Matrilineal behavioral and physiological changes following the death of a non-alpha matriarch in rhesus macaque

In many species, the loss of alpha matriarchs is associated with a number of negative outcomes such as troop fission, eviction, wounding, and reduced vitality. However, whether the dramatic consequences of their loss are due to their role as an old experienced figure or to their alpha status remains unclear. In a retrospective study, we tested that in a semi-free ranging colony of rhesus macaques (Macaca mulatta), the removal of a non-alpha matriarch, who had a large set of kin, led to changes in behavior and physiological stress within her matriline. Following her removal, her matriline increased in aggression, vigilance, and social grooming. Additionally, hierarchical stability, measured by levels of rank changes, decreased within her matriline, and levels of intense aggression by high-ranking animals were more frequent, as well as matrilineal wounding. Although ordinal rank was positively associated with higher chronic hair cortisol concentrations (HCCs) in the months before the matriarch’s removal, following her removal, only those who experienced large increases in rank within her matriline displayed higher HCCs. Changes in matrilineal stability, aggression, behavior, and HCCs within the other two matrilines in the troop were not evident, although caution is needed due to the small sample sizes. We conclude that the removal of the non-alpha matriarch led to matrilineal instability, characterized by higher levels of aggression and subsequent vigilance, rank changes, physiological stress, and grooming. We suggest that non-alpha matriarchs with a large number of kin and social support can be integral to the stability of matrilines.Division of Intramural Research, National Institute of Child Health and Human Development, 1ZIAHD001107- 3

Identifying Low pH Active and Lactate-Utilizing Taxa within Oral Microbiome Communities from Healthy Children Using Stable Isotope Probing Techniques

<div><h3>Background</h3><p>Many human microbial infectious diseases including dental caries are polymicrobial in nature. How these complex multi-species communities evolve from a healthy to a diseased state is not well understood. Although many health- or disease-associated oral bacteria have been characterized <em>in vitro</em>, their physiology within the complex oral microbiome is difficult to determine with current approaches. In addition, about half of these species remain uncultivated to date with little known besides their 16S rRNA sequence. Lacking culture-based physiological analyses, the functional roles of uncultivated species will remain enigmatic despite their apparent disease correlation. To start addressing these knowledge gaps, we applied a combination of Magnetic Resonance Spectroscopy (MRS) with RNA and DNA based Stable Isotope Probing (SIP) to oral plaque communities from healthy children for <em>in vitro</em> temporal monitoring of metabolites and identification of metabolically active and inactive bacterial species.</p> <h3>Methodology/Principal Findings</h3><p>Supragingival plaque samples from caries-free children incubated with ¹³C-substrates under imposed healthy (buffered, pH 7) and diseased states (pH 5.5 and pH 4.5) produced lactate as the dominant organic acid from glucose metabolism. Rapid lactate utilization upon glucose depletion was observed under pH 7 conditions. SIP analyses revealed a number of genera containing cultured and uncultivated taxa with metabolic capabilities at pH 5.5. The diversity of active species decreased significantly at pH 4.5 and was dominated by <em>Lactobacillus</em> and <em>Propionibacterium</em> species, both of which have been previously found within carious lesions from children.</p> <h3>Conclusions/Significance</h3><p>Our approach allowed for identification of species that metabolize carbohydrates under different pH conditions and supports the importance of Lactobacilli and Propionibacterium in the development of childhood caries. Identification of species within healthy subjects that are active at low pH can lead to a better understanding of oral caries onset and generate appropriate targets for preventative measures in the early stages.</p> </div

An Efficient High Order Algorithm for Solving Reaction-Diffusion Equations

An efficient higher order finite difference algorithm is presented in this paper for solving systems of two-dimensional reaction-diffusion equations with nonlinear reaction terms. It is fourth order accurate in both the temporal and spatial dimensions. A regular five-point difference of stencil similar to that used in the Crank-Nicolson algorithm, which is only second order accurate in the temporal and spatial dimensions, is used in the discretization. The higher order accuracy in the new algorithm is achieved by using the Pade approximation for the second order spatial derivatives and extrapolations in the temporal dimension. Numerical examples will be presented in the paper to demonstrate efficiency and accuracy improvement using the new algorithm

An Efficient High Order Algorithm for Solving Reaction-Diffusion Equations

An efficient higher order finite difference algorithm is presented in this paper for solving systems of two-dimensional reaction-diffusion equations with nonlinear reaction terms. It is fourth order accurate in both the temporal and spatial dimensions. A regular five-point difference of stencil similar to that used in the Crank-Nicolson algorithm, which is only second order accurate in the temporal and spatial dimensions, is used in the discretization. The higher order accuracy in the new algorithm is achieved by using the Pade approximation for the second order spatial derivatives and extrapolations in the temporal dimension. Numerical examples will be presented in the paper to demonstrate efficiency and accuracy improvement using the new algorithm

A review of neural network based techniques for nonlinear microwave device modeling

Nonlinear microwave device modeling is an important part of computer-aided design (CAD) and many papers have been published in the literature. This paper presents a review of neural network based techniques for nonlinear microwave device modeling including recurrent neural network (RNN), neuro-space mapping (Neuro-SM) and dynamic Neuro-SM techniques. Large-signal waveforms or DC, small-signal and large-signal harmonic data are used as training data. Compared with conventional equivalent circuit models, the models generated by these neural network based methods are more accurate and more efficient to represent the behavior of the device

A novel context-aware recommendation algorithm with two-level SVD in social networks

With the rapid development of Internet applications and social networks, we have entered an era of big data, and people are hard to effectively find the information they want. Therefore, lots of recommendation algorithms have been proposed to help users select useful and beneficial information, and save their time. Moreover, context-aware recommendation methods are becoming more and more popular since they could provide more accurate or personalized recommendation information, compared with traditional recommendation methods. Singular value decomposition (SVD) has been successfully integrated with some traditional recommendation algorithms. However, the basic SVD can only extra