Alien Registration- Shea, William P. (Houlton, Aroostook County)

https://digitalmaine.com/alien_docs/34899/thumbnail.jp

Active Adaptive Management in Insect Pest and Weed Control: Intervention with a Plan for Learning

A major problem in insect pest and weed management is uncertainty. Managers are faced with three main types of uncertainty: uncertainty about biological and environmental processes, and observational uncertainty. Active adaptive management (AAM) is management with a deliberate plan for learning about the managed system, so that management can be improved in the face of uncertainty. We discuss the potential benefits of applying AAM to insect pest and weed control with reference to a number of examples. We first address the possible uses for AAM in biological control, with particular reference to agent selection and release. We also propose applying AAM methods to resistance management and to spatial strategies for pest control. We conclude with an overview of AAM, a discussion of some of the potential limitations to its use in pest management, and the possibilities for increased implementation of AAM in the future

Child relationships in the middle grades

Thesis (Ed.M.)--Boston Universit

Comparative Genomics of Recent Shiga Toxin-Producing Escherichia coli O104:H4: Short-Term Evolution of an Emerging Pathogen

The large outbreak of diarrhea and hemolytic uremic syndrome (HUS) caused by Shiga toxin-producing Escherichia coli O104:H4 in Europe from May to July 2011 highlighted the potential of a rarely identified E. coli serogroup to cause severe disease. Prior to the outbreak, there were very few reports of disease caused by this pathogen and thus little known of its diversity and evolution. The identification of cases of HUS caused by E. coli O104:H4 in France and Turkey after the outbreak and with no clear epidemiological links raises questions about whether these sporadic cases are derived from the outbreak. Here, we report genome sequences of five independent isolates from these cases and results of a comparative analysis with historical and 2011 outbreak isolates. These analyses revealed that the five isolates are not derived from the outbreak strain; however, they are more closely related to the outbreak strain and each other than to isolates identified prior to the 2011 outbreak. Over the short time scale represented by these closely related organisms, the majority of genome variation is found within their mobile genetic elements: none of the nine O104:H4 isolates compared here contain the same set of plasmids, and their prophages and genomic islands also differ. Moreover, the presence of closely related HUS-associated E. coli O104:H4 isolates supports the contention that fully virulent O104:H4 isolates are widespread and emphasizes the possibility of future food-borne E. coli O104:H4 outbreaks

Post-Traumatic Epilepsy Associations with Mental Health Outcomes in the First Two Years after Moderate to Severe TBI: A TBI Model Systems Analysis

Purpose Research suggests that there are reciprocal relationships between mental health (MH) disorders and epilepsy risk. However, MH relationships to post-traumatic epilepsy (PTE) have not been explored. Thus, the objective of this study was to assess associations between PTE and frequency of depression and/or anxiety in a cohort of individuals with moderate-to-severe TBI who received acute inpatient rehabilitation. Methods Multivariate regression models were developed using a recent (2010–2012) cohort (n = 867 unique participants) from the TBI Model Systems (TBIMS) National Database, a time frame during which self-reported seizures, depression [Patient Health Questionnaire (PHQ)-9], and anxiety [Generalized Anxiety Disorder (GAD-7)] follow-up measures were concurrently collected at year-1 and year-2 after injury. Results PTE did not significantly contribute to depression status in either the year-1 or year-2 cohort, nor did it contribute significantly to anxiety status in the year-1 cohort, after controlling for other known depression and anxiety predictors. However, those with PTE in year-2 had 3.34 times the odds (p = .002) of having clinically significant anxiety, even after accounting for other relevant predictors. In this model, participants who self-identified as Black were also more likely to report clinical symptoms of anxiety than those who identified as White. PTE was the only significant predictor of comorbid depression and anxiety at year-2 (Odds Ratio 2.71; p = 0.049). Conclusions Our data suggest that PTE is associated with MH outcomes 2 years after TBI, findings whose significance may reflect reciprocal, biological, psychological, and/or experiential factors contributing to and resulting from both PTE and MH status post-TBI. Future work should consider temporal and reciprocal relationships between PTE and MH as well as if/how treatment of each condition influences biosusceptibility to the other condition

Anticipating future learning affects current control decisions : a comparison between passive and active adaptive management in an epidemiological setting

Infectious disease epidemics present a difficult task for policymakers, requiring the implementation of control strategies under significant time constraints and uncertainty. Mathematical models can be used to predict the outcome of control interventions, providing useful information to policymakers in the event of such an epidemic. However, these models suffer in the early stages of an outbreak from a lack of accurate, relevant information regarding the dynamics and spread of the disease and the efficacy of control. As such, recommendations provided by these models are often incorporated in an ad hoc fashion, as and when more reliable information becomes available. In this work, we show that such trial-and-error-type approaches to management, which do not formally take into account the resolution of uncertainty and how control actions affect this, can lead to sub-optimal management outcomes. We compare three approaches to managing a theoretical epidemic: a non-adaptive management (AM) approach that does not use real-time outbreak information to adapt control, a passive AM approach that incorporates real-time information if and when it becomes available, and an active AM approach that explicitly incorporates the future resolution of uncertainty through gathering real-time information into its initial recommendations. The structured framework of active AM encourages the specification of quantifiable objectives, models of system behaviour and possible control and monitoring actions, followed by an iterative learning and control phase that is able to employ complex control optimisations and resolve system uncertainty. The result is a management framework that is able to provide dynamic, long-term projections to help policymakers meet the objectives of management. We investigate in detail the effect of different methods of incorporating up-to-date outbreak information. We find that, even in a highly simplified system, the method of incorporating new data can lead to different results that may influence initial policy decisions, with an active AM approach to management providing better information that can lead to more desirable outcomes from an epidemic

Incidence and risk factors of posttraumatic seizures following traumatic brain injury: A Traumatic Brain Injury Model Systems Study

Objective Determine incidence of posttraumatic seizure (PTS) following traumatic brain injury (TBI) among individuals with moderate-to-severe TBI requiring rehabilitation and surviving at least 5 years. Methods Using the prospective TBI Model Systems National Database, we calculated PTS incidence during acute hospitalization, and at years 1, 2, and 5 postinjury in a continuously followed cohort enrolled from 1989 to 2000 (n = 795). Incidence rates were stratified by risk factors, and adjusted relative risk (RR) was calculated. Late PTS associations with immediate (7 day) versus no seizure prior to discharge from acute hospitalization was also examined. Results PTS incidence during acute hospitalization was highest immediately (<24 h) post-TBI (8.9%). New onset PTS incidence was greatest between discharge from inpatient rehabilitation and year 1 (9.2%). Late PTS cumulative incidence from injury to year 1 was 11.9%, and reached 20.5% by year 5. Immediate/early PTS RR (2.04) was increased for those undergoing surgical evacuation procedures. Late PTS RR was significantly greater for individuals who self-identified as a race other than black/white (year 1 RR = 2.22), and for black individuals (year 5 RR = 3.02) versus white individuals. Late PTS was greater for individuals with subarachnoid hemorrhage (year 1 RR = 2.06) and individuals age 23–32 (year 5 RR = 2.43) and 33–44 (year 5 RR = 3.02). Late PTS RR years 1 and 5 was significantly higher for those undergoing surgical evacuation procedures (RR: 3.05 and 2.72, respectively). Significance In this prospective, longitudinal, observational study, PTS incidence was similar to that in studies published previously. Individuals with immediate/late seizures during acute hospitalization have increased late PTS risk. Race, intracranial pathologies, and neurosurgical procedures also influenced PTS RR. Further studies are needed to examine the impact of seizure prophylaxis in high-risk subgroups and to delineate contributors to race/age associations on long-term seizure outcomes

Prognostic models for predicting posttraumatic seizures during acute hospitalization, and at 1 and 2 years following traumatic brain injury

Objective Posttraumatic seizures (PTS) are well-recognized acute and chronic complications of traumatic brain injury (TBI). Risk factors have been identified, but considerable variability in who develops PTS remains. Existing PTS prognostic models are not widely adopted for clinical use and do not reflect current trends in injury, diagnosis, or care. We aimed to develop and internally validate preliminary prognostic regression models to predict PTS during acute care hospitalization, and at year 1 and year 2 postinjury. Methods Prognostic models predicting PTS during acute care hospitalization and year 1 and year 2 post-injury were developed using a recent (2011–2014) cohort from the TBI Model Systems National Database. Potential PTS predictors were selected based on previous literature and biologic plausibility. Bivariable logistic regression identified variables with a p-value < 0.20 that were used to fit initial prognostic models. Multivariable logistic regression modeling with backward-stepwise elimination was used to determine reduced prognostic models and to internally validate using 1,000 bootstrap samples. Fit statistics were calculated, correcting for overfitting (optimism). Results The prognostic models identified sex, craniotomy, contusion load, and pre-injury limitation in learning/remembering/concentrating as significant PTS predictors during acute hospitalization. Significant predictors of PTS at year 1 were subdural hematoma (SDH), contusion load, craniotomy, craniectomy, seizure during acute hospitalization, duration of posttraumatic amnesia, preinjury mental health treatment/psychiatric hospitalization, and preinjury incarceration. Year 2 significant predictors were similar to those of year 1: SDH, intraparenchymal fragment, craniotomy, craniectomy, seizure during acute hospitalization, and preinjury incarceration. Corrected concordance (C) statistics were 0.599, 0.747, and 0.716 for acute hospitalization, year 1, and year 2 models, respectively. Significance The prognostic model for PTS during acute hospitalization did not discriminate well. Year 1 and year 2 models showed fair to good predictive validity for PTS. Cranial surgery, although medically necessary, requires ongoing research regarding potential benefits of increased monitoring for signs of epileptogenesis, PTS prophylaxis, and/or rehabilitation/social support. Future studies should externally validate models and determine clinical utility

Abundance, rarity and invasion debt among exotic species in a patchy ecosystem

Community assembly through species invasions is a long-term process, for which vital information regarding future trends can be contained in current patterns. Using comparative analyses of native and exotic plant assemblages from meadow patches on islands in British Columbia, Canada, we examined multiple lines of evidence for ‘invasion debt’, a latent expansion of exotic species populations. We show that: (1) short-dispersing species are underrepresented compared to their long-dispersing counterparts in exotic species only; (2) among species that are invasive elsewhere in North America, a greater proportion of long dispersers are common in the study area and a greater proportion of short dispersers are rare; and (3) time since arrival in the study region is positively related to number of occurrences in exotic species. In addition, we show that a suite of exotic species possesses the facility of rapid long-distance dispersal and ability to establish viable populations on even the most isolated and least disturbed patches. While some highly-dispersive exotic species can rapidly colonize new areas, short dispersers appear to exhibit invasion debt, with their potential distributions only being realized in the long term. Removing or even reducing populations of many rapid colonizers could be extremely difficult; however, for species exhibiting patterns most consistent with invasion debt, an opportunity exists for monitoring and removal to help reduce potential competition with native species