g., increased body size in colder/more northern populations); however, several phenotypic responses were not consistent between sampling years, pointing towards plastic phenotypes. Our analysis of common-garden reared individuals uncovered moderate heritability estimates only for two measures of male body size (intraclass correlation coefficient, ICC = 0.628 and 0.556) and offspring fat content (ICC = 0.734), while suggesting high levels of plasticity in most other phenotypic traits (ICC ≤ 0.407). Our results highlight the importance of phenotypic plasticity in invasive species during range expansions and demonstrate that strong selective pressures-in this case towards increased body size in colder environments-simultaneously promote rapid evolutionary divergence.Since the mid-1990s, the decline of the yellow perch population of Lake Saint-Pierre (hereinafter LSP) in Quebec, Canada has been the subject of several research programs. The combined effect of habitat deterioration, the presence of invasive species, and poor water quality negatively affected the yellow perch population in this lake. In 2013, we sampled yellow perch (larvae, juveniles and adults) at six sites along the St. Lawrence River representing a gradient of increasing human influences from upstream to downstream and measured several biomarkers including retinoid compounds (vitamin A). In the most contaminated sites (LSP, north and south shores), we found that retinoid stores were decreased in all three stages of development. To corroborate these results and to test other biomarkers, we once again sampled yellow perch (adults only) from the same sites. Results from our 2014 and 2015 samplings confirmed that LSP yellow perch appeared to be at a disadvantage compared to fish from upstream populations. Individuals from LSP have lower acetylcholinesterase (AChE) activity as well as lower retinoid levels in liver and plasma. These fish were also marked by lower levels of antioxidants such as lycopene and vitamin E. A discriminant analysis of this set of results confirmed that the yellow perch of the LSP could be easily discriminated from those of the other sites (2014 and 2015) on the basis of liver retinoid and, to a lesser extent, of the liver tocopherol and protein concentration of the muscle, as well as AChE activity and DROH (all-trans-3,4-dehydroretinol) measured in plasma.Vegetation phenology such as the start (SOS) and end (EOS) of the growing season, physiology (represented by seasonal maximum capacity of carbon uptake, GPPmax), and gross primary production (GPP) are sensitive indicators for monitoring ecosystem response to environmental change. However, uncertainty and disagreement between models limit the use phenology metrics and GPP derived from remote sensing data. Statistical models for estimating phenology and physiology were constructed based on key predictor variables derived from enhanced vegetation index (EVI) and land surface temperature (LST) data. Then, a statistical model that integrated remote sensing-based phenology and physiology (RS-SMIPP) data was constructed to estimate seasonal and annual GPP. These models were calibrated and validated with GPP observations from 512 site-years of FLUXNET data covering four plant functional types (PFTs) in the northern hemisphere deciduous broadleaf forest, evergreen needle-leaf forest, mixed forest, and grassland. Our results showed that phenology and physiology were accurately estimated with relative root mean squared error (RMSEr) less then 20%, and the errors varied among the PFTs. Spring EVI was an important factor in explaining variation of GPPmax. The RS-SMIPP model outperformed the MOD17 algorithm in accurately estimating seasonal and annual GPP and reduced RMSEr from 25.34%-43.44% to 9.53%-26.19% for annual GPP of the different PFTs. These findings demonstrate that remote sensing-based phenological and physiological indicators could be used to explain the variations of seasonal and annual GPP, and provide an efficient way for improving GPP estimations at a global scale.Indoor dust often contains organic contaminants, which adversely impacts human health. In this study, the organic contaminants in the indoor dust from commercial offices and residential houses in Nanjing, China were extracted and their effects on human breast cancer cells (MCF-7) were investigated. Both dust extracts promoted proliferation of MCF-7 cells at ≤24 μg/100 μL, with cell viability being decreased with increasing dust concentrations. Based on LC50, house dust was less toxic than office dust. At 8 μg/100 μL, both extracts caused more MCF-7 cells into active cycling (G2/M + S) and increased intracellular Ca2+ influx, with house dust inducing stronger effects than office dust. Further, the expression of estrogen-responsive genes for TFF1 and EGR3 was enhanced by 3-9 and 4-9 folds, while the expression of cell cycle regulatory genes for cyclin D was enhanced by 2-5 folds. The results suggested that organic dust extract influenced cell viability, altered cell cycle, increased intracellular Ca2+ levels, and activated cell cycle regulatory and estrogen-responsive gene expressions, with house dust showing lower cytotoxicity but higher estrogenic potential on MCF-7 cells. The results indicate the importance of reducing organic contaminants in indoor dust to mitigate their adverse impacts on human health.A significant part of the common agricultural policy (CAP) focuses on implementing environmentally friendly practices, which have been evaluated in many studies. However, these analyses do not usually consider spatial spillovers that may concern pollution and biodiversity, as well as participation in policy schemes. Most studies evaluate national environmental policies at the macroeconomic level, focusing on cities. However, the majority of natural resources are in rural districts, and environmental policy is mainly implemented at the local level, where most of the budgets for environmental protection are decided. Thus, in this paper, our first objective is to assess the cost-effectiveness of Poland's environmental policy schemes, combining local expenditures at the county level with the CAP's green schemes.  https://www.selleckchem.com/products/mln2480.html  Additionally, we investigate the spatial (neighbourhood) effects of environment quality and the policy, as well as their mutual interactions. First, the environmental quality at the county level is proxied by the composite environmental quality index (CEQI); second, the Spatial Durbin Model (SDM) with endogenous covariates is estimated.