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We develop a conceptual framework for studying collective adaptation in complex socio-cognitive systems, driven by dynamic interactions of social integration strategies, social environments and problem structures. Going beyond searching for 'intelligent' collectives, we integrate research from different disciplines and outline modelling approaches that can be used to begin answering questions such as why collectives sometimes fail to reach seemingly obvious solutions, how they change their strategies and network structures in response to different problems and how we can anticipate and perhaps change future harmful societal trajectories. We discuss the importance of considering path dependence, lack of optimization and collective myopia to understand the sometimes counterintuitive outcomes of collective adaptation. We call for a transdisciplinary, quantitative and societally useful social science that can help us to understand our rapidly changing and ever more complex societies, avoid collective disasters and reach the full potential of our ability to organize in adaptive collectives.

The ability to 'sense' the social environment and thereby to understand the thoughts and actions of others allows humans to fit into their social worlds, communicate and cooperate, and learn from others' experiences. Here we argue that, through the lens of computational social science, this ability can be used to advance research into human sociality. When strategically selected to represent a specific population of interest, human social sensors can help to describe and predict societal trends. In addition, their reports of how they experience their social worlds can help to build models of social dynamics that are constrained by the empirical reality of human social systems.

Belief change and spread have been studied in many disciplines-from psychology, sociology, economics and philosophy, to biology, computer science and statistical physics-but we still do not have a firm grasp on why some beliefs change more easily and spread faster than others. To fully capture the complex social-cognitive system that gives rise to belief dynamics, we first review insights about structural components and processes of belief dynamics studied within different disciplines. We then outline a unifying quantitative framework that enables theoretical and empirical comparisons of different belief dynamic models. This framework uses a statistical physics formalism, grounded in cognitive and social theory, as well as empirical observations. We show how this framework can be used to integrate extant knowledge and develop a more comprehensive understanding of belief dynamics.

The BD Phoenix (BD Diagnostics, Sparks, MD) and Vitek 2 (bioMérieux, Durham, NC) automated susceptibility testing systems have implemented the use of cefoxitin to enhance the detection of methicillin (meticillin)-resistant Staphylococcus aureus (MRSA). To assess the impact of this change, 620 clinically significant S. aureus isolates were tested in parallel on Phoenix PMIC/ID-102 panels and Vitek 2 AST-GP66 cards. The results for oxacillin and cefoxitin generated by the automated systems were compared to those generated by two reference methods: mecA gene detection and MICs of oxacillin previously determined by broth microdilution according to CLSI guidelines. Testing of isolates with discordant results was repeated to attain a majority or consensus final result. There was 100% final agreement between the results of the two reference methods. For the 448 MRSA and 172 methicillin-susceptible S. aureus isolates tested, the rates of categorical agreement of the results obtained with the automated systems with those obtained by the reference methods were 99.8% for the Phoenix panels and 99.7% for the Vitek 2 cards. A single very major error occurred on each instrument (0.2%) with different MRSA isolates. The only major error was attributed to the Vitek 2 system overcalling oxacillin resistance. In 16 instances (9 on the Phoenix system, 7 on the Vitek 2 system), an oxacillin MIC in the susceptible range was correctly changed to resistant by the expert system on the basis of the cefoxitin result. The inclusion of cefoxitin in the Phoenix and Vitek 2 panels has optimized the detection of MRSA by both systems.

Klebsiella pneumoniae isolates from Taiwan medical centers (50 strains; 1998 to 2000) with a CTX-M resistance phenotype (ceftazidime susceptible and ceftriaxone or cefotaxime nonsusceptible) were selected for initial isoelectric focusing analysis. beta-Lactamases with pIs of 7.9 (n = 22) and 8.4 (n = 28) in addition to 5.4 and/or 7.6 were detected. DNA gene sequencing identified the beta-lactamases with pIs of 7.9 and 8.4 as CTX-M-14 and CTX-M-3, respectively. Molecular typing suggested inter- and intrahospital clonal dissemination of these Taiwanese CTX-M-producing Klebsiella strains.

We discuss the generic time behavior of reaction-diffusion processes capable of modeling various types of biological transport processes, such as ligand migration in proteins and gating fluctuations in ion channel proteins. The main observable in these two cases, the fraction of unbound ligands and the probability of finding the channel in the closed state, respectively, exhibits an algebraic t-1/2 decay at intermediate times, followed by an exponential cutoff. We provide a simple framework for understanding these observations and explain their ubiquity by showing that these qualitative results are independent of space dimension. We also derive an experimental criterion to distinguish between a one-dimensional process and one whose effective dimension is higher.

We propose a mathematical model for the next stage in the origin of life after that treated in our earlier work. At this stage we introduce the possibility of the modification of the environment by the information-containing entities and feedback between the environment and the population of macromolecules and hence provide a model for the development of the Eigen hypercycle.

Computer simulations of a "spin glass" model for the origin of biological information are discussed. Selection is found to occur among a wide diversity of possible species, and in addition competition, adaptation, and hysteresis are all exhibited.

The fluorescence decay of the rare earth terbium when bound to the protein calmodulin changes from a simple exponential decay to a complex nonexponential decay as the temperature is lowered below 200 K. We have fit the observed decay curves by assuming that the terbium emission is a forced electric dipole transition and proteins have a distribution of continuous conformational states. Quantitative fits to the data indicate that the root-mean-square configurational deviation of the atoms surrounding the terbium ion is 0.2 A, in good agreement with other measurements. We further point out that because the protein seems to undergo a glass transition yet retains configurational order at room temperature, the proper name for the physical state of a protein at room temperature is the rubber-like state.

Many proteins have been observed to exist in a large number of conformations that are believed to play an important role in their dynamics. A model of protein conformational substates that incorporates the ideas of frustration and disorder in analogy to glasses and spin glasses is proposed. Applications to x-ray diffraction, Mössbauer studies, and recombination experiments are discussed.