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©2015. American Geophysical Union. All Rights Reserved. As part of the Deep Convective Cloud and Chemistry (DC3) experiment, the National Science Foundation/National Center for Atmospheric Research (NCAR) Gulfstream-V (GV) and NASA DC-8 research aircraft probed the chemical composition of the inflow and outflow of two convective storms (north storm, NS, south storm, SS) originating in the Colorado region on 22 June 2012, a time when the High Park wildfire was active in the area. A wide range of trace species were measured on board both aircraft including biomass burning (BB) tracers hydrogen cyanide (HCN) and acetonitrile (ACN). Acrolein, a much shorter lived tracer for BB, was also quantified on the GV. The data demonstrated that the NS had ingested fresh smoke from the High Park fire and as a consequence had a higher VOC OH reactivity than the SS. The SS lofted aged fire tracers along with other boundary layer ozone precursors and was more impacted by lightning NOx (LNOx) than the NS. The NCAR master mechanism box model was initialized with measurements made in the outflow of the two storms. The NS and SS were predicted to produce 11 and 14ppbv of O3, respectively, downwind of the storm over 2days. Sensitivity tests revealed that the ozone production potential of the SS was highly dependent on LNOx. Normalized excess mixing ratios, ΔX/ΔCO, for HCN and ACN were determined in both the fire plume and the storm outflow and found to be 7.0±0.5 and 2.3±0.5pptvppbv-1, respectively, and 1.4±0.3pptvppbv-1 for acrolein in the outflow only.

Emissions of methane (CH4) and volatile organic compounds (VOCs) from oil and gas production may have large impacts on air quality and climate change. Methane and VOCs were measured over the Haynesville and Marcellus shale gas plays on board the National Center for Atmospheric Research C-130 and NOAA WP-3D research aircraft in June–July of 2013. We used an eddy covariance technique to measure in situ fluxes of CH4 and benzene from both C-130 flights with high-resolution data (10 Hz) and WP-3D flights with low-resolution data (1 Hz). Correlation (R = 0.65) between CH4 and benzene fluxes was observed when flying over shale gas operations, and the enhancement ratio of fluxes was consistent with the corresponding concentration observations. Fluxes calculated by the eddy covariance method show agreement with a mass balance approach within their combined uncertainties. In general, CH4 fluxes in the shale gas regions follow a lognormal distribution, with some deviations for relatively large fluxes (>10 μgm-2 s-1). Statistical analysis of the fluxes shows that a small number of facilities (i.e., ~10%) are responsible for up to ~40% of the total CH4 emissions in the two regions. We show that the airborne eddy covariance method can also be applied in some circumstances when meteorological conditions do not favor application of the mass balance method. We suggest that the airborne eddy covariance method is a reliable alternative and complementary analysis method to estimate emissions from oil and gas extraction.

Millions of livestock animals worldwide are infected with the haematophagous barber's pole worm, Haemonchus contortus, the aetiological agent of haemonchosis. Despite the major significance of this parasite worldwide and its widespread resistance to current treatments, the lack of a high-quality genome for the well-defined strain of this parasite from Australia, called Haecon-5, has constrained research in a number of areas including host-parasite interactions, drug discovery and population genetics. To enable research in these areas, we report here a chromosome-contiguous genome (∼280 Mb) for Haecon-5 with high-quality models for 19,234 protein-coding genes. Comparative genomic analyses show significant genomic similarity (synteny) with a UK strain of H. contortus, called MHco3(ISE).N1 (abbreviated as "ISE"), but we also discover marked differences in genomic structure/gene arrangements, distribution of nucleotide variability (single nucleotide polymorphisms (SNPs) and indels) and orthology between Haecon-5 and ISE. We used the genome and extensive transcriptomic resources for Haecon-5 to predict a subset of essential single-copy genes employing a "cross-species" machine learning (ML) approach using a range of features from nucleotide/protein sequences, protein orthology, subcellular localisation, single-cell RNA-seq and/or histone methylation data available for the model organisms Caenorhabditis elegans and Drosophila melanogaster. From a set of 1,464 conserved single copy genes, transcribed in key life-cycle stages of H. contortus, we identified 232 genes whose homologs have critical functions in C. elegans and/or D. melanogaster, and prioritised 10 of them for further characterisation; nine of the 10 genes likely play roles in neurophysiological processes, germline, hypodermis and/or respiration, and one is an unknown (orphan) gene for which no detailed functional information exists. Future studies of these genes/gene products are warranted to elucidate their roles in parasite biology, host-parasite interplay and/or disease. Clearly, the present Haecon-5 reference genome and associated resources now underpin a broad range of fundamental investigations of H. contortus and could assist in accelerating the discovery of novel intervention targets and drug candidates to combat haemonchosis., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

The Orthobunyavirus oropoucheense species encompasses a group of arthropod-borne zoonotic viruses transmitted by biting midges to animals including humans. Several large-scale human outbreaks caused by the prototype member of this species, Oropouche virus (OROV) have been documented since the 1970s and were primarily confined to the Amazon basin. However, since 2022, more widespread OROV outbreaks have been unfolding in Brazil and across South America, with cases exported to Cuba, Italy, Spain, USA and Germany. In Brazil, the virus has reached and established communitary transmission in all geographic areas of the country. We isolated, characterized the cytopathic effect and recovered the full genome of two OROV isolates from the 2022-24 outbreak detected in patients from the Pernambuco state. Phylogenetic data supports a direct introduction from the Amazonas state, the epicenter of the epidemics in the country. As case counts accumulate in the state mounting evidence is supporting the establishiment of sustained transmission chains. Continued studies are critical to understand the transmission cycle in this region, including the most important vectors and reservoirs, to appropriately deploy control measures., (© 2024 The Author(s). Journal of Medical Virology published by Wiley Periodicals LLC.)

Multisystem Inflammatory Syndrome in Children (MIS-C) is a rare, potentially fatal complication of SARS-CoV-2 infection. Genetic defects in inflammation-related pathways have been linked to MIS-C, but additional research is needed, especially in diverse ethnic groups. The present study aimed to identify genetic variants underlying MIS-C in Brazilian patients. Whole-exome sequencing was performed, focusing on genes involved in the host immune response to SARS-CoV-2. Functional assays assessed the impact of selected variants on NF-κB signaling. Nine rare, potentially deleterious variants were found in eight of 21 patients, located in IL17RC, IFNA10, or NLRP12 genes. Unlike the wild-type NLRP12 protein, which inhibits NF-κB activation in HEK 293T cells, the mutant NLRP12 proteins have significantly reduced inhibitory properties. In conclusion, our results indicate that rare autosomal variants in immune-related genes may underlie MIS-C, highlighting the potential role of NLRP12 in its predisposition. These findings provide new insights for the appropriate management of MIS-C., (© The Author(s) 2024. Published by Oxford University Press on behalf of Infectious Diseases Society of America. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

The Brazilian western Amazon is experiencing its largest laboratory-confirmed Oropouche virus (OROV) outbreak, with more than 6,300 reported cases between 2022 and 2024. In this study, we sequenced and analyzed 382 OROV genomes from human samples collected in Amazonas, Acre, Rondônia and Roraima states, between August 2022 and February 2024, to uncover the origin and genetic evolution of OROV in the current outbreak. Genomic analyses revealed that the upsurge of OROV cases in the Brazilian Amazon coincides with spread of a novel reassortant lineage containing the M segment of viruses detected in the eastern Amazon region (2009-2018) and the L and S segments of viruses detected in Peru, Colombia and Ecuador (2008-2021). The novel reassortant likely emerged in the Amazonas state between 2010 and 2014 and spread through long-range dispersion events during the second half of the 2010s. Phylodynamics reconstructions showed that the current OROV spread was driven mainly by short-range (< 2 km) movements consistent with the flight range of vectors. Nevertheless, a substantial proportion (22%) of long-range (>10 km) OROV migrations were also detected, consistent with viral dispersion by humans. Our data provide a view of the unprecedented spread and evolution of OROV in the Brazilian western Amazon region., (© 2024. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Detailed explorations of the model organisms Caenorhabditis elegans (elegant worm) and Drosophila melanogaster (vinegar fly) have substantially improved our knowledge and understanding of biological processes and pathways in metazoan organisms. Extensive functional genomic and multi-omic data sets have enabled the discovery and characterisation of 'essential' genes that are critical for the survival of these organisms. Recently, we showed that a machine learning (ML)-based pipeline could be utilised to predict essential genes in both C. elegans and D. melanogaster using features from DNA, RNA, protein and/or cellular data or associated information. As these distantly-related species are within the Ecdysozoa, we hypothesised that this approach could be suited for non-model organisms within the same group (phylum) of protostome animals. In the present investigation, we cross-predicted essential genes within the phylum Nematoda - between C. elegans and the parasitic filarial nematodes Brugia malayi and Onchocerca volvulus , and then ranked and prioritised these genes. Highly ranked genes were linked to key biological pathways or processes, such as ribosome biogenesis, translation and RNA processing, and were expressed at relatively high levels in the germline, gonad, hypodermis and/or nerves. The present in silico workflow is hoped to expedite the identification of drug targets in parasitic organisms for subsequent experimental validation in the laboratory., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors. Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology.)

Over the years, comprehensive explorations of the model organisms Caenorhabditis elegans (elegant worm) and Drosophila melanogaster (vinegar fly) have contributed substantially to our understanding of complex biological processes and pathways in multicellular organisms generally. Extensive functional genomic-phenomic, genomic, transcriptomic, and proteomic data sets have enabled the discovery and characterisation of genes that are crucial for life, called 'essential genes'. Recently, we investigated the feasibility of inferring essential genes from such data sets using advanced bioinformatics and showed that a machine learning (ML)-based workflow could be used to extract or engineer features from DNA, RNA, protein, and/or cellular data/information to underpin the reliable prediction of essential genes both within and between C. elegans and D. melanogaster . As these are two distantly related species within the Ecdysozoa, we proposed that this ML approach would be particularly well suited for species that are within the same phylum or evolutionary clade. In the present study, we cross-predicted essential genes within the phylum Nematoda (evolutionary clade V)-between C. elegans and the pathogenic parasitic nematode H. contortus -and then ranked and prioritised H. contortus proteins encoded by these genes as intervention (e.g., drug) target candidates. Using strong, validated predictors, we inferred essential genes of H. contortus that are involved predominantly in crucial biological processes/pathways including ribosome biogenesis, translation, RNA binding/processing, and signalling and which are highly transcribed in the germline, somatic gonad precursors, sex myoblasts, vulva cell precursors, various nerve cells, glia, or hypodermis. The findings indicate that this in silico workflow provides a promising avenue to identify and prioritise panels/groups of drug target candidates in parasitic nematodes for experimental validation in vitro and/or in vivo.

ViralFlow v1.0 is a computational workflow developed for viral genomic surveillance. Several key changes turned ViralFlow into a general-purpose reference-based genome assembler for all viruses with an available reference genome. New virus-agnostic modules were implemented to further study nucleotide and amino acid mutations. ViralFlow v1.0 runs on a broad range of computational infrastructures, from laptop computers to high-performance computing (HPC) environments, and generates standard and well-formatted outputs suited for both public health reporting and scientific problem-solving. ViralFlow v1.0 is available at: https://viralflow.github.io/index-en.html., (© The Author(s) 2024. Published by Oxford University Press on behalf of NAR Genomics and Bioinformatics.)

The Mayaro virus (MAYV) is an arbovirus with emerging potential, though with a limited understanding of its epidemiology and evolution due to the lack of studies and surveillance. Here, we investigated 71 MAYV genome sequences from the Americas available at GenBank and characterized the phylogenetic relationship among virus strains. A phylogenetic analysis showed that sequences were grouped according to the genotypes L, D, and N. Genotype D sequences were closely related to sequences collected in adjacent years and from their respective countries, suggesting that isolates may have originated from circulating lineages. The coalescent analysis demonstrated similar results, indicating the continuous circulation of the virus between countries as well. An unidentified sequence from the USA was grouped with genotype D, suggesting the insertion of this genotype in the country. Furthermore, the recombination analysis detected homologous and three heterologous hybrids which presented an insertion into the nsP3 protein. Amino acid substitutions among sequences indicated selective pressure sites, suggesting viral adaptability. This also impacted the binding affinity between the E1-E2 protein complex and the Mxra8 receptor, associated with MAYV entry into human cells. These results provide information for a better understanding of genotypes circulating in the Americas.

Advances in single cell technologies are allowing investigations of a wide range of biological processes and pathways in animals, such as the multicellular model organism Caenorhabditis elegans - a free-living nematode. However, there has been limited application of such technology to related parasitic nematodes which cause major diseases of humans and animals worldwide. With no vaccines against the vast majority of parasitic nematodes and treatment failures due to drug resistance or inefficacy, new intervention targets are urgently needed, preferably informed by a deep understanding of these nematodes' cellular and molecular biology - which is presently lacking for most worms. Here, we created the first single cell atlas for an early developmental stage of Haemonchus contortus - a highly pathogenic, C. elegans -related parasitic nematode. We obtained and curated RNA sequence (snRNA-seq) data from single nuclei from embryonating eggs of H. contortus (150,000 droplets), and selected high-quality transcriptomic data for > 14,000 single nuclei for analysis, and identified 19 distinct clusters of cells. Guided by comparative analyses with C. elegans , we were able to reproducibly assign seven cell clusters to body wall muscle, hypodermis, neuronal, intestinal or seam cells, and identified eight genes that were transcribed in all cell clusters/types, three of which were inferred to be essential in H. contortus . Two of these genes (i.e. Hc-eef-1A and Hc-eef1G ), coding for eukaryotic elongation factors (called Hc- eEF1A and Hc -eEF1G), were also demonstrated to be transcribed and expressed in all key developmental stages of H. contortus. Together with these findings, sequence- and structure-based comparative analyses indicated the potential of Hc -eEF1A and/or Hc -eEF1G as intervention targets within the protein biosynthesis machinery of H. contortus . Future work will focus on single cell studies of all key developmental stages and tissues of H. contortus , and on evaluating the suitability of the two elongation factor proteins as drug targets in H. contortus and related nematodes, with a view to finding new nematocidal drug candidates., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

The identification and characterization of essential genes are central to our understanding of the core biological functions in eukaryotic organisms, and has important implications for the treatment of diseases caused by, for example, cancers and pathogens. Given the major constraints in testing the functions of genes of many organisms in the laboratory, due to the absence of in vitro cultures and/or gene perturbation assays for most metazoan species, there has been a need to develop in silico tools for the accurate prediction or inference of essential genes to underpin systems biological investigations. Major advances in machine learning approaches provide unprecedented opportunities to overcome these limitations and accelerate the discovery of essential genes on a genome-wide scale. Here, we developed and evaluated a large language model- and graph neural network (LLM-GNN)-based approach, called 'Bingo', to predict essential protein-coding genes in the metazoan model organisms Caenorhabditis elegans and Drosophila melanogaster as well as in Mus musculus and Homo sapiens (a HepG2 cell line) by integrating LLM and GNNs with adversarial training. Bingo predicts essential genes under two 'zero-shot' scenarios with transfer learning, showing promise to compensate for a lack of high-quality genomic and proteomic data for non-model organisms. In addition, the attention mechanisms and GNNExplainer were employed to manifest the functional sites and structural domain with most contribution to essentiality. In conclusion, Bingo provides the prospect of being able to accurately infer the essential genes of little- or under-studied organisms of interest, and provides a biological explanation for gene essentiality., (© The Author(s) 2023. Published by Oxford University Press.)

Dengue virus serotype 2, genotype Cosmopolitan (DENV-2-GII), is one of the most widespread DENV strains globally. In the USA, DENV-2 epidemics have been dominated by DENV-2 genotype Asian-American (DENV-2-GIII), and the first cases of DENV-2-GII were only described in 2019, in Peru, and in 2021 in Brazil. To gain new information about the circulation of DENV-2-GII in Brazil, we sequenced 237 DENV-2 confirmed cases sampled between March 2021 and March 2023 and revealed that DENV-2-GII is already present in all geographic regions of Brazil. The phylogeographic analysis inferred that DENV-2-GII was introduced at least four times in Brazil, between May 2020 and August 2022, generating multiple clades that spread throughout the country with different success. Despite multiple introductions of DENV-2-GII, analysis of the country-wide laboratory surveillance data showed that the Brazilian dengue epidemic in 2022 was dominated by DENV-1 in most states. We hypothesize that massive circulation of DENV-2-GIII in previous years in Brazil might have created a population immune barrier against symptomatic homotypic reinfections by DENV-2-GII, leading to sustained cryptic circulation in asymptomatic cases and localized outbreaks of this new genotype. In summary, our study stresses the importance of arboviral genomic surveillance to close monitoring and better understanding the potential impact of DENV-2-GII in the coming years., Competing Interests: The authors report there are no competing interests to declare., (© The Author(s) 2023. Published by Oxford University Press.)

Objectives: We aimed to investigate the real-life performance of the rapid antigen test in the context of a primary healthcare setting, including symptomatic and asymptomatic individuals that sought diagnosis during an Omicron infection wave., Methods: We prospectively accessed the performance of the DPP SARS-CoV-2 Antigen test in the context of an Omicron-dominant real-life setting. We evaluated 347 unselected individuals (all-comers) from a public testing centre in Brazil, performing the rapid antigen test diagnosis at point-of-care with fresh samples. The combinatory result from two distinct real-time quantitative PCR (RT-qPCR) methods was employed as a reference and 13 samples with discordant PCR results were excluded., Results: The assessment of the rapid test in 67 PCR-positive and 265 negative samples revealed an overall sensitivity of 80.5% (CI 95% = 69.1%-89.2%), specificity of 99.2% (CI 95% = 97.3%-99.1%) and positive/negative predictive values higher than 95%. However, we observed that the sensitivity was dependent on the viral load (sensitivity in Ct < 31 = 93.7%, CI = 82.8%-98.7%; Ct > 31 = 47.4%, CI = 24.4%-71.1%). The positive samples evaluated in the study were Omicron (BA.1/BA.1.1) by whole-genome sequencing (n = 40) and multiplex RT-qPCR (n = 17)., Conclusions: Altogether, the data obtained from a real-life prospective cohort supports that the rapid antigen test sensitivity for Omicron remains high and underscores the reliability of the test for COVID-19 diagnosis in settings with high disease prevalence and limited PCR testing capability., (Copyright © 2022 European Society of Clinical Microbiology and Infectious Diseases. Published by Elsevier Ltd. All rights reserved.)

Acinetobacter baumannii is Gram-negative pathogen with extensive role in healthcare-associated infections (HAIs). Plasmids in this species are important carriers of antimicrobial resistance genes. In this work, we investigated the plasmids of 227 Brazilian A. baumannii genomes. A total of 389 plasmid sequences with 424 Rep proteins typed to 22 different homology groups (GRs) were identified. The GR2 plasmid group was the most predominant (40.6%), followed by the GR4 group (16.7%), representing ∼57% of all plasmids. There is a wide distribution of plasmids among the isolates and most strains carry more than one plasmid. Our analyses revealed a significant prevalence of GR4 plasmids in Brazilian A. baumannii genomes carrying several antimicrobial resistance genes, notably to carbapenem (39.43%). These plasmids harbor a MOBQ relaxase that might confer increased spreading potential in the environment. Most plasmids of the predominant groups belong to the same plasmid taxonomic unit (PTU-Pse7) and have a AbkA/AbkB toxin-antitoxin system that has a role in plasmid stability and dissemination of carbapenem resistance genes. The results of this work should contribute to our understanding of the molecular content of plasmids in a large and populous country, highlighting the importance of genomics for enhanced epidemiological surveillance., (© The Author(s) 2023. Published by Oxford University Press on behalf of FEMS.)

The COVID-19 pandemic is driven by Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) that emerged in 2019 and quickly spread worldwide. Genomic surveillance has become the gold standard methodology used to monitor and study this fast-spreading virus and its constantly emerging lineages. The current deluge of SARS-CoV-2 genomic data generated worldwide has put additional pressure on the urgent need for streamlined bioinformatics workflows. Here, we describe a workflow developed by our group to process and analyze large-scale SARS-CoV-2 Illumina amplicon sequencing data. This workflow automates all steps of SARS-CoV-2 reference-based genomic analysis: data processing, genome assembly, PANGO lineage assignment, mutation analysis and the screening of intrahost variants. The pipeline is capable of processing a batch of around 100 samples in less than half an hour on a personal laptop or in less than five minutes on a server with 50 threads. The workflow presented here is available through Docker or Singularity images, allowing for implementation on laptops for small-scale analyses or on high processing capacity servers or clusters. Moreover, the low requirements for memory and CPU cores and the standardized results provided by ViralFlow highlight it as a versatile tool for SARS-CoV-2 genomic analysis.

The availability of high-quality genomes and advances in functional genomics have enabled large-scale studies of essential genes in model eukaryotes, including the 'elegant worm' (Caenorhabditis elegans; Nematoda) and the 'vinegar fly' (Drosophila melanogaster; Arthropoda). However, this is not the case for other, much less-studied organisms, such as socioeconomically important parasites, for which functional genomic platforms usually do not exist. Thus, there is a need to develop innovative techniques or approaches for the prediction, identification and investigation of essential genes. A key approach that could enable the prediction of such genes is machine learning (ML). Here, we undertake an historical review of experimental and computational approaches employed for the characterisation of essential genes in eukaryotes, with a particular focus on model ecdysozoans (C. elegans and D. melanogaster), and discuss the possible applicability of ML-approaches to organisms such as socioeconomically important parasites. We highlight some recent results showing that high-performance ML, combined with feature engineering, allows a reliable prediction of essential genes from extensive, publicly available 'omic data sets, with major potential to prioritise such genes (with statistical confidence) for subsequent functional genomic validation. These findings could 'open the door' to fundamental and applied research areas. Evidence of some commonality in the essential gene-complement between these two organisms indicates that an ML-engineering approach could find broader applicability to ecdysozoans such as parasitic nematodes or arthropods, provided that suitably large and informative data sets become/are available for proper feature engineering, and for the robust training and validation of algorithms. This area warrants detailed exploration to, for example, facilitate the identification and characterisation of essential molecules as novel targets for drugs and vaccines against parasitic diseases. This focus is particularly important, given the substantial impact that such diseases have worldwide, and the current challenges associated with their prevention and control and with drug resistance in parasite populations., (Copyright © 2021 The Author(s). Published by Elsevier Inc. All rights reserved.)

Background: The ZIKA virus (ZIKV) belongs to the Flaviviridae family, was first isolated in the 1940s, and remained underreported until its global threat in 2016, where drastic consequences were reported as Guillan-Barre syndrome and microcephaly in newborns. Understanding molecular interactions of ZIKV proteins during the host infection is important to develop treatments and prophylactic measures; however, large-scale experimental approaches normally used to detect protein-protein interaction (PPI) are onerous and labor-intensive. On the other hand, computational methods may overcome these challenges and guide traditional approaches on one or few protein molecules. The prediction of PPIs can be used to study host-parasite interactions at the protein level and reveal key pathways that allow viral infection., Results: Applying Random Forest and Support Vector Machine (SVM) algorithms, we performed predictions of PPI between two ZIKV strains and human proteomes. The consensus number of predictions of both algorithms was 17,223 pairs of proteins. Functional enrichment analyses were executed with the predicted networks to access the biological meanings of the protein interactions. Some pathways related to viral infection and neurological development were found for both ZIKV strains in the enrichment analysis, but the JAK-STAT pathway was observed only for strain PE243 when compared with the FSS13025 strain., Conclusions: The consensus network of PPI predictions made by Random Forest and SVM algorithms allowed an enrichment analysis that corroborates many aspects of ZIKV infection. The enrichment results are mainly related to viral infection, neuronal development, and immune response, and presented differences among the two compared ZIKV strains. Strain PE243 presented more predicted interactions between proteins from the JAK-STAT signaling pathway, which could lead to a more inflammatory immune response when compared with the FSS13025 strain. These results show that the methodology employed in this study can potentially reveal new interactions between the ZIKV and human cells., Competing Interests: The authors declare that they have no competing interests., (© 2021 Pitta et al.)

Decades of air quality improvements have substantially reduced the motor vehicle emissions of volatile organic compounds (VOCs). Today, volatile chemical products (VCPs) are responsible for half of the petrochemical VOCs emitted in major urban areas. We show that VCP emissions are ubiquitous in US and European cities and scale with population density. We report significant VCP emissions for New York City (NYC), including a monoterpene flux of 14.7 to 24.4 kg ⋅ d -1 ⋅ km -2 from fragranced VCPs and other anthropogenic sources, which is comparable to that of a summertime forest. Photochemical modeling of an extreme heat event, with ozone well in excess of US standards, illustrates the significant impact of VCPs on air quality. In the most populated regions of NYC, ozone was sensitive to anthropogenic VOCs (AVOCs), even in the presence of biogenic sources. Within this VOC-sensitive regime, AVOCs contributed upwards of ∼20 ppb to maximum 8-h average ozone. VCPs accounted for more than 50% of this total AVOC contribution. Emissions from fragranced VCPs, including personal care and cleaning products, account for at least 50% of the ozone attributed to VCPs. We show that model simulations of ozone depend foremost on the magnitude of VCP emissions and that the addition of oxygenated VCP chemistry impacts simulations of key atmospheric oxidation products. NYC is a case study for developed megacities, and the impacts of VCPs on local ozone are likely similar for other major urban regions across North America or Europe., Competing Interests: The authors declare no competing interest.

Introduction: Population aging is associated with increased prevalence of cardiovascular diseases that have a significant impact on overall morbidity and mortality. Insulin resistance (IR) and visceral obesity are risk factors for vascular damage and cardiometabolic diseases., Aims: Estimating the correlation between lipid accumulation product (LAP) and IR in elderly individuals and comparing them to traditional anthropometric indices., Methods: Cross-sectional study comprising 411 individuals >60 years, who were treated in a primary care service. Body mass index (BMI), neck circumference (NC), waist circumference (WC), hip circumference (HC), arm circumference (AC), sagittal abdominal diameter (SAD) and waist-hip ratio (WHR) were recorded. IR was estimated based on HOMA-IR (homeostasis model assessment IR index). LAP a index was calculated as [WC-65]×[triglyceride (TG)] in men, and as [WC-58]×[TG] in women, whereas LAP b was calculated by using the minimum WC values recorded for the current sample, i.e., 61.5 cm for women and 71.5 cm for men., Results: There was correlation among LAP a (0.506), LAP b (0.515) and HOMA-IR. LAP was better correlated to HOMA-IR and showed higher area under the curve than BMI, NC, WHR and SAD. Based on the receiver operating characteristic curve analysis, LAP b ≥47.40 and LAP a ≥52.5 were the best cut-off values used to identify individuals with IR presenting 68.8% and 68.2% sensitivity, and 68.6% and 68.6% specificity, respectively., Conclusion: LAP may be a useful and simple clinical marker to assess cardiometabolic risk factors in the elderly population treated at a primary care service., (Copyright © 2021 Sociedade Portuguesa de Cardiologia. Published by Elsevier España, S.L.U. All rights reserved.)

Experimental studies of Caenorhabditis elegans and Drosophila melanogaster have contributed substantially to our understanding of molecular and cellular processes in metazoans at large. Since the publication of their genomes, functional genomic investigations have identified genes that are essential or non-essential for survival in each species. Recently, a range of features linked to gene essentiality have been inferred using a machine learning (ML)-based approach, allowing essentiality predictions within a species. Nevertheless, predictions between species are still elusive. Here, we undertake a comprehensive study using ML to discover and validate features of essential genes common to both C. elegans and D. melanogaster . We demonstrate that the cross-species prediction of gene essentiality is possible using a subset of features linked to nucleotide/protein sequences, protein orthology and subcellular localisation, single-cell RNA-seq, and histone methylation markers. Complementary analyses showed that essential genes are enriched for transcription and translation functions and are preferentially located away from heterochromatin regions of C. elegans and D. melanogaster chromosomes. The present work should enable the cross-prediction of essential genes between model and non-model metazoans.

OGEE is an Online GEne Essentiality database. Gene essentiality is not a static and binary property, rather a context-dependent and evolvable property in all forms of life. In OGEE we collect not only experimentally tested essential and non-essential genes, but also associated gene properties that contributes to gene essentiality. We tagged conditionally essential genes that show variable essentiality statuses across datasets to highlight complex interplays between gene functions and environmental/experimental perturbations. OGEE v3 contains gene essentiality datasets for 91 species; almost doubled from 48 species in previous version. To accommodate recent advances on human cancer essential genes (as known as tumor dependency genes) that could serve as targets for cancer treatment and/or drug development, we expanded the collection of human essential genes from 16 cell lines in previous to 581. These human cancer cell lines were tested with high-throughput experiments such as CRISPR-Cas9 and RNAi; in total, 150 of which were tested by both techniques. We also included factors known to contribute to gene essentiality for these cell lines, such as genomic mutation, methylation and gene expression, along with extensive graphical visualizations for ease of understanding of these factors. OGEE v3 can be accessible freely at https://v3.ogee.info., (© The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Trichomonas vaginalis is a protozoan parasite that causes trichomoniasis, the most prevalent non-viral sexually transmitted infection worldwide. Trichomonas vaginalis releases extracellular vesicles that play a role in parasite:parasite and parasite:host interactions. The aim of this study was to characterise the RNA cargo of these vesicles. Trichomonas vaginalis extracellular vesicles were found to encapsulate a cargo of RNAs of small size. RNA-seq analysis showed that tRNA-derived small RNAs, mostly 5' tRNA halves, are the main type of small RNA in these vesicles. The tRNA-derived small RNAs in T. vaginalis extracellular vesicles were shown to be derived from the specific processing of tRNAs within cells. The specificity of this RNA cargo in T. vaginalis extracellular vesicles suggests a preference for packaging. The RNA cargo of T. vaginalis was shown to be rapidly internalised by human cells via lipid raft-dependent endocytosis. The potential role of these tsRNAs - an emerging class of small RNAs with regulatory functions - on altering host cellular responses requires further examination, suggesting a new mode of parasite:host communication., (Copyright © 2020 Australian Society for Parasitology. Published by Elsevier Ltd. All rights reserved.)

The evolution of organic aerosol (OA) and brown carbon (BrC) in wildfire plumes, including the relative contributions of primary versus secondary sources, has been uncertain in part because of limited knowledge of the precursor emissions and the chemical environment of smoke plumes. We made airborne measurements of a suite of reactive trace gases, particle composition, and optical properties in fresh western US wildfire smoke in July through August 2018. We use these observations to quantify primary versus secondary sources of biomass-burning OA (BBPOA versus BBSOA) and BrC in wildfire plumes. When a daytime wildfire plume dilutes by a factor of 5 to 10, we estimate that up to one-third of the primary OA has evaporated and subsequently reacted to form BBSOA with near unit yield. The reactions of measured BBSOA precursors contribute only 13 ± 3% of the total BBSOA source, with evaporated BBPOA comprising the rest. We find that oxidation of phenolic compounds contributes the majority of BBSOA from emitted vapors. The corresponding particulate nitrophenolic compounds are estimated to explain 29 ± 15% of average BrC light absorption at 405 nm (BrC Abs 405 ) measured in the first few hours of plume evolution, despite accounting for just 4 ± 2% of average OA mass. These measurements provide quantitative constraints on the role of dilution-driven evaporation of OA and subsequent radical-driven oxidation on the fate of biomass-burning OA and BrC in daytime wildfire plumes and point to the need to understand how processing of nighttime emissions differs., Competing Interests: The authors declare no competing interest.

Characterizing genes that are critical for the survival of an organism (i.e. essential) is important to gain a deep understanding of the fundamental cellular and molecular mechanisms that sustain life. Functional genomic investigations of the vinegar fly, Drosophila melanogaster , have unravelled the functions of numerous genes of this model species, but results from phenomic experiments can sometimes be ambiguous. Moreover, the features underlying gene essentiality are poorly understood, posing challenges for computational prediction. Here, we harnessed comprehensive genomic-phenomic datasets publicly available for D. melanogaster and a machine-learning-based workflow to predict essential genes of this fly. We discovered strong predictors of such genes, paving the way for computational predictions of essentiality in less-studied arthropod pests and vectors of infectious diseases., (© The Author(s) 2019. Published by Oxford University Press on behalf of NAR Genomics and Bioinformatics.)

Acinetobacter baumannii is an opportunistic bacterial pathogen infecting immunocompromised patients and has gained attention worldwide due to its increased antimicrobial resistance. Here, we report a comparative whole-genome sequencing and analysis coupled with an assessment of antibiotic resistance of 46 Acinetobacter strains (45 A. baumannii plus one Acinetobacter nosocomialis ) originated from five hospitals from the city of Recife, Brazil, between 2010 and 2014. An average of 3,809 genes were identified per genome, although only 2,006 genes were single copy orthologs or core genes conserved across all sequenced strains, with an average of 42 new genes found per strain. We evaluated genetic distance through a phylogenetic analysis and MLST as well as the presence of antibiotic resistance genes, virulence markers and mobile genetic elements (MGE). The phylogenetic analysis recovered distinct monophyletic A. baumannii groups corresponding to five known (ST1, ST15, ST25, ST79, and ST113) and one novel ST (ST881, related to ST1). A large number of ST specific genes were found, with the ST79 strains having the largest number of genes in common that were missing from the other STs. Multiple genes associated with resistance to β-lactams, aminoglycosides and other antibiotics were found. Some of those were clearly mapped to defined MGEs and an analysis of those revealed known elements as well as a novel Tn 7 -Tn 3 transposon with a clear ST specific distribution. An association of selected resistance/virulence markers with specific STs was indeed observed, as well as the recent spread of the OXA-253 carbapenemase encoding gene. Virulence genes associated with the synthesis of the capsular antigens were noticeably more variable in the ST113 and ST79 strains. Indeed, several resistance and virulence genes were common to the ST79 and ST113 strains only, despite a greater genetic distance between them, suggesting common means of genetic exchange. Our comparative analysis reveals the spread of multiple STs and the genomic plasticity of A. baumannii from different hospitals in a single metropolitan area. It also highlights differences in the spread of resistance markers and other MGEs between the investigated STs, impacting on the monitoring and treatment of Acinetobacter in the ongoing and future outbreaks., (Copyright © 2020 Leal, Campos, Rezende, Docena, Mendes-Marques, de Sá Cavalcanti, Wallau, Rocha, Cavalcanti, Veras, Alves, Andrade-Figueiredo, de Barros, de Almeida, de Morais, Leal-Balbino, Xavier and de-Melo-Neto.)

Defining genes that are essential for life has major implications for understanding critical biological processes and mechanisms. Although essential genes have been identified and characterised experimentally using functional genomic tools, it is challenging to predict with confidence such genes from molecular and phenomic data sets using computational methods. Using extensive data sets available for the model organism Caenorhabditis elegans , we constructed here a machine-learning (ML)-based workflow for the prediction of essential genes on a genome-wide scale. We identified strong predictors for such genes and showed that trained ML models consistently achieve highly-accurate classifications. Complementary analyses revealed an association between essential genes and chromosomal location. Our findings reveal that essential genes in C. elegans tend to be located in or near the centre of autosomal chromosomes; are positively correlated with low single nucleotide polymorphim (SNP) densities and epigenetic markers in promoter regions; are involved in protein and nucleotide processing; are transcribed in most cells; are enriched in reproductive tissues or are targets for small RNAs bound to the argonaut CSR-1. Based on these results, we hypothesise an interplay between epigenetic markers and small RNA pathways in the germline, with transcription-based memory; this hypothesis warrants testing. From a technical perspective, further work is needed to evaluate whether the present ML-based approach will be applicable to other metazoans (including Drosophila melanogaster ) for which comprehensive data sets (i.e. genomic, transcriptomic, proteomic, variomic, epigenetic and phenomic) are available., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2020 The Authors.)

Aeromonads are mainly opportunistic pathogens; however, many species are emerging as important human pathogens. Therefore, monitoring these bacteria and their accurate characterization of its species is highly important. Aeromonas Aer593 strain was recovered from a diarrhoea outbreak and did not group with any previously described Aeromonas species by housekeeping gene sequencing. To clarify the taxonomic position of Aer593, its genome was sequenced and analysed by multilocus phylogenetic analysis (MLPA), in silico DNA-DNA hybridization (isDDH), average nucleotide identity (ANI) and core genome-based phylogenetic analyzes. The MLPA with the housekeeping genes gyrB, rpoD, recA, dnaJ, gyrA and dnaX ranked the Aer593 isolate into an independent branch suggesting that it could represent a new species. However, the identity percentages of Aer593 to A. caviae strains using robust genomic analysis by isDDH and ANI were at least 81.3% and 97.8%, respectively, defining Aer593 as A. caviae. Multilocus sequence typing (MLST) presented an exact match against only a single allele (groL96) and the novel ST648 was assigned for this strain. The core genome-based phylogenetic analyses with a total of 863 orthologous genes also grouped the Aer593 isolate with A. caviae reference strains. These findings warn about the possibility of misidentification of some Aeromonas strains by MLPA and show that high-resolution genome-wide analysis is essential for the correct identification of ambiguous Aeromonas strains., (© FEMS 2019.)

The availability of whole-genome sequences and associated multi-omics data sets, combined with advances in gene knockout and knockdown methods, has enabled large-scale annotation and exploration of gene and protein functions in eukaryotes. Knowing which genes are essential for the survival of eukaryotic organisms is paramount for an understanding of the basic mechanisms of life, and could assist in identifying intervention targets in eukaryotic pathogens and cancer. Here, we studied essential gene orthologs among selected species of eukaryotes, and then employed a systematic machine-learning approach, using protein sequence-derived features and selection procedures, to investigate essential gene predictions within and among species. We showed that the numbers of essential gene orthologs comprise small fractions when compared with the total number of orthologs among the eukaryotic species studied. In addition, we demonstrated that machine-learning models trained with subsets of essentiality-related data performed better than random guessing of gene essentiality for a particular species. Consistent with our gene ortholog analysis, the predictions of essential genes among multiple (including distantly-related) species is possible, yet challenging, suggesting that most essential genes are unique to a species. The present work provides a foundation for the expansion of genome-wide essentiality investigations in eukaryotes using machine learning approaches.

Chikungunya virus (CHIKV) is an RNA virus from the Togaviridae family transmitted by mosquitoes in both sylvatic and urban cycles. In humans, CHIKV infection leads to a febrile illness, denominated Chikungunya fever (CHIKF), commonly associated with more intense and debilitating outcomes. CHIKV arrived in Brazil in 2014 through two independent introductions: the Asian/Caribbean genotype entered through the North region and the African ECSA genotype was imported through the Northeast region. Following their initial introduction, both genotypes established their urban cycle among large naive human populations causing several outbreaks in the Americas. Here, we sequenced CHIKV genomes from a recent outbreak in the Northeast region of Brazil, employing an in-house developed Next-Generation Sequencing (NGS) protocol capable of directly detecting multiple known CHIKV genotypes from clinical positive samples. Our results demonstrate that both Asian/Caribbean and ECSA genotypes expanded their ranges, reaching cocirculation in the Northeast region of Brazil. In addition, our NGS data supports the findings of simultaneous infection by these two genotypes, suggesting that coinfection might be more common than previously thought in highly endemic areas. Future efforts to understand CHIKV epidemiology should thus take into consideration the possibility of coinfection by different genotypes in the human population., Competing Interests: The authors have declared that no competing interests exist.

The rapid worldwide spread of chikungunya (CHIKV), dengue (DENV), and Zika (ZIKV) viruses have raised great international concern. Knowledge about the entry routes and geographic expansion of these arboviruses to the mainland Americas remain incomplete and controversial. Epidemics caused by arboviruses continue to cause socioeconomic burden globally, particularly in countries where vector control is difficult due to climatic or infrastructure factors. Understanding how the virus circulates and moves from one country to another is of paramount importance to assist government and health officials in anticipating future epidemics, as well as to take steps to help control or mitigate the spread of the virus. Through the analyses of the sequences of arbovirus genomes collected at different locations over time, we identified patterns of accumulated mutations, being able to trace routes of dispersion of these viruses. Here, we applied robust phylogenomic methods to trace the evolutionary dynamics of these arboviruses with special focus on Brazil, the epicenter of these triple epidemics. Our results show that CHIKV, DENV-1-4, and ZIKV followed a similar path prior to their first introductions into the mainland Americas, underscoring the need for systematic arboviral surveillance at major entry points of human population movement between countries such as airports and seaports.

Sulfate ([Formula: see text]) and nitrate ([Formula: see text]) account for half of the fine particulate matter mass over the eastern United States. Their wintertime concentrations have changed little in the past decade despite considerable precursor emissions reductions. The reasons for this have remained unclear because detailed observations to constrain the wintertime gas-particle chemical system have been lacking. We use extensive airborne observations over the eastern United States from the 2015 Wintertime Investigation of Transport, Emissions, and Reactivity (WINTER) campaign; ground-based observations; and the GEOS-Chem chemical transport model to determine the controls on winter [Formula: see text] and [Formula: see text] GEOS-Chem reproduces observed [Formula: see text]-[Formula: see text]-[Formula: see text] particulate concentrations (2.45 μg [Formula: see text]) and composition ([Formula: see text]: 47%; [Formula: see text]: 32%; [Formula: see text]: 21%) during WINTER. Only 18% of [Formula: see text] emissions were regionally oxidized to [Formula: see text] during WINTER, limited by low [H 2 O 2 ] and [OH]. Relatively acidic fine particulates (pH∼1.3) allow 45% of nitrate to partition to the particle phase. Using GEOS-Chem, we examine the impact of the 58% decrease in winter [Formula: see text] emissions from 2007 to 2015 and find that the H 2 O 2 limitation on [Formula: see text] oxidation weakened, which increased the fraction of [Formula: see text] emissions oxidizing to [Formula: see text] Simultaneously, NOx emissions decreased by 35%, but the modeled [Formula: see text] particle fraction increased as fine particle acidity decreased. These feedbacks resulted in a 40% decrease of modeled [[Formula: see text]] and no change in [[Formula: see text]], as observed. Wintertime [[Formula: see text]] and [[Formula: see text]] are expected to change slowly between 2015 and 2023, unless [Formula: see text] and NOx emissions decrease faster in the future than in the recent past., Competing Interests: The authors declare no conflict of interest.

We present airborne observations of gaseous reactive halogen species (HCl, Cl 2 , ClNO 2 , Br 2 ,BrNO 2 , and BrCl), sulfur dioxide (SO 2 ), and nonrefractory fine particulate chloride (pCl) and sulfate(pSO 4 ) in power plant exhaust. Measurements were conducted during the Wintertime INvestigation of Transport, Emissions, and Reactivity campaign in February-March of 2015 aboard the NCAR-NSF C-130 aircraft. Fifty air mass encounters were identified in which SO 2 levels were elevated ~5 ppb above ambient background levels and in proximity to operational power plants. Each encounter was attributed to one or more potential emission sources using a simple wind trajectory analysis. In case studies, we compare measured emission ratios to those reported in the 2011 National Emissions Inventory and present evidence of the conversion of HCl emitted from power plants to ClNO 2 . Taking into account possible chemical conversion downwind, there was general agreement between the observed and reported HCl: SO 2 emission ratios. Reactive bromine species (Br 2 , BrNO 2 , and/or BrCl) were detected in the exhaust of some coal-fired power plants, likely related to the absence of wet flue gas desulfurization emission control technology. Levels of bromine species enhanced in some encounters exceeded those expected assuming all of the native bromide in coal was released to the atmosphere, though there was no reported use of bromide salts (as a way to reduce mercury emissions) during Wintertime INvestigation of Transport, Emissions, and Reactivity observations. These measurements represent the first ever in-flight observations of reactive gaseous chlorine and bromine containing compounds present in coal-fired power plant exhaust.

Horizontal Transfer (HT) of genetic material between species is a common phenomenon among Bacteria and Archaea species and several databases are available for information retrieval and data mining. However, little attention has been given to this phenomenon among eukaryotic species mainly due to the lower proportion of these events. In the last years, a vertiginous amount of new HT events involving eukaryotic species was reported in the literature, highlighting the need of a common repository to keep the scientific community up to date and describe overall trends. Recently, we published the first HT database focused on HT of transposable elements among eukaryotes: the Horizontal Transposon Transfer DataBase (http://lpa.saogabriel.unipampa.edu.br: 8080/httdatabase/). Here, we present new features and updates of this unique database: (i) its expansion to include virus-host exchange of genetic material, which we called Horizontal Virus Transfer (HVT) and (ii) the availability of a web server for HT detection, where we implemented the online version of vertical and horizontal inheritance consistence analysis (VHICA), an R package developed for HT detection. These improvements will help researchers to navigate through known HVT cases, take data-informed decision and export figures based on keywords searches. Moreover, the availability of the VHICA as an online tool will make this software easily reachable even for researchers with no or little computation knowledge as well as foster our capability to detect new HT events in a wide variety of taxa. (Database URL: http://lpa.saogabriel.unipampa.edu.br:8080/httdatabase/)., (© The Author(s) 2018. Published by Oxford University Press.)

The Convective Transport of Active Species in the Tropics (CONTRAST) experiment was conducted from Guam (13.5° N, 144.8° E) during January-February 2014. Using the NSF/NCAR Gulfstream V research aircraft, the experiment investigated the photochemical environment over the tropical western Pacific (TWP) warm pool, a region of massive deep convection and the major pathway for air to enter the stratosphere during Northern Hemisphere (NH) winter. The new observations provide a wealth of information for quantifying the influence of convection on the vertical distributions of active species. The airborne in situ measurements up to 15 km altitude fill a significant gap by characterizing the abundance and altitude variation of a wide suite of trace gases. These measurements, together with observations of dynamical and microphysical parameters, provide significant new data for constraining and evaluating global chemistry climate models. Measurements include precursor and product gas species of reactive halogen compounds that impact ozone in the upper troposphere/lower stratosphere. High accuracy, in-situ measurements of ozone obtained during CONTRAST quantify ozone concentration profiles in the UT, where previous observations from balloon-borne ozonesondes were often near or below the limit of detection. CONTRAST was one of the three coordinated experiments to observe the TWP during January-February 2014. Together, CONTRAST, ATTREX and CAST, using complementary capabilities of the three aircraft platforms as well as ground-based instrumentation, provide a comprehensive quantification of the regional distribution and vertical structure of natural and pollutant trace gases in the TWP during NH winter, from the oceanic boundary to the lower stratosphere.

The aim of this article was to discuss the recommendation of mammogram screening for breast cancer and its technical basis. The first part discusses criteria for the decision, which should be consistent with high-quality scientific evidence. The second part discusses over-diagnosis (the greatest harm of screening) and its meaning in questioning the natural history of disease model. The third part summarizes studies on the efficacy, effectiveness, and harms of screening, showing that the latter (especially over-diagnosis and false-positives) are significant, shedding doubt on the balance between harms and benefits. In conclusion, the recommendation of mammogram screening at any age should be reconsidered by Brazilian health authorities.

Air parcels with mixing ratios of high O3 and low H2O (HOLW) are common features in the tropical western Pacific (TWP) mid-troposphere (300-700 hPa). Here, using data collected during aircraft sampling of the TWP in winter 2014, we find strong, positive correlations of O3 with multiple biomass burning tracers in these HOLW structures. Ozone levels in these structures are about a factor of three larger than background. Models, satellite data and aircraft observations are used to show fires in tropical Africa and Southeast Asia are the dominant source of high O3 and that low H2O results from large-scale descent within the tropical troposphere. Previous explanations that attribute HOLW structures to transport from the stratosphere or mid-latitude troposphere are inconsistent with our observations. This study suggest a larger role for biomass burning in the radiative forcing of climate in the remote TWP than is commonly appreciated.

Halogens in the troposphere are increasingly recognized as playing an important role for atmospheric chemistry, and possibly climate. Bromine and iodine react catalytically to destroy ozone (O3), oxidize mercury, and modify oxidative capacity that is relevant for the lifetime of greenhouse gases. Most of the tropospheric O3 and methane (CH4) loss occurs at tropical latitudes. Here we report simultaneous measurements of vertical profiles of bromine oxide (BrO) and iodine oxide (IO) in the tropical and subtropical free troposphere (10 °N to 40 °S), and show that these halogens are responsible for 34% of the column-integrated loss of tropospheric O3. The observed BrO concentrations increase strongly with altitude (∼ 3.4 pptv at 13.5 km), and are 2-4 times higher than predicted in the tropical free troposphere. BrO resembles model predictions more closely in stratospheric air. The largest model low bias is observed in the lower tropical transition layer (TTL) over the tropical eastern Pacific Ocean, and may reflect a missing inorganic bromine source supplying an additional 2.5-6.4 pptv total inorganic bromine (Bry), or model overestimated Bry wet scavenging. Our results highlight the importance of heterogeneous chemistry on ice clouds, and imply an additional Bry source from the debromination of sea salt residue in the lower TTL. The observed levels of bromine oxidize mercury up to 3.5 times faster than models predict, possibly increasing mercury deposition to the ocean. The halogen-catalyzed loss of tropospheric O3 needs to be considered when estimating past and future ozone radiative effects.