Patterns of Ongoing Activity and the Functional Architecture of the Primary Visual Cortex

AbstractOngoing spontaneous activity in the cerebral cortex exhibits complex spatiotemporal patterns in the absence of sensory stimuli. To elucidate the nature of this ongoing activity, we present a theoretical treatment of two contrasting scenarios of cortical dynamics: (1) fluctuations about a single background state and (2) wandering among multiple “attractor” states, which encode a single or several stimulus features. Studying simplified network rate models of the primary visual cortex (V1), we show that the single state scenario is characterized by fast and high-dimensional Gaussian-like fluctuations, whereas in the multiple state scenario the fluctuations are slow, low dimensional, and highly non-Gaussian. Studying a more realistic model that incorporates correlations in the feed-forward input, spatially restricted cortical interactions, and an experimentally derived layout of pinwheels, we show that recent optical-imaging data of ongoing activity in V1 are consistent with the presence of either a single background state or multiple attractor states encoding many features

Applying New Research Methods to Inform Mountain Lion Harvest Management in Western Montana

The lack of reliable methods to accurately estimate mountain lion abundance has made lion (Puma concolor) management one of the most contentious wildlife issues in western Montana over the last 20 years. Lion harvest prescriptions and hunting season structure varied widely during that period because social factors drove management decisions in the absence of objective population data. During winter 2012-2013, we used a DNA-based spatial capture-recapture (SCR) approach to estimate mountain lion abundance in hunting districts 250 and 270 in the southern Bitterroot Watershed of western Montana. Mountain lion hair, scat, and muscle samples were collected for genetic analysis to identify individuals. We developed extensions to standard SCR models to accommodate simultaneous sampling and harvest events and incorporate existing information regarding mountain lion habitat quality. We estimated the abundance of 85 (95% CI = 54, 141) independent mountain lions in hunting district 250 and 82 (95% CI = 51, 137) in hunting district 270. These results are 2 - 3 times higher than previously reported mountain lion abundance in this area and correspond to density estimates of 4.6 and 5.4 lions per 100 km2. Because current harvest regulations in western Montana were developed under the assumption of lower population abundance, lion management objectives are unlikely to be met unless harvest prescriptions are adjusted to account for this new understanding of lion population status. More broadly, the analytic improvements in SCR methods will enhance the ability of wildlife managers to reliably and economically estimate abundance of harvested species

Genomics of Loa loa, a Wolbachia-free filarial parasite of humans

Loa loa, the African eyeworm, is a major filarial pathogen of humans. Unlike most filariae, Loa loa does not contain the obligate intracellular Wolbachia endosymbiont. We describe the 91.4 Mb genome of Loa loa, and the genome of the related filarial parasite Wuchereria bancrofti, and predict 14,907 Loa loa genes based on microfilarial RNA sequencing. By comparing these genomes to that of another filarial parasite, Brugia malayi, and to several other nematode genomes, we demonstrate synteny among filariae but not with non-parasitic nematodes. The Loa loa genome encodes many immunologically relevant genes, as well as protein kinases targeted by drugs currently approved for humans. Despite lacking Wolbachia, Loa loa shows no new metabolic synthesis or transport capabilities compared to other filariae. These results suggest that the role played by Wolbachia in filarial biology is more subtle than previously thought and reveal marked differences between parasitic and non-parasitic nematodes

Genotypic and phenotypic analyses of a Pseudomonas aeruginosa chronic bronchiectasis isolate reveal differences from cystic fibrosis and laboratory strains

Background Pseudomonas aeruginosa is an environmentally ubiquitous Gram-negative bacterium and important opportunistic human pathogen, causing severe chronic respiratory infections in patients with underlying conditions such as cystic fibrosis (CF) or bronchiectasis. In order to identify mechanisms responsible for adaptation during bronchiectasis infections, a bronchiectasis isolate, PAHM4, was phenotypically and genotypically characterized. Results This strain displays phenotypes that have been associated with chronic respiratory infections in CF including alginate over-production, rough lipopolysaccharide, quorum-sensing deficiency, loss of motility, decreased protease secretion, and hypermutation. Hypermutation is a key adaptation of this bacterium during the course of chronic respiratory infections and analysis indicates that PAHM4 encodes a mutated mutS gene responsible for a ~1,000-fold increase in mutation rate compared to wild-type laboratory strain P. aeruginosa PAO1. Antibiotic resistance profiles and sequence data indicate that this strain acquired numerous mutations associated with increased resistance levels to β-lactams, aminoglycosides, and fluoroquinolones when compared to PAO1. Sequencing of PAHM4 revealed a 6.38 Mbp genome, 5.9 % of which were unrecognized in previously reported P. aeruginosa genome sequences. Transcriptome analysis suggests a general down-regulation of virulence factors, while metabolism of amino acids and lipids is up-regulated when compared to PAO1 and metabolic modeling identified further potential differences between PAO1 and PAHM4. Conclusions This work provides insights into the potential differential adaptation of this bacterium to the lung of patients with bronchiectasis compared to other clinical settings such as cystic fibrosis, findings that should aid the development of disease-appropriate treatment strategies for P. aeruginosa infections

Baryon Acoustic Oscillations in the Sloan Digital Sky Survey Data Release 7 Galaxy Sample

The spectroscopic Sloan Digital Sky Survey (SDSS) Data Release 7 (DR7) galaxy sample represents the final set of galaxies observed using the original SDSS target selection criteria. We analyse the clustering of galaxies within this sample, including both the Luminous Red Galaxy (LRG) and Main samples, and also include the 2-degree Field Galaxy Redshift Survey (2dFGRS) data. Baryon Acoustic Oscillations are observed in power spectra measured for different slices in redshift; this allows us to constrain the distance--redshift relation at multiple epochs. We achieve a distance measure at redshift z=0.275, of r_s(z_d)/D_V(0.275)=0.1390+/-0.0037 (2.7% accuracy), where r_s(z_d) is the comoving sound horizon at the baryon drag epoch, D_V(z)=[(1+z)^2D_A^2cz/H(z)]^(1/3), D_A(z) is the angular diameter distance and H(z) is the Hubble parameter. We find an almost independent constraint on the ratio of distances D_V(0.35)/D_V(0.2)=1.736+/-0.065, which is consistent at the 1.1sigma level with the best fit Lambda-CDM model obtained when combining our z=0.275 distance constraint with the WMAP 5-year data. The offset is similar to that found in previous analyses of the SDSS DR5 sample, but the discrepancy is now of lower significance, a change caused by a revised error analysis and a change in the methodology adopted, as well as the addition of more data. Using WMAP5 constraints on Omega_bh^2 and Omega_ch^2, and combining our BAO distance measurements with those from the Union Supernova sample, places a tight constraint on Omega_m=0.286+/-0.018 and H_0 = 68.2+/-2.2km/s/Mpc that is robust to allowing curvature and non-Lambda dark energy. This result is independent of the behaviour of dark energy at redshifts greater than those probed by the BAO and supernova measurements. (abridged)Comment: 22 pages, 16 figures, minor changes to match version published in MNRA

Metabolomics-driven quantitative analysis of ammonia assimilation in E. coli

Despite extensive study of individual enzymes and their organization into pathways, the means by which enzyme networks control metabolite concentrations and fluxes in cells remains incompletely understood. Here, we examine the integrated regulation of central nitrogen metabolism in Escherichia coli through metabolomics and ordinary-differential-equation-based modeling. Metabolome changes triggered by modulating extracellular ammonium centered around two key intermediates in nitrogen assimilation, α-ketoglutarate and glutamine. Many other compounds retained concentration homeostasis, indicating isolation of concentration changes within a subset of the metabolome closely linked to the nutrient perturbation. In contrast to the view that saturated enzymes are insensitive to substrate concentration, competition for the active sites of saturated enzymes was found to be a key determinant of enzyme fluxes. Combined with covalent modification reactions controlling glutamine synthetase activity, such active-site competition was sufficient to explain and predict the complex dynamic response patterns of central nitrogen metabolites

Understanding and improving model representation of aerosol optical properties for a Chinese haze event measured during KORUS-AQ

KORUS-AQ was an international cooperative air quality field study in South Korea that measured local and remote sources of air pollution affecting the Korean Peninsula during May–June 2016. Some of the largest aerosol mass concentrations were measured during a Chinese haze transport event (24 May). Air quality forecasts using the WRF-Chem model with aerosol optical depth (AOD) data assimilation captured AOD during this pollution episode but overpredicted surface particulate matter concentrations in South Korea, especially PM2.5, often by a factor of 2 or larger. Analysis revealed multiple sources of model deficiency related to the calculation of optical properties from aerosol mass that explain these discrepancies. Using in situ observations of aerosol size and composition as inputs to the optical properties calculations showed that using a low-resolution size bin representation (four bins) underestimates the efficiency with which aerosols scatter and absorb light (mass extinction efficiency). Besides using finer-resolution size bins (8–16 bins), it was also necessary to increase the refractive indices and hygroscopicity of select aerosol species within the range of values reported in the literature to achieve better consistency with measured values of the mass extinction efficiency (6.7 m2 g−1 observed average) and light-scattering enhancement factor (f(RH)) due to aerosol hygroscopic growth (2.2 observed average). Furthermore, an evaluation of the optical properties obtained using modeled aerosol properties revealed the inability of sectional and modal aerosol representations in WRF-Chem to properly reproduce the observed size distribution, with the models displaying a much wider accumulation mode. Other model deficiencies included an underestimate of organic aerosol density (1.0 g cm−3 in the model vs. observed average of 1.5 g cm−3) and an overprediction of the fractional contribution of submicron inorganic aerosols other than sulfate, ammonium, nitrate, chloride, and sodium corresponding to mostly dust (17 %–28 % modeled vs. 12 % estimated from observations). These results illustrate the complexity of achieving an accurate model representation of optical properties and provide potential solutions that are relevant to multiple disciplines and applications such as air quality forecasts, health impact assessments, climate projections, solar power forecasts, and aerosol data assimilation

Overweight, obesity, and risk of cardiometabolic multimorbidity: pooled analysis of individual-level data for 120 813 adults from 16 cohort studies from the USA and Europe

Summary Background Although overweight and obesity have been studied in relation to individual cardiometabolic diseases, their association with risk of cardiometabolic multimorbidity is poorly understood. Here we aimed to establish the risk of incident cardiometabolic multimorbidity (ie, at least two from: type 2 diabetes, coronary heart disease, and stroke) in adults who are overweight and obese compared with those who are a healthy weight. Methods We pooled individual-participant data for BMI and incident cardiometabolic multimorbidity from 16 prospective cohort studies from the USA and Europe. Participants included in the analyses were 35 years or older and had data available for BMI at baseline and for type 2 diabetes, coronary heart disease, and stroke at baseline and follow-up. We excluded participants with a diagnosis of diabetes, coronary heart disease, or stroke at or before study baseline. According to WHO recommendations, we classified BMI into categories of healthy (20·0–24·9 kg/m2), overweight (25·0–29·9 kg/m2), class I (mild) obesity (30·0–34·9 kg/m2), and class II and III (severe) obesity (≥35·0 kg/m2). We used an inclusive definition of underweight (Peer reviewe