The Effect of Forest Management Options on Forest Resilience to Pathogens

Invasive pathogens threaten the ability of forests globally to produce a range of valuable ecosystem services over time. However, the ability to detect such pathogen invasions—and thus to produce appropriate and timely management responses—is relatively low. We argue that a promising approach is to plan and manage forests in a way that increases their resilience to invasive pathogens not yet present or ubiquitous in the forest. This paper is based on a systematic search and critical review of empirical evidence of the effect of a wide range of forest management options on the primary and secondary infection rates of forest pathogens, and on subsequent forest recovery. Our goals are to inform forest management decision making to increase forest resilience, and to identify the most important evidence gaps for future research. The management options for which there is the strongest evidence that they increase forest resilience to pathogens are: reduced forest connectivity, removal or treatment of inoculum sources such as cut stumps, reduced tree density, removal of diseased trees and increased tree species diversity. In all cases the effect of these options on infection dynamics differs greatly amongst tree and pathogen species and between forest environments. However, the lack of consistent effects of silvicultural systems or of thinning, pruning or coppicing treatments is notable. There is also a lack of evidence of how the effects of treatments are influenced by the scale at which they are applied, e.g., the mixture of tree species. An overall conclusion is that forest managers often need to trade-off increased resilience to tree pathogens against other benefits obtained from forests

What a difference a stochastic process makes: epidemiological-based real options models of optimal treatment of disease

The real options approach has been used within environmental economics to investigate the impact of uncertainty on the optimal timing of control measures to minimise the impacts of invasive species, including pests and diseases. Previous studies typically model the growth in infected area using geometric Brownian motion (GBM). The advantage of this simple approach is that it allows for closed form solutions. However, such a process does not capture the mechanisms underlying the spread of infection. In particular the GBM assumption does not respect the natural upper boundary of the system, which is determined by the maximum size of the host species, nor the deceleration in the rate of infection as this boundary is approached. We show how the stochastic process describing the growth in infected area can be derived from the characteristics of the spread of infection. If the model used does not appropriately capture uncertainty in infection dynamics, then the excessive delay before treatment implies that the full value of the option to treat is not realised. Indeed, when uncertainty is high or the disease is fast spreading, ignoring the mechanisms of infection spread can lead to control never being deployed. Thus the results presented here have important implications for the way in which the real options approach is applied to determine optimal timing of disease control given uncertainty in future disease progression

Value of the First Post-Transplant Biopsy for Predicting Long-Term Cardiac Allograft Vasculopathy (CAV) and Graft Failure in Heart Transplant Patients

BACKGROUND: Cardiac allograft vasculopathy (CAV) is the principal cause of long-term graft failure following heart transplantation. Early identification of patients at risk of CAV is essential to target invasive follow-up procedures more effectively and to establish appropriate therapies. We evaluated the prognostic value of the first heart biopsy (median: 9 days post-transplant) versus all biopsies obtained within the first three months for the prediction of CAV and graft failure due to CAV. METHODS AND FINDINGS: In a prospective cohort study, we developed multivariate regression models evaluating markers of atherothrombosis (fibrin, antithrombin and tissue plasminogen activator [tPA]) and endothelial activation (intercellular adhesion molecule-1) in serial biopsies obtained during the first three months post-transplantation from 172 patients (median follow-up = 6.3 years; min = 0.37 years, max = 16.3 years). Presence of fibrin was the dominant predictor in first-biopsy models (Odds Ratio [OR] for one- and 10-year graft failure due to CAV = 38.70, p = 0.002, 95% CI = 4.00-374.77; and 3.99, p = 0.005, 95% CI = 1.53-10.40) and loss of tPA was predominant in three-month models (OR for one- and 10-year graft failure due to CAV = 1.81, p = 0.025, 95% CI = 1.08-3.03; and 1.31, p = 0.001, 95% CI = 1.12-1.55). First-biopsy and three-month models had similar predictive and discriminative accuracy and were comparable in their capacities to correctly classify patient outcomes, with the exception of 10-year graft failure due to CAV in which the three-month model was more predictive. Both models had particularly high negative predictive values (e.g., First-biopsy vs. three-month models: 99% vs. 100% at 1-year and 96% vs. 95% at 10-years). CONCLUSIONS: Patients with absence of fibrin in the first biopsy and persistence of normal tPA in subsequent biopsies rarely develop CAV or graft failure during the next 10 years and potentially could be monitored less invasively. Presence of early risk markers in the transplanted heart may be secondary to ischemia/reperfusion injury, a potentially modifiable factor

Unveiling relationships between crime and property in England and Wales via density scale-adjusted metrics and network tools

Scale-adjusted metrics (SAMs) are a significant achievement of the urban scaling hypothesis. SAMs remove the inherent biases of per capita measures computed in the absence of isometric allometries. However, this approach is limited to urban areas, while a large portion of the world’s population still lives outside cities and rural areas dominate land use worldwide. Here, we extend the concept of SAMs to population density scale-adjusted metrics (DSAMs) to reveal relationships among different types of crime and property metrics. Our approach allows all human environments to be considered, avoids problems in the definition of urban areas, and accounts for the heterogeneity of population distributions within urban regions. By combining DSAMs, cross-correlation, and complex network analysis, we find that crime and property types have intricate and hierarchically organized relationships leading to some striking conclusions. Drugs and burglary had uncorrelated DSAMs and, to the extent property transaction values are indicators of affluence, twelve out of fourteen crime metrics showed no evidence of specifically targeting affluence. Burglary and robbery were the most connected in our network analysis and the modular structures suggest an alternative to "zero-tolerance" policies by unveiling the crime and/or property types most likely to affect each other

Potential effects of oilseed rape expressing oryzacystatin-1 (OC-1) and of purified insecticidal proteins on larvae of the solitary bee Osmia bicornis

Despite their importance as pollinators in crops and wild plants, solitary bees have not previously been included in non-target testing of insect-resistant transgenic crop plants. Larvae of many solitary bees feed almost exclusively on pollen and thus could be highly exposed to transgene products expressed in the pollen. The potential effects of pollen from oilseed rape expressing the cysteine protease inhibitor oryzacystatin-1 (OC-1) were investigated on larvae of the solitary bee Osmia bicornis (= O. rufa). Furthermore, recombinant OC-1 (rOC-1), the Bt toxin Cry1Ab and the snowdrop lectin Galanthus nivalis agglutinin (GNA) were evaluated for effects on the life history parameters of this important pollinator. Pollen provisions from transgenic OC-1 oilseed rape did not affect overall development. Similarly, high doses of rOC-1 and Cry1Ab as well as a low dose of GNA failed to cause any significant effects. However, a high dose of GNA (0.1%) in the larval diet resulted in significantly increased development time and reduced efficiency in conversion of pollen food into larval body weight. Our results suggest that OC-1 and Cry1Ab expressing transgenic crops would pose a negligible risk for O. bicornis larvae, whereas GNA expressing plants could cause detrimental effects, but only if bees were exposed to high levels of the protein. The described bioassay with bee brood is not only suitable for early tier non-target tests of transgenic plants, but also has broader applicability to other crop protection products

Efficiency of two-phase methods with focus on a planned population-based case-control study on air pollution and stroke

<p>Abstract</p> <p>Background</p> <p>We plan to conduct a case-control study to investigate whether exposure to nitrogen dioxide (NO₂) increases the risk of stroke. In case-control studies, selective participation can lead to bias and loss of efficiency. A two-phase design can reduce bias and improve efficiency by combining information on the non-participating subjects with information from the participating subjects. In our planned study, we will have access to individual disease status and data on NO₂exposure on group (area) level for a large population sample of Scania, southern Sweden. A smaller sub-sample will be selected to the second phase for individual-level assessment on exposure and covariables. In this paper, we simulate a case-control study based on our planned study. We develop a two-phase method for this study and compare the performance of our method with the performance of other two-phase methods.</p> <p>Methods</p> <p>A two-phase case-control study was simulated with a varying number of first- and second-phase subjects. Estimation methods: <it>Method 1</it>: Effect estimation with second-phase data only. <it>Method 2</it>: Effect estimation by adjusting the first-phase estimate with the difference between the adjusted and unadjusted second-phase estimate. The first-phase estimate is based on individual disease status and residential address for all study subjects that are linked to register data on NO₂-exposure for each geographical area. <it>Method 3</it>: Effect estimation by using the expectation-maximization (EM) algorithm without taking area-level register data on exposure into account. <it>Method 4</it>: Effect estimation by using the EM algorithm and incorporating group-level register data on NO₂-exposure.</p> <p>Results</p> <p>The simulated scenarios were such that, unbiased or marginally biased (< 7%) odds ratio (OR) estimates were obtained with all methods. The efficiencies of method 4, are generally higher than those of methods 1 and 2. The standard errors in method 4 decreased further when the case/control ratio is above one in the second phase. For all methods, the standard errors do not become substantially reduced when the number of first-phase controls is increased.</p> <p>Conclusion</p> <p>In the setting described here, method 4 had the best performance in order to improve efficiency, while adjusting for varying participation rates across areas.</p

International Veterinary Epilepsy Task Force Consensus Proposal: Outcome of therapeutic interventions in canine and feline epilepsy

Common criteria for the diagnosis of drug resistance and the assessment of outcome are needed urgently as a prerequisite for standardized evaluation and reporting of individual therapeutic responses in canine epilepsy. Thus, we provide a proposal for the definition of drug resistance and partial therapeutic success in canine patients with epilepsy. This consensus statement also suggests a list of factors and aspects of outcome, which should be considered in addition to the impact on seizures. Moreover, these expert recommendations discuss criteria which determine the validity and informative value of a therapeutic trial in an individual patient and also suggest the application of individual outcome criteria. Agreement on common guidelines does not only render a basis for future optimization of individual patient management, but is also a presupposition for the design and implementation of clinical studies with highly standardized inclusion and exclusion criteria. Respective standardization will improve the comparability of findings from different studies and renders an improved basis for multicenter studies. Therefore, this proposal provides an in-depth discussion of the implications of outcome criteria for clinical studies. In particular ethical aspects and the different options for study design and application of individual patient-centered outcome criteria are considered

Breathing adapted radiotherapy: a 4D gating software for lung cancer

<p>Abstract</p> <p>Purpose</p> <p>Physiological respiratory motion of tumors growing in the lung can be corrected with respiratory gating when treated with radiotherapy (RT). The optimal respiratory phase for beam-on may be assessed with a respiratory phase optimizer (RPO), a 4D image processing software developed with this purpose.</p> <p>Methods and Materials</p> <p>Fourteen patients with lung cancer were included in the study. Every patient underwent a 4D-CT providing ten datasets of ten phases of the respiratory cycle (0-100% of the cycle). We defined two morphological parameters for comparison of 4D-CT images in different respiratory phases: tumor-volume to lung-volume ratio and tumor-to-spinal cord distance. The RPO automatized the calculations (200 per patient) of these parameters for each phase of the respiratory cycle allowing to determine the optimal interval for RT.</p> <p>Results</p> <p>Lower lobe lung tumors not attached to the diaphragm presented with the largest motion with breathing. Maximum inspiration was considered the optimal phase for treatment in 4 patients (28.6%). In 7 patients (50%), however, the RPO showed a most favorable volumetric and spatial configuration in phases other than maximum inspiration. In 2 cases (14.4%) the RPO showed no benefit from gating. This tool was not conclusive in only one case.</p> <p>Conclusions</p> <p>The RPO software presented in this study can help to determine the optimal respiratory phase for gated RT based on a few simple morphological parameters. Easy to apply in daily routine, it may be a useful tool for selecting patients who might benefit from breathing adapted RT.</p

Electron Transfer from Cyt b559 and Tyrosine-D to the S2 and S3 states of the water oxidizing complex in Photosystem II at Cryogenic Temperatures

The Mn4CaO5 cluster of photosystem II (PSII) catalyzes the oxidation of water to molecular oxygen through the light-driven redox S-cycle. The water oxidizing complex (WOC) forms a triad with Tyrosine(Z) and P-680, which mediates electrons from water towards the acceptor side of PSII. Under certain conditions two other redox-active components, Tyrosine(D) (Y-D) and Cytochrome b (559) (Cyt b (559)) can also interact with the S-states. In the present work we investigate the electron transfer from Cyt b (559) and Y-D to the S-2 and S-3 states at 195 K. First, Y-D (aEuro cent) and Cyt b (559) were chemically reduced. The S-2 and S-3 states were then achieved by application of one or two laser flashes, respectively, on samples stabilized in the S-1 state. EPR signals of the WOC (the S-2-state multiline signal, ML-S-2), Y-D (aEuro cent) and oxidized Cyt b (559) were simultaneously detected during a prolonged dark incubation at 195 K. During 163 days of incubation a large fraction of the S-2 population decayed to S-1 in the S-2 samples by following a single exponential decay. Differently, S-3 samples showed an initial increase in the ML-S-2 intensity (due to S-3 to S-2 conversion) and a subsequent slow decay due to S-2 to S-1 conversion. In both cases, only a minor oxidation of Y-D was observed. In contrast, the signal intensity of the oxidized Cyt b (559) showed a two-fold increase in both the S-2 and S-3 samples. The electron donation from Cyt b (559) was much more efficient to the S-2 state than to the S-3 state