Generation and analysis of a mouse multitissue genome annotation atlas.

Generating an accurate and complete genome annotation for an organism is complex because the cells within each tissue can express a unique set of transcript isoforms from a unique set of genes. A comprehensive genome annotation should contain information on what tissues express what transcript isoforms at what level. This tissue-level isoform information can then inform a wide range of research questions as well as experiment designs. Long-read sequencing technology combined with advanced full-length cDNA library preparation methods has now achieved throughput and accuracy where generating these types of annotations is achievable. Here, we show this by generating a genome annotation of the mouse (Mus musculus). We used the nanopore-based R2C2 long-read sequencing method to generate 64 million highly accurate full-length cDNA consensus reads-averaging 5.4 million reads per tissue for a dozen tissues. Using the Mandalorion tool, we processed these reads to generate the Tissue-level Atlas of Mouse Isoforms which is available as a trackhub for the UCSC Genome Browser and contains at least one full-length isoform for the vast majority of expressed genes in each tissue.

Systematic assessment of long-read RNA-seq methods for transcript identification and quantification.

The Long-read RNA-Seq Genome Annotation Assessment Project Consortium was formed to evaluate the effectiveness of long-read approaches for transcriptome analysis. Using different protocols and sequencing platforms, the consortium generated over 427 million long-read sequences from complementary DNA and direct RNA datasets, encompassing human, mouse and manatee species. Developers utilized these data to address challenges in transcript isoform detection, quantification and de novo transcript detection. The study revealed that libraries with longer, more accurate sequences produce more accurate transcripts than those with increased read depth, whereas greater read depth improved quantification accuracy. In well-annotated genomes, tools based on reference sequences demonstrated the best performance. Incorporating additional orthogonal data and replicate samples is advised when aiming to detect rare and novel transcripts or using reference-free approaches. This collaborative study offers a benchmark for current practices and provides direction for future method development in transcriptome analysis.

Sequencing Illumina libraries at high accuracy on the ONT MinION using R2C2.

High-throughput short-read sequencing has taken on a central role in research and diagnostics. Hundreds of different assays take advantage of Illumina short-read sequencers, the predominant short-read sequencing technology available today. Although other short-read sequencing technologies exist, the ubiquity of Illumina sequencers in sequencing core facilities and the high capital costs of these technologies have limited their adoption. Among a new generation of sequencing technologies, Oxford Nanopore Technologies (ONT) holds a unique position because the ONT MinION, an error-prone long-read sequencer, is associated with little to no capital cost. Here we show that we can make short-read Illumina libraries compatible with the ONT MinION by using the rolling circle to concatemeric consensus (R2C2) method to circularize and amplify the short library molecules. This results in longer DNA molecules containing tandem repeats of the original short library molecules. This longer DNA is ideally suited for the ONT MinION, and after sequencing, the tandem repeats in the resulting raw reads can be converted into high-accuracy consensus reads with similar error rates to that of the Illumina MiSeq. We highlight this capability by producing and benchmarking RNA-seq, ChIP-seq, and regular and target-enriched Tn5 libraries. We also explore the use of this approach for rapid evaluation of sequencing library metrics by implementing a real-time analysis workflow.

Unlocking ensemble ecosystem modelling for large and complex networks.

The potential effects of conservation actions on threatened species can be predicted using ensemble ecosystem models by forecasting populations with and without intervention. These model ensembles commonly assume stable coexistence of species in the absence of available data. However, existing ensemble-generation methods become computationally inefficient as the size of the ecosystem network increases, preventing larger networks from being studied. We present a novel sequential Monte Carlo sampling approach for ensemble generation that is orders of magnitude faster than existing approaches. We demonstrate that the methods produce equivalent parameter inferences, model predictions, and tightly constrained parameter combinations using a novel sensitivity analysis method. For one case study, we demonstrate a speed-up from 108 days to 6 hours, while maintaining equivalent ensembles. Additionally, we demonstrate how to identify the parameter combinations that strongly drive feasibility and stability, drawing ecological insight from the ensembles. Now, for the first time, larger and more realistic networks can be practically simulated and analysed.

Genotyping Plasmodium falciparum gametocytes using amplicon deep sequencing.

BACKGROUND: Understanding the dynamics of gametocyte production in polyclonal Plasmodium falciparum infections requires a genotyping method that detects distinct gametocyte clones and estimates their relative frequencies. Here, a marker was identified and evaluated to genotype P. falciparum mature gametocytes using amplicon deep sequencing. METHODS: A data set of polymorphic regions of the P. falciparum genome was mined to identify a gametocyte genotyping marker. To assess marker resolution, the number of unique haplotypes in the marker region was estimated from 95 Malawian P. falciparum whole genome sequences. Specificity of the marker for detection of mature gametocytes was evaluated using reverse transcription-polymerase chain reaction of RNA extracted from NF54 mature gametocytes and rings from a non-gametocyte-producing strain of P. falciparum. Amplicon deep sequencing was performed on experimental mixtures of mature gametocytes from two distinct parasite clones, as well as gametocyte-positive P. falciparum field isolates to evaluate the quantitative ability and determine the limit of detection of the genotyping approach. RESULTS: A 400 bp region of the pfs230 gene was identified as a gametocyte genotyping marker. A larger number of unique haplotypes was observed at the pfs230 marker (34) compared to the sera-2 (18) and ama-1 (14) markers in field isolates from Malawi. RNA and DNA genotyping accurately estimated gametocyte and total parasite clone frequencies when evaluating agreement between expected and observed haplotype frequencies in gametocyte mixtures, with concordance correlation coefficients of 0.97 [95% CI: 0.92-0.99] and 0.92 [95% CI: 0.83-0.97], respectively. The detection limit of the genotyping method for male gametocytes was 0.41 pfmget transcripts/µl [95% CI: 0.28-0.72] and for female gametocytes was 1.98 ccp4 transcripts/µl [95% CI: 1.35-3.68]. CONCLUSIONS: A region of the pfs230 gene was identified as a marker to genotype P. falciparum gametocytes. Amplicon deep sequencing of this marker can be used to estimate the number and relative frequency of parasite clones among mature gametocytes within P. falciparum infections. This gametocyte genotyping marker will be an important tool for studies aimed at understanding dynamics of gametocyte production in polyclonal P. falciparum infections.

Whole-genome analysis of Malawian Plasmodium falciparum isolates identifies possible targets of allele-specific immunity to clinical malaria.

Individuals acquire immunity to clinical malaria after repeated Plasmodium falciparum infections. Immunity to disease is thought to reflect the acquisition of a repertoire of responses to multiple alleles in diverse parasite antigens. In previous studies, we identified polymorphic sites within individual antigens that are associated with parasite immune evasion by examining antigen allele dynamics in individuals followed longitudinally. Here we expand this approach by analyzing genome-wide polymorphisms using whole genome sequence data from 140 parasite isolates representing malaria cases from a longitudinal study in Malawi and identify 25 genes that encode possible targets of naturally acquired immunity that should be validated immunologically and further characterized for their potential as vaccine candidates.

Cost-benefit analysis of ecosystem modeling to support fisheries management.

Mathematical and statistical models underlie many of the world's most important fisheries management decisions. Since the 19th century, difficulty calibrating and fitting such models has been used to justify the selection of simple, stationary, single-species models to aid tactical fisheries management decisions. Whereas these justifications are reasonable, it is imperative that we quantify the value of different levels of model complexity for supporting fisheries management, especially given a changing climate, where old methodologies may no longer perform as well as in the past. Here we argue that cost-benefit analysis is an ideal lens to assess the value of model complexity in fisheries management. While some studies have reported the benefits of model complexity in fisheries, modeling costs are rarely considered. In the absence of cost data in the literature, we report, as a starting point, relative costs of single-species stock assessment and marine ecosystem models from two Australian organizations. We found that costs varied by two orders of magnitude, and that ecosystem model costs increased with model complexity. Using these costs, we walk through a hypothetical example of cost-benefit analysis. The demonstration is intended to catalyze the reporting of modeling costs and benefits.

Complete characterization of the human immune cell transcriptome using accurate full-length cDNA sequencing.

The human immune system relies on highly complex and diverse transcripts and the proteins they encode. These include transcripts encoding human leukocyte antigen (HLA) receptors as well as B cell and T cell receptors (BCR and TCR). Determining which alleles an individual possesses for each HLA gene (high-resolution HLA typing) is essential to establish donor-recipient compatibility in organ and bone marrow transplantations. In turn, the repertoires of millions of unique BCR and TCR transcripts in each individual carry a vast amount of health-relevant information. Both short-read RNA-seq-based HLA typing and BCR/TCR repertoire sequencing (AIRR-seq) currently rely on our incomplete knowledge of the genetic diversity at HLA and BCR/TCR loci. Here, we generated over 10,000,000 full-length cDNA sequences at a median accuracy of 97.9% using our nanopore sequencing-based Rolling Circle Amplification to Concatemeric Consensus (R2C2) protocol. We used this data set to (1) show that deep and accurate full-length cDNA sequencing can be used to provide isoform-level transcriptome analysis for more than 9000 loci, (2) generate accurate sequences of HLA alleles, and (3) extract detailed AIRR data for the analysis of the adaptive immune system. The HLA and AIRR analysis approaches we introduce here are untargeted and therefore do not require prior knowledge of the composition or genetic diversity of HLA and BCR/TCR loci.

A New CSRML Structure-Based Fingerprint Method for Profiling and Categorizing Per- and Polyfluoroalkyl Substances (PFAS).

The term PFAS encompasses diverse per- and polyfluorinated alkyl (and increasingly aromatic) chemicals spanning industrial processes, commercial uses, environmental occurrence, and potential concerns. With increased chemical curation, currently exceeding 14,000 structures in the PFASSTRUCTV5 inventory on EPA's CompTox Chemicals Dashboard, has come increased motivation to profile, categorize, and analyze the PFAS structure space using modern cheminformatics approaches. Making use of the publicly available ToxPrint chemotypes and ChemoTyper application, we have developed a new PFAS-specific fingerprint set consisting of 129 TxP_PFAS chemotypes coded in CSRML, a chemical-based XML-query language. These are split into two groups, the first containing 56 mostly bond-type ToxPrints modified to incorporate attachment to either a CF group or F atom to enforce proximity to the fluorinated portion of the chemical. This focus resulted in a dramatic reduction in TxP_PFAS chemotype counts relative to the corresponding ToxPrint counts (averaging 54%). The remaining TxP_PFAS chemotypes consist of various lengths and types of fluorinated chains, rings, and bonding patterns covering indications of branching, alternate halogenation, and fluorotelomers. Both groups of chemotypes are well represented across the PFASSTRUCT inventory. Using the ChemoTyper application, we show how the TxP_PFAS chemotypes can be visualized, filtered, and used to profile the PFASSTRUCT inventory, as well as to construct chemically intuitive, structure-based PFAS categories. Lastly, we used a selection of expert-based PFAS categories from the OECD Global PFAS list to evaluate a small set of analogous structure-based TxP_PFAS categories. TxP_PFAS chemotypes were able to recapitulate the expert-based PFAS category concepts based on clearly defined structure rules that can be computationally implemented and reproducibly applied to process large PFAS inventories without need to consult an expert. The TxP_PFAS chemotypes have the potential to support computational modeling, harmonize PFAS structure-based categories, facilitate communication, and allow for more efficient and chemically informed exploration of PFAS chemicals moving forward.

Artemether-lumefantrine efficacy among adults on antiretroviral therapy in Malawi.

BACKGROUND: When people with human immunodeficiency virus (HIV) infection (PWH) develop malaria, they are at risk of poor anti-malarial treatment efficacy resulting from impairment in the immune response and/or drug-drug interactions that alter anti-malarial metabolism. The therapeutic efficacy of artemether-lumefantrine was evaluated in a cohort of PWH on antiretroviral therapy (ART) and included measurement of day 7 lumefantrine levels in a subset to evaluate for associations between lumefantrine exposure and treatment response. METHODS: Adults living with HIV (≥ 18 years), on ART for ≥ 6 months with undetectable HIV RNA viral load and CD4 count ≥ 250/mm3 were randomized to daily trimethoprim-sulfamethoxazole (TS), weekly chloroquine (CQ) or no prophylaxis. After diagnosis of uncomplicated Plasmodium falciparum malaria, a therapeutic efficacy monitoring was conducted with PCR-correction according to WHO guidelines. The plasma lumefantrine levels on day 7 in 100 episodes of uncomplicated malaria was measured. A frailty proportional hazards model with random effects models to account for clustering examined the relationship between participant characteristics and malaria treatment failure within 28 days. Pearson's Chi-squared test was used to compare lumefantrine concentrations among patients with treatment failure and adequate clinical and parasitological response (ACPR). RESULTS: 411 malaria episodes were observed among 186 participants over 5 years. The unadjusted ACPR rate was 81% (95% CI 77-86). However, after PCR correction to exclude new infections, ACPR rate was 94% (95% CI 92-97). Increasing age and living in Ndirande were associated with decreased hazard of treatment failure. In this population of adults with HIV on ART, 54% (51/94) had levels below a previously defined optimal day 7 lumefantrine level of 200 ng/ml. This occurred more commonly among participants who were receiving an efavirenz-based ART compared to other ART regimens (OR 5.09 [95% CI 1.52-7.9]). Participants who experienced treatment failure had lower day 7 median lumefantrine levels (91 ng/ml [95% CI 48-231]) than participants who experienced ACPR (190 ng/ml [95% CI 101-378], p-value < 0.008). CONCLUSION: Recurrent malaria infections are frequent in this population of PWH on ART. The PCR-adjusted efficacy of AL meets the WHO criteria for acceptable treatment efficacy. Nevertheless, lumefantrine levels tend to be low in this population, particularly in those on efavirenz-based regimens, with lower concentrations associated with more frequent malaria infections following treatment. These results highlight the importance of understanding drug-drug interactions when diseases commonly co-occur.

The impact of wildfires on air pollution and health across land use categories in Brazil over a 16-year period.

Forest fires cause many environmental impacts, including air pollution. Brazil is a very fire-prone region where few studies have investigated the impact of wildfires on air quality and health. We proposed to test two hypotheses in this study: i) the wildfires in Brazil have increased the levels of air pollution and posed a health hazard in 2003-2018, and ii) the magnitude of this phenomenon depends on the type of land use and land cover (e.g., forest area, agricultural area, etc.). Satellite and ensemble models derived data were used as input in our analyses. Wildfire events were retrieved from Fire Information for Resource Management System (FIRMS), provided by NASA; air pollution data from the Copernicus Atmosphere Monitoring Service (CAMS); meteorological variables from the ERA-Interim model; and land use/cover data were derived from pixel-based classification of Landsat satellite images by MapBiomas. We used a framework that infers the "wildfire penalty" by accounting for differences in linear pollutant annual trends (ß) between two models to test these hypotheses. The first model was adjusted for Wildfire-related Land Use activities (WLU), considered as an adjusted model. In the second model, defined as an unadjusted model, we removed the wildfire variable (WLU). Both models were controlled by meteorological variables. We used a generalized additive approach to fit these two models. To estimate mortality associated with wildfire penalties, we applied health impact function. Our findings suggest that wildfire events between 2003 and 2018 have increased the levels of air pollution and posed a significant health hazard in Brazil, supporting our first hypothesis. For example, in the Pampa biome, we estimated an annual wildfire penalty of 0.005 µg/m3 (95%CI: 0.001; 0.009) on PM2.5. Our results also confirm the second hypothesis. We observed that the greatest impact of wildfires on PM2.5 concentrations occurred in soybean areas in the Amazon biome. During the 16 years of the study period, wildfires originating from soybean areas in the Amazon biome were associated with a total penalty of 0.64 µg/m3 (95%CI: 0.32; 0.96) on PM2.5, causing an estimated 3872 (95%CI: 2560; 5168) excess deaths. Sugarcane crops were also a driver of deforestation-related wildfires in Brazil, mainly in Cerrado and Atlantic Forest biomes. Our findings suggest that between 2003 and 2018, fires originating from sugarcane crops were associated with a total penalty of 0.134 µg/m3 (95%CI: 0.037; 0.232) on PM2.5 in Atlantic Forest biome, resulting in an estimated 7600 (95%CI: 4400; 10,800) excess deaths during the study period, and 0.096 µg/m3 (95%CI: 0.048; 0.144) on PM2.5 in Cerrado biome, resulting in an estimated 1632 (95%CI: 1152; 2112) excess deaths during the study period. Considering that the wildfire penalties observed during our study period may continue to be a challenge in the future, this study should be of interest to policymakers to prepare future strategies related to forest protection, land use management, agricultural activities, environmental health, climate change, and sources of air pollution.

Long-term study of the cognitive profile of Moyamoya Disease in adults.

Moyamoya Disease (MMD) is a rare cerebrovascular disorder which can have significant cognitive consequences. The aim of the current study was to describe comprehensively the domain-specific cognitive profile of adult patients with MMD and to assess whether this changes in the absence of recurrent stroke over long-term follow-up. Comprehensive neuropsychological assessment covering seven cognitive domains was conducted on 61 adult patients with MMD at baseline and then at up to 3 further time points during follow up (median=2.31, 4.87 and 7.12 years). Although 27 patients had had prior surgical revasculariation, none had surgery between neuropsychological assessments. Cognitive impairment was common. At baseline, impairment in executive functions was most frequent (57%), followed by performance IQ (36%), speed of information processing (31%) and visual memory (30%). We found that the neuropsychological profile remains broadly stable over long-term follow-up with no clear indication of improvement or significant decline. The pattern of impairment also did not differ depending on age of onset or whether there was a history of either prior stroke at presentation or revascularisation surgery at presentation.

Iatrogenic cerebral amyloid angiopathy: an emerging clinical phenomenon.

In the last 6 years, following the first pathological description of presumed amyloid-beta (Aß) transmission in humans (in 2015) and subsequent experimental confirmation (in 2018), clinical cases of iatrogenic cerebral amyloid angiopathy (CAA)-attributed to the transmission of Aß seeds-have been increasingly recognised and reported. This newly described form of CAA is associated with early disease onset (typically in the third to fifth decade), and often presents with intracerebral haemorrhage, but also seizures and cognitive impairment. Although assumed to be rare, it is important that clinicians remain vigilant for potential cases, particularly as the optimal management, prognosis, true incidence and public health implications remain unknown. This review summarises our current understanding of the clinical spectrum of iatrogenic CAA and provides a diagnostic framework for clinicians. We provide clinical details for three patients with pathological evidence of iatrogenic CAA and present a summary of the published cases to date (n=20), identified following a systematic review. Our aims are: (1) To describe the clinical features of iatrogenic CAA, highlighting important similarities and differences between iatrogenic and sporadic CAA; and (2) To discuss potential approaches for investigation and diagnosis, including suggested diagnostic criteria for iatrogenic CAA.

Green areas and students' academic performance in the Federal District, Brazil: An assessment of three greenness metrics.

Most of the epidemiological investigations looking at the health benefits of green spaces have measured the level of green areas by using only one approach, mainly the Normalized Difference Index - NDVI (a satellite-derived indicator). We hypothesized a difference in the association between health and green space depending on the metric used to measure green exposure. This study considers students' academic performance as a proxy of cognitive abilities (a health indicator). We estimated the relationship between green areas and students' academic performance in the Federal District (FD), Brazil, with three different greenness metrics: NDVI, distance to green spaces (m) - obtained from land use data, and quantity of green spaces (m2) - also from land use data. We assessed student-level academic performance data provided by the Department of the Education in the FD. The data includes students from the public schools in the FD for 256 schools (all the public schools in the FD) and 344,175 students (all the students enrolled in the public schools in the FD in 2017-2020).). For the first metric represented by the distance to green spaces, we estimated the straight-line distance between each school and the nearest green area. For NDVI and quantity of green spaces, we estimated the area of all green spaces within buffers of 500 m, 750 m, and 1 km around the schools. We applied a cross-sectional study design using mixed-effects regression models to analyze the association exposure to green areas around schools and student-level academic performance. Our results confirmed our hypothesis showing that the impact of green areas on students' performance varied significantly depending on the type of green metric. After adjustments for the covariates, we estimated that NDVI is positively associated with school-level academic performance, with an estimated coefficient of 0.91 (95%CI: 0.83; 0.99) for NDVI values at a school's centroid. Distance to green areas was negatively associated with academic performance [-2.09 × 10-5 (95CI: 3.91 × 10-5; -2.84 × 10-6]. The quantity of green areas was estimated with mixed results (direction of the association), depending on the buffer size. Results from this paper suggest that epidemiological investigations must consider the different effects of greenness measures when looking at the association between green space and academic performance. More studies on residual confounding from this association with a different study design are needed to promote public health by making schools healthier.

Natural and human factors influencing urban particulate matter concentrations in central heating areas with long-term wearable monitoring devices.

In northern China, central heating, as an important source of urban particulate matter (UPM), causes more than half of the air pollution during the heating season and has significant spatial-temporal heterogeneity. Owing to the limitations of stationary air monitoring networks, few studies distinguish between heating/non-heating seasons and few have been conducted in urban areas. However, fixed monitoring cannot accurately capture the dynamic exposure of residents to UPM, and there is a lack of comprehensive evaluation of the factors affecting UPM. Therefore, this study used wearable Sniffer 4D equipment to monitor the concentrations of UPM (PM1, PM2.5, and PM10) in selected typical areas of Shenyang City from March 2019 to February 2020. A random forest model was combined with land use and point-of-interest data to analyze the contributions and marginal effects of multiple influences on UPM, in both heating and non-heating seasons. The results showed that in the eastern part of the study area, UPM showed completely opposite spatial distribution characteristics during the two seasons. The concentrations of UPM were higher during the heating season than during the non-heating season. The results indicated that temperature and humidity were important factors in diffusing UPM. The production and operation of boilers were important for the production of UPM. In two-dimensional landscape pattern indices, the percentage of forest and Shannon diversity index were the first and second most important factors, respectively. The three-dimensional pattern of buildings had important effects on the transport and diffusion of UPM (landscape height range >100, floor area ratio >1.3, and landscape volume density >5). Wearable devices could monitor the real situation of residents' exposure to UPM and quantify the factors influencing the spatial-temporal distribution of UPM in an ecological sense. These results provide a scientific basis for urban planning and for health risk reduction for residents.

One fly-one genome: chromosome-scale genome assembly of a single outbred Drosophila melanogaster.

A high quality genome assembly is a vital first step for the study of an organism. Recent advances in technology have made the creation of high quality chromosome scale assemblies feasible and low cost. However, the amount of input DNA needed for an assembly project can be a limiting factor for small organisms or precious samples. Here we demonstrate the feasibility of creating a chromosome scale assembly using a hybrid method for a low input sample, a single outbred Drosophila melanogaster. Our approach combines an Illumina shotgun library, Oxford nanopore long reads, and chromosome conformation capture for long range scaffolding. This single fly genome assembly has a N50 of 26 Mb, a length that encompasses entire chromosome arms, contains 95% of expected single copy orthologs, and a nearly complete assembly of this individual's Wolbachia endosymbiont. The methods described here enable the accurate and complete assembly of genomes from small, field collected organisms as well as precious clinical samples.

Can the Future-Like-Ours Argument Survive Ontological Scrutiny?

We argue that the future-like-ours argument against abortion rests on an important assumption. Namely, in the first trimester of an aborted pregnancy, there exists something that would have gone on to enjoy conscious mental states, had the abortion not occurred. To accommodate this assumption, we argue, a proponent of the future-like-ours argument must presuppose that there is ontic vagueness. We anticipate the objection that our argument achieves "too much" because it also applies mutatis mutandis to conscious humans. We respond by showing that an explanation can be given for why it is wrong to kill conscious humans that is independent of the underlying metaphysics. Our response brings into focus a reason why-at least in the context of an ethical argument like the future-like-ours argument-appeal to a highly controversial metaphysics is ad hoc. Such metaphysics is not necessary to explain the wrongness of killing conscious humans, only nonconscious fetuses.

Epitope-Specific Antibody Responses to a Plasmodium falciparum Subunit Vaccine Target in a Malaria-Endemic Population.

Circumsporozoite protein (CSP) coats the Plasmodium falciparum sporozoite surface and is a major malaria subunit vaccine target. We measured epitope-specific reactivity to field-derived CSP haplotypes in serum samples from Malian adults and children on a custom peptide microarray. Compared to children, adults showed greater antibody responses and responses to more variants in regions proximal to and within the central repeat region. Children acquired short-lived immunity to an epitope proximal to the central repeat region but not to the central repeat region itself. This approach has the potential to differentiate immunodominant from protective epitope-specific responses when combined with longitudinal infection data.

Distribution and Temporal Dynamics of Plasmodium falciparum Chloroquine Resistance Transporter Mutations Associated With Piperaquine Resistance in Northern Cambodia.

BACKGROUND: Newly emerged mutations within the Plasmodium falciparum chloroquine resistance transporter (PfCRT) can confer piperaquine resistance in the absence of amplified plasmepsin II (pfpm2). In this study, we estimated the prevalence of co-circulating piperaquine resistance mutations in P. falciparum isolates collected in northern Cambodia from 2009 to 2017. METHODS: The sequence of pfcrt was determined for 410 P. falciparum isolates using PacBio amplicon sequencing or whole genome sequencing. Quantitative polymerase chain reaction was used to estimate pfpm2 and pfmdr1 copy number. RESULTS: Newly emerged PfCRT mutations increased in prevalence after the change to dihydroartemisinin-piperaquine in 2010, with >98% of parasites harboring these mutations by 2017. After 2014, the prevalence of PfCRT F145I declined, being outcompeted by parasites with less resistant, but more fit PfCRT alleles. After the change to artesunate-mefloquine, the prevalence of parasites with amplified pfpm2 decreased, with nearly half of piperaquine-resistant PfCRT mutants having single-copy pfpm2. CONCLUSIONS: The large proportion of PfCRT mutants that lack pfpm2 amplification emphasizes the importance of including PfCRT mutations as part of molecular surveillance for piperaquine resistance in this region. Likewise, it is critical to monitor for amplified pfmdr1 in these PfCRT mutants, as increased mefloquine pressure could lead to mutants resistant to both drugs.

Associations between socioeconomic status and ultrafine particulate exposure in the school commute: An environmental inequality study for Toronto, Canada.

Ultrafine particulate matter (UFP) air pollution is unevenly distributed across urban environments. Disparities in routine activity patterns, such as the exposure risk we face at work or on the commute, can contribute to chronic exposure-related health outcomes that place excess burdening on vulnerable population groups. In Canada, there is disagreement in the literature on the nature of these exposure-related inequalities, and our understanding of disparities associated with specific activity patterns such as commuting is limited. In the context of UFP specific exposure, these relationships are almost entirely unexplored in the environmental inequality literature. Our study presents an exploratory analysis of UFP exposure patterns in Toronto, Canada. We examined UFP dosage disparities experienced by children during routine school commutes. We estimated single trip dosages that accounted for variation in ambient UFP concentration, route morphology (distance, slope) and their effect on inhalation rate and trip duration. We aggregated these values at the dissemination-area level and collected socioeconomic status descriptors from the 2016 census. Our OLS model showed significant spatial autocorrelation (MI = 0.59, p < 0.001), and we instead applied a spatial error model to account for spatial effects in our dataset. We identified significant associations related to median income (ß = -0.087, p < 0.05), government transfer dependence (ß = -0.107, p < 0.005), immigration status (ß = 0.119, p < 0.001), and education rates (ß = -0.059, p < 0.05). Our results diverged from other pollutants in Toronto-based literature and could indicate that UFPs exhibit unique patterns of inequality. Our findings suggest a need to further study UFP dosage from an environmental inequality perspective.