Apoptotic and anti-proliferative effects of 17β-estradiol and 17β-estradiol-like compounds in the Hep3B cell line

Since there is evidence for estrogen and estrogen-like compounds to have beneficial effect on the pathogenesis of hepatocellular carcinoma (HCC), this study was designed to investigative the apoptotic and anti-proliferative effects of these compounds on the human hepatoma Hep3B cell line. The Hep3B cells were treated with 17β-estradiol (E2), diethylstilbestrol (DES), tamoxifen, and genistein. After treatments of these compounds at the concentration of 10^-6 or 10^-8 M, the Hep3B cells were demonstrated to have significant DNA fragmentation, nucleus condensation, cytochrome-c leaking from the mitochondria and caspase-3 activation by DAPI and Western blotting. The cells were also observed to have declined proliferative potential by MTT assay, arrested cell cycle by flow-cytometry measurements. However, the cytochrome-c leaking from the mitochondria induced by E2 and E2-like compounds was blocked totally by ICI 182,780 treatment. These finding suggest that estrogen and the estrogen-like compounds may induce anti-proliferative and apoptotic effects in Hep3B cells, and the E2 and the E2-like compounds mediated apoptotic effect was estrogen receptor dependent. Among the drugs tested, E2, E2 agonists (DES and genistein) and partial antagonist (tamoxifen), all showed the stronger anti-tumor potential. The last two authors, Wei-Wen Kuo and Chih-Yang Huang, share equal contribution.     

Interaction between maternal effects and temperature affects diapause occurrence in the cricket Allonemobius socius

The induction of diapause can be adaptive for egg survival during unfavorable conditions, while direct development can be advantageous under favorable conditions by allowing additional generations to exploit abundant resources. Therefore, the physiological capability of a female to respond to environmental cues indicative of habitat quality by producing eggs of the appropriate developmental phenotype should be under strong selection. Additionally, developing embryos may alter the developmental trajectory initiated by the female in response to changing environmental conditions. In this study, we used a cross-fostering approach to isolate the maternal effects of parental diapause history (not previously studied) and egg-laying temperature from the influence of the incubation environment experienced by the developing embryo on the proportion of diapause eggs produced by the striped ground cricket, Allonemobius socius. We found that an interaction between egg-incubation temperature and parental diapause history strongly affected the proportion of diapause eggs produced and the proportion of eggs that hatched within a 16–18 day incubation period, while egg-laying temperature and all other interactions did not. These novel results indicate that embryos can respond directly to the environmental conditions they experience during development, but that their ability to do so is influenced by maternal effects such as parental diapause history. The results of this study not only provide evidence, for the first time, of parental diapause history affecting diapause proportions, but also raise additional questions about the mechanism by which environmental information is transmitted from parent to offspring and how offspring are able to respond to conditions experienced during their own development.     

An ESS for the Height of a Plant Population, or an Optimal Height for an Individual?—Rethinking Game-Theoretic Models for Plant Height

Plants only interact with neighbors over restricted distances, so local conditions are of great significance for plants. It is therefore important to consider spatial structure and neighborhood effects if we are to understand plants' strategies. We constructed a spatially-explicit, game theory model to explore optimal height growth at the individual-level. In the model, there is no ESS for height growth at the population level, because there is an “instantaneous” optimal height growth strategy for the individual plant that changes depending on the local light environment. The optimal strategy is plasticity in response to local conditions. Game-theoretic models for plant phenotypic traits should move from “mean-field approximations” towards explicit modeling of local interactions.     

Mercaptoethanesulfonic acid (CoM imitator) interaction studies with nickel(II) complexes of pyridyl groups containing tetradentate ligands: Synthesis, structure, spectra and redox properties

Nickel(II) complexes of N,N′-dimethyl-N,N′-bis(pyridyl-2yl-methyl)ethylene-diamine (L¹), N,N′-dimethyl-N,N′-bis(pyridyl-2-ylmethyl)-1,2-diaminopropane (L²) and N,N′-dimethyl-N,N′-bis(pyridyl-2-ylmethyl)-1,3-diaminopropane (L³) were prepared and their spectroscopic and redox properties studied. The distorted octahedral structure was determined for [NiL³ClCH₃OH](ClO₄) by using X-ray crystallography. The electronic spectral behavior of the complexes at different pHs was analyzed; it is shown that a new band grew at the expense of the other band intensity in acid media. The redox properties of ligands and their complexes show the peaks of Ni(II) → Ni(III) and Ni(II) → Ni(0) as these were detected at low concentration while Ni(II) → Ni(I) process was detectable clearly at high concentration. Furthermore, the interaction studies of 2-mercaptoethanesulfonic acid as a simulator of coenzyme M reductase (CoM) with NiN₄ chromophores are discussed.     

Periodic habitat loss alters the competitive coexistence between brown trout and bullheads in a small stream over 34 years

1. Changes in the population density of juvenile sea trout Salmo trutta L. and bullheads Cottus gobio L. were compared in a small stream over 34 years. Both species have a similar diet and obviously live in the same general habitat. Habitat loss was most marked in seven summer droughts: severest in 1976, 1983, 1984, 1995, and less severe but followed by autumn droughts in 1969, 1989 and 1993. The contrasting effects of habitat loss on the two species were examined. 2. For both species, the Ricker curvilinear model significantly fit (P < 0.001) the relationship between initial egg density and survivor density for successive life stages, even though egg densities were much lower for bullheads than trout. These analyses provided evidence for density-dependent population regulation and also identified extreme outliers, most being for year-classes affected by summer droughts. 3. The variable effects of changes in habitable area (= % wettable area in sampling section) were quantified by using the residuals, each residual being the absolute value expressed as a percentage of the expected value from the Ricker curve. Significant relationships between the residuals and habitable area showed that habitat loss had a marked effect on survivor density, this being negative for 0+ and 1+ trout, and positive for 0+, 1+ and 2+/3+ bullheads. 4. Therefore, during periods of habitat loss in the summer months, bullhead density increased at the expense of trout density. Low flows and a decrease in wettable area were associated with a marked reduction in habitat quality for drift-feeding trout and an increase in habitat quality, and perhaps also quantity, for benthic-feeding bullheads. This case study shows that, during a major perturbation, the relationship between the densities of two species can change markedly in favour of the less numerous species. The competitive coexistence between the two species is therefore a dynamic process that changes through time with periodic changes in the environment.     

A nonlinear model with latent process for cognitive evolution using multivariate longitudinal data

Cognition is not directly measurable. It is assessed using psychometric tests, which can be viewed as quantitative measures of cognition with error. The aim of this article is to propose a model to describe the evolution in continuous time of unobserved cognition in the elderly and assess the impact of covariates directly on it. The latent cognitive process is defined using a linear mixed model including a Brownian motion and time-dependent covariates. The observed psychometric tests are considered as the results of parameterized nonlinear transformations of the latent cognitive process at discrete occasions. Estimation of the parameters contained both in the transformations and in the linear mixed model is achieved by maximizing the observed likelihood and graphical methods are performed to assess the goodness of fit of the model. The method is applied to data from PAQUID, a French prospective cohort study of ageing.     

A general approach for two-stage analysis of multilevel clustered non-Gaussian data

In this article, we propose a two-stage approach to modeling multilevel clustered non-Gaussian data with sufficiently large numbers of continuous measures per cluster. Such data are common in biological and medical studies utilizing monitoring or image-processing equipment. We consider a general class of hierarchical models that generalizes the model in the global two-stage (GTS) method for nonlinear mixed effects models by using any square-root-n-consistent and asymptotically normal estimators from stage 1 as pseudodata in the stage 2 model, and by extending the stage 2 model to accommodate random effects from multiple levels of clustering. The second-stage model is a standard linear mixed effects model with normal random effects, but the cluster-specific distributions, conditional on random effects, can be non-Gaussian. This methodology provides a flexible framework for modeling not only a location parameter but also other characteristics of conditional distributions that may be of specific interest. For estimation of the population parameters, we propose a conditional restricted maximum likelihood (CREML) approach and establish the asymptotic properties of the CREML estimators. The proposed general approach is illustrated using quartiles as cluster-specific parameters estimated in the first stage, and applied to the data example from a collagen fibril development study. We demonstrate using simulations that in samples with small numbers of independent clusters, the CREML estimators may perform better than conditional maximum likelihood estimators, which are a direct extension of the estimators from the GTS method.     

Case-control and case-only designs with genotype and family history data: estimating relative risk, residual familial aggregation, and cumulative risk

In case-control studies of inherited diseases, participating subjects (probands) are often interviewed to collect detailed data about disease history and age-at-onset information in their family members. Genotype data are typically collected from the probands, but not from their relatives. In this article, we introduce an approach that combines case-control analysis of data on the probands with kin-cohort analysis of disease history data on relatives. Assuming a marginally specified multivariate survival model for joint risk of disease among family members, we describe methods for estimating relative risk, cumulative risk, and residual familial aggregation. We also describe a variation of the methodology that can be used for kin-cohort analysis of the family history data from a sample of genotyped cases only. We perform simulation studies to assess performance of the proposed methodologies with correct and mis-specified models for familial aggregation. We illustrate the proposed methodologies by estimating the risk of breast cancer from BRCA1/2 mutations using data from the Washington Ashkenazi Study.     

A goodness-of-fit test for multinomial logistic regression

This article presents a score test to check the fit of a logistic regression model with two or more outcome categories. The null hypothesis that the model fits well is tested against the alternative that residuals of samples close to each other in covariate space tend to deviate from the model in the same direction. We propose a test statistic that is a sum of squared smoothed residuals, and show that it can be interpreted as a score test in a random effects model. By specifying the distance metric in covariate space, users can choose the alternative against which the test is directed, making it either an omnibus goodness-of-fit test or a test for lack of fit of specific model variables or outcome categories.