scholarly journals Early Detection of Airborne Inoculum of Nothopassalora personata in Spore Trap Samples from Peanut Fields Using Quantitative PCR

Plants ◽  
2020 ◽  
Vol 9 (10) ◽  
pp. 1327
Author(s):  
Misbakhul Munir ◽  
Hehe Wang ◽  
Nicholas S. Dufault ◽  
Daniel J. Anco
Keyword(s):  
Quantitative Pcr ◽  
Integrated Management ◽  
Environmental Parameters ◽  
Decision Support Tool ◽  
Qpcr Assay ◽  
Symptom Development ◽  
Spore Trap ◽  
Support Tool ◽  
Airborne Inoculum ◽  
History Of

A quantitative PCR (qPCR)-assay was developed to detect airborne inoculum of Nothopassalora personata, causal agent of late leaf spot (LLS) on peanut, collected with a modified impaction spore trap. The qPCR assay was able to consistently detect as few as 10 spores with purified DNA and 25 spores based on crude DNA extraction from rods. In 2019, two spore traps were placed in two peanut fields with a history of LLS. Sampling units were replaced every 2 to 4 days and tested with the developed qPCR assay, while plots were monitored for symptom development. The system detected inoculum 35 to 56 days before visual symptoms developed in the field, with detection related to environmental parameters affecting pathogen life-cycle and disease development. This study develops the framework of the qPCR spore trap system and represents the initial steps towards validation of the performance of the system for use as a decision support tool to complement integrated management of LLS.

scholarly journals Early Detection of Airborne Inoculum of Magnaporthe oryzae in Turfgrass Fields Using a Quantitative LAMP Assay

Plant Disease ◽  
2017 ◽  
Vol 101 (1) ◽  
pp. 170-177 ◽  
Author(s):  
Caterina Villari ◽  
Walter F. Mahaffee ◽  
Thomas K. Mitchell ◽  
Kerry F. Pedley ◽  
Michael L. Pieck ◽  
...  
Keyword(s):  
Perennial Ryegrass ◽  
Magnaporthe Oryzae ◽  
Management Practices ◽  
Lamp Assay ◽  
Decision Support Tool ◽  
Gray Leaf Spot ◽  
Spore Trap ◽  
Support Tool ◽  
Airborne Inoculum ◽  
Trap System

Gray leaf spot (GLS) is a destructive disease of perennial ryegrass caused by a host specific pathotype of the ascomycete Magnaporthe oryzae. Early diagnosis is crucial for effective disease management and the implementation of Integrated Pest Management practices. However, a rapid protocol for the detection of low levels of airborne inoculum is still missing. We developed a pathogen-specific quantitative loop-mediated isothermal amplification (qLAMP) assay coupled with a spore trap system for rapid detection and quantification of airborne inoculum of the M. oryzae perennial ryegrass pathotype, and tested its suitability for implementation in GLS-infected turfgrass fields. In summer 2015, two perennial ryegrass plots were artificially inoculated with the pathogen, with four continuously running custom impaction spore traps placed in each plot. Sampling units were replaced daily and tested with the developed qLAMP assay, while plots were monitored for symptom development. Results confirmed that the qLAMP assay-trap system was able to detect as few as 10 conidia up to 12 days before symptoms developed in the field. LAMP technology is particularly appropriate for field implementation by nontechnical users, and has the potential to be a powerful decision support tool to guide timing of fungicide applications for GLS management.

scholarly journals PACK Child: the development of a practical guide to extend the scope of integrated primary care for children and young adolescents

2018 ◽  
Vol 3 (Suppl 5) ◽  
pp. e000957 ◽  
Author(s):  
Sandy Picken ◽  
Juliet Hannington ◽  
Lara Fairall ◽  
Tanya Doherty ◽  
Eric Bateman ◽  
...  
Keyword(s):  
Primary Care ◽  
Quality Of Care ◽  
Low Income ◽  
Integrated Management ◽  
Decision Support Tool ◽  
Clinical Decision ◽  
Childhood Mortality ◽  
Middle Income ◽  
Support Tool

Pioneering strategies like WHO’s Integrated Management of Childhood Illness (IMCI) have resulted in substantial progress in addressing infant and child mortality. However, large inequalities exist in access to and the quality of care provided in different regions of the world. In many low-income and middle-income countries, childhood mortality remains a major concern, and the needs of children present a large burden upon primary care services. The capacity of services and quality of care offered require greater support to address these needs and extend integrated curative and preventive care, specifically, for the well child, the child with a long-term health need and the child older than 5 years, not currently included in IMCI. In response to these needs, we have developed an innovative method, based on experience with a similar approach in adults, that expands the scope and reach of integrated management and training programmes for paediatric primary care. This paper describes the development and key features of the PACK Child clinical decision support tool for the care of children up to 13 years, and lessons learnt during its development.

scholarly journals The agent-based modelling as a decision support tool for brownfield redevelopment

2020 ◽  
Vol 18 (1) ◽  
pp. 65-75
Author(s):  
Tanja Mitrovic ◽  
Milica Vracaric
Keyword(s):  
Decision Support ◽  
Decision Support Tool ◽  
Sustainable Urban Development ◽  
Brownfield Redevelopment ◽  
Support Tool ◽  
Agent Based ◽  
Agent Based Modelling ◽  
History Of ◽  
Development Plans

In recent history of urban studies there is a focus on sustainable urban development and long-term strategies. Dealing with brownfield redevelopment is of vital importance for the prosperous practice of urban planning. The current decisionmaking methods for brownfield redevelopment are mainly used for evaluating on-site situation, but not for future development plans. The purpose of this paper is to consider potential uses of agent-based modelling (ABM) in brownfield redevelopment decision support practice. In these models, agents are assigned with certain rules of behaviour that define their mutual interactions and allow simulations in a previously defined spatial framework. These collective behaviours influence the spatial patterns through interactions of individuals, which is reflected in the fact that the actions of the agents do not simply sum to the activity of the whole. This tool provides us with opportunity of observing possible scenarios of future brownfield development and making adequate decisions and strategies accordingly.

scholarly journals Role of Knowledge Networks and Boundary Organizations in Coproduction: A Short History of a Decision-Support Tool and Model for Adapting Multiuse Reservoir and Water-Energy Governance to Climate Change in California

2019 ◽  
Vol 11 (4) ◽  
pp. 823-849
Author(s):  
S. Ziaja
Keyword(s):  
Decision Support ◽  
Climate Adaptation ◽  
Decision Support Tool ◽  
Knowledge Networks ◽  
Positive Case ◽  
Theoretical Frameworks ◽  
Support Tool ◽  
Boundary Organizations ◽  
History Of ◽  
Collaborative Engagement

Abstract Climate adaptation relies on theoretical frameworks of coproduced science and knowledge networks to produce acceptable outcomes for politically contentious resources. As adaptation moves from theory to implementation, there is a need for positive case studies to use as benchmarks. Building from literature on actionable science this paper presents one such positive case—the development of a hydropower and reservoir decision-support tool. The focus of this history is on the multiple phases of interaction (and noninteraction) between researchers and a semidefined community of stakeholders. The lessons presented from the Integrated Forecast and Reservoir Management (INFORM) system project stress that collaborations between managers and researchers were crucial to the success of the project by building knowledge networks, which could outlast formal processes, and by incorporating policy preferences of end users into the model. The history also provides examples of how even successful collaborative projects do not always follow the usual expectations for coproduced science and shows that, even when those guidelines are followed, external circumstances can threaten the adoption of research products. Ultimately, this paper argues for the importance of building strong knowledge networks alongside more formal processes—like those in boundary organizations—for effective collaborative engagement.

scholarly journals Towards Improving the Identification of Anterior Cruciate Ligament Tears in Primary Point-of-Care Settings

2020 ◽  
Author(s):  
Jackie L Whittaker ◽  
Michelle Chan ◽  
Bo Pan ◽  
Imran Hassan ◽  
Terry Defreitas ◽  
...  
Keyword(s):  
Point Of Care ◽  
Cruciate Ligament ◽  
Decision Support Tool ◽  
Clinical Decision ◽  
Support Tool ◽  
Acl Tear ◽  
Patient Reported ◽  
History Of ◽  
Clinical Decision Support Tool ◽  
Anterior Cruciate

Abstract Background: Only a small proportion of anterior cruciate ligament (ACL) tears are diagnosed on initial healthcare consultation. Current clinical guidelines do not acknowledge that primary point-of-care practitioners rely more heavily on a clinical history than special clinical tests for diagnosis of an ACL tear. This research will assess the accuracy of combinations of patient-reported variables alone, and in combination with clinician-generated variables to identify an ACL tear as a preliminary step to designing a primary point-of-care clinical decision support tool.Methods: Electronic medical records (EMRs) of individuals aged 15-45 years, with ICD-9 codes corresponding to a knee condition, and confirmed (ACL+) or denied (ACL-) first-time ACL tear seen at a University-based Clinic between 2014 and 2016 were eligible for inclusion. Demographics, relevant diagnostic indicators and ACL status based on orthopaedic surgeon assessment and/or MRI reports were manually extracted. Descriptive statistics calculated for all variables by ACL status. Univariate between group comparisons, clinician surveys (n=17), availability of data and univariable logistic regression (95%CI) were used to select variables for inclusion into multivariable logistic regression models that assessed the odds (95%CI) of an ACL-tear based on patient-reported variables alone (consistent with primary point-of-care practice), or in combination with clinician-generated variables. Model performance was assessed by accuracy, sensitivity, specificity, positive and negative predictive values, and positive and negative likelihood ratios (95%CI).Results: Of 1,512 potentially relevant EMRs, 725 were included. Participant median age was 26 years (range 15-45), 48% were female and 60% had an ACL tear. A combination of patient-reported (age, sport-related injury, immediate swelling, family history of ACL tear) and clinician-generated variables (Lachman test result) were superior for ACL tear diagnosis [accuracy; 0.95 (90,98), sensitivity; 0.97 (0.88,0.98), specificity; 0.95 (0.82,0.99)] compared to the patient-reported variables alone [accuracy; 84% (77,89), sensitivity; 0.60 (0.44,0.74), specificity; 0.95 (0.89,0.98)].Conclusions: A high proportion of individuals without an ACL tear can be accurately identified by considering patient-reported age, injury setting, immediate swelling and family history of ACL tear. These findings directly inform the development of a clinical decision support tool to facilitate timely and accurate ACL tear diagnosis in primary care settings.

scholarly journals Towards Improving the Identification of Anterior Cruciate Ligament Tears in Primary Point-of-Care Settings

2019 ◽  
Author(s):  
Jackie L Whittaker ◽  
Michelle Chan ◽  
Bo Pan ◽  
Imran Hassan ◽  
Terry Defreitas ◽  
...  
Keyword(s):  
Point Of Care ◽  
Cruciate Ligament ◽  
Decision Support Tool ◽  
Clinical Decision ◽  
Support Tool ◽  
Acl Tear ◽  
Patient Reported ◽  
History Of ◽  
Clinical Decision Support Tool ◽  
Anterior Cruciate

Abstract BackgroundOnly a small proportion of anterior cruciate ligament (ACL) tears are diagnosed on initial healthcare consultation. Current clinical guidelines do not acknowledge that primary point-of-care practitioners rely more heavily on a clinical history than special clinical tests for diagnosis of an ACL tear. This research will assess the accuracy of combinations of patient-reported variables alone, and in combination with clinician-generated variables to identify an ACL tear as a preliminary step to designing a primary point-of-care care clinical decision support tool.MethodsElectronic medical records (EMRs) of individuals aged 15-45 years, with ICD-9 codes corresponding to a knee condition, and confirmed (ACL+) or denied (ACL-) first-time ACL tear seen at a University-based Clinic between 2014 and 2016 were eligible for inclusion. Demographics, relevant diagnostic indicators and ACL status based on orthopaedic surgeon assessment and/or MRI reports were manually extracted. Descriptive statistics calculated for all variables by ACL status. Univariate between group comparisons, clinician surveys (n=17), availability of data and univariable logistic regression (95%CI) were used to select variables for inclusion into multivariable logistic regression models that assessed the odds (95%CI) of an ACL-tear based on patient-reported variables alone (consistent with primary point-of-care practice), or in combination with clinician-generated variables. Model performance was assessed by accuracy, sensitivity, specificity, positive and negative predictive values, and positive and negative likelihood ratios (95%CI).ResultsOf 1,512 potentially relevant EMRs, 725 were included. Participant median age was 26 years (range 15-45), 48% were female and 60% had an ACL tear. A combination of patient-reported (age, sport-related injury, immediate swelling, family history of ACL tear) and clinician-generated variables (Lachman test result) were superior for ACL tear diagnosis [accuracy; 95%CI (90,98), sensitivity; 0.97 (0.88,0.98), specificity; 0.95 (0.82,0.99)] compared to the patient-reported variables alone [accuracy; 84% (77,89), sensitivity; 0.60 (0.44,0.74), specificity; 0.95 (0.89,0.98)].ConclusionsA high proportion of individuals without an ACL tear can be accurately identified by considering patient-reported age, injury setting, immediate swelling and family history of ACL tear. These findings directly inform the development of a clinical decision support tool to facilitate timely and accurate ACL tear diagnosis in primary care settings.

scholarly journals Towards Improving the Identification of Anterior Cruciate Ligament Tears in Primary Point-of-Care Settings

2020 ◽  
Author(s):  
Jackie L Whittaker ◽  
Michelle Chan ◽  
Bo Pan ◽  
Imran Hassan ◽  
Terry Defreitas ◽  
...  
Keyword(s):  
Point Of Care ◽  
Cruciate Ligament ◽  
Decision Support Tool ◽  
Clinical Decision ◽  
Support Tool ◽  
Acl Tear ◽  
Patient Reported ◽  
History Of ◽  
Clinical Decision Support Tool ◽  
Anterior Cruciate

Abstract Background: Only a small proportion of anterior cruciate ligament (ACL) tears are diagnosed on initial healthcare consultation. Current clinical guidelines do not acknowledge that primary point-of-care practitioners rely more heavily on a clinical history than special clinical tests for diagnosis of an ACL tear. This research will assess the accuracy of combinations of patient-reported variables alone, and in combination with clinician-generated variables to identify an ACL tear as a preliminary step to designing a primary point-of-care clinical decision support tool. Methods: Electronic medical records (EMRs) of individuals aged 15-45 years, with ICD-9 codes corresponding to a knee condition, and confirmed (ACL + ) or denied (ACL - ) first-time ACL tear seen at a University-based Clinic between 2014 and 2016 were eligible for inclusion. Demographics, relevant diagnostic indicators and ACL status based on orthopaedic surgeon assessment and/or MRI reports were manually extracted. Descriptive statistics calculated for all variables by ACL status. Univariate between group comparisons, clinician surveys (n=17), availability of data and univariable logistic regression (95%CI) were used to select variables for inclusion into multivariable logistic regression models that assessed the odds (95%CI) of an ACL-tear based on patient-reported variables alone (consistent with primary point-of-care practice), or in combination with clinician-generated variables. Model performance was assessed by accuracy, sensitivity, specificity, positive and negative predictive values, and positive and negative likelihood ratios (95%CI). Results: Of 1,512 potentially relevant EMRs, 725 were included. Participant median age was 26 years (range 15-45), 48% were female and 60% had an ACL tear. A combination of patient-reported (age, sport-related injury, immediate swelling, family history of ACL tear) and clinician-generated variables (Lachman test result) were superior for ACL tear diagnosis [accuracy; 0.95 (90,98), sensitivity; 0.97 (0.88,0.98), specificity; 0.95 (0.82,0.99)] compared to the patient-reported variables alone [accuracy; 84% (77,89), sensitivity; 0.60 (0.44,0.74), specificity; 0.95 (0.89,0.98)]. Conclusions: A high proportion of individuals without an ACL tear can be accurately identified by considering patient-reported age, injury setting, immediate swelling and family history of ACL tear. These findings directly inform the development of a clinical decision support tool to facilitate timely and accurate ACL tear diagnosis in primary care settings.

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