848 research outputs found

    Enhancement of chemotherapy using oncolytic virotherapy: Mathematical and optimal control analysis

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    Oncolytic virotherapy (OV) has been emerging as a promising novel cancer treatment that may be further combined with the existing therapeutic modalities to enhance their effects. To investigate how OV could enhance chemotherapy, we propose an ODE based model describing the interactions between tumour cells, the immune response, and a treatment combination with chemotherapy and oncolytic viruses. Stability analysis of the model with constant chemotherapy treatment rates shows that without any form of treatment, a tumour would grow to its maximum size. It also demonstrates that chemotherapy alone is capable of clearing tumour cells provided that the drug efficacy is greater than the intrinsic tumour growth rate. Furthermore, OV alone may not be able to clear tumour cells from body tissue but would rather enhance chemotherapy if viruses with high viral potency are used. To assess the combined effect of OV and chemotherapy we use the forward sensitivity index to perform a sensitivity analysis, with respect to chemotherapy key parameters, of the virus basic reproductive number and the tumour endemic equilibrium. The results from this sensitivity analysis indicate the existence of a critical dose of chemotherapy above which no further significant reduction in the tumour population can be observed. Numerical simulations show that a successful combinational therapy of the chemotherapeutic drugs and viruses depends mostly on the virus burst size, infection rate, and the amount of drugs supplied. Optimal control analysis was performed, by means of Pontryagin's principle, to further refine predictions of the model with constant treatment rates by accounting for the treatment costs and sides effects.Comment: This is a preprint of a paper whose final and definite form is with 'Mathematical Biosciences and Engineering', ISSN 1551-0018 (print), ISSN 1547-1063 (online), available at [http://www.aimsciences.org/journal/1551-0018]. Submitted 27-March-2018; revised 04-July-2018; accepted for publication 10-July-201

    Exploring Short-Term Responses to Changes in the Control Strategy for Chlamydia trachomatis

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    Chlamydia has a significant impact on public health provision in the developed world. Using pair approximation equations we investigate the efficacy of control programmes for chlamydia on short time scales that are relevant to policy makers. We use output from the model to estimate critical measures, namely, prevalence, incidence, and positivity in those screened and their partners. We combine these measures with a costing tool to estimate the economic impact of different public health strategies. Increasing screening coverage significantly increases the annual programme costs whereas an increase in tracing efficiency initially increases annual costs but over time reduces costs below baseline, with tracing accounting for around 10% of intervention costs. We found that partner positivity is insensitive to changes in prevalence due to screening, remaining at around 33%. Whether increases occur in screening or tracing levels, the cost per treated infection increases from the baseline because of reduced prevalence

    Using Ripple Effects Maps to Identify Story Threads: A Framework to Link Private to Public Value

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    Extension professionals must demonstrate organizational value to garner public awareness and support. Measuring and communicating outcomes that have public value can be challenging. In this study, Ripple Effects Mapping incorporating the Community Capitals Framework was used to evaluate a childhood obesity prevention study, iCook 4-H, of youth-adult pairs in Maine. The objective was to describe the process of generating impact statements through story threads about program benefits to the participants and the potential benefits to nonparticipants, such as family members, friends, and other community members. Extension professionals can use storylines, or story threads, as a qualitative research technique to generate stories about private and public value from participants’ actions, experiences, and emotions following community programs. The story threads process can be used across disciplines to leverage community program data into public value messaging

    Male frequent attenders of general practice and their help seeking preferences

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    Background: Low rates of health service usage by men are commonly linked to masculine values and traditional male gender roles. However, not all men conform to these stereotypical notions of masculinity, with some men choosing to attend health services on a frequent basis, for a variety of different reasons. This study draws upon the accounts of male frequent attenders of the General Practitioner's (GP) surgery, examining their help-seeking preferences and their reasons for choosing services within general practice over other sources of support. Methods: The study extends thematic analysis of interview data from the Self Care in Primary Care study (SCinPC), a large scale multi-method evaluation study of a self care programme delivered to frequent attenders of general practice. Data were collected from 34 semi-structured interviews conducted with men prior to their exposure to the intervention. Results: The ages of interviewed men ranged from 16 to 72 years, and 91% of the sample (n= 31) stated that they had a current health condition. The thematic analysis exposed diverse perspectives within male help-seeking preferences and the decision-making behind men's choice of services. The study also draws attention to the large variation in men's knowledge of available health services, particularly alternatives to general practice. Furthermore, the data revealed some men's lack of confidence in existing alternatives to general practice. Conclusions: The study highlights the complex nature of male help-seeking preferences, and provides evidence that there should be no 'one size fits all' approach to male service provision. It also provides impetus for conducting further studies into this under researched area of interest. © 2011 WPMH GmbH

    Pathways to diagnosis of non-small cell lung cancer : a descriptive cohort study

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    Little has been published on the diagnostic and referral pathway for lung cancer in Australia. This study set out to quantify general practitioner (GP) and lung specialist attendance and diagnostic imaging in the lead-up to a diagnosis of non-small cell lung cancer (NSCLC) and identify common pathways to diagnosis in New South Wales (NSW), Australia. We used linked health data for participants of the 45 and Up Study (a NSW population-based cohort study) diagnosed with NSCLC between 2006 and 2012. Our main outcome measures were GP and specialist attendances, X-rays and computed tomography (CT) scans of the chest and lung cancer-related hospital admissions. Among our study cohort (N = 894), 60% (n = 536) had ≥4 GP attendances in the 3 months prior to diagnosis of NSCLC, 56% (n = 505) had GP-ordered imaging (chest X-ray or CT scan), 39% (N = 349) attended a respiratory physician and 11% (N = 102) attended a cardiothoracic surgeon. The two most common pathways to diagnosis, accounting for one in three people, included GP and lung specialist (respiratory physician or cardiothoracic surgeon) involvement. Overall, 25% of people (n = 223) had an emergency hospital admission. For 14% of people (N = 129), an emergency hospital admission was the only event identified on the pathway to diagnosis. We found little effect of remoteness of residence on access to services. This study identified a substantial proportion of people with NSCLC being diagnosed in an emergency setting. Further research is needed to establish whether there were barriers to the timely diagnosis of these cases

    Can One Trust Quantum Simulators?

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    Various fundamental phenomena of strongly-correlated quantum systems such as high-TcT_c superconductivity, the fractional quantum-Hall effect, and quark confinement are still awaiting a universally accepted explanation. The main obstacle is the computational complexity of solving even the most simplified theoretical models that are designed to capture the relevant quantum correlations of the many-body system of interest. In his seminal 1982 paper [Int. J. Theor. Phys. 21, 467], Richard Feynman suggested that such models might be solved by "simulation" with a new type of computer whose constituent parts are effectively governed by a desired quantum many-body dynamics. Measurements on this engineered machine, now known as a "quantum simulator," would reveal some unknown or difficult to compute properties of a model of interest. We argue that a useful quantum simulator must satisfy four conditions: relevance, controllability, reliability, and efficiency. We review the current state of the art of digital and analog quantum simulators. Whereas so far the majority of the focus, both theoretically and experimentally, has been on controllability of relevant models, we emphasize here the need for a careful analysis of reliability and efficiency in the presence of imperfections. We discuss how disorder and noise can impact these conditions, and illustrate our concerns with novel numerical simulations of a paradigmatic example: a disordered quantum spin chain governed by the Ising model in a transverse magnetic field. We find that disorder can decrease the reliability of an analog quantum simulator of this model, although large errors in local observables are introduced only for strong levels of disorder. We conclude that the answer to the question "Can we trust quantum simulators?" is... to some extent.Comment: 20 pages. Minor changes with respect to version 2 (some additional explanations, added references...
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