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Abstract Tuberculosis disease (TB), caused by Mycobacterium tuberculosis (Mtb), is a major global public health problem, resulting in > 1 million deaths each year. Drug resistance (DR), including the multi-drug form (MDR-TB), is challenging control of the disease. Whilst many DR mutations in the Mtb genome are known, analysis of large datasets generated using whole genome sequencing (WGS) platforms can reveal new variants through the assessment of genotype-phenotype associations. Here, we apply tree-based ensemble methods to a dataset comprised of 35,777 Mtb WGS and phenotypic drug-susceptibility test data across first- and second-line drugs. We compare model performance across models trained using mutations in drug-specific regions and genome-wide variants, and find high predictive ability for both first-line (area under ROC curve (AUC); range 88.3–96.5) and second-line (AUC range 84.1–95.4) drugs. To aggregate information from low-frequency variants, we pool mutations by functional impact and observe large improvements in predictive accuracy (e.g., sensitivity: pyrazinamide + 25%; ethionamide + 10%). We further characterise loss-of-function mutations observed in resistant phenotypes, uncovering putative markers of resistance (e.g., ndh 293dupG, Rv3861 78delC). Finally, we profile the distribution of known DR-associated single nucleotide polymorphisms across discretised minimum inhibitory concentration (MIC) data generated from phenotypic testing (n = 12,066), and identify mutations associated with highly resistant phenotypes (e.g., inhA − 779G > T and 62T > C). Overall, our work demonstrates that applying machine learning to large-scale WGS data is useful for providing insights into predicting Mtb binary drug resistance and MIC phenotypes, thereby potentially assisting diagnosis and treatment decision-making for infection control.

Abstract Tuberculosis (TB) remains one of the leading infectious disease killers in the world. The ongoing development of novel anti-TB medications has yielded potent compounds that often target single sites with well-defined mechanisms of action. However, despite the identification of resistance-associated mutations through target deconvolution studies, comparing these findings with the diverse Mycobacterium tuberculosis populations observed in clinical settings is often challenging. To address this gap, we constructed an open-access database encompassing genetic variations from > 50,000 clinical isolates, spanning the entirety of the M. tuberculosis protein-encoding genome. This resource offers a valuable tool for investigating the prevalence of target-based resistance mutations in any drug target within clinical contexts. To demonstrate the practical application of this dataset in drug discovery, we focused on drug targets currently undergoing phase II clinical trials. By juxtaposing genetic variations of these targets with resistance mutations derived from laboratory-adapted strains, we identified multiple positions across three targets harbouring resistance-associated mutations already present in clinical isolates. Furthermore, our analysis revealed a discernible correlation between genetic diversity within each protein and their predicted essentiality. This meta-analysis, openly accessible via a dedicated dashboard, enables comprehensive exploration of genetic diversity pertaining to any drug target or resistance determinant in M. tuberculosis.

Abstract The Philippines is a high-incidence country for tuberculosis, with the increasing prevalence of multi- (MDR-TB) and extensively-drug (XDR-TB) resistant Mycobacterium tuberculosis strains posing difficulties to disease control. Understanding the genetic diversity of circulating strains can provide insights into underlying drug resistance mutations and transmission dynamics, thereby assisting the design of diagnostic tools, including those using next generation sequencing (NGS) platforms. By analysing genome sequencing data of 732 isolates from Philippines drug-resistance survey collections spanning from 2011 to 2019, we found that the majority belonged to lineages L1 (531/732; 72.5%) and L4 (European-American; n = 174; 23.8%), with the Manila strain (L1.2.1.2.1) being the most prominent (475/531). Approximately two-thirds of isolates were found to be at least MDR-TB (483/732; 66.0%), and potential XDR-TB genotypic resistance was observed (3/732; 0.4%), highlighting an emerging problem in the country. Genotypic resistance was highly concordant with laboratory drug susceptibility testing. By finding isolates with (near-)identical genomic variation, five major clusters containing a total of 114 isolates were identified: all containing either L1 or L4 isolates with at least MDR-TB resistance and spanning multiple years of collection. Closer inspection of clusters revealed transmission in prisons, some involving isolates with XDR-TB, and mutations linked to third-line drug bedaquiline. We have also identified previously unreported mutations linked to resistance for isoniazid, rifampicin, ethambutol, and fluoroquinolones. Overall, this study provides important insights into the genetic diversity, transmission and circulating drug resistance mutations of M. tuberculosis in the Philippines, thereby informing clinical and surveillance decision-making, which is increasingly using NGS platforms.

Airway macrophages (AM) are the predominant immune cell in the lung and play a crucial role in preventing infection, making them a target for host directed therapy. Macrophage effector functions are associated with cellular metabolism. A knowledge gap remains in understanding metabolic reprogramming and functional plasticity of distinct human macrophage subpopulations, especially in lung resident AM. We examined tissue-resident AM and monocyte-derived macrophages (MDM; as a model of blood derived macrophages) in their resting state and after priming with IFN-γ or IL-4 to model the Th1/Th2 axis in the lung. Human macrophages, regardless of origin, had a strong induction of glycolysis in response to IFN-γ or upon stimulation. IFN-γ significantly enhanced cellular energetics in both AM and MDM by upregulating both glycolysis and oxidative phosphorylation. Upon stimulation, AM do not decrease oxidative phosphorylation unlike MDM which shift to ‘Warburg’-like metabolism. IFN-γ priming promoted cytokine secretion in AM. Blocking glycolysis with 2-deoxyglucose significantly reduced IFN-γ driven cytokine production in AM, indicating that IFN-γ induces functional plasticity in human AM, which is mechanistically mediated by glycolysis. Directly comparing responses between macrophages, AM were more responsive to IFN-γ priming and dependent on glycolysis for cytokine secretion than MDM. Interestingly, TNF production was under the control of glycolysis in AM and not in MDM. MDM exhibited glycolysis-dependent upregulation of HLA-DR and CD40, whereas IFN-γ upregulated HLA-DR and CD40 on AM independently of glycolysis. These data indicate that human AM are functionally plastic and respond to IFN-γ in a manner distinct from MDM. These data provide evidence that human AM are a tractable target for inhalable immunomodulatory therapies for respiratory diseases.

Abstract Tuberculosis (TB), caused by Mycobacterium tuberculosis, has a significant impact on global health worldwide. The development of multi-drug resistant strains that are resistant to the first-line drugs isoniazid and rifampicin threatens public health security. Rifampicin and isoniazid resistance are largely underpinned by mutations in rpoB and katG respectively and are associated with fitness costs. Compensatory mutations are considered to alleviate these fitness costs and have been observed in rpoC/rpoA (rifampicin) and oxyR’-ahpC (isoniazid). We developed a framework (CompMut-TB) to detect compensatory mutations from whole genome sequences from a large dataset comprised of 18,396 M . tuberculosis samples. We performed association analysis (Fisher’s exact tests) to identify pairs of mutations that are associated with drug-resistance, followed by mediation analysis to identify complementary or full mediators of drug-resistance. The analyses revealed several potential mutations in rpoC (N = 47), rpoA (N = 4), and oxyR’-ahpC (N = 7) that were considered either ‘highly likely’ or ‘likely’ to confer compensatory effects on drug-resistance, including mutations that have previously been reported and validated. Overall, we have developed the CompMut-TB framework which can assist with identifying compensatory mutations which is important for more precise genome-based profiling of drug-resistant TB strains and to further understanding of the evolutionary mechanisms that underpin drug-resistance.

Abstract A significant number of pregnancies are lost in the first trimester and 1–2% are ectopic pregnancies (EPs). Early pregnancy loss in general can cause significant morbidity with bleeding or infection, while EPs are the leading cause of maternal mortality in the first trimester. Symptoms of pregnancy loss and EP are very similar (including pain and bleeding); however, these symptoms are also common in live normally sited pregnancies (LNSP). To date, no biomarkers have been identified to differentiate LNSP from pregnancies that will not progress beyond early gestation (non-viable or EPs), defined together as combined adverse outcomes (CAO). In this study, we present a novel machine learning pipeline to create prediction models that identify a composite biomarker to differentiate LNSP from CAO in symptomatic women. This prospective cohort study included 370 participants. A single blood sample was prospectively collected from participants on first emergency presentation prior to final clinical diagnosis of pregnancy outcome: LNSP, miscarriage, pregnancy of unknown location (PUL) or tubal EP (tEP). Miscarriage, PUL and tEP were grouped together into a CAO group. Human chorionic gonadotrophin β (β-hCG) and progesterone concentrations were measured in plasma. Serum samples were subjected to untargeted metabolomic profiling. The cohort was randomly split into train and validation data sets, with the train data set subjected to variable selection. Nine metabolite signals were identified as key discriminators of LNSP versus CAO. Random forest models were constructed using stable metabolite signals alone, or in combination with plasma hormone concentrations and demographic data. When comparing LNSP with CAO, a model with stable metabolite signals only demonstrated a modest predictive accuracy (0.68), which was comparable to a model of β-hCG and progesterone (0.71). The best model for LNSP prediction comprised stable metabolite signals and hormone concentrations (accuracy = 0.79). In conclusion, serum metabolite levels and biochemical markers from a single blood sample possess modest predictive utility in differentiating LNSP from CAO pregnancies upon first presentation, which is improved by variable selection and combination using machine learning. A diagnostic test to confirm LNSP and thus exclude pregnancies affecting maternal morbidity and potentially life-threatening outcomes would be invaluable in emergency situations.

Abstract Climate change and atmospheric deposition of nitrogen (N) and sulfur (S) impact the health and productivity of forests. Here, we explored the potential impacts of these environmental stressors on ecosystem services provided by future forests in the contiguous U.S. We found that all stand-level services benefitted (+ 2.6 to 8.1%) from reductions in N+S deposition, largely attributable to positive responses to reduced S that offset the net negative effects of lower N levels. Sawtimber responded positively (+ 0.5 to 0.6%) to some climate change, but negatively (− 2.4 to − 3.8%) to the most extreme scenarios. Aboveground carbon (C) sequestration and forest diversity were negatively impacted by all modelled changes in climate. Notably, the most extreme climate scenario eliminated gains in all three services achieved through reduced deposition. As individual tree species responded differently to climate change and atmospheric deposition, associated services unique to each species increased or decreased under future scenarios. Our results suggest that climate change should be considered when evaluating the benefits of N and S air pollution policies on the services provided by U.S. forests.

Abstract Whole genome sequencing (WGS) of Mycobacterium tuberculosis offers valuable insights for tuberculosis (TB) control. High throughput platforms like Illumina and Oxford Nanopore Technology (ONT) are increasingly used globally, although ONT is known for higher error rates and is less established for genomic studies. Here we present a study comparing the sequencing outputs of both Illumina and ONT platforms, analysing DNA from 59 clinical isolates in highly endemic TB regions of Thailand. The resulting sequence data were used to profile the M. tuberculosis pairs for their lineage, drug resistance and presence in transmission chains, and were compared to publicly available WGS data from Thailand (n = 1456). Our results revealed isolates that are predominantly from lineages 1 and 2, with consistent drug resistance profiles, including six multidrug-resistant strains; however, analysis of ONT data showed longer phylogenetic branches, emphasising the technologies higher error rate. An analysis incorporating the larger dataset identified fifteen of our samples within six potential transmission clusters, including a significant clade of 41 multi-drug resistant isolates. ONT's extended sequences also revealed strain-specific structural variants in pe/ppe genes (e.g. ppe50), which are candidate loci for vaccine development. Despite some limitations, our results show that ONT sequencing is a promising approach for TB genomic research, supporting precision medicine and decision-making in areas with less developed infrastructure, which is crucial for tackling the disease’s significant regional burden.

Abstract Despite Plasmodium ovale curtisi (Poc) and wallikeri (Pow) being important human-infecting malaria parasites that are widespread across Africa and Asia, little is known about their genome diversity. Morphologically identical, Poc and Pow are indistinguishable and commonly misidentified. Recent rises in the incidence of Poc/Pow infections have renewed efforts to address fundamental knowledge gaps in their biology, and to develop diagnostic tools to understand their epidemiological dynamics and malaria burden. A major roadblock has been the incompleteness of available reference assemblies (PocGH01, PowCR01; ~ 33.5 Mbp). Here, we applied multiple sequencing platforms and advanced bioinformatics tools to generate new reference genomes, Poc221 (South Sudan; 36.0 Mbp) and Pow222 (Nigeria; 34.3 Mbp), with improved nuclear genome contiguity (> 4.2 Mbp), annotation and completeness (> 99% Plasmodium spp., single copy orthologs). Subsequent sequencing of 6 Poc and 15 Pow isolates from Africa revealed a total of 22,517 and 43,855 high-quality core genome SNPs, respectively. Genome-wide levels of nucleotide diversity were determined to be 2.98 × 10–4 (Poc) and 3.43 × 10–4 (Pow), comparable to estimates for other Plasmodium species. Overall, the new reference genomes provide a robust foundation for dissecting the biology of Poc/Pow, their population structure and evolution, and will contribute to uncovering the recombination barrier separating these species.

Abstract Injury mechanism is an important consideration when conducting clinical trials in trauma. Mechanisms of injury may be associated with differences in mortality risk and immune response to injury, impacting the potential success of the trial. We sought to characterize clinical and endothelial cell damage marker differences across blunt and penetrating injured patients enrolled in three large, prehospital randomized trials which focused on hemorrhagic shock. In this secondary analysis, patients with systolic blood pressure 108 were included. In addition, patients with both blunt and penetrating injuries were excluded. The primary outcome was 30-day mortality. Mortality was characterized using Kaplan–Meier and Cox proportional-hazards models. Generalized linear models were used to compare biomarkers. Chi squared tests and Wilcoxon rank-sum were used to compare secondary outcomes. We characterized data of 696 enrolled patients that met all secondary analysis inclusion criteria. Blunt injured patients had significantly greater 24-h (18.6% vs. 10.7%, log rank p = 0.048) and 30-day mortality rates (29.7% vs. 14.0%, log rank p = 0.001) relative to penetrating injured patients with a different time course. After adjusting for confounders, blunt mechanism of injury was independently predictive of mortality at 30-days (HR 1.84, 95% CI 1.06–3.20, p = 0.029), but not 24-h (HR 1.65, 95% CI 0.86–3.18, p = 0.133). Elevated admission levels of endothelial cell damage markers, VEGF, syndecan-1, TM, S100A10, suPAR and HcDNA were associated with blunt mechanism of injury. Although there was no difference in multiple organ failure (MOF) rates across injury mechanism (48.4% vs. 42.98%, p = 0.275), blunt injured patients had higher Denver MOF score (p

Abstract The quantum limit in a Fermi liquid, realized when a single Landau level is occupied in strong magnetic fields, gives rise to unconventional states, including the fractional quantum Hall effect and excitonic insulators. Stronger interactions in metals with nearly localized f-electron degrees of freedom increase the likelihood of these unconventional states. However, access to the quantum limit is typically impeded by the tendency of f-electrons to polarize in a strong magnetic field, consequently weakening the interactions. In this study, we propose that the quantum limit in such systems must be approached in reverse, starting from an insulating state at zero magnetic field. In this scenario, Landau levels fill in the reverse order compared to regular metals and are closely linked to a field-induced insulator-to-metal transition. We identify YbB12 as a prime candidate for observing this effect and propose the presence of an excitonic insulator state near this transition.

HERV-K(HML-2), the youngest clade of human endogenous retroviruses (HERVs), includes many intact or nearly intact proviruses, but no replication competent HML-2 proviruses have been identified in humans. HML-2-related proviruses are present in other primates, including rhesus macaques, but the extent and timing of HML-2 activity in macaques remains unclear. We have identified 145 HML-2-like proviruses in rhesus macaques, including a clade of young, rhesus-specific insertions. Age estimates, intact open reading frames, and insertional polymorphism of these insertions are consistent with recent or ongoing infectious activity in macaques. 106 of the proviruses form a clade characterized by an ~750 bp sequence between env and the 3′ long terminal repeat (LTR), derived from an ancient recombination with a HERV-K(HML-8)-related virus. This clade is found in Old World monkeys (OWM), but not great apes, suggesting it originated after the ape/OWM split. We identified similar proviruses in white-cheeked gibbons; the gibbon insertions cluster within the OWM recombinant clade, suggesting interspecies transmission from OWM to gibbons. The LTRs of the youngest proviruses have deletions in U3, which disrupt the Rec Response Element (RcRE), required for nuclear export of unspliced viral RNA. We show that the HML-8-derived region functions as a Rec-independent constitutive transport element (CTE), indicating the ancestral Rec–RcRE export system was replaced by a CTE mechanism.

Abstract Vector control strategies have been successful in reducing the number of malaria cases and deaths globally, but the spread of insecticide resistance represents a significant threat to disease control. Insecticide resistance has been reported across Anopheles (An.) vector populations, including species within the An. funestus group. These mosquitoes are responsible for intense malaria transmission across sub-Saharan Africa, including in the Democratic Republic of the Congo (DRC), a country contributing > 12% of global malaria infections and mortality events. To support the continuous efficacy of vector control strategies, it is essential to monitor insecticide resistance using molecular surveillance tools. In this study, we developed an amplicon sequencing (“Amp-seq”) approach targeting An. funestus, and using multiplex PCR, dual index barcoding, and next-generation sequencing for high throughput and low-cost applications. Using our Amp-seq approach, we screened 80 An. funestus field isolates from the DRC across a panel of nine genes with mutations linked to insecticide resistance (ace-1, CYP6P4, CYP6P9a, GSTe2, vgsc, and rdl) and mosquito speciation (cox-1, mtND5, and ITS2). Amongst the 18 non-synonymous mutations detected, was N485I, in the ace-1 gene associated with carbamate resistance. Overall, our panel represents an extendable and much-needed method for the molecular surveillance of insecticide resistance in An. funestus populations.

Abstract Tuberculosis disease (TB), caused by Mycobacterium tuberculosis, is a major global public health problem, resulting in more than 1 million deaths each year. Drug resistance (DR), including multi-drug (MDR-TB), is making TB control difficult and accounts for 16% of new and 48% of previously treated cases. To further complicate treatment decision-making, many clinical studies have reported patients harbouring multiple distinct strains of M. tuberculosis across the main lineages (L1 to L4). The extent to which drug-resistant strains can be deconvoluted within mixed strain infection samples is understudied. Here, we analysed M. tuberculosis isolates with whole genome sequencing data (n = 50,723), which covered the main lineages (L1 9.1%, L2 27.6%, L3 11.8%, L4 48.3%), with genotypic resistance to isoniazid (HR-TB; n = 9546 (29.2%)), rifampicin (RR-TB; n = 7974 (24.4%)), and at least MDR-TB (n = 5385 (16.5%)). TB-Profiler software revealed 531 (1.0%) isolates with potential mixed sub-lineage infections, including some with DR mutations (RR-TB 21/531; HR-TB 59/531; at least MDR-TB 173/531). To assist with the deconvolution of such mixtures, we adopted and evaluated a statistical Gaussian Mixture model (GMM) approach. By simulating 240 artificial mixtures of different ratios from empirical data across L1 to L4, a GMM approach was able to accurately estimate the DR profile of each lineage, with a low error rate for the estimated mixing proportions (mean squared error 0.012) and high accuracy for the DR predictions (93.5%). Application of the GMM model to the clinical mixtures (n = 531), found that 33.3% (188/531) of samples consisted of DR and sensitive lineages, 20.2% (114/531) consisted of lineages with only DR mutations, and 40.6% (229/531) consisted of lineages with genotypic pan-susceptibility. Overall, our work demonstrates the utility of combined whole genome sequencing data and GMM statistical analysis approaches for providing insights into mono and mixed M. tuberculosis infections, thereby potentially assisting diagnosis, treatment decision-making, drug resistance and transmission mapping for infection control.

Abstract As the COVID-19 pandemic unfolded in the spring of 2020, governments around the world began to implement policies to mitigate and manage the outbreak. Significant research efforts were deployed to track and analyse these policies in real-time to better inform the response. While much of the policy analysis focused narrowly on social distancing measures designed to slow the spread of disease, here, we present a dataset focused on capturing the breadth of policy types implemented by jurisdictions globally across the whole-of-government. COVID Analysis and Mapping of Policies (COVID AMP) includes nearly 50,000 policy measures from 150 countries, 124 intermediate areas, and 235 local areas between January 2020 and June 2022. With up to 40 structured and unstructured characteristics encoded per policy, as well as the original source and policy text, this dataset provides a uniquely broad capture of the governance strategies for pandemic response, serving as a critical data source for future work in legal epidemiology and political science.

Abstract Malaria has exhibited the strongest known selective pressure on the human genome in recent history and is the evolutionary driving force behind genetic conditions, such as sickle-cell disease, glucose-6-phosphatase deficiency, and some other erythrocyte defects. Genomic studies (e.g., The 1000 Genomes project) have provided an invaluable baseline for human genetics, but with an estimated two thousand ethno-linguistic groups thought to exist across the African continent, our understanding of the genetic differences between indigenous populations and their implications on disease is still limited. Low-cost sequencing-based approaches make it possible to target specific molecular markers and genes of interest, leading to potential insights into genetic diversity. Here we demonstrate the versatility of custom dual-indexing technology and Illumina next generation sequencing to generate a genetic profile of human polymorphisms associated with malaria pathology. For 100 individuals diagnosed with severe malaria in Northeast Tanzania, variants were successfully characterised on the haemoglobin subunit beta (HBB), glucose-6-phosphate dehydrogenase (G6PD), atypical chemokine receptor 1 (ACKR1) genes, and the intergenic Dantu genetic blood variant, then validated using pre-existing genotyping data. High sequencing coverage was observed across all amplicon targets in HBB, G6PD, ACKR1, and the Dantu blood group, with variants identified at frequencies previously observed within this region of Tanzania. Sequencing data exhibited high concordance rates to pre-existing genotyping data (> 99.5%). Our work demonstrates the potential utility of amplicon sequencing for applications in human genetics, including to personalise medicine and understand the genetic diversity of loci linked to important host phenotypes, such as malaria susceptibility.

Abstract Bacterial strain-types in the Mycobacterium tuberculosis complex underlie tuberculosis disease, and have been associated with drug resistance, transmissibility, virulence, and host–pathogen interactions. Spoligotyping was developed as a molecular genotyping technique used to determine strain-types, though recent advances in whole genome sequencing (WGS) technology have led to their characterization using SNP-based sub-lineage nomenclature. Notwithstanding, spoligotyping remains an important tool and there is a need to study the congruence between spoligotyping-based and SNP-based sub-lineage assignation. To achieve this, an in silico spoligotype prediction method (“Spolpred2”) was developed and integrated into TB-Profiler. Lineage and spoligotype predictions were generated for > 28 k isolates and the overlap between strain-types was characterized. Major spoligotype families detected were Beijing (25.6%), T (18.6%), LAM (13.1%), CAS (9.4%), and EAI (8.3%), and these broadly followed known geographic distributions. Most spoligotypes were perfectly correlated with the main MTBC lineages (L1-L7, plus animal). Conversely, at lower levels of the sub-lineage system, the relationship breaks down, with only 65% of spoligotypes being perfectly associated with a sub-lineage at the second or subsequent levels of the hierarchy. Our work supports the use of spoligotyping (membrane or WGS-based) for low-resolution surveillance, and WGS or SNP-based systems for higher-resolution studies.

Abstract Malaria control initiatives require rapid and reliable methods for the detection and monitoring of molecular markers associated with antimalarial drug resistance in Plasmodium falciparum parasites. Ngodhe island, Kenya, presents a unique malaria profile, with lower P. falciparum incidence rates than the surrounding region, and a high proportion of sub-microscopic and low-density infections. Here, using custom dual-indexing and Illumina next generation sequencing, we generate resistance profiles on seventy asymptomatic and low-density P. falciparum infections from a mass drug administration program implemented on Ngodhe island between 2015 and 2016. Our assay encompasses established molecular markers on the Pfcrt, Pfmdr1, Pfdhps, Pfdhfr, and Pfk13 genes. Resistance markers for sulfadoxine-pyrimethamine were identified at high frequencies, including a quintuple mutant haplotype (Pfdhfr/Pfdhps: N51I, C59R, S108N/A437G, K540E) identified in 62.2% of isolates. The Pfdhps K540E biomarker, used to inform decision making for intermittent preventative treatment in pregnancy, was identified in 79.2% of isolates. Several variants on Pfmdr1, associated with reduced susceptibility to quinolones and lumefantrine, were also identified (Y184F 47.1%; D1246Y 16.0%; N86 98%). Overall, we have presented a low-cost and extendable approach that can provide timely genetic profiles to inform clinical and surveillance activities, especially in settings with abundant low-density infections, seeking malaria elimination.

Abstract The search for new elementary particles is one of the most basic pursuits in physics, spanning from subatomic physics to quantum materials. Magnons are the ubiquitous elementary quasiparticle to describe the excitations of fully-ordered magnetic systems. But other possibilities exist, including fractional and multipolar excitations. Here, we demonstrate that strong quantum interactions exist between three flavors of elementary quasiparticles in the uniaxial spin-one magnet FeI2. Using neutron scattering in an applied magnetic field, we observe spontaneous decay between conventional and heavy magnons and the recombination of these quasiparticles into a super-heavy bound-state. Akin to other contemporary problems in quantum materials, the microscopic origin for unusual physics in FeI2 is the quasi-flat nature of excitation bands and the presence of Kitaev anisotropic magnetic exchange interactions.

Abstract Sequence analysis of Plasmodium falciparum parasites is informative in ensuring sustained success of malaria control programmes. Whole-genome sequencing technologies provide insights into the epidemiology and genome-wide variation of P. falciparum populations and can characterise geographical as well as temporal changes. This is particularly important to monitor the emergence and spread of drug resistant P. falciparum parasites which is threatening malaria control programmes world-wide. Here, we provide a detailed characterisation of genome-wide genetic variation and drug resistance profiles in asymptomatic individuals in South-Western Mali, where malaria transmission is intense and seasonal, and case numbers have recently increased. Samples collected from Ouélessébougou, Mali (2019–2020; n = 87) were sequenced and placed in the context of older Malian (2007–2017; n = 876) and African-wide (n = 711) P. falciparum isolates. Our analysis revealed high multiclonality and low relatedness between isolates, in addition to increased frequencies of molecular markers for sulfadoxine-pyrimethamine and lumefantrine resistance, compared to older Malian isolates. Furthermore, 21 genes under selective pressure were identified, including a transmission-blocking vaccine candidate (pfCelTOS) and an erythrocyte invasion locus (pfdblmsp2). Overall, our work provides the most recent assessment of P. falciparum genetic diversity in Mali, a country with the second highest burden of malaria in West Africa, thereby informing malaria control activities.

Abstract This study examined the effects of maternal and/or post-weaning Bacillus altitudinis supplementation on the microbiota in sow colostrum and faeces, and offspring digesta and faeces. Sows (n = 12/group) were assigned to: (1) standard diet (CON), or (2) CON supplemented with probiotic B. altitudinis spores (PRO) from day (d)100 of gestation to weaning (d26 of lactation). At weaning, offspring were assigned to CON or PRO for 28d, resulting in: (1) CON/CON, (2) CON/PRO, (3) PRO/CON, and (4) PRO/PRO, after which all received CON. Samples were collected from sows and selected offspring (n = 10/group) for 16S rRNA gene sequencing. Rothia was more abundant in PRO sow colostrum. Sow faeces were not impacted but differences were identified in offspring faeces and digesta. Most were in the ileal digesta between PRO/CON and CON/CON on d8 post-weaning; i.e. Bacteroidota, Alloprevotella, Prevotella, Prevotellaceae, Turicibacter, Catenibacterium and Blautia were more abundant in PRO/CON, with Firmicutes and Blautia more abundant in PRO/PRO compared with CON/CON. Lactobacillus was more abundant in PRO/CON faeces on d118 post-weaning. This increased abundance of polysaccharide-fermenters (Prevotella, Alloprevotella, Prevotellaceae), butyrate-producers (Blautia) and Lactobacillus likely contributed to previously reported improvements in growth performance. Overall, maternal, rather than post-weaning, probiotic supplementation had the greatest impact on intestinal microbiota.

To mitigate pyrethroid resistance in mosquito vectors of emerging and re-emerging human pathogens, there is an urgent need to discover insecticides with novel modes of action. Natural alternatives, such as extracts derived from plants, may serve as substitutes for traditional synthetic insecticides if they prove to be sustainable, cost-effective, and safe for non-target organisms. Hemp (Cannabis sativa) is a sustainable plant known to produce various secondary metabolites with insecticidal properties, including terpenoids and flavonoids. The goal of this study was to assess the larvicidal activity of hemp leaf extract on mosquito larvae from both pyrethroid-susceptible (PS) and pyrethroid-resistant (PR) strains of Aedes aegypti. Another goal was to identify which components of the extract were responsible for any observed larvicidal activity. We found that a methanol extract of hemp leaves induced similar concentration-dependent larvicidal activity against PS (LC50: 4.4 ppm) and PR (LC50: 4.3 ppm) strains within 48 h. Partitioning of the leaf extract between methanol and hexane fractions revealed that full larvicidal activity was restricted to the methanol fraction. Analysis of this fraction by gas chromatography–mass spectrometry and nuclear magnetic resonance showed it to be dominated by cannabidiol (CBD). Larvicidal assays using authentic CBD confirmed this compound was primarily responsible for the toxicity of the hemp leaf extract against both strains. We conclude that hemp leaf extracts and CBD have the potential to serve as viable sources for the development of novel mosquito larvicides.

[This corrects the article DOI: 10.1371/journal.pone.0286218.].

BackgroundThe symptom profiles of acute SARS-CoV-2 infection and long-COVID in children and young people (CYP), risk factors, and associated healthcare needs, are poorly defined. The Schools Infection Survey 1 (SIS-1) was a nationwide study of SARS-CoV-2 infection in primary and secondary schools in England during the 2020/21 school year. The Covid-19 Mapping and Mitigation in Schools (CoMMinS) study was conducted in schools in the Bristol area over a similar period. Both studies conducted testing to identify current and previous SARS-CoV-2 infection, and recorded symptoms and school attendance. These research data have been linked to routine electronic health record (EHR) data.AimsTo better understand the short- and long-term consequences of SARS-CoV-2 infection, and their risk factors, in CYP.MethodsRetrospective cohort and nested case-control analyses will be conducted for SIS-1 and CoMMinS data linked to EHR data for the association between (1) acute symptomatic SARS-CoV-2 infection and risk factors; (2) SARS-CoV-2 infection and long-term effects on health: (a) persistent symptoms; (b) any new diagnosis; (c) a new prescription in primary care; (d) health service attendance; (e) a high rate of school absence.ResultsOur study will improve understanding of long-COVID in CYP by characterising the trajectory of long-COVID in CYP in terms of things like symptoms and diagnoses of conditions. The research will inform which groups of CYP are more likely to get acute- and long-term outcomes of SARS-CoV-2 infection, and patterns of related healthcare-seeking behaviour, relevant for healthcare service planning. Digested information will be produced for affected families, doctors, schools, and the public, as appropriate.ConclusionLinked SIS-1 and CoMMinS data represent a unique and rich resource for understanding the impact of SARS-CoV-2 infection on children's health, benefiting from enhanced SARS-CoV-2 testing and ability to assess a wide range of outcomes.

BackgroundThe role of Vitamin D in immune function is well reported with a growing evidence base linking low levels to poorer outcomes from infectious disease. Vitamin D deficiency and insufficiency are prevalent worldwide with healthcare workers identified as a known at-risk group. Here we aim to investigate serum Vitamin D levels in a UK population of front line healthcare workers and to promote the occupational risk.MethodsA cross-sectional study of 639 volunteers was conducted to identify the prevalence of Vitamin D deficiency and insufficiency amongst a population of front-line health care workers in the UK. Participant demographics and co-morbid factors were collected at the time of serum sampling for multivariate analysis.ResultsOnly 18.8% of the population had a normal vitamin D level greater than or equal to 75nmol/L. This is compared to Public Health England's (PHE) stipulated normal levels of 60% during winter. 81.2% had a level less than 75nmol/L, with 51.2% less than 50nmol/L and 6.6% less than 25nmol/L. For serum levels less than 25nmol/L, Asian ethnicity was more likely to have a vitamin D deficiency than non-asian (OR (95%CI): 3.81 (1.73-8.39), p = 0.001), whereas white ethnicity was less likely to have a vitamin D deficiency compared to non-white (OR (95%CI: 0.43 (0.20-0.83), p = 0.03). Other factors that contributed to a higher likelihood of lower-than-normal levels within this population included male sex, decreased age and not taking supplementation.ConclusionIt is concluded that our population of healthcare workers have higher rates of abnormal vitamin D levels in comparison with the general UK population reported prevalence. Furthermore, Asian ethnicity and age 30 years and below are more at risk of vitamin D insufficiency and deficiency. This highlights an occupational risk factor for the healthcare community to consider.

Deep Learning models such as Convolutional Neural Networks (CNNs) are very effective at extracting complex image features from medical X-rays. However, the limited interpretability of CNNs has hampered their deployment in medical settings as they failed to gain trust among clinicians. In this work, we propose an interactive framework to allow clinicians to ask what-if questions and intervene in the decisions of a CNN, with the aim of increasing trust in the system. The framework translates a layer of a trained CNN into a measurable and compact set of symbolic rules. Expert interactions with visualizations of the rules promote the use of clinically-relevant CNN kernels and attach meaning to the rules. The definition and relevance of the kernels are supported by radiomics analyses and permutation evaluations, respectively. CNN kernels that do not have a clinically-meaningful interpretation are removed without affecting model performance. By allowing clinicians to evaluate the impact of adding or removing kernels from the rule set, our approach produces an interpretable refinement of the data-driven CNN in alignment with medical best practice.

Abstract Following integrated malaria control interventions, malaria burden on the Bijagós Archipelago has significantly decreased. Understanding the genomic diversity of circulating Plasmodium falciparum malaria parasites can assist infection control, through identifying drug resistance mutations and characterising the complexity of population structure. This study presents the first whole genome sequence data for P. falciparum isolates from the Bijagós Archipelago. Amplified DNA from P. falciparum isolates sourced from dried blood spot samples of 15 asymptomatic malaria cases were sequenced. Using 1.3 million SNPs characterised across 795 African P. falciparum isolates, population structure analyses revealed that isolates from the archipelago cluster with samples from mainland West Africa and appear closely related to mainland populations; without forming a separate phylogenetic cluster. This study characterises SNPs associated with antimalarial drug resistance on the archipelago. We observed fixation of the PfDHFR mutations N51I and S108N, associated with resistance to sulphadoxine-pyrimethamine, and the continued presence of PfCRT K76T, associated with chloroquine resistance. These data have relevance for infection control and drug resistance surveillance; particularly considering expected increases in antimalarial drug use following updated WHO recommendations, and the recent implementation of seasonal malaria chemoprevention and mass drug administration in the region.

Abstract Phytophthora cinnamomi is an oomycete found in the soil and capable of invading the roots of a wide range of host plants globally, potentially killing them and affecting the ecosystems they inhabit. This pathogen is often inadvertently dispersed in natural vegetation on the footwear of humans. A range of equipment is often provided or recommended to be carried for cleaning footwear in places where P. cinnamomi poses a threat to biodiversity. These are typically a brush for mechanically removing soil and/or a disinfectant for killing the pathogen. Despite their widespread use, to our knowledge, the majority of hygiene measures have not been experimentally tested for their efficacy. In the current study, we tested whether two types of brush and the two most widely used disinfectants (70% methylated spirits and benzalkonium chloride) were effective in removing the pathogen from boots. We tested the brushes and disinfectants in two soil types and two moisture levels. All hygiene measures were found to be better than doing nothing, although some were only effective with sandy or dry soils. Benzalkonium chloride was largely ineffective as a spray but highly effective when used in a footbath. Brushing did not improve cleaning when used with 70% methylated spirits. None of the hygiene measures was completely effective for cleaning boots that had been in wet loamy soil. Our findings have important implications for management of this threat because some recommended hygiene practices are not doing what they claim.

Abstract Since its first detection in 2012 in Djibouti, Anopheles stephensi has invaded and established in the Horn of Africa, and more recently Nigeria. The expansion of this vector poses a significant threat to malaria control and elimination efforts. Integrated vector management is the primary strategy used to interrupt disease transmission; however, growing insecticide resistance is threatening to reverse gains in global malaria control. We present a next-generation amplicon-sequencing approach, for high-throughput monitoring of insecticide resistance genes (ace1, GSTe2, vgsc and rdl), species identification and characterization of genetic diversity (its2 and cox1) in An. stephensi. Ninety-five An. stephensi mosquitoes, collected in Ethiopia, were screened, identifying 104 SNPs, including the knock-down mutation L958F (L1014F in Musca domestica), and for the first time in this vector species, the A296S substitution (A301S in Drosophila melanogaster) in the rdl locus. Two other amino acid substitutions (ace1-N177D, GSTe2-V189L) were also identified but have not been previously implicated in insecticide resistance. Genetic diversity in the mitochondrial cox1 gene revealed shared haplotypes between Ethiopian An. stephensi with samples from Pakistan, Sudan, and Djibouti. Overall, we present a reliable, cost-effective strategy using amplicon-sequencing to monitor known insecticide resistance mutations, with the potential to identify new genetic variants, to assist in the high-throughput surveillance of insecticide resistance in An. stephensi populations.

Abstract The invasion and establishment of An. stephensi mosquitoes in the Horn of Africa represents a significant regional threat, which may jeopardise malaria control, particularly in urban areas which were formally free from disease transmission. Novel vector surveillance methods are urgently needed, both agnostic to mosquito larval morphology, and simple to implement at the sampling stage. Using new multiplex TaqMan assays, specifically targeting An. stephensi and Ae. aegypti, we validated the use of environmental DNA (eDNA) for simultaneous vector detection in shared artificial breeding sites. Study findings demonstrated that An. stephensi and Ae. aegypti eDNA deposited by as few as one second instar larva in 1L of water was detectable. Characterization of molecular insecticide resistance mechanisms, using novel amplicon-sequencing panels for both vector species, was possible from eDNA shed by as few as 16–32 s instar larvae in 50 ml of water. An. stephensi eDNA, derived from emergent pupae for 24 h, was remarkably stable, and still detectable ~ 2 weeks later. eDNA surveillance has the potential to be implemented in local endemic communities and at points of country entry, to monitor the spread of invasive vector species. Further studies are required to validate the feasibility of this technique under field conditions.

Few genetic loci have been associated with tuberculosis infection, possibly because of the influence of genetic variation in the pathogen. Here, the authors integrate human and Mycobacterium tuberculosis genetics to find genome-genome interactions associated with infection.

Abstract Trauma resuscitation practices have continued to improve with new advances targeting prehospital interventions. The critical care burden associated with severely injured patients at risk of hemorrhage has been poorly characterized. We aim to describe the individual and additive effects of multiorgan failure (MOF) and nosocomial infection (NI) on delayed mortality and resource utilization. A secondary analysis of harmonized data from two large prehospital randomized controlled trials (Prehospital Air Medical Plasma (PAMPer) Trial and Study of Tranexamic Acid during Air and Ground Medical Prehospital Transport (STAAMP) Trial) was conducted. Only those patients who survived beyond the first 24 hours post-injury and spent at least one day in the ICU were included. Patients were stratified by development of MOF only, NI only, both, or neither and diagnosis of early (≤ 3 days) versus late MOF (> 3 days). Risk factors of NI and MOF, time course of these ICU complications, associated mortality, and hospital resource utilization were evaluated. Of the 869 patients who were enrolled in PAMPer and STAAMP and who met study criteria, 27.4% developed MOF only (n = 238), 10.9% developed NI only (n = 95), and 15.3% were diagnosed with both MOF and NI (n = 133). Patients developing NI and/or MOF compared to those who had an uncomplicated ICU course had greater injury severity, lower GCS, and greater shock indexes. Early MOF occurred in isolation, while late MOF more often followed NI. MOF was associated with 65% higher independent risk of 30-day mortality when adjusting for cofounders (OR 1.65; 95% CI 1.04–2.6; p = 0.03), however NI did not significantly affect odds of mortality. NI was individually associated with longer mechanical ventilation, ICU stay, hospital stay, and rehabilitation requirements, and the addition of MOF further increased the burden of inpatient and post-discharge care. MOF and NI remain common complications for those who survive traumatic injury. MOF is a robust independent predictor of mortality following injury in this cohort, and NI is associated with higher resource utilization. Timing of these ICU complications may reveal differences in pathophysiology and offer targets for continued advancements in treatment.

Abstract Resistance to isoniazid (INH) and rifampicin (RIF) first-line drugs in Mycobacterium tuberculosis (Mtb), together called multi-drug resistance, threatens tuberculosis control. Resistance mutations in katG (for INH) and rpoB (RIF) genes often come with fitness costs. To overcome these costs, Mtb compensatory mutations have arisen in rpoC/rpoA (RIF) and ahpC (INH) loci. By leveraging the presence of known compensatory mutations, we aimed to detect novel resistance mutations occurring in INH and RIF target genes. Across ~ 32 k Mtb isolates with whole genome sequencing (WGS) data, there were 6262 (35.7%) with INH and 5435 (30.7%) with RIF phenotypic resistance. Known mutations in katG and rpoB explained ~ 99% of resistance. However, 188 (0.6%) isolates had ahpC compensatory mutations with no known resistance mutations in katG, leading to the identification of 31 putative resistance mutations in katG, each observed in at least 3 isolates. These putative katG mutations can co-occur with other INH variants (e.g., katG-Ser315Thr, fabG1 mutations). For RIF, there were no isolates with rpoC/rpoA compensatory mutations and unknown resistance mutations. Overall, using WGS data we identified putative resistance markers for INH that could be used for genotypic drug-resistance profiling. Establishing the complete repertoire of Mtb resistance mutations will assist the clinical management of tuberculosis.

Abstract Artificial intelligence (AI)-based approaches can now use electrocardiograms (ECGs) to provide expert-level performance in detecting heart abnormalities and diagnosing disease. Additionally, patient age predicted from ECGs by AI models has shown great potential as a biomarker for cardiovascular age, where recent work has found its deviation from chronological age (“delta age”) to be associated with mortality and co-morbidities. However, despite being crucial for understanding underlying individual risk, the genetic underpinning of delta age is unknown. In this work we performed a genome-wide association study using UK Biobank data (n=34,432) and identified eight loci associated with delta age ( $$p\le 5 \times 10^{-8}$$ p ≤ 5 × 10 - 8 ), including genes linked to cardiovascular disease (CVD) (e.g. SCN5A) and (heart) muscle development (e.g. TTN). Our results indicate that the genetic basis of cardiovascular ageing is predominantly determined by genes directly involved with the cardiovascular system rather than those connected to more general mechanisms of ageing. Our insights inform the epidemiology of CVD, with implications for preventative and precision medicine.

Abstract Malaria, caused by Plasmodium parasites, is a major global health challenge. Whole genome sequencing (WGS) of Plasmodium falciparum and Plasmodium vivax genomes is providing insights into parasite genetic diversity, transmission patterns, and can inform decision making for clinical and surveillance purposes. Advances in sequencing technologies are helping to generate timely and big genomic datasets, with the prospect of applying Artificial Intelligence analytical techniques (e.g., machine learning) to support programmatic malaria control and elimination. Here, we assess the potential of applying deep learning convolutional neural network approaches to predict the geographic origin of infections (continents, countries, GPS locations) using WGS data of P. falciparum (n = 5957; 27 countries) and P. vivax (n = 659; 13 countries) isolates. Using identified high-quality genome-wide single nucleotide polymorphisms (SNPs) (P. falciparum: 750 k, P. vivax: 588 k), an analysis of population structure and ancestry revealed clustering at the country-level. When predicting locations for both species, classification (compared to regression) methods had the lowest distance errors, and > 90% accuracy at a country level. Our work demonstrates the utility of machine learning approaches for geo-classification of malaria parasites. With timelier WGS data generation across more malaria-affected regions, the performance of machine learning approaches for geo-classification will improve, thereby supporting disease control activities.

Alterations in lipid metabolism and circulating lipid species have been reported in patients with acute critical illness. Here the authors show that selective rise in systemic phosphatidylethanolamine levels is a common feature of critical illness that associates with worse clinical outcomes.

Background: Inference on pneumococcal transmission has mostly relied on longitudinal studies which are costly and resource intensive. Therefore, we conducted a pilot study to test the ability to infer who infected whom from cross-sectional pneumococcal sequences using phylogenetic inference. Methods: Five suspected transmission pairs, for which there was epidemiological evidence of who infected whom, were selected from a household study. For each pair, Streptococcus pneumoniae full genomes were sequenced from nasopharyngeal swabs collected on the same day. The within-host genetic diversity of the pneumococcal population was used to infer the transmission direction and then cross-validated with the direction suggested by the epidemiological records. Results: The pneumococcal genomes clustered into the five households from which the samples were taken. The proportion of concordantly inferred transmission direction generally increased with increasing minimum genome fragment size and single nucleotide polymorphisms. We observed a larger proportion of unique polymorphic sites in the source bacterial population compared to that of the recipient in four of the five pairs, as expected in the case of a transmission bottleneck. The only pair that did not exhibit this effect was also the pair that had consistent discordant transmission direction compared to the epidemiological records suggesting potential misdirection as a result of false-negative sampling. Conclusions: This pilot provided support for further studies to test if the direction of pneumococcal transmission can be reliably inferred from cross-sectional samples if sequenced with sufficient depth and fragment length.

Solid electrolyte interphase (SEI) formation on Li-ion battery anodes is critical for long-term performance. Here, the authors use operando soft X-ray absorption spectroscopy in total electron yield mode to resolve the chemical evolution of the SEI during electrochemical formation on silicon anodes.

RAS mutations are commonly found in multiple myeloma (MM). Here, the authors show that oncogenic RAS mutations activate mTORC1 signalling in MM and combining mTORC1 and MEK/ERK inhibitors synergize to improve survival in preclinical models.

Abstract Surveillance of malaria vector species and the monitoring of insecticide resistance are essential to inform malaria control strategies and support the reduction of infections and disease. Genetic barcoding of mosquitoes is a useful tool to assist the high-throughput surveillance of insecticide resistance, discriminate between sibling species and to detect the presence of Plasmodium infections. In this study, we combined multiplex PCR, custom designed dual indexing, and Illumina next generation sequencing for high throughput single nucleotide polymorphism (SNP)-profiling of four species from the Anopheles (An.) gambiae complex (An. gambiae sensu stricto, An. coluzzii, An. arabiensis and An. melas). By amplifying and sequencing only 14 genetic fragments (500 bp each), we were able to simultaneously detect Plasmodium infection; insecticide resistance-conferring SNPs in ace1, gste2, vgsc and rdl genes; the partial sequences of nuclear ribosomal internal transcribed spacers (ITS1 and ITS2) and intergenic spacers (IGS), Short INterspersed Elements (SINE), as well as mitochondrial genes (cox1 and nd4) for species identification and genetic diversity. Using this amplicon sequencing approach with the four selected An. gambiae complex species, we identified a total of 15 non-synonymous mutations in the insecticide target genes, including previously described mutations associated with resistance and two new mutations (F1525L in vgsc and D148E in gste2). Overall, we present a reliable and cost-effective high-throughput panel for surveillance of An. gambiae complex mosquitoes in malaria endemic regions.

Abstract Klebsiella pneumoniae (Kp) bacteria are an increasing threat to public health and represent one of the most concerning pathogens involved in life-threatening infections and antimicrobial resistance (AMR). To understand the epidemiology of AMR of Kp in Portugal, we analysed whole genome sequencing, susceptibility testing and other meta data on 509 isolates collected nationwide from 16 hospitals and environmental settings between years 1980 and 2019. Predominant sequence types (STs) included ST15 (n = 161, 32%), ST147 (n = 36, 7%), ST14 (n = 26, 5%) or ST13 (n = 26, 5%), while 31% of isolates belonged to STs with fewer than 10 isolates. AMR testing revealed widespread resistance to aminoglycosides, fluoroquinolones, cephalosporins and carbapenems. The most common carbapenemase gene was bla KPC-3 . Whilst the distribution of AMR linked plasmids appears uncorrelated with ST, their frequency has changed over time. Before year 2010, the dominant plasmid group was associated with the extended spectrum beta-lactamase gene bla CTX-M-15 , but this group appears to have been displaced by another carrying the bla KPC-3 gene. Co-carriage of bla CTX-M and bla KPC-3 was uncommon. Our results from the largest genomics study of Kp in Portugal highlight the active transmission of strains with AMR genes and provide a baseline set of variants for future resistance monitoring and epidemiological studies.

Abstract Tuberculosis, caused by Mycobacterium tuberculosis, is a high-burden disease in Pakistan, with multi-drug (MDR) and extensive-drug (XDR) resistance, complicating infection control. Whole genome sequencing (WGS) of M. tuberculosis is being used to infer lineages (strain-types), drug resistance mutations, and transmission patterns—all informing infection control and clinical decision making. Here we analyse WGS data on 535 M. tuberculosis isolates sourced across Pakistan between years 2003 and 2020, to understand the circulating strain-types and mutations related to 12 anti-TB drugs, as well as identify transmission clusters. Most isolates belonged to lineage 3 (n = 397; 74.2%) strain-types, and were MDR (n = 328; 61.3%) and (pre-)XDR (n = 113; 21.1%). By inferring close genomic relatedness between isolates (

Forest composition and ecosystem services are sensitive to anthropogenic pressures like climate change and atmospheric deposition of nitrogen (N) and sulfur (S). Here we extend recent forest projections for the current cohort of trees in the contiguous US, characterizing potential changes in aboveground tree carbon at the county level in response to varying mean annual temperature, precipitation, and N and S deposition. We found that relative to a scenario with N and S deposition reduction and no climate change, greater climate change led generally to decreasing aboveground carbon (mean −7.5% under RCP4.5, −16% under RCP8.5). Keeping climate constant, reduced N deposition tended to lessen aboveground carbon (mean −7%), whereas reduced S deposition tended to increase aboveground carbon (+3%) by 2100. Through mid-century (2050), deposition was more important for predicting carbon responses except under the extreme climate scenarios (RCP _8.5 ); but, by 2100, climate drivers generally outweighed deposition. While more than 70% of counties showed reductions in aboveground carbon relative to the reference scenario, these were not evenly distributed across the US. Counties in the Northwest and Northern Great Plains, and the northern parts of New England and the Midwest, primarily showed positive responses, while counties in the Southeast showed negative responses. Counties with greater initial biomass showed less negative responses to climate change while those which exhibited the greatest change in composition (>15%) had a 95% chance of losing carbon relative to a no-climate change scenario. This analysis highlights that declines in forest growth and survival due to increases in mean temperature and reductions in atmospheric N deposition are likely to outweigh positive impacts of reduced S deposition and potential increases in precipitation. These effects vary at the regional and county level, however, so forest managers must consider local rather than national dynamics to maximize forest carbon sinks in the future.

T follicular helper (Tfh) and T help type 1 (Th1) cells both arise from naïve CD4 T cells, but detailed knowledge of their differentiation remains incomplete. Here the authors pursue an in vivo CRISPR screen to identify genes, focusing on druggable targets, regulating Tfh versus Th1 to provide a resource for related studies, while also implicating HIF-1α and VHL in this regulation.

ImportanceUpward income mobility is associated with better health outcomes and reduced stress. However, opportunities are unequally distributed, particularly so for those in rural communities and whose family have lower educational attainment.ObjectiveTo test the impact of parental supervision on their children's income two decades later adjusting for parental economic and educational status.DesignThis study is a longitudinal, representative cohort study. From 1993-2000, annual assessments of 1,420 children were completed until age 16, then followed up at age 35, 2018-2021, for further assessment. Models tested direct effects of parental supervision on child income, and indirect effects via child educational attainment.SettingThis study is an ongoing longitudinal population-based study of families in 11 predominately rural counties of the Southeastern U.S.ParticipantsAbout 8% of the residents and sample are African American and fewer than 1% are Hispanic. American Indians make up 4% of the population in study but were oversampled to make up 25% of the sample. 49% of the 1,420 participants are female.Main outcomes and measures1258 children and parents were assessed for sex, race/ethnicity, household income, parent educational attainment, family structure, child behavioral problems, and parental supervision. The children were followed up at age 35 to assess their household income and educational attainment.ResultsParental educational attainment, income, and family structure were strongly associated with their children's household income at age 35 (e.g., r = .392, p < .05). Parental supervision of the child was associated with increased household income for the child at age 35, adjusting for SES of the family of origin. Children of parents who did not engage in adequate supervision earned approximately $14,000 less/year (i.e., ~13% of the sample's median household income) than those who did. The association of parental supervision and child income at 35 was mediated by the child's educational attainment.Conclusion and relevanceThis study suggests adequate parental supervision during early adolescence is associated with children's economic prospects two decades later, in part by improving their educational prospects. This is particularly important in areas such as rural Southeast U.S.

BackgroundDirect access to diagnostic imaging in General Practice provides an avenue to reduce referrals to hospital-based specialities and emergency departments, and to ensure timely diagnosis. Enhanced GP access to radiology imaging could potentially reduce hospital referrals, hospital admissions, enhance patient care, and improve disease outcomes. This scoping review aims to demonstrate the value of direct access to diagnostic imaging in General Practice and how it has impacted on healthcare delivery and patient care.MethodsA search was conducted of 'PubMed', 'Cochrane Library', 'Embase' and 'Google Scholar' for papers published between 2012-2022 using Arksey and O'Malley's scoping review framework. The search process was guided by the PRISMA extension for Scoping Reviews checklist (PRISMA-ScR).ResultsTwenty-three papers were included. The studies spanned numerous geographical locations (most commonly UK, Denmark, and Netherlands), encompassing several study designs (most commonly cohort studies, randomised controlled trials and observational studies), and a range of populations and sample sizes. Key outcomes reported included the level of access to imaging serves, the feasibility and cost effectiveness of direct access interventions, GP and patient satisfaction with direct access initiatives, and intervention related scan waiting times and referral process.ConclusionDirect access to imaging for GPs can have many benefits for healthcare service delivery, patient care, and the wider healthcare ecosystem. GP focused direct access initiatives should therefore be considered as a desirable and viable health policy directive. Further research is needed to more closely examine the impacts that access to imaging studies have on health system operations, especially those in General Practice. Research examining the impacts of access to multiple imaging modalities is also warranted.

Data literacy has been defined as "the ability to read, work with, analyze and argue with data". The United Nations has highlighted a growing risk of inequality for people excluded from the new world of data by lack of education, language, poverty, and discrimination and has called for the development of data literacy at all levels of society. Responses to data are shaped by personal, social and cultural influences, as well as by trust in the source. The arts can play an important role in regulating our responses to information and increasing accessibility, engagement and sense-making of data. However, to our knowledge, to date, there has been no comprehensive review of publications on the role of the arts in the context of data literacy. This paper presents a protocol and a methodological framework to perform a scoping review to identify and map the available evidence for the role of the arts in enhancing data literacy. The review aims to provide an overview of research over the past twenty years to develop a clearer understanding of (a) which art forms are represented in the literature (b) which population groups and settings are identified (c) and the rationale for using the arts to enhance data literacy.

Abstract Tuberculosis (TB), caused by Mycobacterium tuberculosis, is one of the deadliest infectious diseases worldwide. Multidrug and extensively drug-resistant strains are making disease control difficult, and exhausting treatment options. New anti-TB drugs bedaquiline (BDQ), delamanid (DLM) and pretomanid (PTM) have been approved for the treatment of multi-drug resistant TB, but there is increasing resistance to them. Nine genetic loci strongly linked to resistance have been identified (mmpR5, atpE, and pepQ for BDQ; ddn, fgd1, fbiA, fbiB, fbiC, and fbiD for DLM/PTM). Here we investigated the genetic diversity of these loci across >33,000 M . tuberculosis isolates. In addition, epistatic mutations in mmpL5-mmpS5 as well as variants in ndh, implicated for DLM/PTM resistance in M. smegmatis, were explored. Our analysis revealed 1,227 variants across the nine genes, with the majority (78%) present in isolates collected prior to the roll-out of BDQ and DLM/PTM. We identified phylogenetically-related mutations, which are unlikely to be resistance associated, but also high-impact variants such as frameshifts (e.g. in mmpR5, ddn) with likely functional effects, as well as non-synonymous mutations predominantly in MDR-/XDR-TB strains with predicted protein destabilising effects. Overall, our work provides a comprehensive mutational catalogue for BDQ and DLM/PTM associated genes, which will assist with establishing associations with phenotypic resistance; thereby, improving the understanding of the causative mechanisms of resistance for these drugs, leading to better treatment outcomes.

Abstract Tuberculosis (TB), caused by Mycobacterium tuberculosis, is endemic in Pakistan. Resistance to both firstline rifampicin and isoniazid drugs (multidrug-resistant TB; MDR-TB) is hampering disease control. Rifampicin resistance is attributed to rpoB gene mutations, but rpoA and rpoC loci may also be involved. To characterise underlying rifampicin resistance mutations in the TB endemic province of Khyber Pakhtunkhwa, we sequenced 51 M. tuberculosis isolates collected between 2016 and 2019; predominantly, MDR-TB (n = 44; 86.3%) and lineage 3 (n = 30, 58.8%) strains. We found that known mutations in rpoB (e.g. S405L), katG (e.g. S315T), or inhA promoter loci explain the MDR-TB. There were 24 unique mutations in rpoA, rpoB, and rpoC genes, including four previously unreported. Five instances of within-host resistance diversity were observed, where two were a mixture of MDR-TB strains containing mutations in rpoB, katG, and the inhA promoter region, as well as compensatory mutations in rpoC. Heteroresistance was observed in two isolates with a single lineage. Such complexity may reflect the high transmission nature of the Khyber Pakhtunkhwa setting. Our study reinforces the need to apply sequencing approaches to capture the full-extent of MDR-TB genetic diversity, to understand transmission, and to inform TB control activities in the highly endemic setting of Pakistan.