Recon 2.2: from reconstruction to model of human metabolism.

IntroductionThe human genome-scale metabolic reconstruction details all known metabolic reactions occurring in humans, and thereby holds substantial promise for studying complex diseases and phenotypes. Capturing the whole human metabolic reconstruction is an on-going task and since the last community effort generated a consensus reconstruction, several updates have been developed.ObjectivesWe report a new consensus version, Recon 2.2, which integrates various alternative versions with significant additional updates. In addition to re-establishing a consensus reconstruction, further key objectives included providing more comprehensive annotation of metabolites and genes, ensuring full mass and charge balance in all reactions, and developing a model that correctly predicts ATP production on a range of carbon sources.MethodsRecon 2.2 has been developed through a combination of manual curation and automated error checking. Specific and significant manual updates include a respecification of fatty acid metabolism, oxidative phosphorylation and a coupling of the electron transport chain to ATP synthase activity. All metabolites have definitive chemical formulae and charges specified, and these are used to ensure full mass and charge reaction balancing through an automated linear programming approach. Additionally, improved integration with transcriptomics and proteomics data has been facilitated with the updated curation of relationships between genes, proteins and reactions.ResultsRecon 2.2 now represents the most predictive model of human metabolism to date as demonstrated here. Extensive manual curation has increased the reconstruction size to 5324 metabolites, 7785 reactions and 1675 associated genes, which now are mapped to a single standard. The focus upon mass and charge balancing of all reactions, along with better representation of energy generation, has produced a flux model that correctly predicts ATP yield on different carbon sources.ConclusionThrough these updates we have achieved the most complete and best annotated consensus human metabolic reconstruction available, thereby increasing the ability of this resource to provide novel insights into normal and disease states in human. The model is freely available from the Biomodels database (http://identifiers.org/biomodels.db/MODEL1603150001)

Complexity and Endogenous Instability

The global financial crisis proved the critical impact of the gap between individual rationality and group rationality. This gap is not supposed to arise in a Neoclassical world, but it frequently arises in a world as complex as ours. The paper explores how endogenous instability might arise due to such a gap, and what behavioral rules might help to mitigate its impact.fallacy of composition, empathy, n-person prisoner’s dilemma games, n-person zero-sum games, symmetry, the golden rule.

The Compassion Balance: Understanding the Interrelation of Self- and Other-Compassion for Optimal Well-being

Objectives: This study examined the role of self-other harmony in the relations between self-compassion, other-compassion, and well-being. Past research has shown self- and other-compassion to be positively related. But we hypothesised that self-compassion can be perceived as incompatible with other-compassion, and that self-compassion and other-compassion might be uncorrelated or negatively correlated in daily life for some individuals. We termed this pattern lack of self-other harmony in compassion and hypothesised that it would undermine the benefits of compassion. Method: Using an experience sampling method in patients (n=154) with a variety of diagnoses, we measured self-compassion, other-compassion, life-satisfaction, mood, and contextual variables six times per day for 42 time points. Results: For most participants, self-compassion was positively associated with other-compassion. However, there was substantial heterogeneity in this effect. The degree of self-other harmony moderated the link between compassion directed towards self or other and well-being. Higher levels of compassion were associated with higher levels of well-being, but only for those who experienced the harmony. When the two forms of compassion were not in harmony, levels of self/other-compassion were largely unrelated to well-being. Conclusions: The findings emphasise the importance of personalised compassion interventions rather than a one-size-fits-all approach. Increasing self-compassion or other-compassion is likely to improve well-being for most people. However, for a minority lacking the self-other harmony, it may be necessary to assess their interpretation of self- and other-compassion, then work with them to promote the compassion balance optimal for their well-being

The simulation of social exchange: developing a multidimensional model of exchange rules in human interaction.

Masters Degree. University of KwaZulu-Natal, Pietermaritzburg.Social exchange underpins social structure and as such, social exchange theory has taken a central role in the field of social psychology. The study of exchange rules and how they interact with each other is an area within this theory that has not received much attention up until now. This study has aimed to study the exchange rules of fairness, reciprocity, self-interest, vicinity and ingroup favouritism within an interacting exchange network. Agent based computational modelling with a comparison to empirical data has been proposed as a novel method to uncover the process of exchange from the bottom up. The results of the study indicate that there exists no universal combination of exchange rules that can predict human behaviour in all settings. Exchange rules are adopted based on institutional norms as well as norms that emerge during interaction

Using resting-state DMN effective connectivity to characterize the neurofunctional architecture of empathy

Neuroimaging studies in social neuroscience have largely relied on functional connectivity (FC) methods to characterize the functional integration between different brain regions. However, these methods have limited utility in social-cognitive studies that aim to understand the directed information flow among brain areas that underlies complex psychological processes. In this study we combined functional and effective connectivity approaches to characterize the functional integration within the Default Mode Network (DMN) and its role in self-perceived empathy. Forty-two participants underwent a resting state fMRI scan and completed a questionnaire of dyadic empathy. Independent Component Analysis (ICA) showed that higher empathy scores were associated with an increased contribution of the medial prefrontal cortex (mPFC) to the DMN spatial mode. Dynamic causal modelling (DCM) combined with Canonical Variance Analysis (CVA) revealed that this association was mediated indirectly by the posterior cingulate cortex (PCC) via the right inferior parietal lobule (IPL). More specifically, in participants with higher scores in empathy, the PCC had a greater effect on bilateral IPL and the right IPL had a greater influence on mPFC. These results highlight the importance of using analytic approaches that address directed and hierarchical connectivity within networks, when studying complex psychological phenomena, such as empathy.- This study was funded by BIAL Foundation (Grant number 87/12); by the Portuguese Foundation for Science and Technology and the Portuguese Ministry of Education and Science through national funds and co-financed by FEDER through COMPETE2020 under the PT2020 Partnership Agreement (POCI-01-0145-FEDER-007653); by the postdoctoral scholarship UMINHO/BPD/18/2017 and by the Portuguese Foundation for Science Doctoral scholarship (PD/BD/105963/2014). This work was conducted at Psychology Research Centre (UID/PSI/01662/2013), University of Minho