Structure of a dimeric photosystem II complex from a cyanobacterium acclimated to far-red light

Photosystem II (PSII) is the water-splitting enzyme central to oxygenic photosynthesis. To drive water oxidation, light is harvested by accessory pigments, mostly chlorophyll (Chl) a molecules, which absorb visible light (400–700 nm). Some cyanobacteria facultatively acclimate to shaded environments by altering their photosynthetic machinery to additionally absorb far-red light (FRL, 700–800 nm), a process termed far-red light photoacclimation or FaRLiP. During far-red light photoacclimation, FRL-PSII is assembled with FRL-specific isoforms of the subunits PsbA, PsbB, PsbC, PsbD, and PsbH, and some Chl-binding sites contain Chls d or f instead of the usual Chl a. The structure of an apo-FRL-PSII monomer lacking the FRL-specific PsbH subunit has previously been determined, but visualization of the dimeric complex has remained elusive. Here, we report the cryo-EM structure of a dimeric FRL–PSII complex. The site assignments for Chls d and f are consistent with those assigned in the previous apo-FRL-PSII monomeric structure. All sites that bind Chl d or Chl f at high occupancy exhibit a FRL-specific interaction of the formyl moiety of the Chl d or Chl f with the protein environment, which in some cases involves a phenylalanine sidechain. The structure retains the FRL-specific PsbH2 subunit, which appears to alter the energetic landscape of FRL-PSII, redirecting energy transfer from the phycobiliprotein complex to a Chl f molecule bound by PsbB2 that acts as a bridge for energy transfer to the electron transfer chain. Collectively, these observations extend our previous understanding of the structure-function relationship that allows PSII to function using lower energy FRL

Building data warehouses in the era of big data: an approach for scalable and flexible big data warehouses

During the last few years, the concept of Big Data Warehousing gained significant attention from the scientific community, highlighting the need to make design changes to the traditional Data Warehouse (DW) due to its limitations, in order to achieve new characteristics relevant in Big Data contexts (e.g., scalability on commodity hardware, real-time performance, and flexible storage). The state-of-the-art in Big Data Warehousing reflects the young age of the concept, as well as ambiguity and the lack of common approaches to build Big Data Warehouses (BDWs). Consequently, an approach to design and implement these complex systems is of major relevance to business analytics researchers and practitioners. In this tutorial, the design and implementation of BDWs is targeted, in order to present a general approach that researchers and practitioners can follow in their Big Data Warehousing projects, exploring several demonstration cases focusing on system design and data modelling examples in areas like smart cities, retail, finance, manufacturing, among others

A meta-analysis of state-of-the-art electoral prediction from Twitter data

Electoral prediction from Twitter data is an appealing research topic. It seems relatively straightforward and the prevailing view is overly optimistic. This is problematic because while simple approaches are assumed to be good enough, core problems are not addressed. Thus, this paper aims to (1) provide a balanced and critical review of the state of the art; (2) cast light on the presume predictive power of Twitter data; and (3) depict a roadmap to push forward the field. Hence, a scheme to characterize Twitter prediction methods is proposed. It covers every aspect from data collection to performance evaluation, through data processing and vote inference. Using that scheme, prior research is analyzed and organized to explain the main approaches taken up to date but also their weaknesses. This is the first meta-analysis of the whole body of research regarding electoral prediction from Twitter data. It reveals that its presumed predictive power regarding electoral prediction has been rather exaggerated: although social media may provide a glimpse on electoral outcomes current research does not provide strong evidence to support it can replace traditional polls. Finally, future lines of research along with a set of requirements they must fulfill are provided.Comment: 19 pages, 3 table

The field-dependence of the solid-state photo-CIDNP effect in two states of heliobacterial reaction centers

Solid state NMR/Biophysical Organic Chemistr

Network Archaeology: Uncovering Ancient Networks from Present-day Interactions

Often questions arise about old or extinct networks. What proteins interacted in a long-extinct ancestor species of yeast? Who were the central players in the Last.fm social network 3 years ago? Our ability to answer such questions has been limited by the unavailability of past versions of networks. To overcome these limitations, we propose several algorithms for reconstructing a network's history of growth given only the network as it exists today and a generative model by which the network is believed to have evolved. Our likelihood-based method finds a probable previous state of the network by reversing the forward growth model. This approach retains node identities so that the history of individual nodes can be tracked. We apply these algorithms to uncover older, non-extant biological and social networks believed to have grown via several models, including duplication-mutation with complementarity, forest fire, and preferential attachment. Through experiments on both synthetic and real-world data, we find that our algorithms can estimate node arrival times, identify anchor nodes from which new nodes copy links, and can reveal significant features of networks that have long since disappeared.Comment: 16 pages, 10 figure

Emergence of scale-free leadership structure in social recommender systems

The study of the organization of social networks is important for understanding of opinion formation, rumor spreading, and the emergence of trends and fashion. This paper reports empirical analysis of networks extracted from four leading sites with social functionality (Delicious, Flickr, Twitter and YouTube) and shows that they all display a scale-free leadership structure. To reproduce this feature, we propose an adaptive network model driven by social recommending. Artificial agent-based simulations of this model highlight a "good get richer" mechanism where users with broad interests and good judgments are likely to become popular leaders for the others. Simulations also indicate that the studied social recommendation mechanism can gradually improve the user experience by adapting to tastes of its users. Finally we outline implications for real online resource-sharing systems

Becoming a Viking: DNA testing, genetic ancestry and placeholder identity

A consensus has developed among social and biological scientists around the problematic nature of genetic ancestry testing, specifically that its popularity will lead to greater genetic essentialism in social identities. Many of these arguments assume a relatively uncritical engagement with DNA, under ‘highstakes’ conditions. We suggest that in a biosocial society, more pervasive ‘lowstakes’ engagement is more likely. Through qualitative interviews with participants in a study of the genetic legacy of the Vikings in Northern England, we investigate how genetic ancestry results are discursively worked through. The identities formed in ‘becoming a Viking’ through DNA are characterized by fluidity and reflexivity, rather than essentialism. DNA results are woven into a wider narrative of selfhood relating to the past, the value of which lies in its potential to be passed on within families. While not unproblematic, the relatively banal nature of such narratives within contemporary society is characteristic of the ‘biosociable’

The First Provenance Challenge

The first Provenance Challenge was set up in order to provide a forum for the community to help understand the capabilities of different provenance systems and the expressiveness of their provenance representations. To this end, a Functional Magnetic Resonance Imaging workflow was defined, which participants had to either simulate or run in order to produce some provenance representation, from which a set of identified queries had to be implemented and executed. Sixteen teams responded to the challenge, and submitted their inputs. In this paper, we present the challenge workflow and queries, and summarise the participants contributions