Sexually dimorphic gene expression emerges with embryonic genome activation and is dynamic throughout development

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public DomainVKR is supported by grants from the Biotechnology and Biological Sciences Research Council, UK (BB/M012494/1), VKR and CG by (BB/G00711/X/1). MLH is supported by a Research Council UK Academic Fellowship. RL is supported by EU-FP7 BLUEPRINT

Mapping the multicausality of Alzheimer's disease through group model building.

Alzheimer's disease (AD) is a complex, multicausal disorder involving several spatiotemporal scales and scientific domains. While many studies focus on specific parts of this system, the complexity of AD is rarely studied as a whole. In this work, we apply systems thinking to map out known causal mechanisms and risk factors ranging from intracellular to psychosocial scales in sporadic AD. We report on the first systemic causal loop diagram (CLD) for AD, which is the result of an interdisciplinary group model building (GMB) process. The GMB was based on the input of experts from multiple domains and all proposed mechanisms were supported by scientific literature. The CLD elucidates interaction and feedback mechanisms that contribute to cognitive decline from midlife onward as described by the experts. As an immediate outcome, we observed several non-trivial reinforcing feedback loops involving factors at multiple spatial scales, which are rarely considered within the same theoretical framework. We also observed high centrality for modifiable risk factors such as social relationships and physical activity, which suggests they may be promising leverage points for interventions. This illustrates how a CLD from an interdisciplinary GMB process may lead to novel insights into complex disorders. Furthermore, the CLD is the first step in the development of a computational model for simulating the effects of risk factors on AD

Disrupted Reproduction, Estrous Cycle, and Circadian Rhythms in Female Mice Deficient in Vasoactive Intestinal Peptide

The female reproductive cycle is gated by the circadian timing system and may be vulnerable to disruptions in the circadian system. Prior work suggests that vasoactive intestinal peptide (VIP)-expressing neurons in the suprachiasmatic nucleus (SCN) are one pathway by which the circadian clock can influence the estrous cycle, but the impact of the loss of this peptide on reproduction has not been assessed. In the present study, we first examine the impact of the genetic loss of the neuropeptide VIP on the reproductive success of female mice. Significantly, mutant females produce about half the offspring of their wild-type sisters even when mated to the same males. We also find that VIP-deficient females exhibit a disrupted estrous cycle; that is, ovulation occurs less frequently and results in the release of fewer oocytes compared with controls. Circadian rhythms of wheel-running activity are disrupted in the female mutant mice, as is the spontaneous electrical activity of dorsal SCN neurons. On a molecular level, the VIP-deficient SCN tissue exhibits lower amplitude oscillations with altered phase relationships between the SCN and peripheral oscillators as measured by PER2-driven bioluminescence. The simplest explanation of our data is that the loss of VIP results in a weakened SCN oscillator, which reduces the synchronization of the female circadian system. These results clarify one of the mechanisms by which disruption of the circadian system reduces female reproductive success

Disrupted Reproduction, Estrous Cycle, and Circadian Rhythms in Female Mice Deficient in Vasoactive Intestinal Peptide

The female reproductive cycle is gated by the circadian timing system and may be vulnerable to disruptions in the circadian system. Prior work suggests that vasoactive intestinal peptide (VIP)-expressing neurons in the suprachiasmatic nucleus (SCN) are one pathway by which the circadian clock can influence the estrous cycle, but the impact of the loss of this peptide on reproduction has not been assessed. In the present study, we first examine the impact of the genetic loss of the neuropeptide VIP on the reproductive success of female mice. Significantly, mutant females produce about half the offspring of their wild-type sisters even when mated to the same males. We also find that VIP-deficient females exhibit a disrupted estrous cycle; that is, ovulation occurs less frequently and results in the release of fewer oocytes compared with controls. Circadian rhythms of wheel-running activity are disrupted in the female mutant mice, as is the spontaneous electrical activity of dorsal SCN neurons. On a molecular level, the VIP-deficient SCN tissue exhibits lower amplitude oscillations with altered phase relationships between the SCN and peripheral oscillators as measured by PER2-driven bioluminescence. The simplest explanation of our data is that the loss of VIP results in a weakened SCN oscillator, which reduces the synchronization of the female circadian system. These results clarify one of the mechanisms by which disruption of the circadian system reduces female reproductive success

A Felder and Silverman Learning Styles Model Based Personalization Approach to Recommend Learning Objects

16th International Conference on Computational Science and Its Applications (ICCSA) -- JUL 04-07, 2016 -- Beijing, PEOPLES R CHINAWOS: 000381936000030In this paper, a new algorithmic personalization approach based on Felder and Silverman learning styles model is presented. The proposed approach uses learning objects modeled with the IEEE LOM metadata standard, which serves as the main standard for representation of learning objects' metadata. Personalization is provided with two steps in the proposed approach. At the first step, each learning object is evaluated by taking into account how values of IEEE LOM metadata elements match each dimension of Felder and Silverman learning styles model. The second step involves recommending appropriate learning objects to learners. Four weight values are calculated for each learning object, describing how related the learner and the learning object in question is at each dimension of Felder and Silverman learning styles model. Then, weight values for each dimension is combined by using Manhattan distance metric to provide a single weight value as a fitness function representing the general relatedness of the learner and the learning object. Results of the personalization approach can be used to recommend learning objects ordered according to their weight values to the learners. An example scenario illustrating the proposed approach is provided, as well as a discussion of current limitations and future work directions.Beijing Univ Post & Telecommunicat, Univ Perugia, Monash Univ, Kyushu Sangyo Univ, Univ Basilicata, Univ Minho, State Key Lab Networking & Switching Technol, Springer Int Publishing AG, NVidia C