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Low-salinity meltwater from Arctic sea ice and its snow cover accumulates and creates under-ice meltwater layers below sea ice. These meltwater layers can result in the formation of new ice layers, or false bottoms, at the interface of this low-salinity meltwater and colder seawater. As part of the Multidisciplinary drifting Observatory for the Study of the Arctic Climate (MOSAiC), we used a combination of sea ice coring, temperature profiles from thermistor strings and underwater multibeam sonar surveys with a remotely operated vehicle (ROV) to study the areal coverage and temporal evolution of under-ice meltwater layers and false bottoms during the summer melt season from mid-June until late July. ROV surveys indicated that the areal coverage of false bottoms for a part of the MOSAiC Central Observatory (350 by 200 m2) was 21%. Presence of false bottoms reduced bottom ice melt by 7–8% due to the local decrease in the ocean heat flux, which can be described by a thermodynamic model. Under-ice meltwater layer thickness was larger below first-year ice and thinner below thicker second-year ice. We also found that thick ice and ridge keels confined the areas in which under-ice meltwater accumulated, preventing its mixing with underlying seawater. While a thermodynamic model could reproduce false bottom growth and melt, it could not describe the observed bottom melt rates of the ice above false bottoms. We also show that the evolution of under-ice meltwater-layer salinity below first-year ice is linked to brine flushing from the above sea ice and accumulating in the meltwater layer above the false bottom. The results of this study aid in estimating the contribution of under-ice meltwater layers and false bottoms to the mass balance and salt budget for Arctic summer sea ice.

Genotype-guided warfarin dosing have been proposed to improve patient’s management. This study is aimed to determine whether a CYP2C9- VKORC1- CYP4F2-based pharmacogenetic algorithm is superior to a standard, clinically adopted, pharmacodynamic method. Two-hundred naïve patients with non-valvular atrial fibrillation were randomized to trial arms and 180 completed the study. No significant differences were found in the number of out-of-range INRs (INR<2.0 or >3.0) (p = 0.79) and in the mean percentage of time spent in the therapeutic range (TTR) after 19 days in the pharmacogenetic (51.9%) and in the control arm (53.2%, p = 0.71). The percentage of time spent at INR>4.0 was significantly lower in the pharmacogenetic (0.7%) than in the control arm (1.8%) (p = 0.02). Genotype-guided warfarin dosing is not superior in overall anticoagulation control when compared to accurate clinical standard of care. ClinicalTrials.gov NCT01178034.

The CMS detector, including its muon system, has been operating at the CERN LHC in increasingly challenging conditions for about 15 years. The muon detector was designed to provide excellent triggering and track reconstruction for muons produced in proton–proton collisons at an instantaneous luminosity ( L ) of 1 × 10 34  cm - 2 s - 1 . During the Run 2 data-taking period (2015–2018), the LHC achieved an instantaneous luminosity of twice its design value, resulting in larger background rates and making the efficient detection of muons more difficult. While some backgrounds result from natural radioactivity, cosmic rays, and interactions of the circulating protons with residual gas in the beam pipe, the dominant source of background hits in the muon system arises from proton–proton interactions themselves. Charged hadrons leaving the calorimeters produce energy deposits in the muon chambers. In addition, high-energy particles interacting in the hadron calorimeter and forward shielding elements generate thermal neutrons, which leak out of the calorimeter and shielding structures, filling the CMS cavern. We describe the method used to measure the background rates in the various muon subsystems. These rates, in conjunction with simulations, can be used to estimate the expected backgrounds in the High-Luminosity LHC. This machine will run for at least 10 years starting in 2029 reaching an instantaneous luminosity of L = 5 × 10 34 cm -2 s -1 and increasing ultimately to L = 7.5 × 10 34 cm -2 s -1 . These background estimates have been a key ingredient for the planning and design of the muon detector upgrade.

PurposeA previous trial failed to demonstrate the superiority of a demographic-genetic algorithm in predicting warfarin (W) dose over a standard clinical approach. The purpose of the present study is to re-analyse the results in subgroups of patients with differing baseline sensitivity to W, integrated with additional pharmacokinetic data.MethodsThe original trial allocated 180 treatment-naïve patients with non-valvular atrial fibrillation to a control arm (CTL, n = 92) or a genetic-guided arm (GEN, n = 88). Before starting anticoagulation treatment, all patients were genotyped for CYP2C9, VKORC1 and CYP4F2 variants and classified into four quartiles (Q1, Q2, Q3, Q4) according to the algorithm-predicted W maintenance dose. International normalised ratios (INR) and plasma concentrations of S-warfarin [S-W]s and R-warfarin [R-W]s were measured at baseline and on days 5, 7, 9, 12, 15 and 19 of therapy.ResultsIn the lowest dose quartile (Q1), the number of INRs > 3 and mean INR values on days 5 and 7 were significantly higher in CTL than in GEN. In Q3 and Q4, the mean INR values reached therapeutic level (> 2) 2 days later in CTL than in GEN. During follow-up, the mean time courses of INRs and [S-W]s in GEN were remarkably stable in all dose quartiles. Thus, mean changes from starting to final doses were significantly smaller in GEN than in CTL. Plasma concentrations of R-W (a partially active enantiomer) steadily increased from day 5 to day 19 in all Qs in both CTL and GEN, except in the Q1 CTL group, due to the marked dose reduction required.ConclusionsThis analysis showed that the demographic-genetic algorithm used to predict the W dose can identify patients with differing degrees of sensitivity to W and to ‘normalise’ their average anticoagulant responses. The progressive rise in [R-W]s throughout the 19-day follow-up indicates that the (partial) contribution of R-W to the W anticoagulant effect changes continually during the early phase of treatment.

The CMS detector, including its muon system, has been operating at the CERN LHC in increasingly challenging conditions for about 15 years. The muon detector was designed to provide excellent triggering and track reconstruction for muons produced in proton–proton collisons at an instantaneous luminosity ($$\\mathcal {L}$$L ) of$$1 \\times 10^{34}$$1 × 10 34  cm$$^{-2}$$- 2 s$$^{-1}$$- 1 . During the Run 2 data-taking period (2015–2018), the LHC achieved an instantaneous luminosity of twice its design value, resulting in larger background rates and making the efficient detection of muons more difficult. While some backgrounds result from natural radioactivity, cosmic rays, and interactions of the circulating protons with residual gas in the beam pipe, the dominant source of background hits in the muon system arises from proton–proton interactions themselves. Charged hadrons leaving the calorimeters produce energy deposits in the muon chambers. In addition, high-energy particles interacting in the hadron calorimeter and forward shielding elements generate thermal neutrons, which leak out of the calorimeter and shielding structures, filling the CMS cavern. We describe the method used to measure the background rates in the various muon subsystems. These rates, in conjunction with simulations, can be used to estimate the expected backgrounds in the High-Luminosity LHC. This machine will run for at least 10 years starting in 2029 reaching an instantaneous luminosity of$$\\mathcal {L} = 5 \\times \\text {10}^\\text {34}\\,\\text {cm}^\\text {-2}\\,\\text {s}^\\text {-1}$$L = 5 × 10 34 cm -2 s -1 and increasing ultimately to$$\\mathcal {L} = 7.5 \\times \\text {10}^\\text {34}\\,\\text {cm}^\\text {-2}\\,\\text {s}^\\text {-1}$$L = 7.5 × 10 34 cm -2 s -1 . These background estimates have been a key ingredient for the planning and design of the muon detector upgrade.

Background Lower urinary tract symptoms (LUTS) and prostate specific antigen-based parameters seem to have only a limited utility for the differential diagnosis of prostate cancer (PCa). MALDI-TOF/MS peptidomic profiling could be a useful diagnostic tool for biomarker discovery, although reproducibility issues have limited its applicability until now. The current study aimed to evaluate a new MALDI-TOF/MS candidate biomarker. Methods Within- and between-subject variability of MALDI-TOF/MS-based peptidomic urine and serum analyses were evaluated in 20 and 15 healthy donors, respectively. Normalizations and approaches for accounting below limit of detection (LOD) values were utilized to enhance reproducibility, while Monte Carlo experiments were performed to verify whether measurement error can be dealt with LOD data. Post-prostatic massage urine and serum samples from 148 LUTS patients were analysed using MALDI-TOF/MS. Regression-calibration and simulation and extrapolation methods were used to derive the unbiased association between peptidomic features and PCa. Results Although the median normalized peptidomic variability was 24.9%, the within- and between-subject variability showed that median normalization, LOD adjustment, and log 2 data transformation were the best combination in terms of reliability; in measurement error conditions, intraclass correlation coefficient was a reliable estimate when the LOD/2 was substituted for below LOD values. In the patients studied, 43 peptides were shared by the urine and serum, and several features were found to be associated with PCa. Only few serum features, however, show statistical significance after the multiple testing procedures were completed. Two serum fragmentation patterns corresponded to the complement C4-A. Conclusions MALDI-TOF/MS serum peptidome profiling was more efficacious with respect to post-prostatic massage urine analysis in discriminating PCa.

The relationship between biodiversity and ecosystem productivity has been explored in detail in herbaceous vegetation, but patterns in forests are far less well understood. Liang et al. have amassed a global forest data set from >770,000 sample plots in 44 countries. A positive and consistent relationship can be discerned between tree diversity and ecosystem productivity at landscape, country, and ecoregion scales. On average, a 10% loss in biodiversity leads to a 3% loss in productivity. This means that the economic value of maintaining biodiversity for the sake of global forest productivity is more than fivefold greater than global conservation costs. Science , this issue p. 196 Global forest inventory records suggest that biodiversity loss would result in a decline in forest productivity worldwide. The biodiversity-productivity relationship (BPR) is foundational to our understanding of the global extinction crisis and its impacts on ecosystem functioning. Understanding BPR is critical for the accurate valuation and effective conservation of biodiversity. Using ground-sourced data from 777,126 permanent plots, spanning 44 countries and most terrestrial biomes, we reveal a globally consistent positive concave-down BPR, showing that continued biodiversity loss would result in an accelerating decline in forest productivity worldwide. The value of biodiversity in maintaining commercial forest productivity alone—US$166 billion to 490 billion per year according to our estimation—is more than twice what it would cost to implement effective global conservation. This highlights the need for a worldwide reassessment of biodiversity values, forest management strategies, and conservation priorities.

Reduced appetite with ageing is a key factor that may increase risk of undernutrition. The objective of this study is to determine the impact of innovative plant protein fibre (PPF) products within a personalised optimised diet (PD), a physical activity (PA) programme, and their combination on appetite, and other nutritional, functional and clinical outcomes in community-dwelling older adults in a multi-country randomised controlled intervention trial. One hundred and eighty community-dwelling adults (approximately sixty per trial centre in Germany, Ireland and Italy) aged 65 years and over will be recruited to participate in a 12-week, parallel-group, controlled trial. Participants will be randomised into one of four groups: 1, PD (incorporating two PPF products): 2, PA; 3, PD + PA; and 4, no intervention (control). The primary outcome is appetite measured by visual analogue scales and energy intake from an ad libitum test meal. Secondary outcomes include fasting and postprandial appetite-related gut hormones, Simplified Nutritional Appetite Questionnaire score, body composition, cardiorespiratory fitness, muscle strength, physical function and PA. In addition, self-efficacy, cognitive status, dietary restraint, depressive symptoms and compliance and acceptability of the intervention will be assessed. Metabolomic profiles, RMR, muscle motor unit properties and gut microbiome will also be assessed to explore potential underlying mechanisms. This multi-centre randomised controlled trial will advance knowledge on how PD (incorporating PPF products), PA and their combination influence appetite, nutritional status and related health outcomes in community-dwelling older adults and contribute to the prevention of undernutrition. Trial registration: Clinical Trials.gov Registry NCT05608707 (registered on 2 November 2022). Protocol Version: NCT05608707 Version 4 (registered on 29 September 2023).

The rapid melt of snow and sea ice during the Arctic summer provides a significant source of low-salinity meltwater to the surface ocean on the local scale. The accumulation of this meltwater on, under, and around sea ice floes can result in relatively thin meltwater layers in the upper ocean. Due to the small-scale nature of these upper-ocean features, typically on the order of 1 m thick or less, they are rarely detected by standard methods, but are nevertheless pervasive and critically important in Arctic summer. Observations during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition in summer 2020 focused on the evolution of such layers and made significant advancements in understanding their role in the coupled Arctic system. Here we provide a review of thin meltwater layers in the Arctic, with emphasis on the

The international and interdisciplinary sea-ice drift expedition “The Multidisciplinary drifting Observatory for the Study of Arctic Climate” (MOSAiC) was conducted from October 2019 to September 2020. The aim of MOSAiC was to study the interconnected physical, chemical, and biological characteristics and processes from the atmosphere to the deep sea of the central Arctic system. The ecosystem team addressed current knowledge gaps and explored unknown biological properties over a complete seasonal cycle focusing on three major research areas: biodiversity, biogeochemical cycles, and linkages to the environment. In addition to the measurements of core properties along a complete seasonal cycle, dedicated projects covered specific processes and habitats, or organisms on higher taxonomic or temporal resolution in specific time windows. A wide range of sampling instruments and approaches, including sea-ice coring, lead sampling with pumps, rosette-based water sampling, plankton nets, remotely operated vehicles, and acoustic buoys, was applied to address the science objectives. Further, a broad range of process-related measurements to address, for example, productivity patterns, seasonal migrations, and diversity shifts, were made both in situ and onboard RV Polarstern. This article provides a detailed overview of the sampling approaches used to address the three main science objectives. It highlights the core sampling program and provides examples of habitat- or process-specific sampling. The initial results presented include high biological activities in wintertime and the discovery of biological hotspots in underexplored habitats. The unique interconnectivity of the coordinated sampling efforts also revealed insights into cross-disciplinary interactions like the impact of biota on Arctic cloud formation. This overview further presents both lessons learned from conducting such a demanding field campaign and an outlook on spin-off projects to be conducted over the next years.