Quantification of mixed contributions of primary producers from amino acid δ15N of marine consumers: a Bayesian approach.

Estimations of the trophic position (TP) and the food web nitrogen baseline from compound-specific isotope analysis of individual amino acids (CSIA-AA) are challenged when the diet of consumer organisms relies on different proportions of vascular and non-vascular primary producers. Here we provide a new method to infer such proportions using the δ15N patterns from individual AAs (δ15NAA) in the consumer. Combining published and new data, we first characterized the δ15NAA signatures in primary producers and determined the isotopic enrichment (β) for the major taxa of primary producers. Then, we applied MixSIAR Bayesian isotope mixing models to investigate the transfer of these signatures to marine primary consumers (molluscs, green turtles, zooplankton and fish), and their utility to quantify autotrophic sources. Reliable source proportions were quantified, using appropriate combinations of trophic discrimination factors (TDFs), and were used to estimate β values for each consumer. We demonstrated that phytoplankton, macroalgae and vascular plants have singular δ15NAA fingerprints that can be tracked from the δ15NAA values in their primary consumers, and can be used to estimate mixed baseline sources. This method is useful to accurately estimate βmix values from consumer δ15NAA signatures with no requirement to sample or characterize the primary producers supporting the food web, thus providing reliable TP estimates in complex environments dominated by vascular and non-vascular autotrophs. This study evidences a suitable integration of δ15NAA fingerprinting and MixSIAR for quantitative estimations of autotrophic sources, complementing other methods to quantify resource utilization in natural systems. This method represents a major advance to unravel trophic dynamics at the aquatic/terrestrial interface using CSIA-AA.PID2020-115620RB-100, funded by MCIN/AEI/10.13039/50110001103

TEMPORAL TRENDS OF HEAVY METAL CONCENTRATIONS IN BROWN MACROALGAE FROM COASTAL ENVIRONMENTS

Heavy metals are one of the major drivers of ecological changes in coastal ecosystems. Macroalgae are primary producers of great relevance for ecosystem structure and functioning in these environments, and play a key role in the trophic transfer of these contaminants in the food web. Here, we present the most extensive assessment until now (>3500 records) of heavy metal concentrations in brown macroalgae (Class Phaeophyceae) sampled between 1933 and 2020 worldwide. The study compiles this information from 420 peer reviewed articles to be used as a proxy of global long-term changes in metal concentrations. We report the first detailed multi-decadal time series of Cd, Co, Cr, Cu, Fe, Hg, Mn, Pb and Zn in algae using generalized additive models (GAMs), confirming a significant decrease in metal contamination in the world’s coastal environments since ca. the 1970s for Pb (84% reduction), Zn (79%), Cd (77%) and Cu (72%), since the 1980s for Mn (75%) and Hg (65%), and since the 1990s for Cr (66%), Fe (64%) and Co (60%). Important environmental consequences for the whole aquatic ecosystem, even for human health, may be expected from these changes. The present results provide a building block for the overall evaluation of the status and trends of marine metal contamination, and will help researchers and policy makers to promote new legal regulations and environmental goals against pollution

REQUITE: A prospective multicentre cohort study of patients undergoing radiotherapy for breast, lung or prostate cancer

Purpose: REQUITE aimed to establish a resource for multi-national validation of models and biomarkers that predict risk of late toxicity following radiotherapy. The purpose of this article is to provide summary descriptive data. Methods: An international, prospective cohort study recruited cancer patients in 26 hospitals in eight countries between April 2014 and March 2017. Target recruitment was 5300 patients. Eligible patients had breast, prostate or lung cancer and planned potentially curable radiotherapy. Radiotherapy was prescribed according to local regimens, but centres used standardised data collection forms. Pre-treatment blood samples were collected. Patients were followed for a minimum of 12 (lung) or 24 (breast/prostate) months and summary descriptive statistics were generated. Results: The study recruited 2069 breast (99% of target), 1808 prostate (86%) and 561 lung (51%) cancer patients. The centralised, accessible database includes: physician-(47,025 forms) and patient-(54,901) reported outcomes; 11,563 breast photos; 17,107 DICOMs and 12,684 DVHs. Imputed genotype data are available for 4223 patients with European ancestry (1948 breast, 1728 prostate, 547 lung). Radiation-induced lymphocyte apoptosis (RILA) assay data are available for 1319 patients. DNA (n = 4409) and PAXgene tubes (n = 3039) are stored in the centralised biobank. Example prevalences of 2-year (1-year for lung) grade >= 2 CTCAE toxicities are 13% atrophy (breast), 3% rectal bleeding (prostate) and 27% dyspnoea (lung). Conclusion: The comprehensive centralised database and linked biobank is a valuable resource for the radiotherapy community for validating predictive models and biomarkers. Patient summary: Up to half of cancer patients undergo radiation therapy and irradiation of surrounding healthy tissue is unavoidable. Damage to healthy tissue can affect short-and long-term quality-of-life. Not all patients are equally sensitive to radiation "damage" but it is not possible at the moment to identify those who are. REQUITE was established with the aim of trying to understand more about how we could predict radiation sensitivity. The purpose of this paper is to provide an overview and summary of the data and material available. In the REQUITE study 4400 breast, prostate and lung cancer patients filled out questionnaires and donated blood. A large amount of data was collected in the same way. With all these data and samples a database and biobank were created that showed it is possible to collect this kind of information in a standardised way across countries. In the future, our database and linked biobank will be a resource for research and validation of clinical predictors and models of radiation sensitivity. REQUITE will also enable a better understanding of how many people suffer with radiotherapy toxicity

A MULTITROPHIC REEVALUATION OF PHENYLALANINE AS ESTIMATOR OF THE ISOTOPIC δ15N BASELINE IN MARINE FOOD WEBS

Compound-specific isotope analysis of amino acids (CSIA-AA) has become an increasingly useful tool to investigate the sources of nitrogen for primary producers in marine ecosystems (i.e. the isotopic baseline). The isotopic baseline can be estimated from changes in δ15N values of those AAs undergoing little isotopic fractionation and variability with each trophic transfer (source-AAs), as Phenylalanine (Phe). However, it is still unclear if Phe is the most representative source-AA in complex environments showing large diversity in the isotopic baseline, as ecosystems with basal resources derived from both terrestrial and aquatic producers. Through a review of the literature we found that δ15N-Phe values vary among primary producer groups, nitrogen sources (e.g. nitrate, ammonium, etc.), regions and seasons. Alternatively, δ15N values of source-AAs from consumers may be a more realistic proxy to estimate the isotopic baseline because they integrate the variability in N sources in space and time. Our study examines whether Phe should be used in preference to other source-AAs to estimate the N baseline in marine food webs as well as the ability of δ15N-Phe to track the exploitation of ecosystems with different baselines by consumers feeding at different trophic levels

Quantification of mixed contributions of primary producers from amino acid δ15N of marine consumers: a Bayesian approach

Estimations of the trophic position (TP) and the food web nitrogen baseline from compound-specific isotope analysis of individual amino acids (CSIA-AA) are challenged when the diet of consumer organisms relies on different proportions of vascular and non-vascular primary producers. Here we provide a new method to infer such proportions using the δ15N patterns from individual AAs (δ15NAA) in the consumer. Combining published and new data, we first characterized the δ15NAA signatures in primary producers and determined the isotopic enrichment (β) for the major taxa of primary producers. Then, we applied MixSIAR Bayesian isotope mixing models to investigate the transfer of these signatures to marine primary consumers (molluscs, green turtles, zooplankton and fish), and their utility to quantify autotrophic sources. Reliable source proportions were quantified, using appropriate combinations of trophic discrimination factors (TDFs), and were used to estimate β values for each consumer. We demonstrated that phytoplankton, macroalgae and vascular plants have singular δ15NAA fingerprints that can be tracked from the δ15NAA values in their primary consumers, and can be used to estimate mixed baseline sources. This method is useful to accurately estimate βmix values from consumer δ15NAA signatures with no requirement to sample or characterize the primary producers supporting the food web, thus providing reliable TP estimates in complex environments dominated by vascular and non-vascular autotrophs. This study evidences a suitable integration of δ15NAA fingerprinting and MixSIAR for quantitative estimations of autotrophic sources, complementing other methods to quantify resource utilization in natural systems. This methodology represents a major advance to unravel trophic dynamics at the aquatic/terrestrial interface using CSIA-AA.Proyecto QLOCKS (Ref. PID2020-115620RB-I00)

Analysis of intra-thallus and temporal variability of trace elements and nitrogen in Fucus vesiculosus: Sampling protocol optimization for biomonitoring

To advance the methodological standardization of the biomonitoring technique using macroalgae, we comprehensively characterized the intra-thallus and temporal patterns of variation in concentrations of a wide set of elements (Al, As, Cd, Co, Cr, Cu, Fe, Hg, Ni, Pb, Zn, N) and δ15N signal in 6 consecutive Fucus vesiculosus apical dichotomous sections collected monthly over a four-year period (2015–2019) at 3 sites on the NW coast of Spain. The concentrations of Al, Co, Fe, Ni, Pb and Zn increased significantly from the youngest to the oldest dichotomies regardless of the sampling time and collection site; As, Cd, N and δ15N showed the opposite trend. Time series analysis revealed a significant and consistent seasonal variation of As, Cd, Co, Cu, Fe, Hg, Ni, Zn, N and δ15N concentrations, with maximum values in winter and minimum values in summer. We discussed the possible mechanisms driving these two sources of variation, and proposed an efficient and effective sampling strategy to minimize their impact in the results of biomonitoring studies, in which the part of the algal thallus selected for chemical analysis and the sampling frequency were carefully considered. This protocol will improve the conclusions and comparability of biomonitoring data from coastal environments.En prens

Cognitive Function with PCSK9 Inhibitors: A 24-Month Follow-Up Observational Prospective Study in the Real World—MEMOGAL Study

Introduction The cognitive safety of monoclonal antibody proprotein convertase subtilisin/kexin type 9 inhibitors (PCSK9i) has been established in clinical trials, but not yet in real-world observational studies. We assessed the cognitive function in patients initiating PCSK9i, and differences in cognitive function domains, to analyze subgroups by the low-density lipoprotein cholesterol (LDL-C) achieved, and differences between alirocumab and evolocumab. Methods This has a multicenter, quasi-experimental design carried out in 12 Spanish hospitals from May 2020 to February 2023. Cognitive function was assessed using the Montreal Cognitive Assessment (MoCA). Results Among 158 patients followed for a median of 99 weeks, 52% were taking evolocumab and 48% alirocumab; the mean change from baseline in MoCA score at follow-up was + 0.28 [95% CI (− 0.17 to 0.73; p = 0.216)]. There were no significant differences in the secondary endpoints—the visuospatial/executive domain + 0.04 (p = 0.651), naming domain − 0.01 (p = 0.671), attention/memory domain + 0.01 (p = 0.945); language domain − 0.10 (p = 0.145), abstraction domain + 0.03 (p = 0.624), and orientation domain − 0.05 (p = 0.224)—but for delayed recall memory the mean change was statistically significant (improvement) + 0.44 (p = 0.001). Neither were there any differences in the three stratified subgroups according to lowest attained LDL-C level—0–54 mg/dL, 55–69 mg/dL and ≥ 70 mg/dL; p = 0.454—or between alirocumab and evolocumab arms. Conclusion We did not find effect of monoclonal antibody PCSK9i on neurocognitive function over 24 months of treatment, either in global MoCA score or different cognitive domains. An improvement in delayed recall memory was shown. The study showed no differences in the cognitive function between the prespecified subgroups, even among patients who achieved very low levels of LDL-C. There were no differences between alirocumab and evolocumab. Registration ClinicalTtrials.gov Identifier number NCT04319081Open Access funding provided thanks to the CRUE-CSIC agreement with Springer NatureS