There are 18 new articles in PLoS ONE today. As always, you should rate the articles, post notes and comments and send trackbacks when you blog about the papers. You can now also easily place articles on various social services (CiteULike, Mendeley, Connotea, Stumbleupon, Facebook and Digg) with just one click. Here are my own picks for the week - you go and look for your own favourites:
Daily heterothermia is used by small mammals for energy and water savings, and seems to be preferentially exhibited during winter rather than during summer. This feature induces a trade-off between the energy saved during daily heterothermia and the energy cost of arousal, which can impact energy balance and survival under harsh environmental conditions. Especially, aging may significantly affect such trade off during cold-induced energy stress, but direct evidences are still lacking. We hypothesized that aging could alter the energetics of daily heterothermia, and that the effects could differ according to season. In the gray mouse lemur (Microcebus murinus), a non-human primate species which exhibits daily heterothermia, we investigated the effects of exposures to 25 and 12Â°C on body composition, energy balance, patterns of heterothermia and water turnover in adult (N = 8) and aged animals (N = 7) acclimated to winter-like or summer-like photoperiods.
Acclimation to summer prevented animals from deep heterothermia, even during aging. During winter, adult animals at 12Â°C and aged animals at 25Â°C exhibited low levels of energy expenditure with minor modulations of heterothermia. The major effects of cold were observed during winter, and were particularly pronounced in aged mouse lemurs which exhibited deep heterothermia phases. Body composition was not significantly affected by age and could not explain the age-related differences in heterothermia patterns. However, aging was associated with increased levels of energy expenditure during cold exposure, in concomitance with impaired energy balance. Interestingly, increased energy expenditure and depth of heterothermia phases were strongly correlated.
In conclusion, it appeared that the exhibition of shallow heterothermia allowed energy savings during winter in adult animals only. Aged animals exhibited deep heterothermia and increased levels of energy expenditure, impairing energy balance. Thus, an impaired control of the heterothermic process induced high energy costs in the aging mouse lemur exposed to cold.
The communicative meaning of human areolae for newborn infants was examined here in directly exposing 3-day old neonates to the secretion from the areolar glands of Montgomery donated by non related, non familiar lactating women. The effect of the areolar stimulus on the infants' behavior and autonomic nervous system was compared to that of seven reference stimuli originating either from human or non human mammalian sources, or from an arbitrarily-chosen artificial odorant. The odor of the native areolar secretion intensified more than all other stimuli the infants' inspiratory activity and appetitive oral responses. These responses appeared to develop independently from direct experience with the breast or milk. Areolar secretions from lactating women are especially salient to human newborns. Volatile compounds carried in these substrates are thus in a position to play a key role in establishing behavioral and physiological processes pertaining to milk transfer and production, and, hence, to survival and to the early engagement of attachment and bonding.
Postmating, prezygotic phenotypes, especially those that underlie reproductive isolation between closely related species, have been a central focus of evolutionary biologists over the past two decades. Such phenotypes are thought to evolve rapidly and be nearly ubiquitous among sexually reproducing eukaryotes where females mate with multiple partners. Because these phenotypes represent interplay between the male ejaculate and female reproductive tract, they are fertile ground for reproductive senescence - as ejaculate composition and female physiology typically change over an individual's life span. Although these phenotypes and their resulting dynamics are important, we have little understanding of the proteins that mediate these phenotypes, particularly for species groups where postmating, prezygotic traits are the primary mechanism of reproductive isolation. Here, we utilize proteomics, RNAi, mating experiments, and the Allonemobius socius complex of crickets, whose members are primarily isolated from one another by postmating, prezygotic phenotypes (including the ability of a male to induce a female to lay eggs), to demonstrate that one of the most abundant ejaculate proteins (a male accessory gland-biased protein similar to a trypsin-like serine protease) decreases in abundance over a male's reproductive lifetime and mediates the induction of egg-laying in females. These findings represent one of the first studies to identify a protein that plays a role in mediating both a postmating, prezygotic isolation pathway and reproductive senescence.
High-throughput gene expression profiling technologies generating a wealth of data, are increasingly used for characterization of tumor biopsies for clinical trials. By applying machine learning algorithms to such clinically documented data sets, one hopes to improve tumor diagnosis, prognosis, as well as prediction of treatment response. However, the limited number of patients enrolled in a single trial study limits the power of machine learning approaches due to over-fitting. One could partially overcome this limitation by merging data from different studies. Nevertheless, such data sets differ from each other with regard to technical biases, patient selection criteria and follow-up treatment. It is therefore not clear at all whether the advantage of increased sample size outweighs the disadvantage of higher heterogeneity of merged data sets. Here, we present a systematic study to answer this question specifically for breast cancer data sets. We use survival prediction based on Cox regression as an assay to measure the added value of merged data sets. Using time-dependent Receiver Operating Characteristic-Area Under the Curve (ROC-AUC) and hazard ratio as performance measures, we see in overall no significant improvement or deterioration of survival prediction with merged data sets as compared to individual data sets. This apparently was due to the fact that a few genes with strong prognostic power were not available on all microarray platforms and thus were not retained in the merged data sets. Surprisingly, we found that the overall best performance was achieved with a single-gene predictor consisting of CYB5D1. Merging did not deteriorate performance on average despite (a) The diversity of microarray platforms used. (b) The heterogeneity of patients cohorts. (c) The heterogeneity of breast cancer disease. (d) Substantial variation of time to death or relapse. (e) The reduced number of genes in the merged data sets. Predictors derived from the merged data sets were more robust, consistent and reproducible across microarray platforms. Moreover, merging data sets from different studies helps to better understand the biases of individual studies and can lead to the identification of strong survival factors like CYB5D1 expression.
The notion that gene duplications generating new genes and functions is commonly accepted in evolutionary biology. However, this assumption is more speculative from theory rather than well proven in genome-wide studies. Here, we generated an atlas of the rate of copy number changes (CNCs) in all the gene families of ten animal genomes. We grouped the gene families with similar CNC dynamics into rate pattern groups (RPGs) and annotated their function using a novel bottom-up approach. By comparing CNC rate patterns, we showed that most of the species-specific CNC rates groups are formed by gene duplication rather than gene loss, and most of the changes in rates of CNCs may be the result of adaptive evolution. We also found that the functions of many RPGs match their biological significance well. Our work confirmed the role of gene duplication in generating novel phenotypes, and the results can serve as a guide for researchers to connect the phenotypic features to certain gene duplications.
Most animals display multiple behavioral states and control the time allocation to each of their activity phases depending on their environment. Here we develop a new quantitative method to analyze Caenorhabditis elegans behavioral states. We show that the dwelling and roaming two-state behavior of C. elegans is tightly controlled by the concentration of food in the environment of the animal. Sensory perception through the amphid neurons is necessary to extend roaming phases while internal metabolic perception of food nutritional value is needed to induce dwelling. Our analysis also shows that the proportion of time spent in each state is modulated by past nutritional experiences of the animal. This two-state behavior is regulated through serotonin as well as insulin and TGF-beta signaling pathways. We propose a model where food nutritional value is assessed through internal metabolic signaling. Biogenic amines signaling could allow the worm to adapt to fast changes in the environment when peptide transcriptional pathways may mediate slower adaptive changes.