Controlled spermatozoa–oocyte interaction improves embryo quality in sheep

The current protocols of in vitro fertilization and culture in sheep rely on paradigms established more than 25 years ago, where Metaphase II oocytes are co-incubated with capacitated spermatozoa overnight. While this approach maximizes the number of fertilized oocytes, on the other side it exposes them to high concentration of reactive oxygen species (ROS) generated by active and degenerating spermatozoa, and positively correlates with polyspermy. Here we set up to precisely define the time frame during which spermatozoa effectively penetrates and fertilizes the oocyte, in order to drastically reduce spermatozoa-oocyte interaction. To do that, in vitro matured sheep oocytes co-incubated with spermatozoa in IVF medium were sampled every 30 min (start of incubation time 0) to verify the presence of a fertilizing spermatozoon. Having defined the fertilization time frame (4 h, data from 105 oocytes), we next compared the standard IVF procedures overnight (about 16 h spermatozoa/oocyte exposure, group o/nIVF) with a short one (4 h, group shIVF). A lower polyspermic fertilization (> 2PN) was detected in shIVF (6.5%) compared to o/nIVF (17.8%), P < 0.05. The o/nIVF group resulted in a significantly lower 2-cell stage embryos, than shIVF [34.6% (81/234) vs 50.6% (122/241) respectively, P < 0.001]. Likewise, the development to blastocyst stage confirmed a better quality [29% (70/241) vs 23.5% (55/234), shIVF vs o/nIVF respectively] and an increased Total Cell Number (TCN) in shIVF embryos, compared with o/n ones. The data on ROS have confirmed that its generation is IVF time-dependent, with high levels in the o/nIVF group. Overall, the data suggest that a shorter oocyte-spermatozoa incubation results in an improved embryo production and a better embryo quality, very likely as a consequence of a shorter exposure to the free oxygen radicals and the ensuing oxidative stress imposed by overnight culture

Regulation of oxytocin receptor gene expression in obsessive–compulsive disorder: a possible role for the microbiota-host epigenetic axis

Background: Obsessive–compulsive disorder (OCD) is a prevalent and severe clinical condition. Robust evidence suggests a gene-environment interplay in its etiopathogenesis, yet the underlying molecular clues remain only partially understood. In order to further deepen our understanding of OCD, it is essential to ascertain how genes interact with environmental risk factors, a cross-talk that is thought to be mediated by epigenetic mechanisms. The human microbiota may be a key player, because bacterial metabolites can act as epigenetic modulators. We analyzed, in the blood and saliva of OCD subjects and healthy controls, the transcriptional regulation of the oxytocin receptor gene and, in saliva, also the different levels of major phyla. We also investigated the same molecular mechanisms in specific brain regions of socially isolated rats showing stereotyped behaviors reminiscent of OCD as well as short chain fatty acid levels in the feces of rats. Results: Higher levels of oxytocin receptor gene DNA methylation, inversely correlated with gene expression, were observed in the blood as well as saliva of OCD subjects when compared to controls. Moreover, Actinobacteria also resulted higher in OCD and directly correlated with oxytocin receptor gene epigenetic alterations. The same pattern of changes was present in the prefrontal cortex of socially-isolated rats, where also altered levels of fecal butyrate were observed at the beginning of the isolation procedure. Conclusions: This is the first demonstration of an interplay between microbiota modulation and epigenetic regulation of gene expression in OCD, opening new avenues for the understanding of disease trajectories and for the development of new therapeutic strategies

Multi Agent System for Machine Learning Under Uncertainty in Cyber Physical Manufacturing System

Recent advancement in predictive machine learning has led to its application in various use cases in manufacturing. Most research focused on maximising predictive accuracy without addressing the uncertainty associated with it. While accuracy is important, focusing primarily on it poses an overfitting danger, exposing manufacturers to risk, ultimately hindering the adoption of these techniques. In this paper, we determine the sources of uncertainty in machine learning and establish the success criteria of a machine learning system to function well under uncertainty in a cyber-physical manufacturing system (CPMS) scenario. Then, we propose a multi-agent system architecture which leverages probabilistic machine learning as a means of achieving such criteria. We propose possible scenarios for which our architecture is useful and discuss future work. Experimentally, we implement Bayesian Neural Networks for multi-tasks classification on a public dataset for the real-time condition monitoring of a hydraulic system and demonstrate the usefulness of the system by evaluating the probability of a prediction being accurate given its uncertainty. We deploy these models using our proposed agent-based framework and integrate web visualisation to demonstrate its real-time feasibility

Tidal deformation of neutron stars from microscopic models of nuclear dynamics

The observation of the gravitational wave signal GW170817, consistent with emission from the inspiral of a binary neutron-star system, provided information on the tidal deformation of the participating stars. The available data may be exploited to constrain the equation of state of dense nuclear matter as well as to shed light on the underlying models describing nuclear dynamics at the microscopic level. In this paper, we compare the experimental results to the predictions of different theoretical models, based on nonrelativistic nuclear many-body theory, the relativistic field-theoretical formalism, and a more phenomenological approach constrained by observed nuclear properties. Although the precision of the available data does not allow to resolve the degeneracy of the models, our analysis shows a distinct sensitivity to the star compactness predicted by the different equations of state, which turns out to be significantly affected by relativistic boost corrections to the nucleon-nucleon potential

Impact of three-nucleon forces on gravitational wave emission from neutron stars

The detection of gravitational radiation, emitted in the aftermath of the excitation of neutron star quasinormal modes, has the potential to provide unprecedented access to the properties of matter in the star interior, and shed new light on the dynamics of nuclear interactions at microscopic level. Of great importance, in this context, will be the sensitivity to the modeling of three-nucleon interactions, which are known to play a critical role in the high-density regime. We report the results of a calculation of the frequencies and damping times of the fundamental mode, carried out using the equation of state of Akmal, Pandharipande and Ravenhall as a baseline, and varying the strength of the isoscalar repulsive term of the Urbana IX potential within a range consistent with multimessenger astrophysical observations. The results of our analysis indicate that repulsive three-nucleon interactions strongly affect the stiffness of the equation of state, which in turn determines the pattern of the gravitational radiation frequencies, largely independent of the mass of the source. The observational implications are also discussed