Search

BackgroundColletotrichum fungi infect a wide diversity of monocot and dicot hosts, causing diseases on almost all economically important plants worldwide. Colletotrichum is also a suitable model for studying gene family evolution on a fine scale to uncover events in the genome associated with biological changes.ResultsHere we present the genome sequences of 30 Colletotrichum species covering the diversity within the genus. Evolutionary analyses revealed that the Colletotrichum ancestor diverged in the late Cretaceous in parallel with the diversification of flowering plants. We provide evidence of independent host jumps from dicots to monocots during the evolution of Colletotrichum, coinciding with a progressive shrinking of the plant cell wall degradative arsenal and expansions in lineage-specific gene families. Comparative transcriptomics of 4 species adapted to different hosts revealed similarity in gene content but high diversity in the modulation of their transcription profiles on different plant substrates. Combining genomics and transcriptomics, we identified a set of core genes such as specific transcription factors, putatively involved in plant cell wall degradation.ConclusionsThese results indicate that the ancestral Colletotrichum were associated with dicot plants and certain branches progressively adapted to different monocot hosts, reshaping the gene content and its regulation.

Abstract: Proton-proton collisions at the LHC generate a high-intensity collimated beam of neutrinos in the forward (beam) direction, characterised by energies of up to several TeV. The recent observation of LHC neutrinos by FASER$$u $$ ν and SND@LHC signifies that this previously overlooked particle beam is now available for scientific investigation. Here we quantify the impact that neutrino deep-inelastic scattering (DIS) measurements at the LHC would have on the parton distributions (PDFs) of protons and heavy nuclei. We generate projections for DIS structure functions for FASER$$u $$ ν and SND@LHC at Run III, as well as for the FASER$$u $$ ν 2, AdvSND, and FLArE experiments to be hosted at the proposed Forward Physics Facility (FPF) operating concurrently with the High-Luminosity LHC (HL-LHC). We determine that up to one million electron-neutrino and muon-neutrino DIS interactions within detector acceptance can be expected by the end of the HL-LHC, covering a kinematic region in x and $$Q^2$$ Q 2 overlapping with that of the Electron-Ion Collider. Including these DIS projections in global (n)PDF analyses, specifically PDF4LHC21, NNPDF4.0, and EPPS21, reveals a significant reduction in PDF uncertainties, in particular for strangeness and the up and down valence PDFs. We show that LHC neutrino data enable improved theoretical predictions for core processes at the HL-LHC, such as Higgs and weak gauge boson production. Our analysis demonstrates that exploiting the LHC neutrino beam effectively provides CERN with a “Neutrino-Ion Collider” without requiring modifications in its accelerator infrastructure.

Aspergillus terreus has attracted interest due to its application in industrial biotechnology, particularly for the production of itaconic acid and bioactive secondary metabolites. As related species also seem to possess a prosperous secondary metabolism, they are of high interest for genome mining and exploitation. Here, we present draft genome sequences for six species from Aspergillus section Terrei and one species from Aspergillus section Nidulantes. Whole-genome phylogeny confirmed that section Terrei is monophyletic. Genome analyses identified between 70 and 108 key secondary metabolism genes in each of the genomes of section Terrei, the highest rate found in the genus Aspergillus so far. The respective enzymes fall into 167 distinct families with most of them corresponding to potentially unique compounds or compound families. Moreover, 53% of the families were only found in a single species, which supports the suitability of species from section Terrei for further genome mining. Intriguingly, this analysis, combined with heterologous gene expression and metabolite identification, suggested that species from section Terrei use a strategy for UV protection different to other species from the genus Aspergillus. Section Terrei contains a complete plant polysaccharide degrading potential and an even higher cellulolytic potential than other Aspergilli, possibly facilitating additional applications for these species in biotechnology.

The import of plant-derived small sugars by sugar transporters (STs) has received increasing interest due to its important biological role and great industrial potential. STs are important targets of genetic engineering to improve fungal plant biomass conversion. Comparatively analysis of the genome-wide prevalence and transcriptomics of STs was performed in four filamentous fungi: Aspergillus niger, Aspergillus nidulans, Penicillium subrubescens and Trichoderma reesei. Using phylogenetic analysis and literature mining, their predicted STs were divided into ten subfamilies with putative sugar specificities assigned. In addition, transcriptome analysis revealed complex expression profiles among different STs subfamilies and fungal species, indicating a sophisticated transcriptome regulation and functional diversity of fungal STs. Several STs showed strong co-expression with other genes involved in sugar utilization, encoding CAZymes and sugar catabolic enzymes. This study provides new insights into the diversity of STs at the genomic/transcriptomic level, facilitating their biochemical characterization and metabolic engineering.

Oceans alleviate the accumulation of atmospheric CO2 by absorbing approximately a quarter of all anthropogenic emissions. In the deep oceans, carbon uptake is dominated by aquatic phase chemistry, whereas in biologically active coastal seas the marine ecosystem and biogeochemistry play an important role in the carbon uptake. Coastal seas are hotspots of organic and inorganic matter transport between the land and the oceans, and thus they are important for the marine carbon cycling. In this study, we investigate the net air–sea CO2 exchange at the Utö Atmospheric and Marine Research Station, located at the southern edge of the Archipelago Sea within the Baltic Sea, using the data collected during 2017–2021. The air–sea fluxes of CO2 were measured using the eddy covariance technique, supported by the flux parameterization based on the pCO2 and wind speed measurements. During the spring–summer months (April–August), the sea was gaining carbon dioxide from the atmosphere, with the highest monthly sink fluxes typically occurring in May, being −0.26 µmol m−2 s−1 on average. The sea was releasing the CO2 to the atmosphere in September–March, and the highest source fluxes were typically observed in September, being 0.42 µmol m−2 s−1 on average. On an annual basis, the study region was found to be a net source of atmospheric CO2, and on average, the annual net exchange was 27.1 gC m−1 yr−1, which is comparable to the exchange observed in the Gulf of Bothnia, the Baltic Sea. The annual net air–sea CO2 exchanges varied between 18.2 (2018) and 39.1 gC m−1 yr−1 (2017). During the coldest year, 2017, the spring–summer sink fluxes remained low compared to the other years, as a result of relatively high seawater pCO2 in summer, which never fell below 220 µatm during that year. The spring–summer phytoplankton blooms of 2017 were weak, possibly due to the cloudy summer and deeply mixed surface layer, which restrained the photosynthetic fixation of dissolved inorganic carbon in the surface waters. The algal blooms in spring–summer 2018 and the consequent pCO2 drawdown were strong, fueled by high pre-spring nutrient concentrations. The systematic positive annual CO2 balances suggest that our coastal study site is affected by carbon flows originating from elsewhere, possibly as organic carbon, which is remineralized and released to the atmosphere as CO2. This coastal source of CO2 fueled by the organic matter originating probably from land ecosystems stresses the importance of understanding the carbon cycling in the land–sea continuum.

Abstract The dataset presents a 43 year-long reanalysis of pollen seasons for three major allergenic genera of trees in Europe: alder (Alnus), birch (Betula), and olive (Olea). Driven by the meteorological reanalysis ERA5, the atmospheric composition model SILAM predicted the flowering period and calculated the Europe-wide dispersion pattern of pollen for the years 1980–2022. The model applied an extended 4-dimensional variational data assimilation of in-situ observations of aerobiological networks in 34 European countries to reproduce the inter-annual variability and trends of pollen production and distribution. The control variable of the assimilation procedure was the total pollen release during each flowering season, implemented as an annual correction factor to the mean pollen production. The dataset was designed as an input to studies on climate-induced and anthropogenically driven changes in the European vegetation, biodiversity monitoring, bioaerosol modelling and assessment, as well as, in combination with intra-seasonal observations, for health-related applications.

Abstract Background Laccases can oxidize a broad spectrum of substrates, offering promising applications in various sectors, such as bioremediation, biomass fractionation in future biorefineries, and synthesis of biochemicals and biopolymers. However, laccase discovery and optimization with a desirable pH optimum remains a challenge due to the labor-intensive and time-consuming nature of the traditional laboratory methods. Results This study presents a machine learning (ML)-integrated approach for predicting pH optima of basidiomycete fungal laccases, utilizing a small, curated dataset against a vast metagenomic data. Comparative computational analyses unveiled the structural and pH-dependent solubility differences between acidic and neutral-alkaline laccases, helping us understand the molecular bases of enzyme pH optimum. The pH profiling of the two ML-predicted alkaline laccase candidates from the basidiomycete fungus Lepista nuda further validated our computational approach, showing the accuracy of this comprehensive method. Conclusions This study uncovers the efficacy of ML in the prediction of enzyme pH optimum from minimal datasets, marking a significant step towards harnessing computational tools for systematic screening of enzymes for biotechnology applications. Graphical Abstract

Speed restrictions for ships have been introduced locally to reduce the waves and turbulence causing erosion, and safety hazards, and to mitigate the air and underwater noise emissions. Ship speed restrictions could be used to minimize the climate impact of maritime transport since many air pollutants in ship exhaust gas are reduced when travelling at lower speeds. However, for example, methane and black carbon emissions do not linearly correlate with the load of internal combustion engines. Therefore, the effect of speed restrictions may not be trivial. Black carbon concentrations from ship plumes were examined at a remote marine site in the southwestern Finnish archipelago. Ships with service speeds over 15 kn and equipped with an exhaust gas cleaning system were analysed for black carbon emissions as a function of speed. Both unadjusted and weather-adjusted main engine loads were modelled to determine load-based emission factors. Black carbon concentration per kilogram of fuel decreased as a function of engine load. However, calculated per hour, the black carbon emission increased as a function of ship speed, reaching peak values at around 15–20 kn and decreasing thereafter. In terms of local air quality, total black carbon emission per nautical mile was the highest around the halved speeds, 10–13 kn, or when the speed was higher than 20–23 kn. From a climate warming perspective, the CO2 emissions dominated the exhaust gas, and reducing the speed decreased the global warming potential in CO2 equivalent, both per hour and per nautical mile.

Abstract Objectives Since Helicopter Emergency Medical Services (HEMS) is an expensive resource in terms of unit price compared to ground-based Emergency Medical Service (EMS), it is important to further investigate which methods would allow for the optimization of these services. The aim of this study was to evaluate the cost-effectiveness of physician-staffed HEMS compared to ground-based EMS in developed scenarios with improvements in triage, aviation performance, and the inclusion of ischemic stroke patients. Methods Incremental cost-effectiveness ratio (ICER) was assessed by comparing health outcomes and costs of HEMS versus ground-based EMS across six different scenarios. Estimated 30-day mortality and quality-adjusted life years (QALYs) were used to measure health benefits. Quality-of-Life (QoL) was assessed with EuroQoL instrument, and a one-way sensitivity analysis was carried out across different patient groups. Survival estimates were evaluated from the national FinnHEMS database, with cost analysis based on the most recent financial reports. Results The best outcome was achieved in Scenario 3.1 which included a reduction in over-alerts, aviation performance enhancement, and assessment of ischemic stroke patients. This scenario yielded 1077.07–1436.09 additional QALYs with an ICER of 33,703-44,937 €/QALY. This represented a 27.72% increase in the additional QALYs and a 21.05% reduction in the ICER compared to the current practice. Conclusions The cost-effectiveness of HEMS can be highly improved by adding stroke patients into the dispatch criteria, as the overall costs are fixed, and the cost-effectiveness is determined based on the utilization rate of capacity.

Background: The combination of an inhaled corticosteroid (ICS) and long-acting β-agonist (LABA) (ICS/LABA) has shown superiority in improving lung function (FEV1) compared with an ICS alone. The clinical effect of a ICS/LABA combination depends on the fine-particle fraction and the pulmonary deposition. Objective: We sought to compare the efficacy of 2 combinations of an ICS and LABA, namely, fluticasone propionate (FP) and formoterol (FORM) (FP/FORM) and fluticasone furoate (FF) and vilanterol (VI) (FF/VI), in asthmatic adolescents with chronic bronchial obstruction. Methods: FP/FORM (125 μg/5 μg, 2 doses twice daily via the k-haler [Mundipharma, Cambridge, UK]) and FF/VI (92 μg/22 μg, once daily via the Ellipta inhaler [GlaxoSmithKline]) were administered to adolescents aged 12 to 17 years who required regular antiasthmatic medication and had a ratio of FEV1 to forced vital capacity (FEV1/FVC) less than –1.65 SD in a 2-sequence, 16-week crossover trial. The primary efficacy end point was change in FEV1 compared with baseline. Secondary end points were FEV1/FVC ratio, maximal expiratory flow at 50% of the FVC, impulse oscillometry indices respiratory resistance at 5 Hz (R5), difference between R5 and respiratory resistance at 20 Hz (R20), area of reactance, and Asthma Control Test score. Results: Both ICS/LABA combinations resulted in a significant improvement in FEV1 and maximal expiratory flow at 50% of the FVC z scores without any significant difference between FP/FORM and FF/VI, with 40% of patients with either treatment achieving a normal prebronchodilator FEV1/FVC z score. Neither area of reactance nor difference between R5 and R20 improved significantly with either treatment. Conclusion: Both ICS/LABA combinations demonstrated significant improvements in FEV1 z score. More than one-third of the asthmatic adolescents with prolonged bronchial obstruction achieved a normal prebronchodilator FEV1/FVC ratio.

Introduction A better understanding of the earliest stages of Alzheimer’s disease (AD) could expedite the development or administration of treatments. Large population biobanks hold the promise to identify individuals at an elevated risk of AD and related dementias based on health registry information. Here, we establish the protocol for an observational clinical recall and biomarker study called TWINGEN with the aim to identify individuals at high risk of AD by assessing cognition, health and AD-related biomarkers. Suitable candidates were identified and invited to participate in the new study among THL Biobank donors according to TWINGEN study criteria.Methods and analysis A multi-centre study (n=800) to obtain blood-based biomarkers, telephone-administered and web-based memory and cognitive parameters, questionnaire information on lifestyle, health and psychological factors, and accelerometer data for measures of physical activity, sedentary behaviour and sleep. A subcohort is being asked to participate in an in-person neuropsychological assessment (n=200) and wear an Oura ring (n=50). All participants in the TWINGEN study have genome-wide genotyping data and up to 48 years of follow-up data from the population-based older Finnish Twin Cohort (FTC) study of the University of Helsinki. The data collected in TWINGEN will be returned to THL Biobank from where it can later be requested for other biobank studies such as FinnGen that supported TWINGEN.Ethics and dissemination This recall study consists of FTC/THL Biobank/FinnGen participants whose data were acquired in accordance with the Finnish Biobank Act. The recruitment protocols followed the biobank protocols approved by Finnish Medicines Agency. The TWINGEN study plan was approved by the Ethics Committee of Hospital District of Helsinki and Uusimaa (number 16831/2022). THL Biobank approved the research plan with the permission no: THLBB2022_83.

The urgent need to mitigate climate change has evoked a broad interest in better understanding and estimating nitrous oxide (N2O) emissions from different ecosystems. Part of the uncertainty in N2O emission estimates still comes from an inadequate understanding of the temporal and small-scale spatial variability of N2O fluxes. Using 4.5 years of N2O flux data collected in a drained peatland forest with six automated chambers, we explored temporal and small-scale spatial variability of N2O fluxes. A random forest with conditional inference trees was used to find immediate and delayed relationships between N2O flux and environmental conditions across seasons and years. The spatiotemporal variation of the N2O flux was large, with daily mean N2O flux varying between −10 and +1760 µgN2Om-2h-1 and annual N2O budgets of different chambers between +60 and +2110 mgN2Om-2yr-1. Spatial differences in fluxes persisted through years of different environmental conditions. Soil moisture, water table level, and air temperature were the most important variables explaining the temporal variation of N2O fluxes. N2O fluxes responded to precipitation events with peak fluxes measured on average 4 d after peaks in soil moisture and water table level. The length of the time lags varied in space and between seasons indicating possible interactions with temperature and other soil conditions. The high temporal variation in N2O flux was related to (a) temporal variation in environmental conditions, with the highest N2O fluxes measured after summer precipitation events and winter soil freezing, and (b) to annually varying seasonal weather conditions, with the highest N2O emissions measured during wet summers and winters with discontinuous snow cover. Climate change may thus increase winter N2O emissions, which may be offset by lower summer N2O emissions in dry years. The high sensitivity of N2O fluxes to seasonal weather conditions suggests increasing variability in annual peatland forest N2O budgets as the frequency of extreme weather events, such as droughts, is predicted to increase.

Abstract Background There has been a proliferation of frameworks with a common goal of bridging the gap between evidence, policy, and practice, but few aim to specifically guide evaluations of academic-policy engagement. We present the modification of an action framework for the purpose of selecting, developing and evaluating interventions for academic-policy engagement. Methods We build on the conceptual work of an existing framework known as SPIRIT (Supporting Policy In Health with Research: an Intervention Trial), developed for the evaluation of strategies intended to increase the use of research in health policy. Our aim was to modify SPIRIT, (i) to be applicable beyond health policy contexts, for example encompassing social, environmental, and economic policy impacts and (ii) to address broader dynamics of academic-policy engagement. We used an iterative approach through literature reviews and consultation with multiple stakeholders from Higher Education Institutions (HEIs) and policy professionals working at different levels of government and across geographical contexts in England, alongside our evaluation activities in the Capabilities in Academic Policy Engagement (CAPE) programme. Results Our modifications expand upon Redman et al.’s original framework, for example adding a domain of ‘Impacts and Sustainability’ to capture continued activities required in the achievement of desirable outcomes. The modified framework fulfils the criteria for a useful action framework, having a clear purpose, being informed by existing understandings, being capable of guiding targeted interventions, and providing a structure to build further knowledge. Conclusion The modified SPIRIT framework is designed to be meaningful and accessible for people working across varied contexts in the evidence-policy ecosystem. It has potential applications in how academic-policy engagement interventions might be developed, evaluated, facilitated and improved, to ultimately support the use of evidence in decision-making.