Emotions are evolved systems of intra- and interpersonal processes that are regulatory in nature, dealing mostly with issues of personal or social concern. They regulate social interaction and in extension, the social sphere. In turn, processes in the social sphere regulate emotions of individuals and groups. In other words, intrapersonal processes project in the interpersonal space, and inversely, interpersonal experiences deeply influence intrapersonal processes. Thus, I argue that the concepts of emotion generation and regulation should not be artificially separated. Similarly, interpersonal emotions should not be reduced to interacting systems of intraindividual processes. Instead, we can consider emotions at different social levels, ranging from dyads to large scale e-communities. The interaction between these levels is complex and does not only involve influences from one level to the next. In this sense the levels of emotion/regulation are messy and a challenge for empirical study. In this article, I discuss the concepts of emotions and regulation at different intra- and interpersonal levels. I extend the concept of auto-regulation of emotions (Kappas, 2008, 2011a,b) to social processes. Furthermore, I argue for the necessity of including mediated communication, particularly in cyberspace in contemporary models of emotion/regulation. Lastly, I suggest the use of concepts from systems dynamics and complex systems to tackle the challenge of the “messy layers.”
An important problem in systems biology is to reconstruct gene regulatory networks (GRNs) from experimental data and other a priori information. The DREAM project offers some types of experimental data, such as knockout data, knockdown data, time series data, etc. Among them, multifactorial perturbation data are easier and less expensive to obtain than other types of experimental data and are thus more common in practice. In this article, a new algorithm is presented for the inference of GRNs using the DREAM4 multifactorial perturbation data. The GRN inference problem among [Formula: see text] genes is decomposed into [Formula: see text] different regression problems. In each of the regression problems, the expression level of a target gene is predicted solely from the expression level of a potential regulation gene. For different potential regulation genes, different weights for a specific target gene are constructed by using the sum of squared residuals and the Pearson correlation coefficient. Then these weights are normalized to reflect effort differences of regulating distinct genes. By appropriately choosing the parameters of the power law, we constructe a 0-1 integer programming problem. By solving this problem, direct regulation genes for an arbitrary gene can be estimated. And, the normalized weight of a gene is modified, on the basis of the estimation results about the existence of direct regulations to it. These normalized and modified weights are used in queuing the possibility of the existence of a corresponding direct regulation. Computation results with the DREAM4 In Silico Size 100 Multifactorial subchallenge show that estimation performances of the suggested algorithm can even outperform the best team. Using the real data provided by the DREAM5 Network Inference Challenge, estimation performances can be ranked third. Furthermore, the high precision of the obtained most reliable predictions shows the suggested algorithm may be helpful in guiding biological experiment designs.
Regulator of G protein Signaling 14 (RGS14) is a multifunctional scaffolding protein that integrates heterotrimeric G protein and H-Ras signaling pathways. RGS14 possesses an RGS domain that binds active Gαi/o-GTP subunits to promote GTP hydrolysis, and a G protein regulatory (GPR) motif that selectively binds inactive Gαi1/3-GDP subunits to form a stable heterodimer at cellular membranes. RGS14 also contains two tandem Ras/Rap-binding domains (RBDs) that bind H-Ras. Here we show that RGS14 preferentially binds activated H-Ras-GTP in live cells to enhance H-Ras cellular actions, and that this interaction is regulated by inactive Gαi1-GDP and GPCRs. Using bioluminescence resonance energy transfer (BRET) in live cells, we show that RGS14-Luciferase and active H-Ras(G/V)-Venus exhibit a robust BRET signal at the plasma membrane that is markedly enhanced in the presence of inactive Gαi1-GDP, but not active Gαi1-GTP. Active H-Ras(G/V) interacts with a native RGS14:Gαi1 complex in brain lysates, and co-expression of RGS14 and Gαi1 in PC12 cells greatly enhances H-Ras(G/V) stimulatory effects on neurite outgrowth. Stimulation of the Gαi-linked α2A-adrenergic receptor induces a conformational change in the Gαi1:RGS14:H-Ras(G/V) complex, which may allow subsequent regulation of the complex by other binding partners. Together, these findings indicate that inactive Gαi1-GDP enhances theaffinity of RGS14 for H-Ras-GTP in live cells, resulting in a ternary signaling complex that is further regulated by GPCRs.
MicroRNAs (miRNAs) are important post-transcriptional regulators. Altered expression of miRNAs has recently demonstrated association with human ulcerative colitis (UC). In this study, we attempted to elucidate the roles of miR-126 in the pathogenesis of UC.
Sleep loss can severely impair the ability to perform, yet the ability to recover from sleep loss is not well understood. Sleep regulatory processes are assumed to lie exclusively within the brain mainly due to the strong behavioral manifestations of sleep. Whole-body knockout of the circadian clock gene Bmal1 in mice affects several aspects of sleep, however, the cells/tissues responsible are unknown. We found that restoring Bmal1 expression in the brains of Bmal1-knockout mice did not rescue Bmal1-dependent sleep phenotypes. Surprisingly, most sleep-amount, but not sleep-timing, phenotypes could be reproduced or rescued by knocking out or restoring BMAL1 exclusively in skeletal muscle, respectively. We also found that overexpression of skeletal-muscle Bmal1 reduced the recovery response to sleep loss. Together, these findings demonstrate that Bmal1 expression in skeletal muscle is both necessary and sufficient to regulate total sleep amount and reveal that critical components of normal sleep regulation occur in muscle.
Social relationships are tightly linked to health and well-being. Recent work suggests that social relationships can even serve vital emotion regulation functions by minimizing threat-related neural activity. But relationship distress remains a significant public health problem in North America and elsewhere. A promising approach to helping couples both resolve relationship distress and nurture effective interpersonal functioning is Emotionally Focused Therapy for couples (EFT), a manualized, empirically supported therapy that is strongly focused on repairing adult attachment bonds. We sought to examine a neural index of social emotion regulation as a potential mediator of the effects of EFT. Specifically, we examined the effectiveness of EFT for modifying the social regulation of neural threat responding using an fMRI-based handholding procedure. Results suggest that EFT altered the brain’s representation of threat cues in the presence of a romantic partner. EFT-related changes during stranger handholding were also observed, but stranger effects were dependent upon self-reported relationship quality. EFT also appeared to increase threat-related brain activity in regions associated with self-regulation during the no-handholding condition. These findings provide a critical window into the regulatory mechanisms of close relationships in general and EFT in particular.
Epigenome-wide association studies represent one means of applying genome-wide assays to identify molecular events that could be associated with human phenotypes. The epigenome is especially intriguing as a target for study, as epigenetic regulatory processes are, by definition, heritable from parent to daughter cells and are found to have transcriptional regulatory properties. As such, the epigenome is an attractive candidate for mediating long-term responses to cellular stimuli, such as environmental effects modifying disease risk. Such epigenomic studies represent a broader category of disease -omics, which suffer from multiple problems in design and execution that severely limit their interpretability. Here we define many of the problems with current epigenomic studies and propose solutions that can be applied to allow this and other disease -omics studies to achieve their potential for generating valuable insights.
Humans are tremendously sensitive to unfairness. Unfairness provokes strong negative emotional reactions and influences our subsequent decision making. These decisions might not only have consequences for ourselves and the person who treated us unfairly but can even transmit to innocent third persons - a phenomenon that has been referred to as generalized negative reciprocity. In this study we aimed to investigate whether regulation of emotions can interrupt this chain of unfairness. Real allocations in a dictator game were used to create unfair situations. Three different regulation strategies, namely writing a message to the dictator who made an unfair offer, either forwarded or not forwarded, describing a neutral picture and a control condition in which subjects just had to wait for three minutes, were then tested on their ability to influence the elicited emotions. Subsequently participants were asked to allocate money between themselves and a third person. We show that writing a message which is forwarded to the unfair actor is an effective emotion regulation strategy and that those participants who regulated their emotions successfully by writing a message made higher allocations to a third person. Thus, using message writing as an emotion regulation strategy can interrupt the chain of unfairness.
It has long been known that the resting potential of tumor cells is depolarized relative to their normal counterparts. More recent work has provided evidence that resting potential is not just a readout of cell state: it regulates cell behavior as well. Thus, the ability to control resting potential in vivo would provide a powerful new tool for the study and treatment of tumors, a tool capable of revealing living-state physiological information impossible to obtain using molecular tools applied to isolated cell components. Here we describe the first use of optogenetics to manipulate ion-flux mediated regulation of membrane potential specifically to prevent and cause regression of oncogene-induced tumors. Injection of mutant-KRAS mRNA induces tumor-like structures with many documented similarities to tumors, in Xenopus tadpoles. We show that expression and activation of either ChR2D156A, a blue-light activated cation channel, or Arch, a green-light activated proton pump, both of which hyperpolarize cells, significantly lowers the incidence of KRAS tumor formation. Excitingly, we also demonstrate that activation of co-expressed light-activated ion translocators after tumor formation significantly increases the frequency with which the tumors regress in a process called normalization. These data demonstrate an optogenetic approach to dissect the biophysics of cancer. Moreover, they provide proof-of-principle for a novel class of interventions, directed at regulating cell state by targeting physiological regulators that can over-ride the presence of mutations.
The tooth is an ectodermal organ that arises from a tooth germ under the regulation of reciprocal epithelial-mesenchymal interactions. Tooth morphogenesis occurs in the tooth-forming field as a result of reaction-diffusion waves of specific gene expression patterns. Here, we developed a novel mechanical ligation method for splitting tooth germs to artificially regulate the molecules that control tooth morphology. The split tooth germs successfully developed into multiple correct teeth through the re-regionalisation of the tooth-forming field, which is regulated by reaction-diffusion waves in response to mechanical force. Furthermore, split teeth erupted into the oral cavity and restored physiological tooth function, including mastication, periodontal ligament function and responsiveness to noxious stimuli. Thus, this study presents a novel tooth regenerative technology based on split tooth germs and the re-regionalisation of the tooth-forming field by artificial mechanical force.