Nitric oxide and nitrous oxide production and cycling during dissimulatory nitrite reduction by Pseudomonas perfectomarina

The denitrifier Pseudomonas perfectomarina reduced nitrite under conditions of kinetic competition between cells and gas sparging for extracellular dissolved nitric and nitrous oxides, NOaq and N2Oaq, in a chemically defined marine medium. Time courses of nitrite reduction and NOg and N2Og removal were integrated to give NOg , and N2Og yields. At high sparging rates, the NOg yield was >50% of nitrite-N reduced, and the yield of NOg + N2Og was ~75%. Hence interrupted denitrification yields NOaq and N2Oaq as major products. The yields varied with sparging rates in agreement with a quantitative model of denitrification (Betlach, M. P., and Tiedje, J. M. (1981) Appl. Environ. Microbiol. 42, 1074-1084) that applies simplified Michaelis-Menten kinetics to NO2 > NOaq > N2Oaq > N2. The fit gave an estimate of the maximum scavengeable NOaq yield of 73 ± 8% of nitrite-N. Thus a minor path independent of NOaq is also required. The fit of the model to data at lower sparging rates, where normal denitrification products predominate, implies that the extracellular NOaq pool yield is independent of gas sparging rate. Thus in P. perfectomarina NOaq and N2Oaq are intermediates, or facilely equilibrate with true intermediates, during complete denitrification. The recovery of most nitrite-N as NO and/or N20 under perturbed conditions is not an artifact of irreversible product removal, but an attribute of denitrification in this species, and most probably it is characteristic of denitrification in other species as well

Rural to Urban Population Density Scaling of Crime and Property Transactions in English and Welsh Parliamentary Constituencies

Urban population scaling of resource use, creativity metrics, and human behaviors has been widely studied. These studies have not looked in detail at the full range of human environments which represent a continuum from the most rural to heavily urban. We examined monthly police crime reports and property transaction values across all 573 Parliamentary Constituencies in England and Wales, finding that scaling models based on population density provided a far superior framework to traditional population scaling. We found four types of scaling: i ) non-urban scaling in which a single power law explained the relationship between the metrics and population density from the most rural to heavily urban environments, ii ) accelerated scaling in which high population density was associated with an increase in the power-law exponent, iii ) inhibited scaling where the urban environment resulted in a reduction in the power-law exponent but remained positive, and iv ) collapsed scaling where transition to the high density environment resulted in a negative scaling exponent. Urban scaling transitions, when observed, took place universally between 10 and 70 people per hectare. This study significantly refines our understanding of urban scaling, making clear that some of what has been previously ascribed to urban environments may simply be the high density portion of non-urban scaling. It also makes clear that some metrics undergo specific transitions in urban environments and these transitions can include negative scaling exponents indicative of collapse. This study gives promise of far more sophisticated scale adjusted metrics and indicates that studies of urban scaling represent a high density subsection of overall scaling relationships which continue into rural environments

Fluctuation Scaling, Taylor’s Law, and Crime

Fluctuation scaling relationships have been observed in a wide range of processes ranging from internet router traffic to measles cases. Taylor’s law is one such scaling relationship and has been widely applied in ecology to understand communities including trees, birds, human populations, and insects. We show that monthly crime reports in the UK show complex fluctuation scaling which can be approximated by Taylor’s law relationships corresponding to local policing neighborhoods and larger regional and countrywide scales. Regression models applied to local scale data from Derbyshire and Nottinghamshire found that different categories of crime exhibited different scaling exponents with no significant difference between the two regions. On this scale, violence reports were close to a Poisson distribution (α = 1.057±0.026) while burglary exhibited a greater exponent (α = 1.292±0.029) indicative of temporal clustering. These two regions exhibited significantly different pre-exponential factors for the categories of anti-social behavior and burglary indicating that local variations in crime reports can be assessed using fluctuation scaling methods. At regional and countrywide scales, all categories exhibited scaling behavior indicative of temporal clustering evidenced by Taylor’s law exponents from 1.43±0.12 (Drugs) to 2.094±0081 (Other Crimes). Investigating crime behavior via fluctuation scaling gives insight beyond that of raw numbers and is unique in reporting on all processes contributing to the observed variance and is either robust to or exhibits signs of many types of data manipulation

When R > 0.8 R0: fluorescence anisotropy, non-additive intensity, and cluster size

Assembly and clustering feature in many biological processes and homo-FRET and fluorescence anisotropy can assist in estimating the aggregation state of a system. The distance dependence of resonance energy transfer is well described and tested. Similarly, assessment of cluster size using steady state anisotropy is well described for non-oriented systems when R 0.8 R0. Fused trimeric DNA clusters labelled with fluorescein were engineered to provide inter-fluorophore distances from 0.7 to 1.6 R/R0 and intensity and anisotropy were measured. These constructs cover a range where anisotropy effects depend on distance. Analytical expressions were derived for fully labelled and fractionally labelled clusters and the experimental results analysed. The experimental results showed that: 1) the system underwent distance dependent quenching; 2) when incompletely labelled both doubly and triply labelled forms could be assessed to obtain distance dependent intensity factors; 3) the anisotropy behaviour of a multiply labelled cluster of a particular size depends on the behaviour of the fluorophores and their distance in a cluster. This work establishes that when emission intensity data are available the analytically useful range for investigating clusters does not have to be restricted to R < 0.8 R0 and is applicable to cases where the anisotropy of a cluster of N fluorophores is not well approximated by r1/N

Statistical models for identifying frequent hitters in high throughput screening

High throughput screening (HTS) interrogates compound libraries to find those that are “active” in an assay. To better understand compound behavior in HTS, we assessed an existing binomial survivor function (BSF) model of “frequent hitters” using 872 publicly available HTS data sets. We found large numbers of “infrequent hitters” using this model leading us to reject the BSF for identifying “frequent hitters.” As alternatives, we investigated generalized logistic, gamma, and negative binomial distributions as models for compound behavior. The gamma model reduced the proportion of both frequent and infrequent hitters relative to the BSF. Within this data set, conclusions about individual compound behavior were limited by the number of times individual compounds were tested (1–1613 times) and disproportionate testing of some compounds. Specifically, most tests (78%) were on a 309,847-compound subset (17.6% of compounds) each tested ≥ 300 times. We concluded that the disproportionate retesting of some compounds represents compound repurposing at scale rather than drug discovery. The approach to drug discovery represented by these 872 data sets characterizes the assays well by challenging them with many compounds while each compound is characterized poorly with a single assay. Aggregating the testing information from each compound across the multiple screens yielded a continuum with no clear boundary between normal and frequent hitting compounds

City size and the spreading of COVID-19 in Brazil

The current outbreak of the coronavirus disease 2019 (COVID-19) is an unprecedented example of how fast an infectious disease can spread around the globe (especially in urban areas) and the enormous impact it causes on public health and socio-economic activities. Despite the recent surge of investigations about different aspects of the COVID-19 pandemic, we still know little about the effects of city size on the propagation of this disease in urban areas. Here we investigate how the number of cases and deaths by COVID-19 scale with the population of Brazilian cities. Our results indicate that large cities are proportionally more affected by COVID-19, such that every 1% rise in population is associated with 0.57% increase in the number of cases per capita and 0.25% in the number of deaths per capita. The difference between the scaling of cases and deaths indicates the case fatality rate decreases with city size. The latest estimates show that a 1% increase in population associates with a 0.14% reduction in the case fatality rate of COVID-19; however, this urban advantage has decreased over time. We interpret this to be due to the existence of proportionally more health infrastructure in the largest cities and a lower proportion of older adults in large urban areas. We also find the initial growth rate of cases and deaths to be higher in large cities; however, these growth rates tend to decrease in large cities and to increase in small ones during the long-term course of the pandemic

Fluctuation scaling, the calibration of dispersion, and the detection of differences

Fluctuation scaling describes the relationship between the mean and standard deviation of a set of measurements. An example is Horwitz scaling which has been reported from inter-laboratory studies. Horwitz and similar studies have reported simple exponential and segmented scaling laws with exponents (α) typically between 0.85 (Horwitz) and 1 when not operating near a detection limit. When approaching a detection limit the exponents change and approach an apparently Gaussian (α = 0) model. This behavior is generally presented as a property of inter-laboratory studies which makes controlled replication to understand the behavior costly to perform. To assess the contribution of instrumentation to larger scale fluctuation scaling, we measured the behavior of two inductively coupled plasma atomic emission spectrometry (ICP-AES) systems, in two laboratories measuring thulium using 2 emission lines. The standard deviation universally increased with the uncalibrated signal indicating the system was heteroscedastic. The response from all lines and both instruments was consistent with a single exponential dispersion model having parameters α = 1.09 and β = 0.0035. No evidence of Horwitz scaling was found and there was no evidence of Poisson noise limiting behavior. The “Gaussian” component was a consequence of background subtraction for all lines and both instruments. The observation of a simple exponential dispersion model in the data allows for the definition of a difference detection limit (DDL) with universal applicability to systems following known dispersion. The DDL is the minimum separation between two points along a dispersion model required to claim they are different according to a particular statistical test. The DDL scales transparently with the mean and works at any location in a response function

The hidden traits of endemic illiteracy in cities

In spite of the considerable progress towards reducing illiteracy rates, many countries, including developed ones, have encountered difficulty achieving further reduction in these rates. This is worrying because illiteracy has been related to numerous health, social, and economic problems. Here, we show that the spatial patterns of illiteracy in urban systems have several features analogous to the spread of diseases such as dengue and obesity. Our results reveal that illiteracy rates are spatially long-range correlated, displaying non-trivial clustering structures characterized by percolation-like transitions and fractality. These patterns can be described in the context of percolation theory of long-range correlated systems at criticality. Together, these results provide evidence that the illiteracy incidence can be related to an infectious-like process, in which the lack of access to minimal education propagates in a population in a similar fashion to endemic diseases

A platform for screening abiotic/biotic interactions using indicator displacement assays

This paper describes novel adaptations of optically sectioned planar format assays to screen compounds for their affinities to materials surfaces. The novel platform, which we name Optical sectioned Indicator Displacement Assays (O-IDA), makes use of displaceable dyes in a format adaptable to high-throughput multi-well plate technologies. We describe two approaches; in the first the dye exhibits fluorescence in both the surface-bound and unbound state. In the second, fluorescence is lost upon displacement of the dye from the surface. Half maximal inhibitory concentration (IC50), binding affinity (Ki), and binding free energy (ΔGads) values can be extracted from the raw data. Representative biomolecules were tested for interactions with silica in aqueous environment and ZnO (0001)-Zn and (10-10) facets in a non-aqueous environment. We provide the first experimental values for both the binding of small molecules to silica and the facet-dependent ZnO binding affinity of key amino acids associated with ZnO-specific oligopeptides. The specific data will be invaluable to those studying interactions at interfaces both experimentally and computationally. O-IDA provides a general framework for the high-throughput screening of molecules binding to materials surfaces, which has important applications in drug delivery, (bio-) catalysis, biosensing and biomaterials engineering