Regulation of α-Transducin and α-Gustducin Expression by a High Protein Diet in the Pig Gastrointestinal Tract

BackgroundThe expression of taste receptors (TASRs) and their signalling molecules in the gastrointestinal (GI) epithelial cells, including enteroendocrine cells (EECs), suggests they participate in chemosensing mechanisms influencing GI physiology via the release of endocrine messengers. TASRs mediate gustatory signalling by interacting with different transducers, including α-gustducin (G_αgust) and α-transducin (G_αtran) G protein subunits. This study tested whether G_αtran and G_αgust immunoreactive (-IR) cells are affected by a short-term (3 days) and long-term (30 days) high protein (Hp) diet in the pig GI tract.ResultIn the stomach, G_αgust and G_αtran-IR cells contained serotonin (5-HT) and ghrelin (GHR), while in the small and large intestine, G_αgust and G_αtran-IR colocalized with 5-HT-, cholecystokinin (CCK)- and peptide YY (PYY)-IR. There was a significant increase in the density of G_αtran-IR cells in the pyloric mucosa in both short- and long-term Hp diet groups (Hp3 and Hp30) vs. the control group (Ctr) (P<0.05), while the increase of G_αgust-IR cells in the pyloric mucosa was significant in Hp30 group vs. Ctr and vs. Hp3 (P<0.05); these cells included G_αtran / 5HT-IR and G_αtran / GHR-IR cells (P<0.05 and P<0.001 vs. Ctr, respectively) as well as G_αgust /5-HT-IR or G_αgust / GHR-IR cells (P<0.05 and P<0.01 vs. Ctr, respectively). In the small intestine, we recorded a significant increase in G_αtran-IR cells in the duodenal crypts and a significant increase of G_αgust-IR cells in the jejunal crypts in Hp3 group compared to HP30 (P<0.05). With regard to the number of G_αtran-G_αgust IR cells colocalized with CCK or 5-HT, there was only a significant increase of G_αtran / CCK-IR cells in Hp3 group compared to Ctr (P = 0.01).ConclusionThis study showed an upregulation of selected subpopulations of G_αgust / G_αtran-IR cells in distinct regions of the pig GI tract by short- and long-term Hp diet lending support to TASR-mediated effects in metabolic homeostasis and satiety mechanisms.     

Distinctive Effects of Cytochalasin B in Chick Primary Myoblasts and Fibroblasts

Actin-based structures play fundamental roles in cellular functions. However it remains controversial how cells cope with the absence of F-actin structures. This report focuses on short- and long-term effects of cytochalasin B (CB) on actin-complexes in fibroblasts and myoblasts. Thirty min of CB treatment dispersed subplasma actin cortices, lamellipodia, ruffled membranes, stress fibers and adhesion plaques into actin patches in fibroblasts and muscle cells. In contrast, 72 hrs CB treatment showed distinct morphological effects. Fibroblasts became giant multinucleated-finger shaped with 5 to 10 protrusions, 3–8 μm in width, and >200 μm in length. They lacked cortical actin, stress fibers, adhesion plaques and ruffled membranes but contained immense lamelliopodia with abnormal adhesion plaque protein complexes. Muscle cells transformed into multinucleated globular-shaped but contained normal I-Z-I and A-bands, indicating that CB did not interfere with the assembly of myofibrils. Within 30 min after CB removal, finger-shaped fibroblasts returned to their original shape and actin-containing structures rapidly reappeared, whereas muscle cells respond slowly to form elongated myotubes following CB washout. The capacity to grow, complete several nuclear cycles, assemble intermediate filaments and microtubules without a morphologically recognizable actin cytoskeleton raises interesting issues related to the role of the actin compartments in eukaryotic cells.     

No Evidence of the Ego-Depletion Effect across Task Characteristics and Individual Differences: A Pre-Registered Study

Ego-depletion, a psychological phenomenon in which participants are less able to engage in self-control after prior exertion of self-control, has become widely popular in the scientific community as well as in the media. However, considerable debate exists among researchers as to the nature of the ego-depletion effect, and growing evidence suggests the effect may not be as strong or robust as the extant literature suggests. We examined the robustness of the ego-depletion effect and aimed to maximize the likelihood of detecting the effect by using one of the most widely used depletion tasks (video-viewing attention control task) and by considering task characteristics and individual differences that potentially moderate the effect. We also sought to make our research plan transparent by pre-registering our hypotheses, procedure, and planned analyses prior to data collection. Contrary to the ego-depletion hypothesis, participants in the depletion condition did not perform worse than control participants on the subsequent self-control task, even after considering moderator variables. These findings add to a growing body of evidence suggesting ego-depletion is not a reliable phenomenon, though more research is needed that uses large sample sizes, considers moderator variables, and pre-registers prior to data collection.     

Distribution and Diversity of Pathogenic Leptospira Species in Peri-domestic Surface Waters from South Central Chile

BackgroundLeptospirosis is a neglected zoonosis affecting animals and humans caused by infection with Leptospira. The bacteria can survive outside of hosts for long periods of time in soil and water. While identification of Leptospira species from human cases and animal reservoirs are increasingly reported, little is known about the diversity of pathogenic Leptospira species in the environment and how surveillance of the environment might be used for monitoring and controlling disease.ConclusionsThis study reports the presence of pathogenic Leptospira in the peri-domestic environment of households in three community types and the differences in Leptospira diversity at the community level. Systematic environmental surveillance of Leptospira can be used for detecting changes in pathogen diversity and to identify and monitor contaminated areas where an increased risk of human infection exists.     

Inertia weight control strategies for particle swarm optimization

Particle swarm optimization (PSO) is a population-based, stochastic optimization technique inspired by the social dynamics of birds. The PSO algorithm is rather sensitive to the control parameters, and thus, there has been a significant amount of research effort devoted to the dynamic adaptation of these parameters. The focus of the adaptive approaches has largely revolved around adapting the inertia weight as it exhibits the clearest relationship with the exploration/exploitation balance of the PSO algorithm. However, despite the significant amount of research efforts, many inertia weight control strategies have not been thoroughly examined analytically nor empirically. Thus, there are a plethora of choices when selecting an inertia weight control strategy, but no study has been comprehensive enough to definitively guide the selection. This paper addresses these issues by first providing an overview of 18 inertia weight control strategies. Secondly, conditions required for the strategies to exhibit convergent behaviour are derived. Finally, the inertia weight control strategies are empirically examined on a suite of 60 benchmark problems. Results of the empirical investigation show that none of the examined strategies, with the exception of a randomly selected inertia weight, even perform on par with a constant inertia weight.     

Turing learning: a metric-free approach to inferring behavior and its application to swarms

We propose Turing Learning, a novel system identification method for inferring the behavior of natural or artificial systems. Turing Learning simultaneously optimizes two populations of computer programs, one representing models of the behavior of the system under investigation, and the other representing classifiers. By observing the behavior of the system as well as the behaviors produced by the models, two sets of data samples are obtained. The classifiers are rewarded for discriminating between these two sets, that is, for correctly categorizing data samples as either genuine or counterfeit. Conversely, the models are rewarded for ‘tricking’ the classifiers into categorizing their data samples as genuine. Unlike other methods for system identification, Turing Learning does not require predefined metrics to quantify the difference between the system and its models. We present two case studies with swarms of simulated robots and prove that the underlying behaviors cannot be inferred by a metric-based system identification method. By contrast, Turing Learning infers the behaviors with high accuracy. It also produces a useful by-product—the classifiers—that can be used to detect abnormal behavior in the swarm. Moreover, we show that Turing Learning also successfully infers the behavior of physical robot swarms. The results show that collective behaviors can be directly inferred from motion trajectories of individuals in the swarm, which may have significant implications for the study of animal collectives. Furthermore, Turing Learning could prove useful whenever a behavior is not easily characterizable using metrics, making it suitable for a wide range of applications.