Integrated groundwater management: An overview of concepts and challenges

Managing water is a grand challenge problem and has become one of humanity’s foremost priorities. Surface water resources are typically societally managed and relatively well understood; groundwater resources, however, are often hidden and more difficult to conceptualize. Replenishment rates of groundwater cannot match past and current rates of depletion in many parts of the world. In addition, declining quality of the remaining groundwater commonly cannot support all agricultural, industrial and urban demands and ecosystem functioning, especially in the developed world. In the developing world, it can fail to even meet essential human needs. The issue is: how do we manage this crucial resource in an acceptable way, one that considers the sustainability of the resource for future generations and the socioeconomic and environmental impacts? In many cases this means restoring aquifers of concern to some sustainable equilibrium over a negotiated period of time, and seeking opportunities for better managing groundwater conjunctively with surface water and other resource uses. However, there are many, often-interrelated, dimensions to managing groundwater effectively. Effective groundwater management is underpinned by sound science (biophysical and social) that actively engages the wider community and relevant stakeholders in the decision making process. Generally, an integrated approach will mean “thinking beyond the aquifer”, a view which considers the wider context of surface water links, catchment management and cross-sectoral issues with economics, energy, climate, agriculture and the environment. The aim of the book is to document for the first time the dimensions and requirements of sound integrated groundwater management (IGM). The primary focus is on groundwater management within its system, but integrates linkages beyond the aquifer. The book provides an encompassing synthesis for researchers, practitioners and water resource managers on the concepts and tools required for defensible IGM, including how IGM can be applied to achieve more sustainable socioeconomic and environmental outcomes, and key challenges of IGM. The book is divided into five parts: integration overview and problem settings; governance; socioeconomics; biophysical aspects; and modelling and decision support. However, IGM is integrated by definition, thus these divisions should be considered a convenience for presenting the topics rather than hard and fast demarcations of the topic area

Genome-wide signatures of convergent evolution in echolocating mammals

Evolution is typically thought to proceed through divergence of genes, proteins, and ultimately phenotypes(1-3). However, similar traits might also evolve convergently in unrelated taxa due to similar selection pressures(4,5). Adaptive phenotypic convergence is widespread in nature, and recent results from a handful of genes have suggested that this phenomenon is powerful enough to also drive recurrent evolution at the sequence level(6-9). Where homoplasious substitutions do occur these have long been considered the result of neutral processes. However, recent studies have demonstrated that adaptive convergent sequence evolution can be detected in vertebrates using statistical methods that model parallel evolution(9,10) although the extent to which sequence convergence between genera occurs across genomes is unknown. Here we analyse genomic sequence data in mammals that have independently evolved echolocation and show for the first time that convergence is not a rare process restricted to a handful of loci but is instead widespread, continuously distributed and commonly driven by natural selection acting on a small number of sites per locus. Systematic analyses of convergent sequence evolution in 805,053 amino acids within 2,326 orthologous coding gene sequences compared across 22 mammals (including four new bat genomes) revealed signatures consistent with convergence in nearly 200 loci. Strong and significant support for convergence among bats and the dolphin was seen in numerous genes linked to hearing or deafness, consistent with an involvement in echolocation. Surprisingly we also found convergence in many genes linked to vision: the convergent signal of many sensory genes was robustly correlated with the strength of natural selection. This first attempt to detect genome-wide convergent sequence evolution across divergent taxa reveals the phenomenon to be much more pervasive than previously recognised

Adaptations to Climate-Mediated Selective Pressures in Humans

Humans inhabit a remarkably diverse range of environments, and adaptation through natural selection has likely played a central role in the capacity to survive and thrive in extreme climates. Unlike numerous studies that used only population genetic data to search for evidence of selection, here we scan the human genome for selection signals by identifying the SNPs with the strongest correlations between allele frequencies and climate across 61 worldwide populations. We find a striking enrichment of genic and nonsynonymous SNPs relative to non-genic SNPs among those that are strongly correlated with these climate variables. Among the most extreme signals, several overlap with those from GWAS, including SNPs associated with pigmentation and autoimmune diseases. Further, we find an enrichment of strong signals in gene sets related to UV radiation, infection and immunity, and cancer. Our results imply that adaptations to climate shaped the spatial distribution of variation in humans

Predictors of Shoulder Pain and Disability Index (SPADI) and work status after 1 year in patients with subacromial shoulder pain

<p>Abstract</p> <p>Background</p> <p>Shoulder pain is a common complaint in primary health care and has an unfavourable outcome in many patients. The objectives were to identify predictors for pain and disability (SPADI) and work status in patients with subacromial shoulder pain.</p> <p>Methods</p> <p>Secondary analyses of data from a randomized clinical controlled trial were performed. Outcome measures were the absolute values of the combined Shoulder Pain and Disability Index (SPADI) and work status 1 year after treatment with supervised exercises (SE) or radial extracorporeal shockwave therapy (rESWT). Predictors of outcome were investigated using multiple linear regression (SPADI) and logistic regression (work status).</p> <p>Results</p> <p>104 patients were included. Low education (≤ 12 years), previous shoulder pain, and a high baseline SPADI score predicted poor results with these variables explaining 29.9% of the variance in SPADI score at 1 year. Low education and poor self-reported health status predicted a work status of "not working": Odds Ratio, OR = 4.3(95% CI (1.3 to 14.9)), p = 0.02 for education, and OR = 1.06 (95% CI (1.0 to 1.1)), p = 0.001 for self-reported health status, respectively. Adjustments for age, gender, and treatment group were performed, but did not change the results.</p> <p>Conclusion</p> <p>Education was the most consistent predictor of pain and disability, and work status at 1 year follow-up. Also, baseline SPADI score, previous shoulder pain and self-reported health status predicted outcome.</p> <p>Trial registration</p> <p>Clinical trials NCT00653081</p

Research methods for subgrouping low back pain

<p>Abstract</p> <p>Background</p> <p>There is considerable clinician and researcher interest in whether the outcomes for patients with low back pain, and the efficiency of the health systems that treat them, can be improved by 'subgrouping research'. Subgrouping research seeks to identify subgroups of people who have clinically important distinctions in their treatment needs or prognoses. Due to a proliferation of research methods and variability in how subgrouping results are interpreted, it is timely to open discussion regarding a conceptual framework for the research designs and statistical methods available for subgrouping studies (a method framework). The aims of this debate article are: (1) to present a method framework to inform the design and evaluation of subgrouping research in low back pain, (2) to describe method options when investigating prognostic effects or subgroup treatment effects, and (3) to discuss the strengths and limitations of research methods suitable for the hypothesis-setting phase of subgroup studies.</p> <p>Discussion</p> <p>The proposed method framework proposes six phases for studies of subgroups: studies of assessment methods, hypothesis-setting studies, hypothesis-testing studies, narrow validation studies, broad validation studies, and impact analysis studies. This framework extends and relabels a classification system previously proposed by McGinn et al (2000) as suitable for studies of clinical prediction rules. This extended classification, and its descriptive terms, explicitly anchor research findings to the type of evidence each provides. The inclusive nature of the framework invites appropriate consideration of the results of diverse research designs. Method pathways are described for studies designed to test and quantify prognostic effects or subgroup treatment effects, and examples are discussed. The proposed method framework is presented as a roadmap for conversation amongst researchers and clinicians who plan, stage and perform subgrouping research.</p> <p>Summary</p> <p>This article proposes a research method framework for studies of subgroups in low back pain. Research designs and statistical methods appropriate for sequential phases in this research are discussed, with an emphasis on those suitable for hypothesis-setting studies of subgroups of people seeking care.</p

Prior immunity helps to explain wave-like behaviour of pandemic influenza in 1918-9

<p>Abstract</p> <p>Background</p> <p>The ecology of influenza may be more complex than is usually assumed. For example, despite multiple waves in the influenza pandemic of 1918-19, many people in urban locations were apparently unaffected. Were they unexposed, or protected by pre-existing cross-immunity in the first wave, by acquired immunity in later waves, or were their infections asymptomatic?</p> <p>Methods</p> <p>We modelled all these possibilities to estimate parameters to best explain patterns of repeat attacks in 24,706 individuals potentially exposed to summer, autumn and winter waves in 12 English populations during the 1918-9 pandemic.</p> <p>Results</p> <p>Before the summer wave, we estimated that only 52% of persons (95% credibility estimates 41-66%) were susceptible, with the remainder protected by prior immunity. Most people were exposed, as virus transmissibility was high with R₀credibility estimates of 3.10-6.74. Because of prior immunity, estimates of effective R at the start of the summer wave were lower at 1.57-3.96. Only 25-66% of exposed and susceptible persons reported symptoms. After each wave, 33-65% of protected persons became susceptible again before the next wave through waning immunity or antigenic drift. Estimated rates of prior immunity were less in younger populations (19-59%) than in adult populations (38-66%), and tended to lapse more frequently in the young (49-92%) than in adults (34-76%).</p> <p>Conclusions</p> <p>Our model for pandemic influenza in 1918-9 suggests that pre-existing immune protection, presumably induced by prior exposure to seasonal influenza, may have limited the pandemic attack-rate in urban populations, while the waning of that protection likely contributed to recurrence of pandemic waves in exposed cities. In contrast, in isolated populations, pandemic attack rates in 1918-9 were much higher than in cities, presumably because prior immunity was less in populations with infrequent prior exposure to seasonal influenza. Although these conclusions cannot be verified by direct measurements of historical immune mechanisms, our modelling inferences from 1918-9 suggest that the spread of the influenza A (H1N1) 2009 pandemic has also been limited by immunity from prior exposure to seasonal influenza. Components of that immunity, which are measurable, may be short-lived, and not necessarily correlated with levels of HI antibody.</p

Chemokine Transfer by Liver Sinusoidal Endothelial Cells Contributes to the Recruitment of CD4+ T Cells into the Murine Liver

Leukocyte adhesion and transmigration are central features governing immune surveillance and inflammatory reactions in body tissues. Within the liver sinusoids, chemokines initiate the first crucial step of T-cell migration into the hepatic tissue. We studied molecular mechanisms involved in endothelial chemokine supply during hepatic immune surveillance and liver inflammation and their impact on the recruitment of CD4+ T cells into the liver. In the murine model of Concanavalin A-induced T cell-mediated hepatitis, we showed that hepatic expression of the inflammatory CXC chemokine ligands (CXCL)9 and CXCL10 strongly increased whereas homeostatic CXCL12 significantly decreased. Consistently, CD4+ T cells expressing the CXC chemokine receptor (CXCR)3 accumulated within the inflamed liver tissue. In histology, CXCL9 was associated with liver sinusoidal endothelial cells (LSEC) which represent the first contact site for T-cell immigration into the liver. LSEC actively transferred basolaterally internalized CXCL12, CXCL9 and CXCL10 via clathrin- coated vesicles to CD4+ T cells leading to enhanced transmigration of CXCR4+ total CD4+ T cells and CXCR3+ effector/memory CD4+ T cells, respectively in vitro. LSEC-expressed CXCR4 mediated CXCL12 transport and blockage of endothelial CXCR4 inhibited CXCL12-dependent CD4+ T-cell transmigration. In contrast, CXCR3 was not involved in the endothelial transport of its ligands CXCL9 and CXCL10. The clathrin-specific inhibitor chlorpromazine blocked endothelial chemokine internalization and CD4+ T-cell transmigration in vitro as well as migration of CD4+ T cells into the inflamed liver in vivo. Moreover, hepatic accumulation of CXCR3+ CD4+ T cells during T cell-mediated hepatitis was strongly reduced after administration of chlorpromazine. These data demonstrate that LSEC actively provide perivascularly expressed homeostatic and inflammatory chemokines by CXCR4- and clathrin-dependent intracellular transport mechanisms thereby contributing to the hepatic recruitment of CD4+ T-cell populations during immune surveillance and liver inflammation

Influenza Virus-Like Particles Containing M2 Induce Broadly Cross Protective Immunity

Current influenza vaccines based on the hemagglutinin protein are strain specific and do not provide good protection against drifted viruses or emergence of new pandemic strains. An influenza vaccine that can confer cross-protection against antigenically different influenza A strains is highly desirable for improving public health.To develop a cross protective vaccine, we generated influenza virus-like particles containing the highly conserved M2 protein in a membrane-anchored form (M2 VLPs), and investigated their immunogenicity and breadth of cross protection. Immunization of mice with M2 VLPs induced anti-M2 antibodies binding to virions of various strains, M2 specific T cell responses, and conferred long-lasting cross protection against heterologous and heterosubtypic influenza viruses. M2 immune sera were found to play an important role in providing cross protection against heterosubtypic virus and an antigenically distinct 2009 pandemic H1N1 virus, and depletion of dendritic and macrophage cells abolished this cross protection, providing new insight into cross-protective immune mechanisms.These results suggest that presenting M2 on VLPs in a membrane-anchored form is a promising approach for developing broadly cross protective influenza vaccines