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Analysis of microplastics (MP) in environmental samples is an emerging field, which is performed with various methods and instruments based either on spectroscopy or thermoanalytical methods. In general, both approaches result in two different types of data sets that are either mass or particle number related. Depending on detection limits of the respective method and instrumentation the derived polymer composition trends may vary. In this study, we compare the results of hyperspectral Fourier-transform infrared (FTIR) imaging analysis and pyrolysis gas chromatography-mass spectrometry (Py-GC/MS) analysis performed on a set of environmental samples that differ in complexity and degree of microplastic contamination. The measurements were conducted consecutively, and on exactly the same sample. First, the samples were investigated with FTIR using aluminum oxide filters; subsequently, these were crushed, transferred to glass fiber filters, in pyrolysis cups, and measured via Py-GC/MS. After a general data harmonization step, the trends in MP contamination were thoroughly investigated with regard to the respective sample set and the derived polymer compositions. While the overall trends in MP contamination were very similar, differences were observed in the polymer compositions. Furthermore, polymer masses were empirically calculated from FTIR data and compared with the Py-GC/MS results. Here, a most plausible shape-related overestimation of the calculated polymer masses was observed in samples with larger particles and increased particle numbers. Taking into account the different measurement principles of both methods, all results were examined and discussed, and future needs for harmonization of intermethodological results were identified and highlighted.

\"In celebration of the 50th anniversary of the Apollo 11 landing, the endlessly-mysterious moon is explored in this reprint short science fiction anthology from award-winning editor and anthologist Neil Clarke ... On July 20, 1969, mankind made what had only years earlier seemed like an impossible leap forward: when Apollo 11 became the first manned mission to land on the moon, and Neil Armstrong the first person to step foot on the lunar surface. While there have only been a handful of new missions since, the fascination with our planet's satellite continues, and generations of writers and artists have imagined the endless possibilities of lunar life. From adventures in the vast gulf of space between the earth and the moon, to journeys across the light face to the dark side, to the establishment of permanent residences on its surface, science fiction has for decades given readers bold and forward-thinking ideas about our nearest interstellar neighbor and what it might mean to humankind, both now and in our future. [This book] collects the best stories written in the fifty years since mankind first stepped foot on the lunar surface, serving as a shining reminder that the moon is and always has been our most visible and constant example of all the infinite possibility of the wider universe\"-- Provided by publisher.

Few studies report the occurrence of microplastics (MP), including tire wear particles (TWP) in the marine atmosphere, and little data is available regarding their size or sources. Here we present active air sampling devices (low- and high-volume samplers) for the evaluation of composition and MP mass loads in the marine atmosphere. Air was sampled during a research cruise along the Norwegian coast up to Bear Island. Samples were analyzed with pyrolysis-gas chromatography-mass spectrometry, generating a mass-based data set for MP in the marine atmosphere. Here we show the ubiquity of MP, even in remote Arctic areas with concentrations up to 37.5 ng m−3. Cluster of polyethylene terephthalate (max. 1.5 ng m−3) were universally present. TWP (max. 35 ng m−3) and cluster of polystyrene, polypropylene, and polyurethane (max. 1.1 ng m−3) were also detected. Atmospheric transport and dispersion models, suggested the introduction of MP into the marine atmosphere equally from sea- and land-based emissions, transforming the ocean from a sink into a source for MP.

Spermatozoa harbour a complex and environment-sensitive pool of small non-coding RNAs (sncRNAs) 1 , which influences offspring development and adult phenotypes 1 – 7 . Whether spermatozoa in the epididymis are directly susceptible to environmental cues is not fully understood 8 . Here we used two distinct paradigms of preconception acute high-fat diet to dissect epididymal versus testicular contributions to the sperm sncRNA pool and offspring health. We show that epididymal spermatozoa, but not developing germ cells, are sensitive to the environment and identify mitochondrial tRNAs (mt-tRNAs) and their fragments (mt-tsRNAs) as sperm-borne factors. In humans, mt-tsRNAs in spermatozoa correlate with body mass index, and paternal overweight at conception doubles offspring obesity risk and compromises metabolic health. Sperm sncRNA sequencing of mice mutant for genes involved in mitochondrial function, and metabolic phenotyping of their wild-type offspring, suggest that the upregulation of mt-tsRNAs is downstream of mitochondrial dysfunction. Single-embryo transcriptomics of genetically hybrid two-cell embryos demonstrated sperm-to-oocyte transfer of mt-tRNAs at fertilization and suggested their involvement in the control of early-embryo transcription. Our study supports the importance of paternal health at conception for offspring metabolism, shows that mt-tRNAs are diet-induced and sperm-borne and demonstrates, in a physiological setting, father-to-offspring transfer of sperm mitochondrial RNAs at fertilization. A study shows that epididymal spermatozoa are sensitive to preconception diet, identifies mitochondrial tRNAs and their fragments as sperm-borne factors and demonstrates epigenetic inheritance of mitochondrial tRNAs.

Atmospheric aerosols significantly impact Earth's climate and air quality. In addition to their number and mass concentrations, chemical composition influences their environmental effects. This study examines global trends in aerosol composition from 2000 to 2020, using the EMAC atmospheric chemistry–climate model and a variety of observational datasets. These include PM2.5 surface data from regional networks and 744 PM1 datasets from 169 aerosol mass spectrometer (AMS) field campaigns worldwide. Organic aerosol (OA) is the dominant fine aerosol component across all continents, particularly in areas with significant biomass burning and biogenic volatile organic compound (VOC) emissions. EMAC reproduces the prevalence of secondary OA but underestimates OA aging, revealing uncertainties in distinguishing fresh versus aged secondary organic aerosol (SOA). Although sulfate remains a major component in filter-based observations, both AMS measurements and model simulations reveal that nitrate has emerged as the dominant aerosol species in Europe and Eastern Asia over the past decade, except in summer. Mineral dust also contributes significantly to specific regions, as highlighted by EMAC. The study identifies substantial declines in sulfate, nitrate, and ammonium in Europe and North America, attributed to emission controls, though EMAC underestimates these reductions, especially sulfate, due to discrepancies in early 2000s levels. In Eastern Asia, sulfate reductions due to SO2 controls are partially captured. OA trends differ between methodologies, with filter data showing slight decreases, while AMS and model results suggest slight increases in PM1 OA across Europe, North America, and Eastern Asia. These findings underscore the need for integrating advanced models and diverse datasets to better understand aerosol trends and guide environmental policy.

We use a genome-wide association of 1 million parental lifespans of genotyped subjects and data on mortality risk factors to validate previously unreplicated findings near CDKN2B-AS1, ATXN2/BRAP, FURIN/FES, ZW10, PSORS1C3, and 13q21.31, and identify and replicate novel findings near ABO, ZC3HC1, and IGF2R. We also validate previous findings near 5q33.3/EBF1 and FOXO3, whilst finding contradictory evidence at other loci. Gene set and cell-specific analyses show that expression in foetal brain cells and adult dorsolateral prefrontal cortex is enriched for lifespan variation, as are gene pathways involving lipid proteins and homeostasis, vesicle-mediated transport, and synaptic function. Individual genetic variants that increase dementia, cardiovascular disease, and lung cancer – but not other cancers – explain the most variance. Resulting polygenic scores show a mean lifespan difference of around five years of life across the deciles. Editorial note: This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (see decision letter ). Ageing happens to us all, and as the cabaret singer Maurice Chevalier pointed out, \"old age is not that bad when you consider the alternative\". Yet, the growing ageing population of most developed countries presents challenges to healthcare systems and government finances. For many older people, long periods of ill health are part of the end of life, and so a better understanding of ageing could offer the opportunity to prolong healthy living into old age. Ageing is complex and takes a long time to study – a lifetime in fact. This makes it difficult to discern its causes, among the countless possibilities based on an individual’s genes, behaviour or environment. While thousands of regions in an individual’s genetic makeup are known to influence their risk of different diseases, those that affect how long they will live have proved harder to disentangle. Timmers et al. sought to pinpoint such regions, and then use this information to predict, based on their DNA, whether someone had a better or worse chance of living longer than average. The DNA of over 500,000 people was read to reveal the specific ‘genetic fingerprints’ of each participant. Then, after asking each of the participants how long both of their parents had lived, Timmers et al. pinpointed 12 DNA regions that affect lifespan. Five of these regions were new and had not been linked to lifespan before. Across the twelve as a whole several were known to be involved in Alzheimer’s disease, smoking-related cancer or heart disease. Looking at the entire genome, Timmers et al. could then predict a lifespan score for each individual, and when they sorted participants into ten groups based on these scores they found that top group lived five years longer than the bottom, on average. Many factors beside genetics influence how long a person will live and our lifespan cannot be read from our DNA alone. Nevertheless, Timmers et al. had hoped to narrow down their search and discover specific genes that directly influence how quickly people age, beyond diseases. If such genes exist, their effects were too small to be detected in this study. The next step will be to expand the study to include more participants, which will hopefully pinpoint further genomic regions and help disentangle the biology of ageing and disease.

In recent years, nitrate aerosols have become a dominant component of atmospheric composition, surpassing sulfate in both concentration and climatic impact. However, accurately simulating nitrate remains a major challenge for global models due to complex formation mechanisms and strong regional variability. This study investigates key factors influencing nitrate aerosol formation to improve simulation accuracy in polluted regions. Using the EMAC climate–chemistry model and the ISORROPIA II thermodynamic module, we assess the effects of grid resolution, emission inventories, chemical kinetics, thermodynamic assumptions, and aerosol scavenging processes. Model predictions are evaluated against PM2.5 and PM1 nitrate observations from filter networks and aerosol mass spectrometer campaigns across Europe, North America, East Asia, and India. Results show that PM2.5 nitrate is generally overestimated, especially in East Asia (up to a factor of three), while PM1 nitrate is underestimated, particularly at urban-downwind sites. Higher grid resolution, adjusted N2O5 uptake, and updated emissions (e.g., CMIP6) improve PM2.5 predictions but do not consistently enhance PM1 accuracy. Seasonal and diurnal biases are most pronounced in Europe, where the model fails to capture observed nitrate variability. Sensitivity tests show limited impact on the total tropospheric nitrate burden (within 25 %). A combined configuration using high grid resolution, reduced N2O5 uptake, and the HTAPv3 emission inventory improves PM2.5 predictions in low-concentration periods and U.S. networks, but PM1 biases persist regionally. These findings highlight the difficulty of achieving consistent improvements across aerosol size modes and diverse geographic regions.

Transition-metal complexes have long attracted interest for fundamental chemical reactivity studies and possible use in solar energy conversion 1 , 2 . Electronic excitation, ligand loss from the metal centre, or a combination of both, creates changes in charge and spin density at the metal site 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 that need to be controlled to optimize complexes for photocatalytic hydrogen production 8 and selective carbon–hydrogen bond activation 9 , 10 , 11 . An understanding at the molecular level of how transition-metal complexes catalyse reactions, and in particular of the role of the short-lived and reactive intermediate states involved, will be critical for such optimization. However, suitable methods for detailed characterization of electronic excited states have been lacking. Here we show, with the use of X-ray laser-based femtosecond-resolution spectroscopy and advanced quantum chemical theory to probe the reaction dynamics of the benchmark transition-metal complex Fe(CO) 5 in solution, that the photo-induced removal of CO generates the 16-electron Fe(CO) 4 species, a homogeneous catalyst 12 , 13 with an electron deficiency at the Fe centre 14 , 15 , in a hitherto unreported excited singlet state that either converts to the triplet ground state or combines with a CO or solvent molecule to regenerate a penta-coordinated Fe species on a sub-picosecond timescale. This finding, which resolves the debate about the relative importance of different spin channels in the photochemistry of Fe(CO) 5 (refs 4 , 16 , 17 , 18 , 19 and 20 ), was made possible by the ability of femtosecond X-ray spectroscopy to probe frontier-orbital interactions with atom specificity. We expect the method to be broadly applicable in the chemical sciences, and to complement approaches that probe structural dynamics in ultrafast processes. Mapping the frontier-orbital interactions with atom specificity using X-ray laser-based femtosecond-resolution spectroscopy reveals that spin crossover and ligation determine the sub-picosecond excited-state dynamics of a transition-metal complex in solution. Dynamics of a transition-metal complex in solution Transition-metal complexes catalyse many reactions of fundamental and practical importance. Their performance is coupled to charge and spin density changes at the metal site caused by electronic excitation, ligand loss from the metal centre or a combination of both. Philippe Wernet et al . show that femtosecond X-ray spectroscopy and quantum chemical theory can deliver unprecedented molecular-level insight into the dynamics of the benchmark transition-metal complex Fe(CO) 5 , revealing that light-induced dissociation creates a previously unreported excited singlet species and its subsequent reactions. These insights are enabled by the ability of femtosecond X-ray spectroscopy to probe, with atom specificity, frontier-orbital interactions that lie at the heart of chemical transformation. The method, expected to be widely applicable, complements approaches that probe the structural changes accompanying ultrafast chemical reactions.

Cavitation bubbles can be seeded from a plasma following optical breakdown, by focusing an intense laser in water. The fast dynamics are associated with extreme states of gas and liquid, especially in the nascent state. This offers a unique setting to probe water and water vapor far-from equilibrium. However, current optical techniques cannot quantify these early states due to contrast and resolution limitations. X-ray holography with single X-ray free-electron laser pulses has now enabled a quasi-instantaneous high resolution structural probe with contrast proportional to the electron density of the object. In this work, we demonstrate cone-beam holographic flash imaging of laser-induced cavitation bubbles in water with nanofocused X-ray free-electron laser pulses. We quantify the spatial and temporal pressure distribution of the shockwave surrounding the expanding cavitation bubble at time delays shortly after seeding and compare the results to numerical simulations. Cavitation bubbles show many nonlinear characteristics of liquid and gas phase. Here the authors demonstrate coherent diffractive imaging of cavitation bubble using infrared pump and XFEL probe and discuss the formation and evolution of the bubbles.