Sr2+/Ca2+ and 44Ca/40Ca fractionation during inorganic calcite formation: III. Impact of salinity/ionic strength

In order to apply Sr/Ca and 44Ca/40Ca fractionation during calcium carbonate (CaCO3) formation as a proxy to reconstruct paleo-environments, it is essential to evaluate the impact of various environmental factors. In this study, a CO2 diffusion technique was used to crystallize inorganic calcite from aqueous solutions at different ionic strength/salinity by the addition of NaCl at 25 °C. Results show that the discrimination of Sr2+ versus Ca2+ during calcite formation is mainly controlled by precipitation rate (R in μmol/m2/h) and is weakly influenced by ionic strength/salinity. In analogy to Sr incorporation, 44Ca/40Ca fractionation during precipitation of calcite is weakly influenced by ionic strength/salinity too. At 25 °C the calcium isotope fractionation between calcite and aqueous calcium ions (Δ44/40Cacalcite-aq = δ44/40Cacalcite − δ44/40Caaq) correlates inversely to log R values for all experiments. In addition, an inverse relationship between Δ44/40Cacalcite-aq and log DSr, which is independent of temperature, precipitation rate, and aqueous (Sr/Ca)aq ratio, is not affected by ionic strength/salinity either. Considering the log DSr and Δ44/40Cacalcite-aq relationship, Sr/Ca and δ44/40Cacalcite values of precipitated calcite can be used as an excellent multi-proxy approach to reconstruct environmental conditions (e.g., temperature, precipitation rate) of calcite growth and diagenetic alteration

Boreal forest riparian zones regulate stream sulfate and dissolved organic carbon

In boreal forest catchments, solute transfer to streams is controlled by hydrological and biogeochemical processes occurring in the riparian zone (RZ). However, RZs are spatially heterogeneous and information about solute chemistry is typically limited. This is problematic when making inferences about stream chemistry. Hypothetically, the strength of links between riparian and stream chemistry is time-scale dependent. Using a ten-year (2003 − 2012) dataset from a northern Swedish catchment, we evaluated the suitability of RZ data to infer stream dynamics at different time scales. We focus on the role of the RZ versus upslope soils in controlling sulfate (SO42−) and dissolved organic carbon (DOC). A priori, declines in acid deposition and redox-mediated SO42− pulses control sulfur (S) fluxes and pool dynamics, which in turn affect dissolved organic carbon (DOC). We found that the catchment is currently a net source of S, presumably due to release of the S pool accumulated during the acidification period. In both, RZ and stream, SO42 − concentrations are declining over time, whereas DOC is increasing. No temporal trends in SO42 − and DOC were observed in upslope mineral soils. SO42 − explained the variation of DOC in stream and RZ, but not in upslope mineral soil. Moreover, as SO42 − decreased with time, temporal variability of DOC increased. These observations indicate that: (1) SO42 − is still an important driver of DOC trends in boreal catchments and (2) RZ processes control stream SO42 − and subsequently DOC independently of upslope soils. These phenomena are likely occurring in many regions recovering from acidification. Because water flows through a heterogeneous mosaic of RZs before entering the stream, upscaling information from limited RZ data to the catchment level is problematic at short-time scales. However, for long-term trends and annual dynamics, the same data can provide reasonable representations of riparian processes and support meaningful inferences about stream chemistry

AbspectroscoPY, a Python toolbox for absorbance-based sensor data in water quality monitoring

The long-term trend of increasing natural organic matter (NOM) in boreal and north European surface waters represents an economic and environmental challenge for drinking water treatment plants (DWTPs). High-frequency measurements from absorbance-based online spectrophotometers are often used in modern DWTPs to measure the chromophoric fraction of dissolved organic matter (CDOM) over time. These data contain valuable information that can be used to optimise NOM removal at various stages of treatment and/or diagnose the causes of underperformance at the DWTP. However, automated monitoring systems generate large datasets that need careful preprocessing, followed by variable selection and signal processing before interpretation. In this work we introduce AbspectroscoPY ("Absorbance spectroscopic analysis in Python"), a Python toolbox for processing time-series datasets collected by in situ spectrophotometers. The toolbox addresses some of the main challenges in data preprocessing by handling duplicates, systematic time shifts, baseline corrections and outliers. It contains automated functions to compute a range of spectral metrics for the time-series data, including absorbance ratios, exponential fits, slope ratios and spectral slope curves. To demonstrate its utility, AbspectroscoPY was applied to 15-month datasets from three online spectrophotometers in a drinking water treatment plant. Despite only small variations in surface water quality over the time period, variability in the spectrophotometric profiles of treated water could be identified, quantified and related to lake turnover or operational changes in the DWTP. This toolbox represents a step toward automated early warning systems for detecting and responding to potential threats to treatment performance caused by rapid changes in incoming water quality

Determinants of cognitive performance and decline in 20 diverse ethno-regional groups: A COSMIC collaboration cohort study

Background: With no effective treatments for cognitive decline or dementia, improving the evidence base for modifiable risk factors is a research priority. This study investigated associations between risk factors and late-life cognitive decline on a global scale, including comparisons between ethno-regional groups. Methods and findings: We harmonized longitudinal data from 20 population-based cohorts from 15 countries over 5 continents, including 48,522 individuals (58.4% women) aged 54–105 (mean = 72.7) years and without dementia at baseline. Studies had 2–15 years of follow-up. The risk factors investigated were age, sex, education, alcohol consumption, anxiety, apolipoprotein E ε4 allele (APOE*4) status, atrial fibrillation, blood pressure and pulse pressure, body mass index, cardiovascular disease, depression, diabetes, self-rated health, high cholesterol, hypertension, peripheral vascular disease, physical activity, smoking, and history of stroke. Associations with risk factors were determined for a global cognitive composite outcome (memory, language, processing speed, and executive functioning tests) and Mini-Mental State Examination score. Individual participant data meta-analyses of multivariable linear mixed model results pooled across cohorts revealed that for at least 1 cognitive outcome, age (B = −0.1, SE = 0.01), APOE*4 carriage (B = −0.31, SE = 0.11), depression (B = −0.11, SE = 0.06), diabetes (B = −0.23, SE = 0.10), current smoking (B = −0.20, SE = 0.08), and history of stroke (B = −0.22, SE = 0.09) were independently associated with poorer cognitive performance (p < 0.05 for all), and higher levels of education (B = 0.12, SE = 0.02) and vigorous physical activity (B = 0.17, SE = 0.06) were associated with better performance (p < 0.01 for both). Age (B = −0.07, SE = 0.01), APOE*4 carriage (B = −0.41, SE = 0.18), and diabetes (B = −0.18, SE = 0.10) were independently associated with faster cognitive decline (p < 0.05 for all). Different effects between Asian people and white people included stronger associations for Asian people between ever smoking and poorer cognition (group by risk factor interaction: B = −0.24, SE = 0.12), and between diabetes and cognitive decline (B = −0.66, SE = 0.27; p < 0.05 for both). Limitations of our study include a loss or distortion of risk factor data with harmonization, and not investigating factors at midlife. Conclusions: These results suggest that education, smoking, physical activity, diabetes, and stroke are all modifiable factors associated with cognitive decline. If these factors are determined to be causal, controlling them could minimize worldwide levels of cognitive decline. However, any global prevention strategy may need to consider ethno-regional differences

The Human Phenotype Ontology in 2024: phenotypes around the world.

The Human Phenotype Ontology (HPO) is a widely used resource that comprehensively organizes and defines the phenotypic features of human disease, enabling computational inference and supporting genomic and phenotypic analyses through semantic similarity and machine learning algorithms. The HPO has widespread applications in clinical diagnostics and translational research, including genomic diagnostics, gene-disease discovery, and cohort analytics. In recent years, groups around the world have developed translations of the HPO from English to other languages, and the HPO browser has been internationalized, allowing users to view HPO term labels and in many cases synonyms and definitions in ten languages in addition to English. Since our last report, a total of 2239 new HPO terms and 49235 new HPO annotations were developed, many in collaboration with external groups in the fields of psychiatry, arthrogryposis, immunology and cardiology. The Medical Action Ontology (MAxO) is a new effort to model treatments and other measures taken for clinical management. Finally, the HPO consortium is contributing to efforts to integrate the HPO and the GA4GH Phenopacket Schema into electronic health records (EHRs) with the goal of more standardized and computable integration of rare disease data in EHRs

Progress in hybrid plasma wakefield acceleration

Plasma wakefield accelerators can be driven either by intense laser pulses (LWFA) or by intense particle beams (PWFA). A third approach that combines the complementary advantages of both types of plasma wakefield accelerator has been established with increasing success over the last decade and is called hybrid LWFA→PWFA. Essentially, a compact LWFA is exploited to produce an energetic, high-current electron beam as a driver for a subsequent PWFA stage, which, in turn, is exploited for phase-constant, inherently laser-synchronized, quasi-static acceleration over extended acceleration lengths. The sum is greater than its parts: the approach not only provides a compact, cost-effective alternative to linac-driven PWFA for exploitation of PWFA and its advantages for acceleration and high-brightness beam generation, but extends the parameter range accessible for PWFA and, through the added benefit of co-location of inherently synchronized laser pulses, enables high-precision pump/probing, injection, seeding and unique experimental constellations, e.g., for beam coordination and collision experiments. We report on the accelerating progress of the approach achieved in a series of collaborative experiments and discuss future prospects and potential impact

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements