Order parameter model for unstable multilane traffic flow

We discuss a phenomenological approach to the description of unstable vehicle motion on multilane highways that explains in a simple way the observed sequence of the phase transitions "free flow -> synchronized motion -> jam" as well as the hysteresis in the transition "free flow synchronized motion". We introduce a new variable called order parameter that accounts for possible correlations in the vehicle motion at different lanes. So, it is principally due to the "many-body" effects in the car interaction, which enables us to regard it as an additional independent state variable of traffic flow. Basing on the latest experimental data (cond-mat/9905216) we assume that these correlations are due to a small group of "fast" drivers. Taking into account the general properties of the driver behavior we write the governing equation for the order parameter. In this context we analyze the instability of homogeneous traffic flow manifesting itself in both of the mentioned above phase transitions where, in addition, the transition "synchronized motion -> jam" also exhibits a similar hysteresis. Besides, the jam is characterized by the vehicle flows at different lanes being independent of one another. We specify a certain simplified model in order to study the general features of the car cluster self-formation under the phase transition "free flow synchronized motion". In particular, we show that the main local parameters of the developed cluster are determined by the state characteristics of vehicle motion only.Comment: REVTeX 3.1, 10 pages with 10 PostScript figure

Investigation of the XCAT phantom as a validation tool in cardiac MRI tracking algorithms.

PURPOSE: To describe our magnetic resonance imaging (MRI) simulated implementation of the 4D digital extended cardio torso (XCAT) phantom to validate our previously developed cardiac tracking techniques. Real-time tracking will play an important role in the non-invasive treatment of atrial fibrillation with MRI-guided radiosurgery. In addition, to show how quantifiable measures of tracking accuracy and patient-specific physiology could influence MRI tracking algorithm design. METHODS: Twenty virtual patients were subjected to simulated MRI scans that closely model the proposed real-world scenario to allow verification of the tracking technique's algorithm. The generated phantoms provide ground-truth motions which were compared to the target motions output from our tracking algorithm. The patient-specific tracking error, ep, was the 3D difference (vector length) between the ground-truth and algorithm trajectories. The tracking errors of two combinations of new tracking algorithm functions that were anticipated to improve tracking accuracy were studied. Additionally, the correlation of key physiological parameters with tracking accuracy was investigated. RESULTS: Our original cardiac tracking algorithm resulted in a mean tracking error of 3.7 ± 0.6 mm over all virtual patients. The two combinations of tracking functions demonstrated comparable mean tracking errors however indicating that the optimal tracking algorithm may be patient-specific. CONCLUSIONS: Current and future MRI tracking strategies are likely to benefit from this virtual validation method since no time-resolved 4D ground-truth signal can currently be derived from purely image-based studies

A model for estimating pathogen variability in shellfish and predicting minimum depuration times

Norovirus is a major cause of viral gastroenteritis, with shellfish consumption being identified as one potential norovirus entry point into the human population. Minimising shellfish norovirus levels is therefore important for both the consumer’s protection and the shellfish industry’s reputation. One method used to reduce microbiological risks in shellfish is depuration; however, this process also presents additional costs to industry. Providing a mechanism to estimate norovirus levels during depuration would therefore be useful to stakeholders. This paper presents a mathematical model of the depuration process and its impact on norovirus levels found in shellfish. Two fundamental stages of norovirus depuration are considered: (i) the initial distribution of norovirus loads within a shellfish population and (ii) the way in which the initial norovirus loads evolve during depuration. Realistic assumptions are made about the dynamics of norovirus during depuration, and mathematical descriptions of both stages are derived and combined into a single model. Parameters to describe the depuration effect and norovirus load values are derived from existing norovirus data obtained from U.K. harvest sites. However, obtaining population estimates of norovirus variability is time-consuming and expensive; this model addresses the issue by assuming a ‘worst case scenario’ for variability of pathogens, which is independent of mean pathogen levels. The model is then used to predict minimum depuration times required to achieve norovirus levels which fall within possible risk management levels, as well as predictions of minimum depuration times for other water-borne pathogens found in shellfish. Times for Escherichia coli predicted by the model all fall within the minimum 42 hours required for class B harvest sites, whereas minimum depuration times for norovirus and FRNA+ bacteriophage are substantially longer. Thus this study provides relevant information and tools to assist norovirus risk managers with future control strategies

Different Catalytic Mechanisms in Mammalian Selenocysteine- and Cysteine-Containing Methionine-R-Sulfoxide Reductases

Selenocysteine (Sec) is found in active sites of several oxidoreductases in which this residue is essential for catalytic activity. However, many selenoproteins have fully functional orthologs, wherein cysteine (Cys) occupies the position of Sec. The reason why some enzymes evolve into selenoproteins if the Cys versions may be sufficient is not understood. Among three mammalian methionine-R-sulfoxide reductases (MsrBs), MsrB1 is a Sec-containing protein, whereas MsrB2 and MsrB3 contain Cys in the active site, making these enzymes an excellent system for addressing the question of why Sec is used in biological systems. In this study, we found that residues, which are uniquely conserved in Cys-containing MsrBs and which are critical for enzyme activity in MsrB2 and MsrB3, were not required for MsrB1, but increased the activity of its Cys mutant. Conversely, selenoprotein MsrB1 had a unique resolving Cys reversibly engaged in the selenenylsulfide bond. However, this Cys was not necessary for activities of either MsrB2, MsrB3, or the Cys mutant of MsrB1. We prepared Sec-containing forms of MsrB2 and MsrB3 and found that they were more than 100-fold more active than the natural Cys forms. However, these selenoproteins could not be reduced by the physiological electron donor, thioredoxin. Yet, insertion of the resolving Cys, which was conserved in MsrB1, into the selenoprotein form of MsrB3 restored the thioredoxin-dependent activity of this enzyme. These data revealed differences in catalytic mechanisms between selenoprotein MsrB1 and non-selenoproteins MsrB2 and MsrB3, and identified catalytic advantages and disadvantages of Sec- and Cys-containing proteins. The data also suggested that Sec- and Cys-containing oxidoreductases require distinct sets of active-site features that maximize their catalytic efficiencies and provide strategies for protein design with improved catalytic properties

Clinical, industrial, and research perspectives on powder bed fusion additively manufactured metal implants

For over ten years, metallic skeletal endoprostheses have been produced in select cases by additive manufacturing (AM) and increasing awareness is driving demand for wider access to the technology. This review brings together key stakeholder perspectives on the translation of AM research; clinical application, ongoing research in the field of powder bed fusion, and the current regulatory framework. The current clinical use of AM is assessed, both on a mass-manufactured scale and bespoke application for patient specific implants. To illuminate the benefits to clinicians, a case study on the provision of custom cranioplasty is provided based on prosthetist testimony. Current progress in research is discussed, with immediate gains to be made through increased design freedom described at both meso- and macro-scale, as well as long-term goals in alloy development including bioactive materials. In all cases, focus is given to specific clinical challenges such as stress shielding and osseointegration. Outstanding challenges in industrialisation of AM are openly raised, with possible solutions assessed. Finally, overarching context is given with a review of the regulatory framework involved in translating AM implants, with particular emphasis placed on customisation within an orthopaedic remit. A viable future for AM of metal implants is presented, and it is suggested that continuing collaboration between all stakeholders will enable acceleration of the translation process

Evaluation of the protection against norovirus afforded by E. coli monitoring of shellfish production areas under EU regulations

EC Regulation 854/2004 requires the classification of bivalve mollusc harvesting areas according to the faecal pollution status of sites. It has been reported that determination of Escherichia coli in bivalve shellfish is a poor predictor of norovirus (NoV) contamination in individual samples. We explore the correlation of shellfish E. coli data with norovirus presence using data from studies across 88 UK sites (1,184 paired samples). We investigate whether current E. coli legislative standards could be refined to reduce NoV infection risk. A significant relationship between E. coli and NoV was found in the winter months (October to February) using data from sites with at least 10 data pairs (51 sites). We found that the ratio of arithmetic means (log10 E. coli to log10 NoV) at these sites ranged from 0.6 to 1.4. The lower ratios (towards 0.6) might typically indicate situations where the contribution from UV disinfected sewage discharges was more significant. Conversely, higher ratios (towards 1.4) might indicate a prevalence of animal sources of pollution; however, this relationship did not always hold true and so further work is required to fully elucidate the factors of relevance. Reducing the current class B maximum (allowed in 10% of samples) from 46,000 E. coli per 100 g (corresponding NoV value of 75750±103) to 18,000 E. coli per 100 g (corresponding NoV value of 29365±69) reduces maximum levels of NoV by a factor of 2.6 to 1; reducing the upper class B limit to 100% compliance with 4,600 E. coli per 100 g (corresponding NoV value of 7403±39) reduces maximum levels of NoV by a factor of 10.2 to 1. We found using the UK filtered winter dataset that a maximum of 200 NoV corresponded to a maximum of 128±7 E. coli per 100 g. A maximum of 1,000 NoV corresponded to a maximum of 631±14 E. coli per 100 g

The immune cell infiltrate populating meningiomas is composed of mature, antigen-experienced T and B cells

BACKGROUND: Meningiomas often harbor an immune cell infiltrate that can include substantial numbers of T and B cells. However, their phenotype and characteristics remain undefined. To gain a deeper understanding of the T and B cell repertoire in this tumor, we characterized the immune infiltrate of 28 resected meningiomas representing all grades. METHODS: Immunohistochemistry was used to grossly characterize and enumerate infiltrating lymphocytes. A molecular analysis of the immunoglobulin variable region of tumor-infiltrating B cells was used to characterize their antigen experience. Flow cytometry of fresh tissue homogenate and paired peripheral blood lymphocytes was used to identify T cell phenotypes and characterize the T cell repertoire. RESULTS: A conspicuous B and T cell infiltrate, primarily clustered in perivascular spaces, was present in the microenvironment of most tumors examined. Characterization of 294 tumor-infiltrating B cells revealed clear evidence of antigen experience, in that the cardinal features of an antigen-driven B cell response were present. Meningiomas harbored populations of antigen-experienced CD4+ and CD8+ memory/effector T cells, regulatory T cells, and T cells expressing the immune checkpoint molecules PD-1 and Tim-3, indicative of exhaustion. All of these phenotypes were considerably enriched relative to their frequency in the circulation. The T cell repertoire in the tumor microenvironment included populations that were not reflected in paired peripheral blood. CONCLUSION: The tumor microenvironment of meningiomas often includes postgerminal center B cell populations. These tumors invariably include a selected, antigen-experienced, effector T cell population enriched by those that express markers of an exhausted phenotype