Hormonal regulation of uterine natural killer cells in mouse preimplantation uterus

Uterine Natural Killer (uNK) cells are the most abundant lymphocyte population recruited in the uteri during murine and human pregnancy. Previous investigation on uNK cells during mouse pregnancy focused more on its accumulation in postimplantation periods, which were believed to play important roles in regulating trophoblast invasion and angiogenesis towards successful placentation. However, by using recently developed methods of Dolichos biflorus agglutinin (DBA) lectin, a closer examination during mouse preimplantation revealed that there were also dynamic regulations of uNK cell, suggesting a major regulation by steroid hormones. Here we provide a detailed examination of uNK cells distribution during mouse early pregnancy by DBA lectin reactivity, with emphasis on preimplantation period and its hormonal regulation profiles. Our results showed that uNK precursor cells or its cell membrane specific components could be recruited in the uterus by estrogen or/and progesterone, and the effects could be completely abolished by specific antagonists of their nuclear receptors (estrogen and progesterone receptor). These results suggested that the preimplantation uterus, through concerted hormone regulation, could recruit uNK precursor cell or its specific cellular component, which might be conducive for uterine receptivity and further uNK construction/function during postimplantation.     

Mating behavior of the cabbage beetle, Colaphellus bowringi (Coleoptera: Chrysomelidae)

Abstract  Circadian mating rhythms, mating frequency, mating duration, and the effect of mating duration on fecundity and fertility in the cabbage beetle, Colaphellus bowringi were investigated in the laboratory. Mating occurred throughout the 24-h cycle but the majority of copulations occurred in the photophase with two apparent peaks, one at 8:00 and another at 16:00. Mating frequency observations for 10 consecutive days indicated that pre-mating period of C. bowringi was about 4 days, and pairs mated an average of 5 times per day and an average of 40 times during the first 10 days. There was a negative correlation between mating frequency and mating duration during the consecutive mating. The mean duration of the first copulation (136.24 ± 4.62 min) was significantly longer than those of the second (57.87 ± 2.03 min), third (53.05 ± 2.05 min) and fourth copulation (30.86 ± 2.98 min). Fecundity showed a slight increase with increasing mating duration but no significant difference among treatments. However, fertility was significantly influenced by the mating duration in this species. Mating of 20-min duration did not produce viable eggs. The mean percentage of fertile eggs with completed mating duration (204.43 ± 18.96 min, 56.75% fertile eggs) was significantly higher than those with 60 min (39.55%) and 30 min (17.91%) mating duration, suggesting that the longer mating duration might be associated with transfer of more sperm that are used to increase the fertility of eggs.     

The evolutionary impact of androgen levels on prostate cancer in a multi-scale mathematical model

Background  

Androgens bind to the androgen receptor (AR) in prostate cells and are essential survival factors for healthy prostate epithelium. Most untreated prostate cancers retain some dependence upon the AR and respond, at least transiently, to androgen ablation therapy. However, the relationship between endogenous androgen levels and cancer etiology is unclear. High levels of androgens have traditionally been viewed as driving abnormal proliferation leading to cancer, but it has also been suggested that low levels of androgen could induce selective pressure for abnormal cells. We formulate a mathematical model of androgen regulated prostate growth to study the effects of abnormal androgen levels on selection for pre-malignant phenotypes in early prostate cancer development.     

Megf10 regulates the progression of the satellite cell myogenic program

We identify here the multiple epidermal growth factor repeat transmembrane protein Megf10 as a quiescent satellite cell marker that is also expressed in skeletal myoblasts but not in differentiated myofibers. Retroviral expression of Megf10 in myoblasts results in enhanced proliferation and inhibited differentiation. Infected myoblasts that fail to differentiate undergo cell cycle arrest and can reenter the cell cycle upon serum restimulation. Moreover, experimental modulations of Megf10 alter the expression levels of Pax7 and the myogenic regulatory factors. In contrast, Megf10 silencing in activated satellite cells on individual fibers or in cultured myoblasts results in a dramatic reduction in the cell number, caused by myogenin activation and precocious differentiation as well as a depletion of the self-renewing Pax7⁺/MyoD⁻ population. Additionally, Megf10 silencing in MyoD^−/− myoblasts results in down-regulation of Notch signaling components. We conclude that Megf10 represents a novel transmembrane protein that impinges on Notch signaling to regulate the satellite cell population balance between proliferation and differentiation.     

Robust smooth segmentation approach for array CGH data analysis

MOTIVATION: Array comparative genomic hybridization (aCGH) provides a genome-wide technique to screen for copy number alteration. The existing segmentation approaches for analyzing aCGH data are based on modeling data as a series of discrete segments with unknown boundaries and unknown heights. Although the biological process of copy number alteration is discrete, in reality a variety of biological and experimental factors can cause the signal to deviate from a stepwise function. To take this into account, we propose a smooth segmentation (smoothseg) approach. METHODS: To achieve a robust segmentation, we use a doubly heavy-tailed random-effect model. The first heavy-tailed structure on the errors deals with outliers in the observations, and the second deals with possible jumps in the underlying pattern associated with different segments. We develop a fast and reliable computational procedure based on the iterative weighted least-squares algorithm with band-limited matrix inversion. RESULTS: Using simulated and real data sets, we demonstrate how smoothseg can aid in identification of regions with genomic alteration and in classification of samples. For the real data sets, smoothseg leads to smaller false discovery rate and classification error rate than the circular binary segmentation (CBS) algorithm. In a realistic simulation setting, smoothseg is better than wavelet smoothing and CBS in identification of regions with genomic alterations and better than CBS in classification of samples. For comparative analyses, we demonstrate that segmenting the t-statistics performs better than segmenting the data. AVAILABILITY: The R package smoothseg to perform smooth segmentation is available from http://www.meb.ki.se/~yudpaw.     

Metabolic network properties help assign weights to elementary modes to understand physiological flux distributions

MOTIVATION: Elementary modes (EMs) analysis has been well established. The existing methodologies for assigning weights to EMs cannot be directly applied for large-scale metabolic networks, since the tremendous number of modes would make the computation a time-consuming or even an impossible mission. Therefore, developing more efficient methods to deal with large set of EMs is urgent. RESULT: We develop a method to evaluate the performance of employing a subset of the elementary modes to reconstruct a real flux distribution by using the relative error between the real flux vector and the reconstructed one as an indicator. We have found a power function relationship between the decrease of relative error and the increase of the number of the selecting EMs, and a logarithmic relationship between the increases of the number of non-zero weighted EMs and that of the number of the selecting EMs. Our discoveries show that it is possible to reconstruct a given flux distribution by a selected subset of EMs from a large metabolic network and furthermore, they help us identify the 'governing modes' to represent the cellular metabolism for such a condition.     

Nitrogen addition increases aboveground silicon and phytolith concentrations in understory plants of a tropical forest

Plant and Soil - Silicon (Si) is a beneficial element for plants and plays important roles in the biogeochemical cycle of mineral elements. Yet, few studies have focused on the impact of nitrogen...     

Effects of mutations of D1-R323, D1-N322, D1-D319, D1-H304 on the functioning of photosystem II in Thermosynechococcus vulcanus

Photosynthesis Research - Photosystem II (PSII) has a number of hydrogen-bonding networks connecting the manganese cluster with the lumenal bulk solution. The structure of PSII from...