Improving the measurement of QALYs in dementia: Developing patient- and carer-reported health state classification systems using Rasch analysis

Objectives: Cost-utility analysis is increasingly used to inform resource allocation. This requires a means of valuing health states before and after intervention. Although generic measures are typically used to generate values, these do not perform well with people with dementia. We report the development of a health state classification system amenable to valuation for use in studies of dementia, derived from the DEMQOL system, a measure of health-related quality of life in dementia by patient self-report (DEMQOL) and carer proxy-report (DEMQOL-Proxy). Methods: Factor analysis was used to determine the dimensional structure of DEMQOL and DEMQOL-Proxy. Rasch analysis was subsequently used to investigate item performance across factors in terms of item-level ordering, functioning across subgroups, model fit and severity-range coverage. This enabled the selection of one item from each factor for the classification system. A sample of people with a diagnosis of mild/moderate dementia (n=644) and a sample of carers of those with mild/moderate dementia (n=683) were used. Results: Factor analysis found different 5-factor solutions for DEMQOL and DEMQOL-Proxy. Following item reduction and selection using Rasch analysis, a 5-dimension classification for DEMQOL and a 4-dimension classification for DEMQOL-Proxy were developed. Each item contained 4 health state levels. Conclusion: Combining Rasch and classical psychometric analysis is a valid method of selecting items for dementia health state classifications from both the patient and carer perspectives. The next stage is to obtain preference weights so that the measure can be used in the economic evaluation of treatment, care and support arrangements for dementia

Projections of multi-morbidity in the older population in England to 2035: estimates from the Population Ageing and Care Simulation (PACSim) model

Background models projecting future disease burden have focussed on one or two diseases. Little is known on how risk factors of younger cohorts will play out in the future burden of multi-morbidity (two or more concurrent long-term conditions).This work forms part of the MODEM project (A comprehensive approach to MODelling outcome and costs impacts of interventions for DEMentia), funded by the UK Economic and Social Research Council (ESRC) and the National Institute for Health Research (NIHR) (Grant number ES/L001896/1). C.J.’s salary was funded by the AXA Research Fund from 2010 to 2015. C.J. and A.K. also received funding for travel from the Australian Research Council funded Centre of Excellence in Population Ageing Research (CEPAR) project (2014–2017) on which C.J. was an international partner

Chern-Simons Invariants of Torus Links

We compute the vacuum expectation values of torus knot operators in Chern-Simons theory, and we obtain explicit formulae for all classical gauge groups and for arbitrary representations. We reproduce a known formula for the HOMFLY invariants of torus links and we obtain an analogous formula for Kauffman invariants. We also derive a formula for cable knots. We use our results to test a recently proposed conjecture that relates HOMFLY and Kauffman invariants.Comment: 20 pages, 5 figures; v2: minor changes, version submitted to AHP. The final publication is available at http://www.springerlink.com/content/a2614232873l76h6

The First VERITAS Telescope

The first atmospheric Cherenkov telescope of VERITAS (the Very Energetic Radiation Imaging Telescope Array System) has been in operation since February 2005. We present here a technical description of the instrument and a summary of its performance. The calibration methods are described, along with the results of Monte Carlo simulations of the telescope and comparisons between real and simulated data. The analysis of TeV $\gamma$-ray observations of the Crab Nebula, including the reconstructed energy spectrum, is shown to give results consistent with earlier measurements. The telescope is operating as expected and has met or exceeded all design specifications.Comment: Accepted by Astroparticle Physic

Early origins of lung disease: Towards an interdisciplinary approach

The prenatal and perinatal environments can have profound effects on the development of chronic inflammatory diseases. However, mechanistic insight into how the early-life microenvironment can impact upon development of the lung and immune system and consequent initiation and progression of respiratory diseases is still emerging. Recent studies investigating the developmental origins of lung diseases have started to delineate the effects of early-life changes in the lung, environmental exposures and immune maturation on the development of childhood and adult lung diseases. While the influencing factors have been described and studied in mostly animal models, it remains challenging to pinpoint exactly which factors and at which time point are detrimental in lung development leading to respiratory disease later in life. To advance our understanding of early origins of chronic lung disease and to allow for proper dissemination and application of this knowledge, we propose four major focus areas: 1) policy and education; 2) clinical assessment; 3) basic and translational research; and 4) infrastructure and tools, and discuss future directions for advancement. This review is a follow-up of the discussions at the European Respiratory Society Research Seminar “Early origins of lung disease: towards an interdisciplinary approach” (Lisbon, Portugal, November 2019)

Fungal Planet description sheets: 1284–1382

Novel species of fungi described in this study include those from various countries as follows: Antartica, Cladosporium austrolitorale from coastal sea sand. Australia, Austroboletus yourkae on soil, Crepidotus innuopurpureus on dead wood, Curvularia stenotaphri from roots and leaves of Stenotaphrum secundatum and Thecaphora stajsicii from capsules of Oxalis radicosa. Belgium, Paraxerochrysium coryli (incl. Paraxerochrysium gen. nov.) from Corylus avellana. Brazil, Calvatia nordestina on soil, Didymella tabebuiicola from leaf spots on Tabebuia aurea, Fusarium subflagellisporum from hypertrophied floral and vegetative branches of Mangifera indica and Microdochium maculosum from living leaves of Digitaria insularis. Canada, Cuphophyllus bondii fromagrassland. Croatia, Mollisia inferiseptata from a rotten Laurus nobilis trunk. Cyprus, Amanita exilis oncalcareoussoil. Czech Republic, Cytospora hippophaicola from wood of symptomatic Vaccinium corymbosum. Denmark, Lasiosphaeria deviata on pieces of wood and herbaceousdebris. Dominican Republic, Calocybella goethei among grass on a lawn. France (Corsica) , Inocybe corsica onwetground. France (French Guiana) , Trechispora patawaensis on decayed branch of unknown angiosperm tree and Trechispora subregularis on decayed log of unknown angiosperm tree. Germany, Paramicrothecium sambuci (incl. Paramicrothecium gen. nov.)ondeadstemsof Sambucus nigra. India, Aureobasidium microtermitis from the gut of a Microtermes sp. termite, Laccaria diospyricola on soil and Phylloporia tamilnadensis on branches of Catunaregam spinosa. Iran, Pythium serotinoosporum from soil under Prunus dulcis. Italy, Pluteus brunneovenosus on twigs of broad leaved trees on the ground. Japan, Heterophoma rehmanniae on leaves of Rehmannia glutinosa f. hueichingensis. Kazakhstan, Murispora kazachstanica from healthy roots of Triticum aestivum. Namibia, Caespitomonium euphorbiae (incl. Caespitomonium gen. nov.)from stems of an Euphorbia sp. Netherlands, Alfaria junci, Myrmecridium junci, Myrmecridium juncicola, Myrmecridium juncigenum, Ophioceras junci, Paradinemasporium junci (incl. Paradinemasporium gen. nov.), Phialoseptomonium junci, Sporidesmiella juncicola, Xenopyricularia junci and Zaanenomyces quadripartis (incl. Zaanenomyces gen. nov.), fromdeadculmsof Juncus effusus, Cylindromonium everniae and Rhodoveronaea everniae from Evernia prunastri, Cyphellophora sambuci and Myrmecridium sambuci from Sambucus nigra, Kiflimonium junci, Saro cladium junci, Zaanenomyces moderatricis academiae and Zaanenomyces versatilis from dead culms of Juncus inflexus, Microcera physciae from Physcia tenella, Myrmecridium dactylidis from dead culms of Dactylis glomerata, Neochalara spiraeae and Sporidesmium spiraeae from leaves of Spiraea japonica, Neofabraea salicina from Salix sp., Paradissoconium narthecii (incl. Paradissoconium gen. nov.)from dead leaves of Narthecium ossifragum, Polyscytalum vaccinii from Vaccinium myrtillus, Pseudosoloacrosporiella cryptomeriae (incl. Pseudosoloacrosporiella gen. nov.)fromleavesof Cryptomeria japonica, Ramularia pararhabdospora from Plantago lanceolata, Sporidesmiella pini from needles of Pinus sylvestris and Xenoacrodontium juglandis (incl. Xenoacrodontium gen. nov. and Xenoacrodontiaceae fam. nov.)from Juglans regia. New Zealand, Cryptometrion metrosideri from twigs of Metrosideros sp., Coccomyces pycnophyllocladi from dead leaves of Phyllocladus alpinus, Hypoderma aliforme from fallen leaves Fuscopora solandri and Hypoderma subiculatum from dead leaves Phormium tenax. Norway, Neodevriesia kalakoutskii from permafrost and Variabilispora viridis from driftwood of Picea abies. Portugal, Entomortierella hereditatis from abio film covering adeteriorated limestone wall. Russia, Colpoma junipericola from needles of Juniperus sabina, Entoloma cinnamomeum on soil in grasslands, Entoloma verae on soil in grasslands, Hyphodermella pallidostraminea on a dry dead branch of Actinidia sp., Lepiota sayanensis onlitterinamixedforest, Papiliotrema horticola from Malus communis , Paramacroventuria ribis (incl. Paramacroventuria gen. nov.)fromleaves of Ribes aureum and Paramyrothecium lathyri from leaves of Lathyrus tuberosus. South Africa, Harzia combreti from leaf litter of Combretum collinum ssp. sulvense, Penicillium xyleborini from Xyleborinus saxesenii , Phaeoisaria dalbergiae from bark of Dalbergia armata, Protocreopsis euphorbiae from leaf litter of Euphorbia ingens and Roigiella syzygii from twigs of Syzygium chordatum. Spain, Genea zamorana on sandy soil, Gymnopus nigrescens on Scleropodium touretii, Hesperomyces parexochomi on Parexochomus quadriplagiatus, Paraphoma variabilis from dung, Phaeococcomyces kinklidomatophilus from a blackened metal railing of an industrial warehouse and Tuber suaveolens in soil under Quercus faginea. Svalbard and Jan Mayen, Inocybe nivea associated with Salix polaris. Thailand, Biscogniauxia whalleyi oncorticatedwood. UK, Parasitella quercicola from Quercus robur. USA , Aspergillus arizonicus from indoor air in a hospital, Caeliomyces tampanus (incl. Caeliomyces gen. nov.)fromoffice dust, Cippumomyces mortalis (incl. Cippumomyces gen. nov.)fromatombstone, Cylindrium desperesense from air in a store, Tetracoccosporium pseudoaerium from air sample in house, Toxicocladosporium glendoranum from air in a brick room, Toxicocladosporium losalamitosense from air in a classroom, Valsonectria portsmouthensis from airinmen'slockerroomand Varicosporellopsis americana from sludge in a water reservoir. Vietnam, Entoloma kovalenkoi on rotten wood, Fusarium chuoi inside seed of Musa itinerans , Micropsalliota albofelina on soil in tropical evergreen mixed forest sand Phytophthora docyniae from soil and roots of Docynia indica. Morphological and culture characteristics are supported by DNA barcodes

The genetic architecture of the human cerebral cortex

INTRODUCTION The cerebral cortex underlies our complex cognitive capabilities. Variations in human cortical surface area and thickness are associated with neurological, psychological, and behavioral traits and can be measured in vivo by magnetic resonance imaging (MRI). Studies in model organisms have identified genes that influence cortical structure, but little is known about common genetic variants that affect human cortical structure. RATIONALE To identify genetic variants associated with human cortical structure at both global and regional levels, we conducted a genome-wide association meta-analysis of brain MRI data from 51,665 individuals across 60 cohorts. We analyzed the surface area and average thickness of the whole cortex and 34 cortical regions with known functional specializations. RESULTS We identified 306 nominally genome-wide significant loci (P < 5 × 10−8) associated with cortical structure in a discovery sample of 33,992 participants of European ancestry. Of the 299 loci for which replication data were available, 241 loci influencing surface area and 14 influencing thickness remained significant after replication, with 199 loci passing multiple testing correction (P < 8.3 × 10−10; 187 influencing surface area and 12 influencing thickness). Common genetic variants explained 34% (SE = 3%) of the variation in total surface area and 26% (SE = 2%) in average thickness; surface area and thickness showed a negative genetic correlation (rG = −0.32, SE = 0.05, P = 6.5 × 10−12), which suggests that genetic influences have opposing effects on surface area and thickness. Bioinformatic analyses showed that total surface area is influenced by genetic variants that alter gene regulatory activity in neural progenitor cells during fetal development. By contrast, average thickness is influenced by active regulatory elements in adult brain samples, which may reflect processes that occur after mid-fetal development, such as myelination, branching, or pruning. When considered together, these results support the radial unit hypothesis that different developmental mechanisms promote surface area expansion and increases in thickness. To identify specific genetic influences on individual cortical regions, we controlled for global measures (total surface area or average thickness) in the regional analyses. After multiple testing correction, we identified 175 loci that influence regional surface area and 10 that influence regional thickness. Loci that affect regional surface area cluster near genes involved in the Wnt signaling pathway, which is known to influence areal identity. We observed significant positive genetic correlations and evidence of bidirectional causation of total surface area with both general cognitive functioning and educational attainment. We found additional positive genetic correlations between total surface area and Parkinson’s disease but did not find evidence of causation. Negative genetic correlations were evident between total surface area and insomnia, attention deficit hyperactivity disorder, depressive symptoms, major depressive disorder, and neuroticism. CONCLUSION This large-scale collaborative work enhances our understanding of the genetic architecture of the human cerebral cortex and its regional patterning. The highly polygenic architecture of the cortex suggests that distinct genes are involved in the development of specific cortical areas. Moreover, we find evidence that brain structure is a key phenotype along the causal pathway that leads from genetic variation to differences in general cognitive function