Novel Genome-Editing Tools to Model and Correct Primary Immunodeficiencies.

Severe combined immunodeficiency (SCID) and other severe non-SCID primary immunodeficiencies (non-SCID PID) can be treated by allogeneic hematopoietic stem cell (HSC) transplantation, but when histocompatibility leukocyte antigen-matched donors are lacking, this can be a high-risk procedure. Correcting the patient's own HSCs with gene therapy offers an attractive alternative. Gene therapies currently being used in clinical settings insert a functional copy of the entire gene by means of a viral vector. With this treatment, severe complications may result due to integration within oncogenes. A promising alternative is the use of endonucleases such as ZFNs, TALENs, and CRISPR/Cas9 to introduce a double-stranded break in the DNA and thus induce homology-directed repair. With these genome-editing tools a correct copy can be inserted in a precisely targeted "safe harbor." They can also be used to correct pathogenic mutations in situ and to develop cellular or animal models needed to study the pathogenic effects of specific genetic defects found in immunodeficient patients. This review discusses the advantages and disadvantages of these endonucleases in gene correction and modeling with an emphasis on CRISPR/Cas9, which offers the most promise due to its efficacy and versatility.

On evaluating the accuracy and biological plausibility of diffusion MRI tractograms

In diffusion MRI, traditional tractography algorithms do not recover truly quantitative tractograms and the structural connectivity has to be estimated indirectly by counting the number of fiber tracts or averaging scalar maps along them. Recently, global and efficient methods have emerged to estimate more quantitative tractograms by combining tractography with local models for the diffusion signal, like the Convex Optimization Modeling for Microstructure Informed Tractography (COMMIT) framework. In this abstract, we show the importance of using both (i) proper multi-compartment diffusion models and (ii) adequate multi-shell acquisitions, in order to evaluate the accuracy and the biological plausibility of the tractograms.

Evaluation of drug-induced neurotoxicity based on metabolomics, proteomics and electrical activity measurements in complementary CNS in vitro models.

The present study was performed in an attempt to develop an in vitro integrated testing strategy (ITS) to evaluate drug-induced neurotoxicity. A number of endpoints were analyzed using two complementary brain cell culture models and an in vitro blood-brain barrier (BBB) model after single and repeated exposure treatments with selected drugs that covered the major biological, pharmacological and neuro-toxicological responses. Furthermore, four drugs (diazepam, cyclosporine A, chlorpromazine and amiodarone) were tested more in depth as representatives of different classes of neurotoxicants, inducing toxicity through different pathways of toxicity. The developed in vitro BBB model allowed detection of toxic effects at the level of BBB and evaluation of drug transport through the barrier for predicting free brain concentrations of the studied drugs. The measurement of neuronal electrical activity was found to be a sensitive tool to predict the neuroactivity and neurotoxicity of drugs after acute exposure. The histotypic 3D re-aggregating brain cell cultures, containing all brain cell types, were found to be well suited for OMICs analyses after both acute and long term treatment. The obtained data suggest that an in vitro ITS based on the information obtained from BBB studies and combined with metabolomics, proteomics and neuronal electrical activity measurements performed in stable in vitro neuronal cell culture systems, has high potential to improve current in vitro drug-induced neurotoxicity evaluation.

Functional and histopathological identification of the respiratory failure in a DMSXL transgenic mouse model of myotonic dystrophy.

Acute and chronic respiratory failure is one of the major and potentially life-threatening features in individuals with myotonic dystrophy type 1 (DM1). Despite several clinical demonstrations showing respiratory problems in DM1 patients, the mechanisms are still not completely understood. This study was designed to investigate whether the DMSXL transgenic mouse model for DM1 exhibits respiratory disorders and, if so, to identify the pathological changes underlying these respiratory problems. Using pressure plethysmography, we assessed the breathing function in control mice and DMSXL mice generated after large expansions of the CTG repeat in successive generations of DM1 transgenic mice. Statistical analysis of breathing function measurements revealed a significant decrease in the most relevant respiratory parameters in DMSXL mice, indicating impaired respiratory function. Histological and morphometric analysis showed pathological changes in diaphragmatic muscle of DMSXL mice, characterized by an increase in the percentage of type I muscle fibers, the presence of central nuclei, partial denervation of end-plates (EPs) and a significant reduction in their size, shape complexity and density of acetylcholine receptors, all of which reflect a possible breakdown in communication between the diaphragmatic muscles fibers and the nerve terminals. Diaphragm muscle abnormalities were accompanied by an accumulation of mutant DMPK RNA foci in muscle fiber nuclei. Moreover, in DMSXL mice, the unmyelinated phrenic afferents are significantly lower. Also in these mice, significant neuronopathy was not detected in either cervical phrenic motor neurons or brainstem respiratory neurons. Because EPs are involved in the transmission of action potentials and the unmyelinated phrenic afferents exert a modulating influence on the respiratory drive, the pathological alterations affecting these structures might underlie the respiratory impairment detected in DMSXL mice. Understanding mechanisms of respiratory deficiency should guide pharmaceutical and clinical research towards better therapy for the respiratory deficits associated with DM1.

Serum Leptin Concentration, Body Mass Index and Incident Heart Failure: The Health, Aging, and Body Composition Study

Background: Leptin is produced primarily by adipocytes. Although originally associated with the central regulation of satiety and energy metabolism, increasing evidence indicates that leptin may be an important factor for congestive heart faire (CHF). In the study, we aimed to test the hypothesis that leptin may influence CHF pathophysiology via a pathway of increasing body mass index (BMI). Methods: We studied 2,389 elderly participants aged 70 and older (M; 1161, F: 1228) without CHF and with serum leptin measures at the Health Aging, and Body Composition study. We analyzed the association between serum leptin level and risk of incident CHF using Cox hazard proportional regression models. Elevated leptin level was defined as more than the highest quartile (Q4) of leptin distribution in the total sample for each gender. Adjusted-covariates included demographic, behavior, lipid and inflammation variables (partially-adjusted models), and further included BMI (fully-adjusted models). Results: In a mean 9-year follow-up, 316 participants (13.2%) developed CHF. The partially-adjusted models indicated that men and women with elevated serum leptin levels (>=9.89 ng/ml in men and >=25 ng/ml in women) had significantly higher risks of developing CHF than those with leptin level of less than Q4. The adjusted hazard ratios (95%CI) for incident CHF was 1.49 (1.04 -2.13) in men and 1.71 (1.12 -2.58) in women. However, these associations became non-significant after adjustment for including BMI for each gender. The fully-adjusted hazard ratios (95%CI) were 1.43 (0.94 -2.18) in men and 1.24 (0.77-1.99) in women. Conclusion: Subjects with elevated leptin levels have a higher risk of CHF. The study supports the hypothesis that the influence of leptin level on risk of CHF may be through a pathway related to increasing BMI.

Gas6 and its receptors are implicated in sepsis as modulators of innate immunity

Gas6 downregulates the activation state of macrophages and thereby their production of proinflammatory cytokines induced by various stimuli. We aimed to determine whether Gas6 is involved in sepsis. We measured Gas6 plasma levels in 13 healthy subjects, 29 patients with severe sepsis, and 18 patients with non-infectious inflammatory diseases. Gas6 level was higher in septic patients than in control groups (P 0.0001). The sensitivity and specificity of Gas6 levels to predict fatal outcome were 83% and 88%. We next investigated whether Gas6 affects cytokine production and outcome in experimental models of endotoxemia and peritonitis in wild-type (WT) and Gas6-/- mice. Circulating levels of Gas6 after LPS 25mg/kg i.p. peaked at 1 hour (P<0.001). Similarly, TNF- was higher in Gas6-/- than in WT mice 1 hour after LPS (P<0.05). Furthermore, 62 anti- and pro-inflammatory cytokines were quantified in plasma after LPS injection. Their levels were globally higher in Gas6-/- plasma after LPS, 47/62 cytokines being at least 50% higher in Gas6-/- than in WT plasma after 1 hour. Mortality induced by 25mg/kg LPS was 25% in WT versus 87% in Gas6-/- mice (P<0.05). LPS-induced mortality in Gas6 receptors Axl-/-, Tyro3-/- and Merkd was also enhanced when compared to WT mice (P<0.001). In peritonitis models (cecal ligation and puncture, CLP, and i.p. injection of E. coli), Gas6 plasma levels increased and remained elevated at least 24 hours. CLP increased mortality in Gas6-/- mice. Finally, we explored the role of Gas6 in LPS-treated macrophages. We found that Gas6 was released by LPS-stimulated WT macrophages and that Gas6-/- macrophages produced more TNF- and IL-6 than WT macrophages. Cytokine release by Gas6-/- macrophages was higher than by WT macrophages (cytokine array). Adjunction of recombinant Gas6 to the culture medium of Gas6-/- macrophages diminished the cytokine production to WT levels. In LPS-treated Gas6-/- macrophages, Akt and Erk1/2 phosphorylation was reduced whereas p38 and NF B activation was enhanced. Thus, in septic patients, elevated Gas6 levels were associated with fatal outcome. In mice, they raised in experimental endotoxemia and peritonitis models, and correlated also with sepsis severity. However, Gas6-/- mice survival in these models was reduced compared to WT. Gas6 secreted by macrophages in response to LPS activated Akt and restrained p38 and NF B activation, thereby dampening macrophage activation. Altogether these data suggest that, during endotoxemia, Gas6-/- mice phenotype resembles that of mice which have undergone PI3K inhibition, indicating that Gas6 is a major modulator of innate immunity.

Development of mavoglurant and its potential for the treatment of fragile X syndrome.

Introduction: Fragile X syndrome (FXS) is the most common inherited cause of intellectual disability. With no curative treatment available, current therapeutic approaches are aimed at symptom management. FXS is caused by silencing the FMR1 gene, which encodes FMRP; as loss of FMRP leads to the development of symptoms associated with FXS. Areas covered: In this evaluation, the authors examine the role of the metabotropic glutamate receptor 5 (mGluR5) in the pathophysiology of FXS, and its suitability as a target for rescuing the disease state. Furthermore, the authors review the evidence from preclinical studies of pharmacological interventions targeting mGluR5 in FXS. Lastly, the authors assess the findings from clinical studies in FXS, in particular the use of the Aberrant Behavior Checklist-Community Edition (ABC-C) and the recently developed ABC-C for FXS scale, as clinical endpoints to assess disease modification in this patient population. Expert opinion: There is cautious optimism for the successful treatment of the core behavioral and cognitive symptoms of FXS based on preclinical data in animal models and early studies in humans. However, the association between mGluR5-heightened responsiveness and the clinical phenotype in humans remains to be demonstrated. Many questions regarding the optimal treatment and outcome measures of FXS remain unanswered.

Emotional intelligence: On definitions, neuroscience, and marshmallows

In his timely article, Cherniss offers his vision for the future of "Emotional Intelligence" (EI). However, his goal of clarifying the concept by distinguishing definitions from models and his support for "Emotional and Social Competence" (ESC) models will, in our opinion, not make the field advance. To be upfront, we agree that emotions are important for effective decision-making, leadership, performance and the like; however, at this time, EI and ESC have not yet demonstrated incremental validity over and above IQ and personality tests in meta-analyses (Harms & Credé, 2009; Van Rooy & Viswesvaran, 2004). If there is a future for EI, we see it in the ability model of Mayer, Salovey and associates (e.g, Mayer, Caruso, & Salovey, 2000), which detractors and supporters agree holds the most promise (Antonakis, Ashkanasy, & Dasborough, 2009; Zeidner, Roberts, & Matthews, 2008). With their use of quasi-objective scoring measures, the ability model grounds EI in existing frameworks of intelligence, thus differentiating itself from ESC models and their self-rated trait inventories. In fact, we do not see the value of ESC models: They overlap too much with current personality models to offer anything new for science and practice (Zeidner, et al., 2008). In this commentary we raise three concerns we have with Cherniss's suggestions for ESC models: (1) there are important conceptual problems in both the definition of ESC and the distinction of ESC from EI; (2) Cherniss's interpretation of neuroscience findings as supporting the constructs of EI and ESC is outdated, and (3) his interpretation of the famous marshmallow experiment as indicating the existence of ESCs is flawed. Building on the promise of ability models, we conclude by providing suggestions to improve research in EI.

A collaborative approach for incorporating forensic case data into crime investigation using criminal intelligence analysis and visualisation

There is an increasing awareness that the articulation of forensic science and criminal investigation is critical to the resolution of crimes. However, models and methods to support an effective collaboration between these partners are still poorly expressed or even lacking. Three propositions are borrowed from crime intelligence methods in order to bridge this gap: (a) the general intelligence process, (b) the analyses of investigative problems along principal perspectives: entities and their relationships, time and space, quantitative aspects and (c) visualisation methods as a mode of expression of a problem in these dimensions. Indeed, in a collaborative framework, different kinds of visualisations integrating forensic case data can play a central role for supporting decisions. Among them, link-charts are scrutinised for their abilities to structure and ease the analysis of a case by describing how relevant entities are connected. However, designing an informative chart that does not bias the reasoning process is not straightforward. Using visualisation as a catalyser for a collaborative approach integrating forensic data thus calls for better specifications.

Simulation-based systematic review of imatinib population pharmacokinetics and PK-PD relationships in chronic myeloid leukemia (CML) patients

Objectives: Several population pharmacokinetic (PPK) and pharmacokinetic-pharmacodynamic (PK-PD) analyses have been performed with the anticancer drug imatinib. Inspired by the approach of meta-analysis, we aimed to compare and combine results from published studies in a useful way - in particular for improving the clinical interpretation of imatinib concentration measurements in the scope of therapeutic drug monitoring (TDM). Methods: Original PPK analyses and PK-PD studies (PK surrogate: trough concentration Cmin; PD outcomes: optimal early response and specific adverse events) were searched systematically on MEDLINE. From each identified PPK model, a predicted concentration distribution under standard dosage was derived through 1000 simulations (NONMEM), after standardizing model parameters to common covariates. A "reference range" was calculated from pooled simulated concentrations in a semi-quantitative approach (without specific weighting) over the whole dosing interval. Meta-regression summarized relationships between Cmin and optimal/suboptimal early treatment response. Results: 9 PPK models and 6 relevant PK-PD reports in CML patients were identified. Model-based predicted median Cmin ranged from 555 to 1388 ng/ml (grand median: 870 ng/ml and inter-quartile range: 520-1390 ng/ml). The probability to achieve optimal early response was predicted to increase from 60 to 85% from 520 to 1390 ng/ml across PK-PD studies (odds ratio for doubling Cmin: 2.7). Reporting of specific adverse events was too heterogeneous to perform a regression analysis. The general frequency of anemia, rash and fluid retention increased however consistently with Cmin, but less than response probability. Conclusions: Predicted drug exposure may differ substantially between various PPK analyses. In this review, heterogeneity was mainly attributed to 2 "outlying" models. The established reference range seems to cover the range where both good efficacy and acceptable tolerance are expected for most patients. TDM guided dose adjustment appears therefore justified for imatinib in CML patients. Its usefulness remains now to be prospectively validated in a randomized trial.

Predicting smoking cessation and its relapse in HIV-infected patients: the Swiss HIV Cohort Study.

OBJECTIVES: The aim of the study was to assess whether prospective follow-up data within the Swiss HIV Cohort Study can be used to predict patients who stop smoking; or among smokers who stop, those who start smoking again. METHODS: We built prediction models first using clinical reasoning ('clinical models') and then by selecting from numerous candidate predictors using advanced statistical methods ('statistical models'). Our clinical models were based on literature that suggests that motivation drives smoking cessation, while dependence drives relapse in those attempting to stop. Our statistical models were based on automatic variable selection using additive logistic regression with component-wise gradient boosting. RESULTS: Of 4833 smokers, 26% stopped smoking, at least temporarily; because among those who stopped, 48% started smoking again. The predictive performance of our clinical and statistical models was modest. A basic clinical model for cessation, with patients classified into three motivational groups, was nearly as discriminatory as a constrained statistical model with just the most important predictors (the ratio of nonsmoking visits to total visits, alcohol or drug dependence, psychiatric comorbidities, recent hospitalization and age). A basic clinical model for relapse, based on the maximum number of cigarettes per day prior to stopping, was not as discriminatory as a constrained statistical model with just the ratio of nonsmoking visits to total visits. CONCLUSIONS: Predicting smoking cessation and relapse is difficult, so that simple models are nearly as discriminatory as complex ones. Patients with a history of attempting to stop and those known to have stopped recently are the best candidates for an intervention.

Stability analysis of the 2007 Chehalis lake landslide based on long-range terrestrial photogrammetry and airborne LIDAR data

On December 4th 2007, a 3-Mm3 landslide occurred along the northwestern shore of Chehalis Lake. The initiation zone is located at the intersection of the main valley slope and the northern sidewall of a prominent gully. The slope failure caused a displacement wave that ran up to 38 m on the opposite shore of the lake. The landslide is temporally associated with a rain-on-snow meteorological event which is thought to have triggered it. This paper describes the Chehalis Lake landslide and presents a comparison of discontinuity orientation datasets obtained using three techniques: field measurements, terrestrial photogrammetric 3D models and an airborne LiDAR digital elevation model to describe the orientation and characteristics of the five discontinuity sets present. The discontinuity orientation data are used to perform kinematic, surface wedge limit equilibrium and three-dimensional distinct element analyses. The kinematic and surface wedge analyses suggest that the location of the slope failure (intersection of the valley slope and a gully wall) has facilitated the development of the unstable rock mass which initiated as a planar sliding failure. Results from the three-dimensional distinct element analyses suggest that the presence, orientation and high persistence of a discontinuity set dipping obliquely to the slope were critical to the development of the landslide and led to a failure mechanism dominated by planar sliding. The three-dimensional distinct element modelling also suggests that the presence of a steeply dipping discontinuity set striking perpendicular to the slope and associated with a fault exerted a significant control on the volume and extent of the failed rock mass but not on the overall stability of the slope.

New developments and applications in modelling occupational exposure to airborne contaminants

Résumé: L'évaluation de l'exposition aux nuisances professionnelles représente une étape importante dans l'analyse de poste de travail. Les mesures directes sont rarement utilisées sur les lieux même du travail et l'exposition est souvent estimée sur base de jugements d'experts. Il y a donc un besoin important de développer des outils simples et transparents, qui puissent aider les spécialistes en hygiène industrielle dans leur prise de décision quant aux niveaux d'exposition. L'objectif de cette recherche est de développer et d'améliorer les outils de modélisation destinés à prévoir l'exposition. Dans un premier temps, une enquête a été entreprise en Suisse parmi les hygiénistes du travail afin d'identifier les besoins (types des résultats, de modèles et de paramètres observables potentiels). Il a été constaté que les modèles d'exposition ne sont guère employés dans la pratique en Suisse, l'exposition étant principalement estimée sur la base de l'expérience de l'expert. De plus, l'émissions de polluants ainsi que leur dispersion autour de la source ont été considérés comme des paramètres fondamentaux. Pour tester la flexibilité et la précision des modèles d'exposition classiques, des expériences de modélisations ont été effectuées dans des situations concrètes. En particulier, des modèles prédictifs ont été utilisés pour évaluer l'exposition professionnelle au monoxyde de carbone et la comparer aux niveaux d'exposition répertoriés dans la littérature pour des situations similaires. De même, l'exposition aux sprays imperméabilisants a été appréciée dans le contexte d'une étude épidémiologique sur une cohorte suisse. Dans ce cas, certains expériences ont été entreprises pour caractériser le taux de d'émission des sprays imperméabilisants. Ensuite un modèle classique à deux-zone a été employé pour évaluer la dispersion d'aérosol dans le champ proche et lointain pendant l'activité de sprayage. D'autres expériences ont également été effectuées pour acquérir une meilleure compréhension des processus d'émission et de dispersion d'un traceur, en se concentrant sur la caractérisation de l'exposition du champ proche. Un design expérimental a été développé pour effectuer des mesures simultanées dans plusieurs points d'une cabine d'exposition, par des instruments à lecture directe. Il a été constaté que d'un point de vue statistique, la théorie basée sur les compartiments est sensée, bien que l'attribution à un compartiment donné ne pourrait pas se faire sur la base des simples considérations géométriques. Dans une étape suivante, des données expérimentales ont été collectées sur la base des observations faites dans environ 100 lieux de travail différents: des informations sur les déterminants observés ont été associées aux mesures d'exposition des informations sur les déterminants observés ont été associé. Ces différentes données ont été employées pour améliorer le modèle d'exposition à deux zones. Un outil a donc été développé pour inclure des déterminants spécifiques dans le choix du compartiment, renforçant ainsi la fiabilité des prévisions. Toutes ces investigations ont servi à améliorer notre compréhension des outils des modélisations ainsi que leurs limitations. L'intégration de déterminants mieux adaptés aux besoins des experts devrait les inciter à employer cet outil dans leur pratique. D'ailleurs, en augmentant la qualité des outils des modélisations, cette recherche permettra non seulement d'encourager leur utilisation systématique, mais elle pourra également améliorer l'évaluation de l'exposition basée sur les jugements d'experts et, par conséquent, la protection de la santé des travailleurs. Abstract Occupational exposure assessment is an important stage in the management of chemical exposures. Few direct measurements are carried out in workplaces, and exposures are often estimated based on expert judgements. There is therefore a major requirement for simple transparent tools to help occupational health specialists to define exposure levels. The aim of the present research is to develop and improve modelling tools in order to predict exposure levels. In a first step a survey was made among professionals to define their expectations about modelling tools (what types of results, models and potential observable parameters). It was found that models are rarely used in Switzerland and that exposures are mainly estimated from past experiences of the expert. Moreover chemical emissions and their dispersion near the source have also been considered as key parameters. Experimental and modelling studies were also performed in some specific cases in order to test the flexibility and drawbacks of existing tools. In particular, models were applied to assess professional exposure to CO for different situations and compared with the exposure levels found in the literature for similar situations. Further, exposure to waterproofing sprays was studied as part of an epidemiological study on a Swiss cohort. In this case, some laboratory investigation have been undertaken to characterize the waterproofing overspray emission rate. A classical two-zone model was used to assess the aerosol dispersion in the near and far field during spraying. Experiments were also carried out to better understand the processes of emission and dispersion for tracer compounds, focusing on the characterization of near field exposure. An experimental set-up has been developed to perform simultaneous measurements through direct reading instruments in several points. It was mainly found that from a statistical point of view, the compartmental theory makes sense but the attribution to a given compartment could ñó~be done by simple geometric consideration. In a further step the experimental data were completed by observations made in about 100 different workplaces, including exposure measurements and observation of predefined determinants. The various data obtained have been used to improve an existing twocompartment exposure model. A tool was developed to include specific determinants in the choice of the compartment, thus largely improving the reliability of the predictions. All these investigations helped improving our understanding of modelling tools and identify their limitations. The integration of more accessible determinants, which are in accordance with experts needs, may indeed enhance model application for field practice. Moreover, while increasing the quality of modelling tool, this research will not only encourage their systematic use, but might also improve the conditions in which the expert judgments take place, and therefore the workers `health protection.

In silico prediction of human carboxylesterase-1 (hCES1) metabolism combining docking analyses and MD simulations.

Metabolic problems lead to numerous failures during clinical trials, and much effort is now devoted in developing in silico models predicting metabolic stability and metabolites. Such models are well known for cytochromes P450 and some transferases, whereas little has been done to predict the hydrolytic activity of human hydrolases. The present study was undertaken to develop a computational approach able to predict the hydrolysis of novel esters by human carboxylesterase hCES1. The study involves both docking analyses of known substrates to develop predictive models, and molecular dynamics (MD) simulations to reveal the in situ behavior of substrates and products, with particular attention being paid to the influence of their ionization state. The results emphasize some crucial properties of the hCES1 catalytic cavity, confirming that as a trend with several exceptions, hCES1 prefers substrates with relatively smaller and somewhat polar alkyl/aryl groups and larger hydrophobic acyl moieties. The docking results underline the usefulness of the hydrophobic interaction score proposed here, which allows a robust prediction of hCES1 catalysis, while the MD simulations show the different behavior of substrates and products in the enzyme cavity, suggesting in particular that basic substrates interact with the enzyme in their unprotonated form.

Predicting community and ecosystem outcomes of mycorrhizal responses to global change.

Mycorrhizal symbioses link the biosphere with the lithosphere by mediating nutrient cycles and energy flow though terrestrial ecosystems. A more mechanistic understanding of these plant-fungal associations may help ameliorate anthropogenic changes to C and N cycles and biotic communities. We explore three interacting principles: (1) optimal allocation, (2) biotic context and (3) fungal adaptability that may help predict mycorrhizal responses to carbon dioxide enrichment, nitrogen eutrophication, invasive species and land-use changes. Plant-microbial feedbacks and thresholds are discussed in light of these principles with the goal of generating testable hypotheses. Ideas to develop large-scale collaborative research efforts are presented. It is our hope that mycorrhizal symbioses can be effectively integrated into global change models and eventually their ecology will be understood well enough so that they can be managed to help offset some of the detrimental effects of anthropogenic environmental change.