The role of maternal effects on offspring performance in familiar and novel environments

Maternal effects are an important evolutionary force that may either facilitate adaptation to a new environment or buffer against unfavourable conditions. The degree of variation in traits expressed by siblings from different mothers is often sensitive to environmental conditions. This could generate a Maternal-by-Environment interaction (M × E) that inflates estimates of Genotype-by-Environment effects (G × E). We aimed to test for environment-specific maternal effects (M × E) using a paternal full-sib/half-sib breeding design in the seed beetle Callosobruchus maculatus, where we split and reared offspring from the same mother on two different bean host types—original and novel. Our quantitative genetic analysis indicated that maternal effects were very small on both host types for all the measured life-history traits. There was also little evidence that maternal oviposition preference for a particular host type predicted her offspring’s performance on that host. Further, additive genetic variance for most traits was relatively high on both hosts. While there was higher heritability for offspring reared in the novel host, there was no evidence for G × Es, and most cross-host genetic correlations were positive. This suggests that offspring from the same family ranked similarly for performance on both host types. Our results point to a genetic basis of host adaptation in the seed beetle, rather than maternal effects. Even so, we encourage researchers to test for potential M × Es because, due to a lack of testing, it remains unclear how often they arise.Subject terms: Evolutionary genetics, Quantitative trait     

Plant species richness–productivity relationships in a low-productive boreal region

Local species richness–productivity (SR–P) relationship is usually reported as unimodal if long productivity gradients are sampled. However, it tends to be monotonically increasing in low-productive environments due to the decreasing part of the SR–P curve being truncated. Previous work indicated that this can hold true for forest herb layers, because of an upper bound on productivity caused mainly by canopy shading. Here, we ask whether the same pattern exists in a region with an upper bound on productivity caused by a harsh climate. We sampled herbaceous vegetation of boreal forests and grasslands in a low-productive region of central Yakutia (NE Siberia) with dry and winter-cool continental climate. We collected data on species composition, herb-layer productivity (aboveground herbaceous biomass), soil chemistry and light availability. We applied regression models to discriminate between monotonically increasing, decreasing and unimodal responses of herb-layer species richness to measured variables and analysed trends in the species-pool size and beta diversity along the productivity gradient. Our expectation of the monotonically increasing SR–P relationship was confirmed for neither forest herb layers nor grasslands. In the forest herb layers, no relationship was detected. In grasslands, the relationship was unimodal with species richness decline starting at much lower productivity levels than in more productive temperate grasslands. Potential causes for this decline are either limitation of local species richness by the species pool, which contains few species adapted to more productive habitats, or competitive exclusion, which can become an important control of species richness under lower levels of productivity than is the case in temperate grasslands.     

Targeting CD44-STAT3 Signaling by Gemini Vitamin D Analog Leads to Inhibition of Invasion in Basal-Like Breast Cancer

Background

CD44, a transmembrane glycoprotein, is a major receptor for extracellular proteins involved in invasion and metastasis of human cancers. We have previously demonstrated that the novel Gemini vitamin D analog BXL0124 [1α,25-dihydroxy-20R-21(3-hydroxy-3-deuteromethyl-4,4,4-trideuterobutyl)-23-yne-26,27-hexafluro-cholecalciferol] repressed CD44 expression in MCF10DCIS.com basal-like human breast cancer cells and inhibited MCF10DCIS xenograft tumor growth. In the present study, we investigated potential factors downstream of CD44 and the biological role of CD44 repression by BXL0124 in MCF10DCIS cells.

Methods and Findings

The treatment with Gemini vitamin D BXL0124 decreased CD44 protein level, suppressed STAT3 signaling, and inhibited invasion and proliferation of MCF10DCIS cells. The interaction between CD44 and STAT3 was determined by co-immunoprecipitation. CD44 forms a complex with STAT3 and Janus kinase 2 (JAK2) to activate STAT3 signaling, which was inhibited by BXL0124 in MCF10DCIS cells. The role of CD44 in STAT3 signaling and invasion of MCF10DCIS cells was further determined by the knockdown of CD44 using small hairpin RNA in vitro and in vivo. MCF10DCIS cell invasion was markedly decreased by the knockdown of CD44 in vitro. The knockdown of CD44 also significantly decreased mRNA expression levels of invasion markers, matrix metalloproteinases (MMPs) and urokinase plasminogen activator (uPA), in MCF10DCIS cells. In MCF10DCIS xenograft tumors, CD44 knockdown decreased tumor size and weight as well as invasion markers.

Conclusions

The present study identifies STAT3 as an important signaling molecule interacting with CD44 and demonstrates the essential role of CD44-STAT3 signaling in breast cancer invasion. It also suggests that repression of CD44-STAT3 signaling is a key molecular mechanism in the inhibition of breast cancer invasion by the Gemini vitamin D analog BXL0124.     

siMS Score: Simple Method for Quantifying Metabolic Syndrome

Objective

To evaluate siMS score and siMS risk score, novel continuous metabolic syndrome scores as methods for quantification of metabolic status and risk.

Materials and Methods

Developed siMS score was calculated using formula: siMS score = 2*Waist/Height + Gly/5.6 + Tg/1.7 + TA_systolic/130—HDL/1.02 or 1.28 (for male or female subjects, respectively). siMS risk score was calculated using formula: siMS risk score = siMS score * age/45 or 50 (for male or female subjects, respectively) * family history of cardio/cerebro-vascular events (event = 1.2, no event = 1). A sample of 528 obese and non-obese participants was used to validate siMS score and siMS risk score. Scores calculated as sum of z-scores (each component of metabolic syndrome regressed with age and gender) and sum of scores derived from principal component analysis (PCA) were used for evaluation of siMS score. Variants were made by replacing glucose with HOMA in calculations. Framingham score was used for evaluation of siMS risk score.

Results

Correlation between siMS score with sum of z-scores and weighted sum of factors of PCA was high (r = 0.866 and r = 0.822, respectively). Correlation between siMS risk score and log transformed Framingham score was medium to high for age groups 18+,30+ and 35+ (0.835, 0.707 and 0.667, respectively).

Conclusions

siMS score and siMS risk score showed high correlation with more complex scores. Demonstrated accuracy together with superior simplicity and the ability to evaluate and follow-up individual patients makes siMS and siMS risk scores very convenient for use in clinical practice and research as well.     

Performance of the eclipse monitor unit objective tool utilizing volumetric modulated arc therapy for rectal cancer

AimTo assess the performance of the monitor unit (MU) Objective tool in Eclipse treatment planning system (TPS) utilizing volumetric modulated arc therapy (VMAT) for rectal cancer.BackgroundEclipse VMAT planning module includes a tool to control the number of MUs delivered: the MU Objective tool. This tool could be utilized to reduce the total number of MUs in rectal cancer treatments.Materials and methods20 rectal cancer patients were retrospectively studied using VMAT and the MU Objective tool. The baseline plan for each patient was selected as the one with no usage of the MU Objective tool. The number of MUs of this plan was set to be the reference number of MUs (MU_ref). Five plans were re-optimized for each patient only varying the Max MU parameter. The selected values were 30%, 60%, 90%, 120% and 150% of MU_ref for each patient. Differences with respect to the baseline plan were evaluated regarding MU number and parameters for PTVs coverage evaluation, PTVs homogeneity and OARs doses assessment. A two-tailed, paired-samples t-test was used to quantify these differences.ResultsAverage relative differences in MU number obtained was 10% for Max MU values of 30% and 60% of MU_ref, respectively (p < 0.03). PTVs coverage and homogeneity were not compromised and discrepancies obtained with respect to baseline plans were not significant. Furthermore, maximum OARs doses deviations were also not significant.ConclusionsA 10% reduction in the MU number could be obtained without an alteration of PTV coverage and OARs doses for rectal cancer.