The Updated Zwicky Catalog (UZC)

The Zwicky Catalog of galaxies (ZC), with m_Zw<=15.5mag, has been the basis for the Center for Astrophysics (CfA) redshift surveys. To date, analyses of the ZC and redshift surveys based on it have relied on heterogeneous sets of galaxy coordinates and redshifts. Here we correct some of the inadequacies of previous catalogs by providing: (1) coordinates with <~2 arcsec errors for all of the Nuzc catalog galaxies, (2) homogeneously estimated redshifts for the majority (98%) of the data taken at the CfA (14,632 spectra), and (3) an estimate of the remaining "blunder" rate for both the CfA redshifts and for those compiled from the literature. For the reanalyzed CfA data we include a calibrated, uniformly determined error and an indication of the presence of emission lines in each spectrum. We provide redshifts for 7,257 galaxies in the CfA2 redshift survey not previously published; for another 5,625 CfA redshifts we list the remeasured or uniformly re-reduced value. Among our new measurements, Nmul are members of UZC "multiplets" associated with the original Zwicky catalog position in the coordinate range where the catalog is 98% complete. These multiplets provide new candidates for examination of tidal interactions among galaxies. All of the new redshifts correspond to UZC galaxies with properties recorded in the CfA redshift compilation known as ZCAT. About 1,000 of our new measurements were motivated either by inadequate signal-to-noise in the original spectrum or by an ambiguous identification of the galaxy associated with a ZCAT redshift. The redshift catalog we include here is ~96% complete to m_Zw<=15.5, and ~98% complete (12,925 galaxies out of a total of 13,150) for the RA(1950) ranges [20h--4h] and [8h--17h] and DEC(1950) range [-2.5d--50d]. (abridged)Comment: 34 pp, 7 figs, PASP 1999, 111, 43

Modulation of a protein free-energy landscape by circular permutation

Circular permutations usually retain the native structure and function of a protein while inevitably perturb its folding dynamics. By using simulations with a structure-based model and a rigorous methodology to determine free-energy surfaces from trajectories we evaluate the effect of a circular permutation on the free-energy landscape of the protein T4 lysozyme. We observe changes which, while subtle, largely affect the cooperativity between the two subdomains. Such a change in cooperativity has been previously experimentally observed and recently also characterized using single molecule optical tweezers and the Crooks relation. The free-energy landscapes show that both the wild type and circular permutant have an on-pathway intermediate, previously experimentally characterized, where one of the subdomains is completely formed. The landscapes, however, differ in the position of the rate-limiting step for folding, which occurs before the intermediate in the wild-type and after in the circular permutant. This shift of transition state explains the observed change in the cooperativity. The underlying free-energy landscape thus provides a microscopic description of the folding dynamics and the connection between circular permutation and the loss of cooperativity experimentally observed

A Model of Brain Circulation and Metabolism: NIRS Signal Changes during Physiological Challenges

We construct a model of brain circulation and energy metabolism. The model is designed to explain experimental data and predict the response of the circulation and metabolism to a variety of stimuli, in particular, changes in arterial blood pressure, CO2 levels, O2 levels, and functional activation. Significant model outputs are predictions about blood flow, metabolic rate, and quantities measurable noninvasively using near-infrared spectroscopy (NIRS), including cerebral blood volume and oxygenation and the redox state of the CuA centre in cytochrome c oxidase. These quantities are now frequently measured in clinical settings; however the relationship between the measurements and the underlying physiological events is in general complex. We anticipate that the model will play an important role in helping to understand the NIRS signals, in particular, the cytochrome signal, which has been hard to interpret. A range of model simulations are presented, and model outputs are compared to published data obtained from both in vivo and in vitro settings. The comparisons are encouraging, showing that the model is able to reproduce observed behaviour in response to various stimuli

Chlamydia trachomatis Co-opts the FGF2 Signaling Pathway to Enhance Infection

The molecular details of Chlamydia trachomatis binding, entry, and spread are incompletely understood, but heparan sulfate proteoglycans (HSPGs) play a role in the initial binding steps. As cell surface HSPGs facilitate the interactions of many growth factors with their receptors, we investigated the role of HSPG-dependent growth factors in C. trachomatis infection. Here, we report a novel finding that Fibroblast Growth Factor 2 (FGF2) is necessary and sufficient to enhance C. trachomatis binding to host cells in an HSPG-dependent manner. FGF2 binds directly to elementary bodies (EBs) where it may function as a bridging molecule to facilitate interactions of EBs with the FGF receptor (FGFR) on the cell surface. Upon EB binding, FGFR is activated locally and contributes to bacterial uptake into non-phagocytic cells. We further show that C. trachomatis infection stimulates fgf2 transcription and enhances production and release of FGF2 through a pathway that requires bacterial protein synthesis and activation of the Erk1/2 signaling pathway but that is independent of FGFR activation. Intracellular replication of the bacteria results in host proteosome-mediated degradation of the high molecular weight (HMW) isoforms of FGF2 and increased amounts of the low molecular weight (LMW) isoforms, which are released upon host cell death. Finally, we demonstrate the in vivo relevance of these findings by showing that conditioned medium from C. trachomatis infected cells is enriched for LMW FGF2, accounting for its ability to enhance C. trachomatis infectivity in additional rounds of infection. Together, these results demonstrate that C. trachomatis utilizes multiple mechanisms to co-opt the host cell FGF2 pathway to enhance bacterial infection and spread

Cinema-going trajectories in the digital age

The activity of cinema-going constantly evolves and gradually integrates the use of digital data and platforms to become more engaging for the audiences. Combining methods from the fields of Human Computer Interaction and Film Studies, we conducted two workshops seeking to understand cinema audiences’ digital practices and explore how the contemporary cinema-going experience is shaped in the digital age. Our findings suggest that going to the movies constitutes a trajectory during which cinemagoers interact with multiple digital platforms. At the same time, depending on their choices, they construct unique digital identities that represent a set of online behaviours and rituals that cinemagoers adopt before, while and after cinema-going. To inform the design of new, engaging cinemagoing experiences, this research establishes a preliminary map of contemporary cinema-going including digital data and platforms. We then discuss how audiences perceive the potential improvement of the experience and how that would lead to the construction of digital identities

Adaptive learning with covariate shift-detection for motor imagery-based brain–computer interface

A common assumption in traditional supervised learning is the similar probability distribution of data between the training phase and the testing/operating phase. When transitioning from the training to testing phase, a shift in the probability distribution of input data is known as a covariate shift. Covariate shifts commonly arise in a wide range of real-world systems such as electroencephalogram-based brain–computer interfaces (BCIs). In such systems, there is a necessity for continuous monitoring of the process behavior, and tracking the state of the covariate shifts to decide about initiating adaptation in a timely manner. This paper presents a covariate shift-detection and -adaptation methodology, and its application to motor imagery-based BCIs. A covariate shift-detection test based on an exponential weighted moving average model is used to detect the covariate shift in the features extracted from motor imagery-based brain responses. Following the covariate shift-detection test, the methodology initiates an adaptation by updating the classifier during the testing/operating phase. The usefulness of the proposed method is evaluated using real-world BCI datasets (i.e. BCI competition IV dataset 2A and 2B). The results show a statistically significant improvement in the classification accuracy of the BCI system over traditional learning and semi-supervised learning methods

COVID-19: Rapid antigen detection for SARS-CoV-2 by lateral flow assay: A national systematic evaluation of sensitivity and specificity for mass-testing

Background Lateral flow device (LFD) viral antigen immunoassays have been developed around the world as diagnostic tests for SARS-CoV-2 infection. They have been proposed to deliver an infrastructure-light, cost-economical solution giving results within half an hour. Methods LFDs were initially reviewed by a Department of Health and Social Care team, part of the UK government, from which 64 were selected for further evaluation from 1st August to 15th December 2020. Standardised laboratory evaluations, and for those that met the published criteria, field testing in the Falcon-C19 research study and UK pilots were performed (UK COVID-19 testing centres, hospital, schools, armed forces). Findings 4/64 LFDs so far have desirable performance characteristics (orient Gene, Deepblue, Abbott and Innova SARS-CoV-2 Antigen Rapid Qualitative Test). All these LFDs have a viral antigen detection of >90% at 100,000 RNA copies/ml. 8951 Innova LFD tests were performed with a kit failure rate of 5.6% (502/8951, 95% CI: 5.1–6.1), false positive rate of 0.32% (22/6954, 95% CI: 0.20–0.48). Viral antigen detection/sensitivity across the sampling cohort when performed by laboratory scientists was 78.8% (156/198, 95% CI 72.4–84.3). Interpretation Our results suggest LFDs have promising performance characteristics for mass population testing and can be used to identify infectious positive individuals. The Innova LFD shows good viral antigen detection/sensitivity with excellent specificity, although kit failure rates and the impact of training are potential issues. These results support the expanded evaluation of LFDs, and assessment of greater access to testing on COVID-19 transmission. Funding Department of Health and Social Care. University of Oxford. Public Health England Porton Down, Manchester University NHS Foundation Trust, National Institute of Health Research

The Drosophila melanogaster host model

The deleterious and sometimes fatal outcomes of bacterial infectious diseases are the net result of the interactions between the pathogen and the host, and the genetically tractable fruit fly, Drosophila melanogaster, has emerged as a valuable tool for modeling the pathogen–host interactions of a wide variety of bacteria. These studies have revealed that there is a remarkable conservation of bacterial pathogenesis and host defence mechanisms between higher host organisms and Drosophila. This review presents an in-depth discussion of the Drosophila immune response, the Drosophila killing model, and the use of the model to examine bacterial–host interactions. The recent introduction of the Drosophila model into the oral microbiology field is discussed, specifically the use of the model to examine Porphyromonas gingivalis–host interactions, and finally the potential uses of this powerful model system to further elucidate oral bacterial-host interactions are addressed