated therapeutic interventions. Overall, 54/68 (79%) addressed a focussed question. Although 64/68 (94%) reviews had a detailed search description, only 17/68 (25%) searched without language restriction. 32/68 (47%) attempted to include unpublished data and 11/68 (16%) assessed for the risk of missing studies quantitatively. The reviews had deficiencies in the assessment of validity of studies and exploration for heterogeneity. When compared to Cochrane reviews, other reviews were significantly inferior in specifying questions (OR 20.3, 95% CI 1.1–381.3, p = 0.04), framing focussed questions (OR 30.9, 95% CI 3.7- 256.2, p = 0.001), use of unpublished data (OR 5.6, 95% CI 1.9–16.4, p = 0.002), assessment for heterogeneity (OR 38.1, 95%CI 2.1, 688.2, p = 0.01) and use of meta-analyses (OR 3.7, 95% CI 1.3–10.8, p = 0.02). Conclusion This study identifies areas which have a strong influence on maternal morbidity and mortality but lack good quality systematic reviews. Overall quality of the existing systematic reviews was variable. Cochrane reviews were of better quality as compared to other reviews. There is a need for good quality systematic reviews to inform practice in maternal medicine

Calf Performance Related to Pasture Quality and Supplements

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ANALYSIS OF NUCLEI FLUORESCENCE HISTOGRAMS USING NON-LINEAR FUNCTIONS OR WAVELETS

Histograms based on 5,000 nuclei from cells (Chinese hamster ovary cells, bone marrow cells) are used to determine the coefficient of variation (CV) of observations surrounding the highest peak. The cells are subjected to various treatments, for example exposure to herbicides. By eyeballing the histogram, an interval under the highest peak is determined. The CV calculated from the histogram on the eyeballed interval is the response variable in an ANOVA. To avoid the subjectivity of eyeballing the histogram, non-linear functions such as the Gaussian density function can be used to model the histogram. The CV may then be determined from the parameter estimates. In many experiments nonlinear functions modeling the histograms smooth away differences in CV s obtained this way, though visually the histograms appear to be different. Then nonlinear functions or wavelets can be used to obtain intervals for calculating CV s of the histograms restricted to these intervals. The nonlinear models require close initial values for each histogram, while the wavelets just require choice of wavelet and level of decomposition