Some new indole–coumarin hybrids; Synthesis,anticancer and Bcl-2 docking studies

Hybrid molecules have attracted attention for their improved biological activity, selectivity and lesser side effects profile, distinct from their individual components. In the quest for novel anticancer drug entities, three series of indole–coumarin hybrids – 3-(1-benzyl-1H-indol-2-yl)-2H-chromen-2-ones, 2-(2-oxo-2H-chromen-3-yl)-1H-indole-3-carbaldehydes and 2-(2-oxo-2H-chromen-3-yl)-1H-indole-3-carboxylic acids were synthesized. All the synthesized compounds were characterized by spectral techniques like IR, ¹H NMR, ¹³C NMR, mass spectrometry and elemental analysis. In silico docking studies of synthesized molecules with apoptosis related gene Bcl-2 that is recognized to play an important role in tumerogenesis were carried out. Dose-dependent cytotoxic effect of the compounds in human breast adenocarcinoma (MCF-7) and normal cell lines were assessed using MTT assay and compared with that of the standard marketed drug, Vincristine. Compound 4c had a highly lipophilic bromine substituent capable of forming halogen bond and was identified as a potent molecule both in docking as well as cytotoxicity studies. Flow cytometric cell cycle analysis of 4c exhibited apoptotic mode of cell death due to cell cycle arrest in G2/M phase. Structure activity relationship of these hybrid molecules was also studied to determine the effect of steric and electronic properties of the substituents on cell viability.     

7,9-Diaryl-1,6,8-trioxaspiro[4.5]dec-3-en-2-ones: Readily accessible and highly potent anticancer compounds

7,9-Diaryl-1,6,8-trioxaspiro[4.5]dec-3-en-2-ones are a recently described group of spirocyclic butenolides that can be generated rapidly and as a single diastereomer through a cascade process between γ-hydroxybutenolides and aromatic aldehydes. The following outlines our findings that these spirocycles are potently cytotoxic and have a dramatic structure–function profile that provides excellent insight into the structural features required for this potency.     

Effects of carbon dioxide concentration on the interactive effects of temperature and water vapour on stomatal conductance in soybean

Soybeans were grown at three CO₂ concentrations in outdoor growth chambers and at two concentrations in controlled-environment growth chambers to investigate the interactive effects of CO₂, temperature and leaf-to-air vapour pressure difference (LAVPD) on stomatal conductance. The decline in stomatal conductance with CO₂ was a function of both leaf temperature and LAVPD. In the field measurements, stomatal conductance was more sensitive to LAVPD at low CO₂ at 30 °C but not at 35 °C. There was also a direct increase in conductance with temperature, which was greater at the two elevated carbon dioxide concentrations. Environmental growth chamber results showed that the relative stomatal sensitivity to LAVPD decreased with both leaf temperature and CO₂. Measurements in the environmental growth chamber were also performed at the opposing CO₂, and these experiments indicate that the stomatal sensitivity to LAVPD was determined more by growth CO₂ than by measurement CO₂. Two models that describe stomatal responses to LAVPD were compared with the outdoor data to evaluate whether these models described adequately the interactive effects of CO₂, LAVPD and temperature.     

On the Information Matrix of Exponential Mixture Models with Long-term Survivors

The aim of this paper is to study the properties of the asymptotic variances of the maximum likelihood estimators of the parameters of the exponential mixture model with long-term survivors for randomly censored data. In addition, we study the asymptotic relative efficiency of these estimators versus those which would be obtained with complete follow-up. It is shown that fixed censoring at time T produces higher precision as well as higher asymptotic relative efficiency than those obtainable under uniform and uniform-exponential censoring distributions over (0, T). The results are useful in planning the size and duration of survival experiments with long-term survivors under random censoring schemes.     

Understanding telomerase in cancer stem cell biology

Comment on: Vicente-Dueñas C, et al. Oncotarget 2012; Epub ahead of print; PMID:22408137.     

A study on the minimum number of loci required for genetic evaluation using a finite locus model

For a finite locus model, Markov chain Monte Carlo (MCMC) methods can be used to estimate the conditional mean of genotypic values given phenotypes, which is also known as the best predictor (BP). When computationally feasible, this type of genetic prediction provides an elegant solution to the problem of genetic evaluation under non-additive inheritance, especially for crossbred data. Successful application of MCMC methods for genetic evaluation using finite locus models depends, among other factors, on the number of loci assumed in the model. The effect of the assumed number of loci on evaluations obtained by BP was investigated using data simulated with about 100 loci. For several small pedigrees, genetic evaluations obtained by best linear prediction (BLP) were compared to genetic evaluations obtained by BP. For BLP evaluation, used here as the standard of comparison, only the first and second moments of the joint distribution of the genotypic and phenotypic values must be known. These moments were calculated from the gene frequencies and genotypic effects used in the simulation model. BP evaluation requires the complete distribution to be known. For each model used for BP evaluation, the gene frequencies and genotypic effects, which completely specify the required distribution, were derived such that the genotypic mean, the additive variance, and the dominance variance were the same as in the simulation model. For lowly heritable traits, evaluations obtained by BP under models with up to three loci closely matched the evaluations obtained by BLP for both purebred and crossbred data. For highly heritable traits, models with up to six loci were needed to match the evaluations obtained by BLP.     

Twelve-Hour Night Shifts of Healthcare Workers: A Risk to the Patients?

We assessed the impact of 12h fixed night shift (19:00–07:00h) work, followed by 36h of off-time, on the sleep–wake cycle, sleep duration, self-perceived sleep quality, and work-time alertness on a group composed of 5 registered and 15 practical nurses. Wrist actigraphy (Ambulatory Monitoring, Inc.), with data analysis by the Cole-Kripke algorithm, was applied to determine sleep/wake episodes and their duration. The sleep episodes were divided into six categories: sleep during the night shift (x¯=208.6; SD±90.6mins), sleep after the night shift (x¯=138.7; SD±79.6min), sleep during the first night after the night work (x¯=318.5; SD±134.6min), sleep before the night work (x¯=104.3; SD±44.1min), diurnal sleep during the rest day (x¯=70.5; SD±43.0min), and nocturnal sleep during the rest day (x¯=310.4; SD±188.9mins). A significant difference (p<.0001; T-test for dependent samples) was detected between the perceived quality of sleep of the three diurnal sleep categories compared to the three nocturnal sleep categories. Even thought the nurses slept (napped) during the night shift, their self-perceived alertness systematically decreased during it. Statistically significant differences were documented by one-way ANOVA (F=40.534 p<.0001) among the alertness measurements done during the night shift. In particular, there was significant difference in the level of perceived alertness (p<.0001) between the 7^th and 10^thh of the 12h night shift. These findings of decreased alertness during the terminal hours of the night shift are of concern, since they suggest risk of comprised patient care.