While precise mechanisms underlying cardiovascular diseases (CVDs) are still not fully understood, previous studies suggest that the innate immune system, through Toll-like receptor 4 (TLR4), plays a crucial part in the pathways leading to these diseases, mainly because of its interplay with endogenous molecules. The Heat-shock protein 70 family (HSP70-70kDa) is of particular interest in cardiovascular tissues as it may have dual effects when interacting with TLR4 pathways. Although the hypothesis of the HSP70 family members acting as TLR4 ligands is becoming widely accepted, to date no co-crystal structure of this complex is available and it is still unknown whether this process requires the co-adaptor MD2. In this study, we aimed at investigating the interplay between the TLR4/MD2 complex and HSP70 family members in the human cardiovascular system through transcriptomic data analysis and at proposing a putative interaction model between these proteins. We report compelling evidence of correlated expression levels between TLR4 and MD2 with HSP70 cognate family members, especially in heart tissue. In our molecular docking simulations, we found that HSP70 in the ATP-bound state presents a better docking score towards the TLR4/MD2 complex compared to the ADP-bound state (−22.60 vs. −10.29 kcal/mol, respectively). Additionally, we show via a proximity ligation assay for HSP70 and TLR4, that cells stimulated with ATP have higher formation of fluorescent spots and that MD2 might be required for the complexation of these proteins. The insights provided by our computational approach are potential scaffolds for future in vivo studies investigating the interplay between the TLR4/MD2 complex and HSP70 family members in the cardiovascular system.

Political ideology is a major social phenomena that plays a crucial role in the formation and dynamics of ideologically-aligned social groups. This alignment gives rise to some of the most powerful social structures in modern democracies, the political parties. Due to the influence and importance of political parties in society, estimating their ideology is an active topic in political science research. However ideology is a very subjective phenomena and existing quantitative methods for ideology estimation are susceptible to a variety estimation issues, specially when applied in multi-partisan systems. In this work, we developed a data-driven network model for political ideology estimation based on partisan relationships established from party-switching politicians. The model is applied to the Brazilian case and yields results consistent with existing literature in the Brazilian political scenario while addressing data scarcity issues in existing methodologies.

In the last two decades, we have witnessed the widespread use of structural analysis of data. The area, generally called Network Science, concentrates on understanding complex phenomena by looking for properties that emerge from the relationships between the pieces of data instead of the traditional mining of the data itself. A commonly used structural analysis in networks consists of finding subgraphs whose density of connections within the subgraph surpasses that of outside connections; called Community Detection. Many techniques have been proposed to find communities as well as benchmarks to evaluate the algorithms ability to find these substructures. Until recently, the literature has mostly neglected the fact that these communities often represent common characteristic of the elements in the community. For instance, in a social network, communities could represent: people who follow the same particular sport, people from the same classroom, authors working in the same field of study, to name a few. The problem here is one of community detection selection as a function of the ground truth provided by available meta-data. In this work, we propose the use of rank stability (entropy of ranks) to assess communities identified using different techniques from the perspective of meta-data. We validate our approach using a large-scale data set of on-line social interactions across multiple community detection techniques.

Background: Emerging evidence highlights distinct mechanisms driving cardiovascular diseases in males and females. Particularly important in this context are the actions of the Heat Shock Protein 70 (HSP70) family, which are molecular chaperones that, under pathological conditions, modulate innate immune receptors such as Toll-like receptor 4 (TLR4). Activation of TLR4 triggers oxidative stress and inflammation, key elements of vascular diseases. However, it is still unknown if HSP70 stimulates TLR4 in smooth muscle cells (SMCs) as well as how the expression of HSP70 family members relate to TLR4 in the vasculature of type 2 diabetic (T2D) donors. Methods and Results: We used a proximity ligation assay to investigate the association between TLR4 and HSP70 in SMCs, and fluorescent spots were observed indicating both target proteins within interacting range. Additionally, we exposed SMCs to high glucose (25 mM) in presence or absence of an HSP70 inhibitor (VER155008, 10 ^-5 M), and we evaluated TLR4 levels, which showed that HSP70 blockade attenuates TLR4 expression (-3.3-fold vs . high glucose). Next, we analyzed a human transcriptomic dataset of T2D donors from the GTEx database, which contains 46 samples from aorta (30 males and 16 females). To reduce the effects of confounders, we matched two covariates (age and race), and we excluded donors with T1D or unknown T1D status. The statsmodels Python package was used to compute the Pearson correlation among the transcripts per million values of RNA for TLR4 and HSP70 family genes [cognate (HSPA8) and inducible (HSPA1A, HSPA1B, HSPA6)] in T2D donors (n=14 samples for each sex). We observed a positive correlation between HSPA6 and TLR4 in males (r = 0.58; p0.05). On the other hand, the levels of HSPA8 inversely correlate with TLR4 in females (r = -0.55; p0.05). It appears that in males, an increase in the expression of TLR4 induces HSPA6 without affecting the levels of HSPA8 while in females an increase in TLR4 levels does not associate with the inducible genes, but it impairs HSPA8. No association was found in the other analyzed genes. Conclusion: Our results suggest that sex plays a role in the interplay between TLR4 and HSP70 family members in aortic tissue.

Brazil has a multi-party political system with 30 registered parties (as of 2013). However, anyone who knows a little about politics understands that is nearly impossible to have 30 dimensions of political positions (e.g. center, left, right, center-left, etc.) with no overlap. Hence, the obvious challenge is to understand this party system and how parties group together. However there is no obvious way to group these parties because the data we normally have come from the parties' self-assigned positioning. What we see in practice, based on how the alliances are built and how politicians change from one party to another, is that most of them do not have a well-defined positional basis. Such phenomenon has been investigated since the 90s but always based on how elected politicians migrate between different parties. Today, we have at our disposal much more data that may be used to review political leanings. In this paper, we focus on the inter-party movements of candidates and on the relationship between movements and parties' ideology and performance. Results suggest that parties' performance in elections is strongly correlated with the parties' strategies for promoting candidates.