Plankton Ecology and Productivity in Jamaican Waters with New and Unique Applications

Unique applications of plankton ecology and productivity in Jamaican waters are presented. While traditional indices were inadequate descriptors of mangrove lagoon water quality, planktonic indices (total Chlorophyll a, zooplankton groups and species) were more reliable. Phytoplankton biomass was used to indicate a longitudinal gradient along the Hellshire Coastline, identifying non-point sources of enrichment, and movement of water masses in the absence of expensive Eulerian current meters. Along that same coast, mean primary production, determined by 14C techniques, confirmed a gradient from the eutrophic Kingston Harbour (21.1 g C m−2year−1) to the oligotrophic control site (0.52 g C m−2 year−1). Maximum inshore station values (36.75–18.39 g C m−2 year−1) were more than 20 times greater than offshore and exceeded Harbour values, confirming non-point sources and localized mechanisms as important inshore sources of eutrophication. The novel use of Ecopath with Ecosim (EwE) software to model trophic flows within planktonic communities was done in two bays. For Discovery Bay, on Jamaica’s north coast, the model indicated a developing ecosystem with open mineral cycles and poor nutrient conservation while in Foul and Folly Bays on the southeastern coast the model indicated greater resilience and ability to recover from perturbations. These applications have facilitated informed management decisions for sustainable use in Jamaican coastal ecosystems

The argument for integrating vector control with multiple drug administration campaigns to ensure elimination of lymphatic filariasis

BACKGROUND: There is a danger that mass drug administration campaigns may fail to maintain adequate treatment coverage to achieve lymphatic filariasis elimination. Hence, additional measures to suppress transmission might be needed to ensure the success of the Global Program for the Elimination of Lymphatic Filariasis. DISCUSSION: Vector control successfully eliminated lymphatic filariasis when implemented alone or with mass drug administration. Challenges to lymphatic filariasis elimination include uncertainty of the exact level and duration of microfilarial suppression required for elimination, the mobility of infected individuals, consistent non-participation of some infected individuals with mass drug administration, the possible development of anti-filarial drug resistance and treatment strategies in areas co-endemic with loasis. Integration of vector control with mass drug administration can address some of these challenges. The potential benefits of vector control would include: (1) the ability to suppress filariasis transmission without the need to identify all individual 'foci of infection'; (2) minimizing the risk of reestablishment of transmission from imported microfilaria positive individuals; and (3) decreasing the risk of dengue or malaria transmission where, respectively, Aedes or Anopheles are lymphatic filariasis vectors. SUMMARY: With adequate sustained treatment coverage, mass drug administration should meet the criteria for elimination of lymphatic filariasis. However, it may be difficult to sustain sufficiently high mass drug administration coverage to achieve lymphatic filariasis elimination in some areas, particularly, where Aedes species are the vectors. Since vector control was effective in controlling and even eliminating lymphatic filariasis transmission, integration of vector control with mass drug administration will ensure the sustainability of transmission suppression and thereby better ensure the success of national filariasis elimination programs. Although trials of some vector control interventions are needed, proven vector control strategies are ready for immediate integration with mass drug administration for many important vectors. Vector control is the only presently available additional lymphatic filariasis control measure with the potential for immediate implementation

Impacts of climate change on plant diseases – opinions and trends

There has been a remarkable scientific output on the topic of how climate change is likely to affect plant diseases in the coming decades. This review addresses the need for review of this burgeoning literature by summarizing opinions of previous reviews and trends in recent studies on the impacts of climate change on plant health. Sudden Oak Death is used as an introductory case study: Californian forests could become even more susceptible to this emerging plant disease, if spring precipitations will be accompanied by warmer temperatures, although climate shifts may also affect the current synchronicity between host cambium activity and pathogen colonization rate. A summary of observed and predicted climate changes, as well as of direct effects of climate change on pathosystems, is provided. Prediction and management of climate change effects on plant health are complicated by indirect effects and the interactions with global change drivers. Uncertainty in models of plant disease development under climate change calls for a diversity of management strategies, from more participatory approaches to interdisciplinary science. Involvement of stakeholders and scientists from outside plant pathology shows the importance of trade-offs, for example in the land-sharing vs. sparing debate. Further research is needed on climate change and plant health in mountain, boreal, Mediterranean and tropical regions, with multiple climate change factors and scenarios (including our responses to it, e.g. the assisted migration of plants), in relation to endophytes, viruses and mycorrhiza, using long-term and large-scale datasets and considering various plant disease control methods

Measurement of the inclusive jet cross-section in proton-proton collisions at √s=7 TeV using 4.5 fb−1 of data with the ATLAS detector

The inclusive jet cross-section is measured in proton-proton collisions at a centre-of-mass energy of 7 TeV using a data set corresponding to an integrated luminosity of 4.5 fb−1 collected with the ATLAS detector at the Large Hadron Collider in 2011. Jets are identified using the anti-kt algorithm with radius parameter values of 0.4 and 0.6. The double-differential cross-sections are presented as a function of the jet transverse momentum and the jet rapidity, covering jet transverse momenta from 100 GeV to 2 TeV. Next-to-leading-order QCD calculations corrected for non-perturbative effects and electroweak effects, as well as Monte Carlo simulations with next-to-leading-order matrix elements interfaced to parton showering, are compared to the measured cross-sections. A quantitative comparison of the measured cross-sections to the QCD calculations using several sets of parton distribution functions is performed

Measurement of the top quark mass in the tt→ dilepton channel from √s = 8 TeV ATLAS data

The top quark mass is measured in the tt¯ → dilepton channel (lepton = e,μ) using ATLAS data recorded in the year 2012 at the LHC. The data were taken at a proton proton centre-of-mass energy of √s = 8 TeV and correspond to an integrated luminosity of about 20.2 fb−1. Exploiting the template method, and using the distribution of invariant masses of lepton–b-jet pairs, the top quark mass is measured to be mtop = 172.99±0.41 (stat) ±0.74 (syst) GeV, with a total uncertainty of 0.84 GeV. Finally, a combination with previous ATLAS mtop measurements from √s = 7 TeV data in the tt¯ → dilepton and tt¯ → lepton + jets channels results in mtop = 172.84±0.34 (stat)±0.61 (syst) GeV, with a total uncertainty of 0.70 GeV

Polycystic ovary syndrome

The document attached has been archived with permission from the editor of the Medical Journal of Australia. An external link to the publisher’s copy is included.Polycystic ovary syndrome (PCOS) affects 5-20% of women of reproductive age worldwide. The condition is characterized by hyperandrogenism, ovulatory dysfunction and polycystic ovarian morphology (PCOM) - with excessive androgen production by the ovaries being a key feature of PCOS. Metabolic dysfunction characterized by insulin resistance and compensatory hyperinsulinaemia is evident in the vast majority of affected individuals. PCOS increases the risk for type 2 diabetes mellitus, gestational diabetes and other pregnancy-related complications, venous thromboembolism, cerebrovascular and cardiovascular events and endometrial cancer. PCOS is a diagnosis of exclusion, based primarily on the presence of hyperandrogenism, ovulatory dysfunction and PCOM. Treatment should be tailored to the complaints and needs of the patient and involves targeting metabolic abnormalities through lifestyle changes, medication and potentially surgery for the prevention and management of excess weight, androgen suppression and/or blockade, endometrial protection, reproductive therapy and the detection and treatment of psychological features. This Primer summarizes the current state of knowledge regarding the epidemiology, mechanisms and pathophysiology, diagnosis, screening and prevention, management and future investigational directions of the disorder.Robert J Norman, Ruijin Wu and Marcin T Stankiewic

The muon system of the Daya Bay Reactor antineutrino experiment

postprin

Measurement of D*±, D± and Ds± meson production cross sections in pp collisions at √s=7 TeV with the ATLAS detector

The production of D∗±, D± and D±s charmed mesons has been measured with the ATLAS detector in pp collisions at √s= 7 TeV at the LHC, using data corresponding to an integrated luminosity of 280 nb−1. The charmed mesons have been reconstructed in the range of transverse momentum 3.5 <pT(D) <100 GeV and pseudorapidity |η(D)| <2.1. The differential cross sections as a function of transverse momentum and pseudorapidity were measured for D∗± and D± production. The next-to-leading-order QCD predictions are consistent with the data in the visible kinematic region within the large theoretical uncertainties. Using the visible D cross sections and an extrapolation to the full kinematic phase space, the strangeness-suppression factor in charm fragmentation, the fraction of charged non-strange D mesons produced in a vector state, and the total cross section of charm production at √s= 7 TeV were derived

Cerebral small vessel disease genomics and its implications across the lifespan

White matter hyperintensities (WMH) are the most common brain-imaging feature of cerebral small vessel disease (SVD), hypertension being the main known risk factor. Here, we identify 27 genome-wide loci for WMH-volume in a cohort of 50,970 older individuals, accounting for modification/confounding by hypertension. Aggregated WMH risk variants were associated with altered white matter integrity (p = 2.5×10-7) in brain images from 1,738 young healthy adults, providing insight into the lifetime impact of SVD genetic risk. Mendelian randomization suggested causal association of increasing WMH-volume with stroke, Alzheimer-type dementia, and of increasing blood pressure (BP) with larger WMH-volume, notably also in persons without clinical hypertension. Transcriptome-wide colocalization analyses showed association of WMH-volume with expression of 39 genes, of which four encode known drug targets. Finally, we provide insight into BP-independent biological pathways underlying SVD and suggest potential for genetic stratification of high-risk individuals and for genetically-informed prioritization of drug targets for prevention trials.Peer reviewe

Analysis of shared heritability in common disorders of the brain

ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders