ACORN (A Clinically-Oriented Antimicrobial Resistance Surveillance Network) II: protocol for case based antimicrobial resistance surveillance

Background: Antimicrobial resistance surveillance is essential for empiric antibiotic prescribing, infection prevention and control policies and to drive novel antibiotic discovery. However, most existing surveillance systems are isolate-based without supporting patient-based clinical data, and not widely implemented especially in low- and middle-income countries (LMICs). Methods: A Clinically-Oriented Antimicrobial Resistance Surveillance Network (ACORN) II is a large-scale multicentre protocol which builds on the WHO Global Antimicrobial Resistance and Use Surveillance System to estimate syndromic and pathogen outcomes along with associated health economic costs. ACORN-healthcare associated infection (ACORN-HAI) is an extension study which focuses on healthcare-associated bloodstream infections and ventilator-associated pneumonia. Our main aim is to implement an efficient clinically-oriented antimicrobial resistance surveillance system, which can be incorporated as part of routine workflow in hospitals in LMICs. These surveillance systems include hospitalised patients of any age with clinically compatible acute community-acquired or healthcare-associated bacterial infection syndromes, and who were prescribed parenteral antibiotics. Diagnostic stewardship activities will be implemented to optimise microbiology culture specimen collection practices. Basic patient characteristics, clinician diagnosis, empiric treatment, infection severity and risk factors for HAI are recorded on enrolment and during 28-day follow-up. An R Shiny application can be used offline and online for merging clinical and microbiology data, and generating collated reports to inform local antibiotic stewardship and infection control policies. Discussion: ACORN II is a comprehensive antimicrobial resistance surveillance activity which advocates pragmatic implementation and prioritises improving local diagnostic and antibiotic prescribing practices through patient-centred data collection. These data can be rapidly communicated to local physicians and infection prevention and control teams. Relative ease of data collection promotes sustainability and maximises participation and scalability. With ACORN-HAI as an example, ACORN II has the capacity to accommodate extensions to investigate further specific questions of interest

Emergency logistics for wildfire suppression based on forecasted disaster evolution

This paper aims to develop a two-layer emergency logistics system with a single depot and multiple demand sites for wildfire suppression and disaster relief. For the first layer, a fire propagation model is first built using both the flame-igniting attributes of wildfires and the factors affecting wildfire propagation and patterns. Second, based on the forecasted propagation behavior, the emergency levels of fire sites in terms of demand on suppression resources are evaluated and prioritized. For the second layer, considering the prioritized fire sites, the corresponding resource allocation problem and vehicle routing problem (VRP) are investigated and addressed. The former is approached using a model that can minimize the total forest loss (from multiple sites) and suppression costs incurred accordingly. This model is constructed and solved using principles of calculus. To address the latter, a multi-objective VRP model is developed to minimize both the travel time and cost of the resource delivery vehicles. A heuristic algorithm is designed to provide the associated solutions of the VRP model. As a result, this paper provides useful insights into effective wildfire suppression by rationalizing resources regarding different fire propagation rates. The supporting models can also be generalized and tailored to tackle logistics resource optimization issues in dynamic operational environments, particularly those sharing the same feature of single supply and multiple demands in logistics planning and operations (e.g., allocation of ambulances and police forces). © 2017 The Author(s

ACORN (A Clinically-Oriented Antimicrobial Resistance Surveillance Network) II: protocol for case based antimicrobial resistance surveillance

Background: Antimicrobial resistance surveillance is essential for empiric antibiotic prescribing, infection prevention and control policies and to drive novel antibiotic discovery. However, most existing surveillance systems are isolate-based without supporting patient-based clinical data, and not widely implemented especially in low- and middle-income countries (LMICs). Methods: A Clinically-Oriented Antimicrobial Resistance Surveillance Network (ACORN) II is a large-scale multicentre protocol which builds on the WHO Global Antimicrobial Resistance and Use Surveillance System to estimate syndromic and pathogen outcomes along with associated health economic costs. ACORN-healthcare associated infection (ACORN-HAI) is an extension study which focuses on healthcare-associated bloodstream infections and ventilator-associated pneumonia. Our main aim is to implement an efficient clinically-oriented antimicrobial resistance surveillance system, which can be incorporated as part of routine workflow in hospitals in LMICs. These surveillance systems include hospitalised patients of any age with clinically compatible acute community-acquired or healthcare-associated bacterial infection syndromes, and who were prescribed parenteral antibiotics. Diagnostic stewardship activities will be implemented to optimise microbiology culture specimen collection practices. Basic patient characteristics, clinician diagnosis, empiric treatment, infection severity and risk factors for HAI are recorded on enrolment and during 28-day follow-up. An R Shiny application can be used offline and online for merging clinical and microbiology data, and generating collated reports to inform local antibiotic stewardship and infection control policies. Discussion: ACORN II is a comprehensive antimicrobial resistance surveillance activity which advocates pragmatic implementation and prioritises improving local diagnostic and antibiotic prescribing practices through patient-centred data collection. These data can be rapidly communicated to local physicians and infection prevention and control teams. Relative ease of data collection promotes sustainability and maximises participation and scalability. With ACORN-HAI as an example, ACORN II has the capacity to accommodate extensions to investigate further specific questions of interest

A new risk quantification approach in port facility security assessment

Abstract Terrorist attacks in the past decade had raised concern that terrorists capable of the suicide hijackings of airplanes could readily adapt such capabilities to maritime targets like ports. Although a large number of port security control measures have been proposed which have greatly enhanced security performance, the voice of requiring further justification on their effectiveness from various maritime stakeholders remains strong. Indeed, different ports around the world still have very diversified practices and standards regarding “secure” facilities, with a generally accepted assessment methodology found wanting. Despite the existence of previous research works, few have been done to address this issue, which clearly exposes a significant research gap. Understanding such deficiency, this paper introduces a novel fuzzy evidential reasoning approach to facilitate the quantitative analysis of port facility security assessment (PFSA). To achieve it, the major key security performance indicators (KSPIs) used by designated authorities in port facility security plan are identified; the current PFSA practices are reviewed with particular attention to the grades used by port operators when assessing the KSPIs; and a fuzzy evidential reasoning approach is applied to quantify port facility security risks and to conduct the cost benefit analysis of the associated security control measures

Incorporation of formal safety assessment and Bayesian network in navigational risk estimation of the Yangtze River

Abstract Formal safety assessment (FSA), as a structured and systematic risk evaluation methodology, has been increasingly and broadly used in the shipping industry around the world. Concerns have been raised as to navigational safety of the Yangtze River, China\u27s largest and the world\u27s busiest inland waterway. Over the last few decades, the throughput of ships in the Yangtze River has increased rapidly due to the national development of the Middle and Western parts of China. Accidents such as collisions, groundings, contacts, oil-spills and fires occur repeatedly, often causing serious consequences. In order to improve the navigational safety in the Yangtze River, this paper estimates the navigational risk of the Yangtze River using the FSA concept and a Bayesian network (BN) technique. The navigational risk model is established by considering both probability and consequences of accidents with respect to a risk matrix method, followed by a scenario analysis to demonstrate the application of the proposed model

Selection of techniques for reducing shipping NOx and SOx emissions

This paper develops a subjective generic methodology for providing ship owners with a transparent evaluation tool for selecting their preferred NOx and SOx control techniques. We quantitatively analyse the merits of the control methods available in marine air pollution control practice using data collected from shipping companies, shipyards and maritime academies. We also prioritize the applicable control techniques with respect to operational shipping environments

Single-Cell Transcriptomics in Medulloblastoma Reveals Tumor-Initiating Progenitors and Oncogenic Cascades during Tumorigenesis and Relapse

Progenitor heterogeneity and identities underlying tumor initiation and relapse in medulloblastomas remain elusive. Utilizing single-cell transcriptomic analysis, we demonstrated a developmental hierarchy of progenitor pools in Sonic Hedgehog (SHH) medulloblastomas, and identified OLIG2-expressing glial progenitors as transit-amplifying cells at the tumorigenic onset. Although OLIG2+ progenitors become quiescent stem-like cells in full-blown tumors, they are highly enriched in therapy-resistant and recurrent medulloblastomas. Depletion of mitotic Olig2+ progenitors or Olig2 ablation impeded tumor initiation. Genomic profiling revealed that OLIG2 modulates chromatin landscapes and activates oncogenic networks including HIPPO-YAP/TAZ and AURORA-A/MYCN pathways. Co-targeting these oncogenic pathways induced tumor growth arrest. Together, our results indicate that glial lineage-associated OLIG2+ progenitors are tumor-initiating cells during medulloblastoma tumorigenesis and relapse, suggesting OLIG2-driven oncogenic networks as potential therapeutic targets