The Role of Task-Related Learned Representations in Explaining Asymmetries in Task Switching

Task switch costs often show an asymmetry, with switch costs being larger when switching from a difficult task to an easier task. This asymmetry has been explained by difficult tasks being represented more strongly and consequently requiring more inhibition prior to switching to the easier task. The present study shows that switch cost asymmetries observed in arithmetic tasks (addition vs. subtraction) do not depend on task difficulty: Switch costs of similar magnitudes were obtained when participants were presented with unsolvable pseudo-equations that did not differ in task difficulty. Further experiments showed that neither task switch costs nor switch cost asymmetries were due to perceptual factors (e.g., perceptual priming effects). These findings suggest that asymmetrical switch costs can be brought about by the association of some tasks with greater difficulty than others. Moreover, the finding that asymmetrical switch costs were observed (1) in the absence of a task switch proper and (2) without differences in task difficulty, suggests that present theories of task switch costs and switch cost asymmetries are in important ways incomplete and need to be modified.     

Nuclear Localization of the Mitochondrial Factor HIGD1A during Metabolic Stress

Cellular stress responses are frequently governed by the subcellular localization of critical effector proteins. Apoptosis-inducing Factor (AIF) or Glyceraldehyde 3-Phosphate Dehydrogenase (GAPDH), for example, can translocate from mitochondria to the nucleus, where they modulate apoptotic death pathways. Hypoxia-inducible gene domain 1A (HIGD1A) is a mitochondrial protein regulated by Hypoxia-inducible Factor-1α (HIF1α). Here we show that while HIGD1A resides in mitochondria during physiological hypoxia, severe metabolic stress, such as glucose starvation coupled with hypoxia, in addition to DNA damage induced by etoposide, triggers its nuclear accumulation. We show that nuclear localization of HIGD1A overlaps with that of AIF, and is dependent on the presence of BAX and BAK. Furthermore, we show that AIF and HIGD1A physically interact. Additionally, we demonstrate that nuclear HIGD1A is a potential marker of metabolic stress in vivo, frequently observed in diverse pathological states such as myocardial infarction, hypoxic-ischemic encephalopathy (HIE), and different types of cancer. In summary, we demonstrate a novel nuclear localization of HIGD1A that is commonly observed in human disease processes in vivo.     

Affective Computing and the Impact of Gender and Age

Affective computing aims at the detection of users’ mental states, in particular, emotions and dispositions during human-computer interactions. Detection can be achieved by measuring multimodal signals, namely, speech, facial expressions and/or psychobiology. Over the past years, one major approach was to identify the best features for each signal using different classification methods. Although this is of high priority, other subject-specific variables should not be neglected. In our study, we analyzed the effect of gender, age, personality and gender roles on the extracted psychobiological features (derived from skin conductance level, facial electromyography and heart rate variability) as well as the influence on the classification results. In an experimental human-computer interaction, five different affective states with picture material from the International Affective Picture System and ULM pictures were induced. A total of 127 subjects participated in the study. Among all potentially influencing variables (gender has been reported to be influential), age was the only variable that correlated significantly with psychobiological responses. In summary, the conducted classification processes resulted in 20% classification accuracy differences according to age and gender, especially when comparing the neutral condition with four other affective states. We suggest taking age and gender specifically into account for future studies in affective computing, as these may lead to an improvement of emotion recognition accuracy.     

Updating the proteome of the uncultivable hemotrophic Mycoplasma suis in experimentally infected pigs

Mycoplasma suis belongs to the hemotrophic mycoplasmas that are associated with acute and chronic anemia in a wide range of livestock and wild animals. The inability to culture M. suis in vitro has hindered its characterization at the molecular level. Since the publication of M. suis genome sequences in 2011 only one proteome study has been published. Aim of the presented study was to significantly extend the proteome coverage of M. suis strain KI_3806 during acute infection by applying three different protein extraction methods followed by 1D SDS‐PAGE and LC‐MS/MS. A total of 404 of 795 M. suis KI_3806 proteins (50.8%) were identified. Data analysis revealed the expression of 83.7% of the predicted ORFs with assigned functions but also highlights the expression of 179 of 523 (34.2%) hypothetical proteins with unknown functions. Computational analyses identified expressed membrane‐associated hypothetical proteins that might be involved in adhesion or host–pathogen interaction. Furthermore, analyses of the expressed proteins indicated the existence of a hexose‐6‐phosphate‐transporter and an ECF transporter. In conclusion, our proteome study provides a further step toward the elucidation of the unique life cycle of M. suis and the establishment of an in vitro culture. All MS data have been deposited in the ProteomeXchange with identifier PXD002294 ( http://proteomecentral.proteomexchange.org/dataset/PXD002294 ).     

Immunotherapeutic targeting of LIGHT/LTβR/HVEM pathway fully recapitulates the reduced cytotoxic phenotype of LIGHT-deficient T cells

Tumor necrosis factor (TNF)/TNF receptor (TNFR) superfamily members play essential roles in the development of the different phases of the immune response. Mouse LIGHT (TNFSF14) is a type II transmembrane protein with a C-terminus extracellular TNF homology domain (THD) that assembles in homotrimers and regulates the course of the immune responses by signaling through 2 receptors, the herpes virus entry mediator (HVEM, TNFSFR14) and the lymphotoxin β receptor (LTβR, TNFSFR3). LIGHT is a membrane-bound protein transiently expressed on activated T cells, natural killer (NK) cells and immature dendritic cells that can be proteolytically cleaved by a metalloprotease and released to the extracellular milieu. The immunotherapeutic potential of LIGHT blockade was evaluated in vivo. Administration of an antagonist of LIGHT interaction with its receptors attenuated the course of graft-versus-host reaction and recapitulated the reduced cytotoxic activity of LIGHT-deficient T cells adoptively transferred into non-irradiated semiallogeneic recipients. The lack of LIGHT expression on donor T cells or blockade of LIGHT interaction with its receptors slowed down the rate of T cell proliferation and decreased the frequency of precursor alloreactive T cells, retarding T cell differentiation toward effector T cells. The blockade of LIGHT/LTβR/HVEM pathway was associated with delayed downregulation of interleukin-7Rα and delayed upregulation of inducible costimulatory molecule expression on donor alloreactive CD8 T cells that are typical features of impaired T cell differentiation. These results expose the relevance of LIGHT/LTβR/HVEM interaction for the potential therapeutic control of the allogeneic immune responses mediated by alloreactive CD8 T cells that can contribute to prolong allograft survival.     

A Bayesian Modelling Approach with Balancing Informative Prior for Analysing Imbalanced Data

When a dataset is imbalanced, the prediction of the scarcely-sampled subpopulation can be over-influenced by the population contributing to the majority of the data. The aim of this study was to develop a Bayesian modelling approach with balancing informative prior so that the influence of imbalance to the overall prediction could be minimised. The new approach was developed in order to weigh the data in favour of the smaller subset(s). The method was assessed in terms of bias and precision in predicting model parameter estimates of simulated datasets. Moreover, the method was evaluated in predicting optimal dose levels of tobramycin for various age groups in a motivating example. The bias estimates using the balancing informative prior approach were smaller than those generated using the conventional approach which was without the consideration for the imbalance in the datasets. The precision estimates were also superior. The method was further evaluated in a motivating example of optimal dosage prediction of tobramycin. The resulting predictions also agreed well with what had been reported in the literature. The proposed Bayesian balancing informative prior approach has shown a real potential to adequately weigh the data in favour of smaller subset(s) of data to generate robust prediction models.     

The BCL2 -938C>A Promoter Polymorphism Is Associated with Risk for and Time to Aseptic Loosening of Total Hip Arthroplasty

Aseptic loosening is a major cause of revision surgery of total hip arthroplasty (THA). Only few host factors affecting aseptic loosening have been identified until now, although they are urgently needed to identify and possibly treat those patients at higher risk for aseptic loosening. To determine whether the functional single nucleotide polymorphism (SNP) c.-938C>A (rs2279115), located in the promoter region of the BCL2 gene has an impact on aseptic loosening of THA we genotyped and analyzed 234 patients suffering from aseptic loosening and 231 patients after primary THA. The polymorphism is associated with risk for aseptic loosening with the CC genotype at highest risk for aseptic loosening, Odds Ratio CC vs. AA 1.93, 95%CI 1.15–3.25, p = 0.013. In contrast, low risk AA genotype carriers that still developed aseptic loosening showed a significantly shorter time to aseptic loosening than patients carrying the C allele (p = 0.004). These results indicate that the BCL2 -938C>A polymorphism influences the occurrence and course of aseptic loosening and suggests this polymorphism as an interesting candidate for prospective studies and analyses in THA registers.     

Long-Chain Omega-3 Polyunsaturated Fatty Acids Have Developmental Effects on the Crop Pest,the Cabbage White Butterfly Pieris rapae

Nutritional enhancement of crops using genetic engineering can potentially affect herbivorous pests. Recently, oilseed crops have been genetically engineered to produce the long-chain omega-3 polyunsaturated fatty acids, eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) at levels similar to that found in fish oil; to provide a more sustainable source of these compounds than is currently available from wild fish capture. We examined some of the growth and development impacts of adding EPA and DHA to an artificial diet of Pieris rapae, a common pest of Brassicaceae plants. We replaced 1% canola oil with EPA: DHA (11:7 ratio) in larval diets, and examined morphological traits and growth of larvae and ensuing adults across 5 dietary treatments. Diets containing increasing amounts of EPA and DHA did not affect developmental phenology, larval or pupal weight, food consumption, nor larval mortality. However, the addition of EPA and DHA in larval diets resulted in progressively heavier adults (F _{4, 108} = 6.78; p = 0.011), with smaller wings (p < 0.05) and a higher frequency of wing deformities (R = 0.988; p = 0.001). We conclude that the presence of EPA and DHA in diets of larval P. rapae may alter adult mass and wing morphology; therefore, further research on the environmental impacts of EPA and DHA production on terrestrial biota is advisable.     

Incipient Social Groups: An Analysis via In-Vivo Behavioral Tracking

Social psychology is fundamentally the study of individuals in groups, yet there remain basic unanswered questions about group formation, structure, and change. We argue that the problem is methodological. Until recently, there was no way to track who was interacting with whom with anything approximating valid resolution and scale. In the current study we describe a new method that applies recent advances in image-based tracking to study incipient group formation and evolution with experimental precision and control. In this method, which we term “in vivo behavioral tracking,” we track individuals’ movements with a high definition video camera mounted atop a large field laboratory. We report results of an initial study that quantifies the composition, structure, and size of the incipient groups. We also apply in-vivo spatial tracking to study participants’ tendency to cooperate as a function of their embeddedness in those crowds. We find that participants form groups of seven on average, are more likely to approach others of similar attractiveness and (to a lesser extent) gender, and that participants’ gender and attractiveness are both associated with their proximity to the spatial center of groups (such that women and attractive individuals are more likely than men and unattractive individuals to end up in the center of their groups). Furthermore, participants’ proximity to others early in the study predicted the effort they exerted in a subsequent cooperative task, suggesting that submergence in a crowd may predict social loafing. We conclude that in vivo behavioral tracking is a uniquely powerful new tool for answering longstanding, fundamental questions about group dynamics.