Virulence-associated genes in faecal and clinical Escherichia coli isolates cultured from broiler chickens in Australia.

A healthy chicken's intestinal flora harbours a rich reservoir of Escherichia coli as part of the commensal microbiota. However, some strains, known as avian pathogenic E. coli (APEC), carry specific virulence genes (VGs) that enable them to invade and cause extraintestinal infections such as avian colibacillosis. Although several VG combinations have been identified, the pathogenic mechanisms associated with APEC are ill-defined. The current study screened a subset of 88 E. coli isolates selected from 237 pre-existing isolates obtained from commercial poultry flocks in Australia. The 88 isolates were selected based on their enterobacterial repetitive intergenic consensus (ERIC) and antimicrobial resistance (AMR) profiles and included 29 E. coli isolates cultured from chickens with colibacillosis (referred to as clinical E. coli or CEC) and 59 faecal E. coli (FEC) isolates cultured from clinically healthy chickens. The isolates were screened for the presence of 35 previously reported VGs. Of these, 34 were identified, with iucA not being detected. VGs focG, hlyA and sfa/foc were only detected in FEC isolates. Eight VGs had a prevalence of 90% or above in the CEC isolates. Specifically, astA (100%); feoB (96.6%); iutA, iss, ompT, iroN and hlyF (all 93.1%); and vat (89.7%). The prevalence of these were significantly lower in FEC isolates (astA 79.7%, feoB 77.9%, iutA 52.5%, iss 45.8%, ompT 50.9%, iroN 37.3%, hlyF 50.9% and vat 42.4%). The odds ratios that each of these eight VGs were more likely to be associated with CEC than FEC ranged from 7.8 to 21.9. These eight VGs may be used to better define APEC and diagnostically detect APEC in Australia. Further investigations are needed to identify the roles of these VGs in pathogenicity.

A simulated 'sandbox' for exploring the modifiable areal unit problem in aggregation and disaggregation.

We present a spatial testbed of simulated boundary data based on a set of very high-resolution census-based areal units surrounding Guadalajara, Mexico. From these input areal units, we simulated 10 levels of spatial resolutions, ranging from levels with 5,515-52,388 units and 100 simulated zonal configurations for each level - totalling 1,000 simulated sets of areal units. These data facilitate interrogating various realizations of the data and the effects of the spatial coarseness and zonal configurations, the Modifiable Areal Unit Problem (MAUP), on applications such as model training, model prediction, disaggregation, and aggregation processes. Further, these data can facilitate the production of spatially explicit, non-parametric estimates of confidence intervals via bootstrapping. We provide a pre-processed version of these 1,000 simulated sets of areal units, meta- and summary data to assist in their use, and a code notebook with the means to alter and/or reproduce these data.

Triplet Excimer Formation in a DNA Duplex with Silver Ion-Mediated Base Pairs.

The dynamics of excited electronic states in self-assembled structures formed between silver(I) ions and cytosine-containing DNA strands or monomeric cytosine derivatives were investigated by time-resolved infrared (TRIR) spectroscopy and quantum mechanical calculations. The steady-state and time-resolved spectra depend sensitively on the underlying structures, which change with pH and the nucleobase and silver ion concentrations. At pH ∼ 4 and low dC20 strand concentration, an intramolecularly folded i-motif is observed, in which protons, and not silver ions, mediate C-C base pairing. However, at the higher strand concentrations used in the TRIR measurements, dC20 strands associate pairwise to yield duplex structures containing C-Ag+-C base pairs with a high degree of propeller twisting. UV excitation of the silver ion-mediated duplex produces a long-lived excited state, which we assign to a triplet excimer state localized on a pair of stacked cytosines. The computational results indicate that the propeller-twisted motifs induced by metal-ion binding are responsible for the enhanced intersystem crossing that populates the triplet state and not a generic heavy atom effect. Although triplet excimer states have been discussed frequently as intermediates in the formation of cyclobutane pyrimidine dimers, we find neither computational nor experimental evidence for cytosine-cytosine photoproduct formation in the systems studied. These findings provide a rare demonstration of a long-lived triplet excited state that is formed in a significant yield in a DNA duplex, demonstrating that supramolecular structural changes induced by metal ion binding profoundly affect DNA photophysics.

Ultrafast Radical Photogeneration Pathways in Eumelanin.

Eumelanin is a ubiquitous biological pigment that rapidly and efficiently deactivates excited states created by UV or visible radiation. Paradoxically, photoirradiation of eumelanin also generates radicals and harmful reactive oxygen species, but the relationship between these pathways and excited-state deactivation is uncertain. Here, greatly expanding the excitation tuning range (225-620 nm) and probing window (400-1500 nm) in femtosecond transient absorption spectroscopy of the synthetic eumelanin, DOPA melanin, enables the detection of photogenerated radials with ultrafast time resolution for the first time. Despite its heterogeneous nature, the transient absorption signals can be modeled by two spectral components assigned to solvated electrons and photogenerated radicals. Radical absorbance measured several nanoseconds after excitation increases exponentially with increasing photon energy, matching the trend in radical yields measured in electron paramagnetic resonance spectroscopy experiments. Spectral modeling of the transient signals reveals two radical generation mechanisms: (1) photoionization by UV light; and (2) photoinduced charge transfer among eumelanin chromophores by UVA and visible wavelengths capable of reaching the pigment in skin. Concurrent ultrafast relaxation and radical generation underlie the ability of eumelanin to be both photoprotective and photodamaging, and the branching between these pathways likely depends on the wavelength of the absorbed light.

Wildlife impacts and changing climate pose compounding threats to human food security.

High-level policy debates surrounding elephant management often dominate global conservation headlines, yet realities for people living with wildlife are not adequately incorporated into policymaking or evident in related discourse.1,2 Human health and livelihoods can be severely impacted by wildlife and indirectly by policy outcomes.3 In landscapes where growing human and elephant (Loxodonta spp. and Elephas maximus) populations compete over limited resources, human-elephant conflict causes crop loss, human injury and death, and retaliatory killing of wildlife.4-6 Across Africa, these problems may be increasingly compounded by climate change, which intensifies resource competition and food insecurity.6-9 Here, we examine how human-wildlife impacts interact with climate change and household food insecurity across the Kavango-Zambezi Transfrontier Conservation Area, the world's largest terrestrial transboundary conservation area, spanning five African nations. We use hierarchical Bayesian statistical models to analyze multi-country household data together with longitudinal satellite-based climate measures relevant to rainfed agriculture. We find that crop depredation by wildlife, primarily elephants, impacts 58% of sampled households annually and is associated with significant increases in food insecurity. These wildlife impacts compound effects of changing climate on food insecurity, most notably observed as a 5-day shortening of the rainy season per 10 years across the data record (1981-2018). To advance sustainability goals, global conservation policy must better integrate empirical evidence on the challenges of human-wildlife coexistence into longer term strategies at transboundary scales, specifically in the context of climate change.3,9-11.

Ovine FABP4 Variation and Its Association With Flystrike Susceptibility.

Flystrike is a major cost and a welfare issue for the New Zealand sheep industry. There are several factors that can predispose sheep to flystrike, such as having fleecerot, a urine-stained breech, and "dags" (an accumulation of fecal matter in the wool of the breech). The FABP4 gene (FABP4) has been associated with variation in ovine fleecerot resistance, with a strong genetic correlation existing between fleecerot and flystrike occurrence. In this study, blood samples were collected from sheep with and without flystrike for DNA typing. PCR-SSCP analyses were used to genotype two regions of ovine FABP4. Sheep with the A 1 variant of FABP4 were found to be less likely (odds ratio 0.689, P = 0.014) to have flystrike than those without A 1. The likelihood of flystrike occurrence decreased as copy number of A 1 increased (odds ratio 0.695, P = 0.006). This suggests that FABP4 might be a candidate gene for flystrike resilience in sheep, although further research is required to verify this association.

Measuring the contribution of built-settlement data to global population mapping.

Top-down population modelling has gained applied prominence in public health, planning, and sustainability applications at the global scale. These top-down population modelling methods often rely on remote-sensing (RS) derived representation of the built-environment and settlements as key predictive covariates. While these RS-derived data, which are global in extent, have become more advanced and more available, gaps in spatial and temporal coverage remain. These gaps have prompted the interpolation of the built-environment and settlements, but the utility of such interpolated data in further population modelling applications has garnered little research. Thus, our objective was to determine the utility of modelled built-settlement extents in a top-down population modelling application. Here we take modelled global built-settlement extents between 2000 and 2012, created using a spatio-temporal disaggregation of observed settlement growth. We then demonstrate the applied utility of such annually modelled settlement data within the application of annually modelling population, using random forest informed dasymetric disaggregations, across 172 countries and a 13-year period. We demonstrate that the modelled built-settlement data are consistently the 2nd most important covariate in predicting population density, behind annual lights at night, across the globe and across the study period. Further, we demonstrate that this modelled built-settlement data often provides more information than current annually available RS-derived data and last observed built-settlement extents.

Innovating at the human-technology interface in disasters and disease outbreaks.

Disasters and disease outbreaks have long been a catalyst for innovative applications of emerging technologies. The urgent need to respond to an emergency leads to resourceful uses of the technologies at hand. However, the best and most cost-effective use of new technologies is to prevent disease and improve resilience. In this paper, the authors present a range of approaches through which both opportunities can be grasped. Global connectedness enables more data to be collected and processed in emergencies, especially with the rise of open-source data, including social media. In general, the poorest and most remote populations are most vulnerable to disaster. However, with smaller, faster, smarter, cheaper and more connected technology, reliable, efficient, and targeted response and recovery can be provided. Initially, crowdsourcing was used to find people, map affected areas, and determine resource allocation. This led to the generation of an overwhelming amount of data, and the need to extract valuable information from that data in a timely manner. As technology evolved, organisations started outsourcing many tasks, first to other people, then to machines. Since the volume of data generated outpaces human capacity, data analysis is being automated using artificial intelligence and machine learning, which furthers our abilities in predictive analytics. As we move towards prevention rather than remediation, information collection and processing must become faster and more efficient while maintaining accuracy. Moreover, these new strategies and technologies can help us to move forwards, by integrating layers of human, veterinary, public, and environmental health data for a One Health approach.

Les catastrophes et les foyers de maladies font depuis longtemps office de catalyseurs pour l'émergence d'applications technologiques innovantes. Le besoin impérieux de répondre à une urgence encourage les utilisations ingénieuses des technologies disponibles. Cependant, la meilleure utilisation des nouvelles technologies, et la plus rentable, consiste à prévenir les maladies et à améliorer la résilience. Les auteurs présentent une gamme d'approches permettant de tirer le meilleur parti de ces deux possibilités. La connectivité mondiale permet de recueillir et de traiter davantage de données lors des situations d'urgence, en particulier grâce à l'essor des données de sources ouvertes, y compris dans les réseaux sociaux. De manière générale, les populations les plus pauvres et les plus isolées sont aussi les plus vulnérables aux catastrophes. Cependant, en recourant à des technologies plus compactes, plus rapides, plus intelligentes, plus abordables et plus connectées, il est possible de proposer des interventions d'urgence et de redressement fiables, efficaces et ciblées. À l'origine, on a fait appel à la production ouverte et participative (crowdsourcing) pour la recherche de personnes, la cartographie des zones affectées et les décisions d'allocation des ressources. Cela a engendré un volume exorbitant de données, d'où la nécessité de parvenir à extraire l'information utile de cet ensemble de données et ce, en temps opportun. À mesure de l'évolution de la technologie, les organisations ont commencé à externaliser davantage de tâches, en les confiant d'abord à des tiers, puis à des machines. Étant donné que le volume des données générées dépasse les capacités humaines, l'analyse des données a été progressivement automatisée en recourant à l'intelligence artificielle et à l'apprentissage automatique, ce qui a amélioré nos capacités en matière d'analyse prédictive. Lorsqu'il s'agit de passer de la réhabilitation à la prévention, les informations doivent être recueillies et traitées de manière plus rapide et plus efficace, tout en maintenant leur exactitude. En outre, ces nouvelles stratégies et technologies peuvent nous aider à progresser en intégrant différentes strates de données provenant des secteurs de la santé humaine, vétérinaire, publique et environnementale, conformément à l'approche Une seule santé.

Los desastres y los brotes infecciosos vienen catalizando desde hace tiempo aplicaciones innovadoras de las nuevas tecnologías. La acuciante necesidad de responder a una emergencia obliga a aguzar el ingenio con las tecnologías que se tienen a mano. Con todo, el uso idóneo de las nuevas tecnologías, y el más efectivo en relación con el costo, pasa por prevenir las enfermedades y mejorar la resiliencia. Los autores presentan aquí diversos métodos que posibilitan ambas cosas. La interconexión planetaria hace posible que en el curso de las emergencias se reúnan y traten cada vez más datos, sobre todo con el auge de los datos de código abierto (incluidas las redes sociales). Por regla general, las poblaciones más pobres y aisladas son las más vulnerables a los desastres. Sin embargo, la existencia de tecnología cada vez más pequeña, rápida, inteligente, barata e interconectada hace posible una labor fiable, eficiente y selectiva de respuesta y recuperación. En un primer momento, los dispositivos de colaboración abierta (crowdsourcing) fueron utilizados para encontrar a personas, cartografiar áreas afectadas y determinar la asignación de recursos, todo lo cual generaba una ingente cantidad de datos y, a la vez, la necesidad de extraer de ellos información útil sin tardanza. A medida que la tecnología evolucionaba las organizaciones empezaron a externalizar muchas tareas, delegándolas primero en terceras personas y después en máquinas. Dado que el volumen de datos generados supera la capacidad humana, se tiende a automatizar el análisis de datos recurriendo a la inteligencia artificial y el aprendizaje automático, lo que potencia aún más nuestra capacidad de análisis predictivo. Cuanto más avanzamos hacia una lógica de prevención, dejando atrás la de mera reparación, más necesitamos procesos de recogida y tratamiento de datos cada vez más rápidos y eficientes, sin perder por ello en precisión. Por añadidura, estas nuevas estrategias y tecnologías pueden ayudarnos a avanzar gracias a la combinación de acervos de datos de salud humana, veterinaria, pública y ambiental, integrados todos ellos en clave de Una sola salud.

Ultrafast excited state dynamics of silver ion-mediated cytosine-cytosine base pairs in metallo-DNA.

To better understand the nexus between structure and photophysics in metallo-DNA assemblies, the parallel-stranded duplex formed by the all-cytosine oligonucleotide, dC20, and silver nitrate was studied by circular dichroism (CD), femtosecond transient absorption spectroscopy, and time-dependent-density functional theory calculations. Silver(I) ions mediate Cytosine-Cytosine (CC) base pairs by coordinating to the N3 atoms of two cytosines. Although these silver(I) mediated CC base pairs resemble the proton-mediated CC base pairs found in i-motif DNA at first glance, a comparison of experimental and calculated CD spectra reveals that silver ion-mediated i-motif structures do not form. Instead, the parallel-stranded duplex formed between dC20 and silver ions is proposed to contain consecutive silver-mediated base pairs with high propeller twist-like ones seen in a recent crystal structure of an emissive, DNA-templated silver cluster. Femtosecond transient absorption measurements with broadband probing from the near UV to the near IR reveal an unusually long-lived (>10 ns) excited state in the dC20 silver ion complex that is not seen in dC20 in single-stranded or i-motif forms. This state is also absent in a concentrated solution of cytosine-silver ion complexes that are thought to assemble into planar ribbons or sheets that lack stacked silver(I) mediated CC base pairs. The large propeller twist angle present in metal-mediated base pairs may promote the formation of long-lived charged separated or triplet states in this metallo-DNA.

Probing the heterogeneous structure of eumelanin using ultrafast vibrational fingerprinting.

Eumelanin is a brown-black biological pigment with sunscreen and radical scavenging functions important to numerous organisms. Eumelanin is also a promising redox-active material for energy conversion and storage, but the chemical structures present in this heterogeneous pigment remain unknown, limiting understanding of the properties of its light-responsive subunits. Here, we introduce an ultrafast vibrational fingerprinting approach for probing the structure and interactions of chromophores in heterogeneous materials like eumelanin. Specifically, transient vibrational spectra in the double-bond stretching region are recorded for subsets of electronic chromophores photoselected by an ultrafast excitation pulse tuned through the UV-visible spectrum. All subsets show a common vibrational fingerprint, indicating that the diverse electronic absorbers in eumelanin, regardless of transition energy, contain the same distribution of IR-active functional groups. Aggregation of chromophores diverse in oxidation state is the key structural property underlying the universal, ultrafast deactivation behavior of eumelanin in response to photoexcitation with any wavelength.

Wildlife impacts and vulnerable livelihoods in a transfrontier conservation landscape.

Interactions between humans and wildlife resulting in negative impacts are among the most pressing conservation challenges globally. In regions of smallholder livestock and crop production, interactions with wildlife can compromise human well-being and motivate negative sentiment and retaliation toward wildlife, undermining conservation goals. Although impacts may be unavoidable when human and wildlife land use overlap, scant large-scale human data exist quantifying the direct costs of wildlife to livelihoods. In a landscape of global importance for wildlife conservation in southern Africa, we quantified costs for people living with wildlife through a fundamental measure of human well-being, food security, and we tested whether existing livelihood strategies buffer certain households against crop depredation by wildlife, predominantly elephants. To do this, we estimated Bayesian multilevel statistical models based on multicounty household data (n = 711) and interpreted model results in the context of spatial data from participatory land-use mapping. Reported crop depredation by wildlife was widespread. Over half of the sample households were affected and household food security was reduced significantly (odds ratio 0.37 [0.22, 0.63]). The most food insecure households relied on gathered food sources and welfare programs. In the event of crop depredation by wildlife, these 2 livelihood sources buffered or reduced harmful effects of depredation. The presence of buffering strategies suggests a targeted compensation strategy could benefit the region's most vulnerable people. Such strategies should be combined with dynamic and spatially explicit land-use planning that may reduce the frequency of negative human-wildlife impacts. Quantifying and mitigating the human costs from wildlife are necessary steps in working toward human-wildlife coexistence.

Impactos de la Fauna y Medios de Subsistencia Vulnerables en unkl Paisaje de Conservación Transfronteriza Resumen Las interacciones entre los humanos y la fauna que resultan en impactos negativos se encuentran entre los desafíos más apremiantes para la conservación a nivel mundial. En las regiones de ganaderos y agricultores minifundistas, las interacciones con la fauna pueden poner en peligro el bienestar humano y motivar sentimientos negativos y represalias hacia la fauna, lo que debilita los objetivos de conservación. Aunque los impactos pueden evitarse cuando el uso de suelo por humanos y fauna se traslapa, existen pocos datos humanos a gran escala que cuantifiquen el costo directo de la fauna para los medios de subsistencia. Cuantificamos el costo para las personas que conviven con animales silvestres en un paisaje de importancia global para la conservación de fauna en el sur de África. La cuantificación fue realizada por medio de una medida fundamental de bienestar humano y seguridad alimentaria, y probamos si las estrategias existentes de subsistencia amortiguan a ciertos hogares ante la depredación de cultivos realizada por animales silvestres, predominantemente los elefantes. Para realizar esto, estimamos algunos modelos estadísticos bayesianos de niveles múltiples basados en los datos de hogares ubicados en múltiples condados (n = 711) e interpretamos los resultados de los modelos en el contexto de los datos espaciales a partir de un mapeo participativo de uso de suelo. La depredación de cultivos por animales silvestres fue reportada de manera generalizada. Más de la mitad de los hogares en la muestra estuvieron afectados y la seguridad alimenticia de los hogares se redujo significativamente (proporción de probabilidades 0.37 [0.22, 0.63]). Los hogares con la menor seguridad alimentaria dependían de fuentes de recolección de alimentos y programas de bienestar. En el evento de la depredación por fauna de los cultivos, estas dos fuentes de subsistencia amortiguaron o redujeron los efectos dañinos de la depredación. La presencia de las estrategias de amortiguamiento sugiere que una estrategia de compensación enfocada podría beneficiar a las personas más vulnerables de la región. Dichas estrategias deberían estar combinadas con la planeación del uso de suelo dinámica y espacialmente explícita, la cual podría reducir la frecuencia de los impactos negativos entre los humanos y la fauna. La cuantificación y mitificación del costo humano a partir de la fauna son pasos necesarios en el camino hacia la coexistencia entre los humanos y la fauna.

Annually modelling built-settlements between remotely-sensed observations using relative changes in subnational populations and lights at night.

Mapping urban features/human built-settlement extents at the annual time step has a wide variety of applications in demography, public health, sustainable development, and many other fields. Recently, while more multitemporal urban features/human built-settlement datasets have become available, issues still exist in remotely-sensed imagery due to spatial and temporal coverage, adverse atmospheric conditions, and expenses involved in producing such datasets. Remotely-sensed annual time-series of urban/built-settlement extents therefore do not yet exist and cover more than specific local areas or city-based regions. Moreover, while a few high-resolution global datasets of urban/built-settlement extents exist for key years, the observed date often deviates many years from the assigned one. These challenges make it difficult to increase temporal coverage while maintaining high fidelity in the spatial resolution. Here we describe an interpolative and flexible modelling framework for producing annual built-settlement extents. We use a combined technique of random forest and spatio-temporal dasymetric modelling with open source subnational data to produce annual 100 m × 100 m resolution binary built-settlement datasets in four test countries located in varying environmental and developmental contexts for test periods of five-year gaps. We find that in the majority of years, across all study areas, the model correctly identified between 85 and 99% of pixels that transition to built-settlement. Additionally, with few exceptions, the model substantially out performed a model that gave every pixel equal chance of transitioning to built-settlement in each year. This modelling framework shows strong promise for filling gaps in cross-sectional urban features/built-settlement datasets derived from remotely-sensed imagery, provides a base upon which to create urban future/built-settlement extent projections, and enables further exploration of the relationships between urban/built-settlement area and population dynamics.

Global spatio-temporally harmonised datasets for producing high-resolution gridded population distribution datasets.

Multi-temporal, globally consistent, high-resolution human population datasets provide consistent and comparable population distributions in support of mapping sub-national heterogeneities in health, wealth, and resource access, and monitoring change in these over time. The production of more reliable and spatially detailed population datasets is increasingly necessary due to the importance of improving metrics at sub-national and multi-temporal scales. This is in support of measurement and monitoring of UN Sustainable Development Goals and related agendas. In response to these agendas, a method has been developed to assemble and harmonise a unique, open access, archive of geospatial datasets. Datasets are provided as global, annual time series, where pertinent at the timescale of population analyses and where data is available, for use in the construction of population distribution layers. The archive includes sub-national census-based population estimates, matched to a geospatial layer denoting administrative unit boundaries, and a number of co-registered gridded geospatial factors that correlate strongly with population presence and density. Here, we describe these harmonised datasets and their limitations, along with the production workflow. Further, we demonstrate applications of the archive by producing multi-temporal gridded population outputs for Africa and using these to derive health and development metrics. The geospatial archive is available at https://doi.org/10.5258/SOTON/WP00650.

DNA-like Photophysics in Self-Assembled Silver(I)-Nucleobase Nanofibers.

Supramolecular assemblies form when silver nitrate is added to an aqueous solution of adenine (Ade) or 2-aminopurine (2AP) in a 2:1 mole ratio. Atomic force microscopy images reveal nanofibers that are ∼30 nm in diameter and micrometers in length in the dried film formed from a room-temperature solution. Femtosecond broadband transient absorption spectroscopy was used to investigate the dynamics of excited states formed by UV excitation of the nanofibers in room-temperature aqueous solutions in an effort to learn how nonradiative decay pathways of the uncomplexed nucleobases are altered in the silver-ion-mediated assemblies. The changes in the spectroscopy and dynamics of Ade and 2AP upon forming nanofibers with silver ions closely parallel the ones seen when these bases are organized into DNA strands. The similarities strongly suggest that these structures feature extensive π-π stacking interactions between nucleobases. The results show that time-resolved spectroscopy combined with growing understanding of the photophysics of DNA strands can deliver new insights into the properties of metal-nucleobase nanoassemblies.

Probing eumelanin photoprotection using a catechol:quinone heterodimer model system.

Eumelanin is a natural pigment with photoprotective and radical scavenging characteristics, which are vital for a multitude of living organisms. However, the molecular mechanisms behind these functions remain obscure, in part because eumelanin is a heterogeneous polymer composed of a complex assortment of structural and chemical domains. Despite uncertainty about its precise structure, the functional units of eumelanin are thought to include quinones in various oxidation states. Here, we investigate the photochemistry of a catechol : o-quinone heterodimer as a model system for uncovering the photoprotective roots of eumelanin. Ultrafast transient absorption measurements in the UV to near-IR spectral regions are used to identify the photochemical processes that follow selective excitation of the o-quinone in the heterodimer using 395 nm light. We find that both singlet and triplet o-quinone excited states induce hydrogen atom transfer from the catechol, forming semiquinone radical pairs that persist beyond 2.5 ns, which is the upper time limit accessible by our instrument. Furthermore, the hydrogen atom transfer reaction was found to occur 1000 times faster via the singlet channel. Excited state pathways such as these may be important in eumelanin, where similar hydrogen-bonded interfaces are believed to exist between catechol and o-quinone functional groups.

Isotopic substitution affects excited state branching in a DNA duplex in aqueous solution.

Changing the solvent from H2O to D2O dramatically affects the branching of the initial excited electronic states in an alternating G·C DNA duplex into two distinct decay channels. The slower, multisite PCET channel that deactivates more than half of all excited states in D2O becomes six times weaker in H2O.

Intermolecular Hydrogen Bonding Modulates O-H Photodissociation in Molecular Aggregates of a Catechol Derivative.

The catechol functional group plays a major role in the chemistry of a wide variety of molecules important in biology and technology. In eumelanin, intermolecular hydrogen bonding between these functional groups is thought to contribute to UV photoprotective and radical buffering properties, but the mechanisms are poorly understood. Here, aggregates of 4-t-butylcatechol are used as model systems to study how intermolecular hydrogen bonding influences photochemical pathways that may occur in eumelanin. Ultrafast UV-visible and mid-IR transient absorption measurements are used to identify the photochemical processes of 4-t-butylcatechol monomers and their hydrogen-bonded aggregates in cyclohexane solution. Monomer photoexcitation results in hydrogen atom ejection to the solvent via homolytic O-H bond dissociation with a time constant of 12 ps, producing a neutral semiquinone radical with a lifetime greater than 1 ns. In contrast, intermolecular hydrogen bonding interactions within aggregates retard O-H bond photodissociation by over an order of magnitude in time. Excited state structural relaxation is proposed to slow O-H dissociation, allowing internal conversion to the ground state to occur in hundreds of picoseconds in competition with this channel. The semiquinone radicals formed in the aggregates exhibit spectral broadening of both their electronic and vibrational transitions.

Ultrafast spectral hole burning reveals the distinct chromophores in eumelanin and their common photoresponse.

Eumelanin, the brown-black pigment found in organisms from bacteria to humans, dissipates solar energy and prevents photochemical damage. While the structure of eumelanin is unclear, it is thought to consist of an extremely heterogeneous collection of chromophores that absorb from the UV to the infrared, additively producing its remarkably broad absorption spectrum. However, the chromophores responsible for absorption by eumelanin and their excited state decay pathways remain highly uncertain. Using femtosecond broadband transient absorption spectroscopy, we address the excited state behavior of chromophore subsets that make up a synthetic eumelanin, DOPA melanin, and probe the heterogeneity of its chromophores. Tuning the excitation light over more than an octave from the UV to the visible and probing with the broadest spectral window used to study any form of melanin to date enable the detection of spectral holes with a linewidth of 0.6 eV that track the excitation wavelength. Transient spectral hole burning is a manifestation of extreme chemical heterogeneity, yet exciting these diverse chromophores unexpectedly produces a common photoinduced absorption spectrum and similar kinetics. This common photoresponse is assigned to the ultrafast formation of immobile charge transfer excitons that decay locally and that are formed among graphene-like chromophores in less than 200 fs. Raman spectroscopy reveals that chromophore heterogeneity in DOPA melanin arises from different sized domains of sp2-hybridized carbon and nitrogen atoms. Furthermore, we identify for the first time striking parallels between the excited state dynamics of eumelanin and disordered carbon nanomaterials, suggesting that they share common structural attributes.

Missing millions: undercounting urbanization in India.

The measurement and characterization of urbanization crucially depends upon defining what counts as urban. The government of India estimates that only 31% of the population is urban. We show that this is an artifact of the definition of urbanity and an underestimate of the level of urbanization in India. We use a random forest-based model to create a high-resolution (~ 100 m) population grid from district-level data available from the Indian Census for 2001 and 2011, a novel application of such methods to create temporally consistent population grids. We then apply a community-detection clustering algorithm to construct urban agglomerations for the entire country. Compared with the 2011 official statistics, we estimate 12% more of urban population, but find fewer mid-size cities. We also identify urban agglomerations that span jurisdictional boundaries across large portions of Kerala and the Gangetic Plain.

Evaluating nighttime lights and population distribution as proxies for mappinganthropogenic CO2 emission in Vietnam, Cambodia and Laos.

Tracking spatiotemporal changes in GHG emissions is key to successful implementation of the United Nations Framework Convention on Climate Change (UNFCCC). And while emission inventories often provide a robust tool to track emission trends at the country level, subnational emission estimates are often not reported or reports vary in robustness as the estimates are often dependent on the spatial modeling approach and ancillary data used to disaggregate the emission inventories. Assessing the errors and uncertainties of the subnational emission estimates is fundamentally challenging due to the lack of physical measurements at the subnational level. To begin addressing the current performance of modeled gridded CO2 emissions, this study compares two common proxies used to disaggregate CO2 emission estimates. We use a known gridded CO2 model based on satellite-observed nighttime light (NTL) data (Open Source Data Inventory for Anthropogenic CO2, ODIAC) and a gridded population dataset driven by a set of ancillary geospatial data. We examine the association at multiple spatial scales of these two datasets for three countries in Southeast Asia: Vietnam, Cambodia and Laos and characterize the spatiotemporal similarities and differences for 2000, 2005, and 2010. We specifically highlight areas of potential uncertainty in the ODIAC model, which relies on the single use of NTL data for disaggregation of the non-point emissions estimates. Results show, over time, how a NTL-based emissions disaggregation tends to concentrate CO2 estimates in different ways than population-based estimates at the subnational level. We discuss important considerations in the disconnect between the two modeled datasets and argue that the spatial differences between data products can be useful to identify areas affected by the errors and uncertainties associated with the NTL-based downscaling in a region with uneven urbanization rates.