Alkali Extraction of Arsenic from Groundwater Treatment Sludge: An Essential Initial Step for Arsenic Recovery.

Arsenic (As)-bearing Fe(III) precipitate groundwater treatment sludge has traditionally been viewed by the water sector as a disposal issue rather than a resource opportunity, partly due to assumptions of the low value of As. However, As has now been classified as a Critical Raw Material (CRM) in many regions, providing new incentives to recover As and other useful components of the sludge, such as phosphate (P) and the reactive hydrous ferric oxide (HFO) sorbent. Here, we investigate alkali extraction to separate As from a variety of field and synthetic As-bearing HFO sludges, which is a critical first step to enable sludge upcycling. We found that As extraction was most effective using NaOH, with the As extraction efficiency increasing up to >99% with increasing NaOH concentrations (0.01, 0.1, and 1 M). Extraction with Na2CO3 and Ca(OH)2 was ineffective (<5%). Extraction time (hour, day, week) played a secondary role in As release but tended to be important at lower NaOH concentrations. Little difference in As extraction efficiency was observed for several key variables, including sludge aging time (50 days) and cosorbed oxyanions (e.g., Si, P). However, the presence of ∼10 mass% calcite decreased As release from field and synthetic sludges considerably (<70% As extracted). Concomitant with As release, alkali extraction promoted crystallization of poorly ordered HFO and decreased particle specific surface area, with structural modifications increasing with NaOH concentration and extraction time. Taken together, these results provide essential information to inform and optimize the design of resource recovery methods for As-bearing treatment sludge.

Multi-cancer risk stratification based on national health data: a retrospective modelling and validation study.

BACKGROUND: Health care is experiencing a drive towards digitisation, and many countries are implementing national health data resources. Although a range of cancer risk models exists, the utility on a population level for risk stratification across cancer types has not been fully explored. We aimed to close this gap by evaluating pan-cancer risk models built on electronic health records across the Danish population with validation in the UK Biobank. METHODS: In this retrospective modelling and validation study, data for model development and internal validation were derived from the following Danish health registries: the Central Person Registry, the Danish National Patient Registry, the death registry, the cancer registry, and full-text medical records from secondary care records in the capital region. The development data included adults aged 16-86 years without previous malignant cancers in the time period from Jan 1, 1995, to Dec 31, 2014. The internal validation period was from Jan 1, 2015, to April 10, 2018, and the data included all adults without a previous indication of cancer aged 16-75 years on Dec 31, 2014. The external validation cohort from the UK Biobank included all adults without a previous indication of cancer aged 50-75 years. We used time-dependent Bayesian Cox hazard models built on the combined medical history of Danish individuals. A set of 1392 covariates from available clinical disease trajectories, text-mined basic health factors, and family histories were used to train predictive models of 20 major cancer types. The models were validated on cancer incidence between 2015 and 2018 across Denmark and on individuals in the UK Biobank. The primary outcomes were discrimination and calibration performance. FINDINGS: From the Danish registries, we included 6 732 553 individuals covering 60 million hospital visits, 90 million diagnoses, and a total of 193 million life-years between Jan 1, 1978, and April 10, 2018. Danish registry data covering the period from Jan 1, 2015, to April 10, 2018, were used to internally validate risk models, containing a total of 4 248 491 individuals who remained at risk of a primary malignant cancer diagnosis and 67 401 cancer cases recorded. For the external validation, we evaluated the same time period in the UK Biobank covering 377 004 individuals with 11 486 cancer cases. The predictive performance of the models on Danish data showed good discrimination (concordance index 0·81 [SD 0·08], ranging from 0·66 [95% CI 0·65-0·67] for cervix uteri cancer to 0·91 [0·90-0·92] for liver cancer). Performance was similar on the UK Biobank in a direct transfer when controlling for shifts in the age distribution (concordance index 0·66 [SD 0·08], ranging from 0·55 [95% CI 0·44-0·66] for cervix uteri cancer to 0·78 [0·77-0·79] for lung cancer). Cancer risks were associated, in addition to heritable components, with a broad range of preceding diagnoses and health factors. The best overall performance was seen for cancers of the digestive system (oesophageal, stomach, colorectal, liver, and pancreatic) but also thyroid, kidney, and uterine cancers. INTERPRETATION: Data available in national electronic health databases can be used to approximate cancer risk factors and enable risk predictions in most cancer types. Model predictions generalise between the Danish and UK health-care systems. With the emergence of multi-cancer early detection tests, electronic health record-based risk models could supplement screening efforts. FUNDING: Novo Nordisk Foundation and the Danish Innovation Foundation.

The robot butler: How and why should we study predictive algorithms and artificial intelligence (AI) in healthcare?

Artificial intelligence (AI) and algorithms are heralded as significant solutions to the widening gap between the rising healthcare needs of ageing and multi-morbid populations and the scarcity of resources to provide such care. Objective: This article investigates how the PMHnet algorithm - an AI prognostication tool developed in Denmark to predict the one-year all-cause mortality risk for patients hospitalized with ischemic heart disease - was presented to cardiologists working in the hospital setting, and how they responded to this novel decision-support tool. Methods: Empirically, we draw upon ethnographic fieldwork in the Danish-led international research project, PM Heart, which since 2019 has developed the PMHnet algorithm and implemented the software into the electronic health record system in hospitals in Eastern Denmark (the Capital Region and Region Zealand). Results: Paying careful attention to the hopes and concerns of cardiologists who will have to embrace and adapt to algorithmic tools in their everyday work of diagnosing and treating patients, we identify three analytical themes meriting attention when AI is implemented in healthcare: 1) the re-negotiation of agency and autonomy in human-algorithm relations, 2) accountability in algorithmic prognostication and 3) the complex relationship between association and causation actualized by predictive algorithms. From these analytical themes, we elicit methodological questions to guide future ethnographic explorations of how AI and advanced algorithms are put to use in the healthcare system, with what implications, and for whom. Conclusion: We conclude that local, qualitative investigations of how algorithms are used, embraced and contested in everyday clinical practice are needed in order to understand their implications - good and bad, intended and unintended - for clinicians, patients and healthcare provision.

Assessment of the stabilization effect of ferrous sulfate for arsenic-contaminated soils based on chemical extraction methods and in vitro methods: Methodological differences and linkages.

Stabilization of arsenic-contaminated soils with ferrous sulfate has been reported in many studies, but there are few stabilization effects assessments simultaneously combined chemical extraction methods and in vitro methods, and further explored the corresponding alternative relationships. In this study, ferrous sulfate was added at FeAs molar ratio of 0, 5, 10 and 20 to stabilize As in 10 As spiked soils. Stabilization effects were assessed by 6 chemical extraction methods (toxicity characteristic leaching procedures (TCLP), HCl, diethylenetriamine pentaacetic acid (DTPA), CaCl2, CH3COONH4, (NH4)2SO4), and 4 in vitro methods (physiologically based extraction test (PBET), in vitro gastrointestinal method (IVG), Solubility Bioaccessibility Research Consortium (SBRC) method, and the Unified Bioaccessibility Research Group of Europe method (UBM)). The results showed that the HCl method provides the most conservative assessment results in non-calcareous soils, and in alkaline calcareous soils, (NH4)2SO4 method provides a more conservative assessment. In vitro methods provided significantly higher As concentrations than chemical extraction methods. The components of the simulated digestion solution as well as the parameters may have contributed to this result. The small intestinal phase of PBET and SBRC method produced the highest and lowest ranges of As concentrations, and in the range of 127-462 mg/kg and 68-222 mg/kg when the FeAs molar ratio was 5. So the small intestinal phase of PBET method may provide the most conservative assessment results, while the same phase of SBRC may underestimate the human health risks of As in stabilized soil by 51 %(at a FeAs molar ratio of 5). Spearman correlation analysis indicated that the small intestinal phase of PBET method correlated best with HCl method (correlation coefficient: 0.71). This study provides ideas for the assessment of stabilization efforts to ensure that stabilization meets ecological needs while also being less harmful to humans.

Co-cropping vetiver grass and legume for the phytoremediation of an acid mine drainage (AMD) impacted soil.

Acid mine drainage (AMD) is a form of environmental pollution from mining activity that can negatively affect soil environments by acidification, salinisation, and metal(loid) contamination. The use of plants to remediate (phytoremediation) these impacted environments while generating plant-based value is a promising approach to more accessible and cost-benefiting restoration of post-mining, marginal lands. In this study, a 3-month growth-chamber pot experiment was conducted to investigate the influence of co-cropping two plant species, Chrysopogon zizanioides (vetiver grass) and the legume Medicago truncatula (barrel clover) with a wheat straw biochar amendment on the phytostabilisation of metal(loid)s Cr, Zn, and As and the phytoextraction of rare earth element (REE) in an AMD impacted soil from a gold mining region in South Africa. The results showed that co-cropping with vetiver significantly lowered the legume's Cr, Zn, and As root contents by 80%, 32% and 54%, respectively, and improved the plant's overall metal(loid) tolerance by increasing its translocation from root to shoot tissue. The biochar further inhibited root uptake of Cr and Zn, by 71% and 36%, and increased the legume biomass by 40%. Both plant species and cropping treatments exhibited low REE extraction capabilities by shoot tissue, which accounted for less than 0.2% of total soil REE contents. The study shows that co-cropping with vetiver and biochar amendment are effective tools for the phytoremediation of AMD impacted soil mainly by lowering plant uptake and improving plant metal(loid) tolerance. Likely mechanisms at play include the alteration of rhizosphere chemistry and species-specific physiological and molecular responses. These effects offer support for the phytostabilisation of AMD impacted soil with the generation of plant-based value through dual (and safe) cultivation (phytoprotection) rather than through REE recovery from plant biomass (phytoextraction). These techniques could allow for the simultaneous restoration of post-mining, mining-impacted and marginal lands with agricultural production.

Development of a shared item repository for progress testing in veterinary education.

Introduction: Progress testing in education is an assessment principle for the measurement of students' progress over time, e.g., from start to graduation. Progress testing offers valid longitudinal formative measurement of the growth in the cognitive skills of the individual students within the subjects of the test as well as a tool for educators to monitor potential educational gaps and mismatches within the curriculum in relation to the basic veterinary learning outcomes. Methods: Six veterinary educational establishments in Denmark, Finland, Germany (Hannover), the Netherlands, Norway, and Sweden established in cooperation with the European Association of Establishments for Veterinary Education (EAEVE) a common veterinary item repository that can be used for progress testing in European Veterinary Education Establishments (VEEs), linear as well as computer adaptive, covering the EAEVE veterinary subjects and theoretical "Day One Competencies." First, a blueprint was created, suitable item formats were identified, and a quality assurance process for reviewing and approving items was established. The items were trialed to create a database of validated and calibrated items, and the responses were subsequently psychometrically analyzed according to Modern Test Theory. Results: In total, 1,836 items were submitted of which 1,342 were approved by the reviewers for trial testing. 1,119 students from all study years and all partners VEEs participated in one or more of six item trials, and 1,948 responses were collected. Responses were analyzed using Rasch Modeling (analysis of item-fit, differential item function, item-response characteristics). A total of 821 calibrated items of various difficulty levels matching the veterinary students' abilities and covering the veterinary knowledge domains have been banked. Discussion: The item bank is now ready to be used for formative progress testing in European veterinary education. This paper presents and discusses possible pitfalls, problems, and solutions when establishing an international veterinary progress test.

Phosphorus doped cyanobacterial biochar catalyzes efficient persulfate oxidation of the antibiotic norfloxacin.

In this study, cyanobacterial biochars (CBs) enriched/doped with non-metallic elements were prepared by pyrolysis of biomass amended with different N, S, and P containing compounds. Their catalytic reactivity was tested for persulfate oxidation of the antibiotic norfloxacin (NOR). N and S doping failed to improve CB catalytic reactivity, while P doping increased reactivity 5 times compared with un-doped biochar. Biochars produced with organic phosphorus dopants showed the highest reactivity. Post-acid-washing improved catalytic reactivity. In particular, 950 ℃ acid-washed triphenyl-phosphate doped CB showed the largest degradation rate and reached 79% NOR mineralization in 2 h. Main attributes for P-doped CBs high reactivity were large specific surface areas (up to 655 m2/g), high adsorption, high C-P-O content, graphitic P and non-radical degradation pathway (electron transfer). This study demonstrates a new way to reuse waste biomass by producing efficient P-doped metal-free biochars and presents a basic framework for designing carbon-based catalysts for organic pollutant degradation.

Impacts of biochar materials on copper speciation, bioavailability, and toxicity in chromated copper arsenate polluted soil.

Trace element polluted soils pose risks to human and environmental health. Biochar can decrease trace element bioavailability in soils, but their resulting ability to reduce soil toxicity may vary significantly depending on feedstocks used, pyrolysis conditions, and the target pollutants. Chromated copper arsenate (CCA) polluted sites are common, but only very few types of biochar have been tested for these sites. Hence, we tested fourteen well-characterized biochar materials for their ability to bind Cu and reduce toxicity in a CCA polluted soil in a 56-day experiment. Biochar (1%, wt/wt) increased plant (wheat, Triticum aestivum L.) shoot and root growth by 6-58% and 0-73%, reduced soil toxicity to Arthrobacter globiformis by 7-55%, decreased bioavailable Cu (Pseudomonas fluorescens bioreporter) by 5-65%, and decreased free Cu2+ ion activities by 27-89%. The A. globiformis solid-contact test constituted a sensitive ecotoxicological endpoint and deserves further attention for assessment of soil quality. Oil seed rape straw biochar generally performed better than other tested biochar materials. Biochar performance was positively correlated with its high cation exchange capacity, multiple surface functional groups, and high nitrogen and phosphorus content. Our results pave the way for future selection of feedstocks for creation of modified biochar materials with optimal performance in CCA polluted soil.

DanMAC5: a browser of aggregated sequence variants from 8,671 whole genome sequenced Danish individuals.

OBJECTIVES: Allele counts of sequence variants obtained by whole genome sequencing (WGS) often play a central role in interpreting the results of genetic and genomic research. However, such variant counts are not readily available for individuals in the Danish population. Here, we present a dataset with allele counts for sequence variants (single nucleotide variants (SNVs) and indels) identified from WGS of 8,671 (5,418 females) individuals from the Danish population. The data resource is based on WGS data from three independent research projects aimed at assessing genetic risk factors for cardiovascular, psychiatric, and headache disorders. To enable the sharing of information on sequence variation in Danish individuals, we created summarized statistics on allele counts from anonymized data and made them available through the European Genome-phenome Archive (EGA, https://identifiers.org/ega. DATASET: EGAD00001009756 ) and in a dedicated browser, DanMAC5 (available at www.danmac5.dk ). The summary level data and the DanMAC5 browser provide insight into the allelic spectrum of sequence variants segregating in the Danish population, which is important in variant interpretation. DATA DESCRIPTION: Three WGS datasets with an average coverage of 30x were processed independently using the same quality control pipeline. Subsequently, we summarized, filtered, and merged allele counts to create a high-quality summary level dataset of sequence variants.

Comparing cadmium uptake kinetics, xylem translocation, chemical forms, and subcellular distribution of two tobacco (Nicotiana tabacum L.) cultivars.

Tobacco (Nicotiana tabacum L.) is a potential phytoremediator that can reduce soil cadmium (Cd) contamination. Pot and hydroponic experiments were conducted to investigate the difference in absorption kinetics, translocation patterns, accumulation capacity, and extraction amounts between two leading tobacco cultivars in China. We studied the chemical forms and subcellular distribution of Cd in the plants to understand the diversity of the detoxification mechanism of the cultivars. The concentration-dependent kinetics of Cd accumulation in leaves, stems, roots, and xylem sap for cultivars Zhongyan 100 (ZY100) and K326, fitted well with the Michaelis-Menten equation. K326 exhibited high biomass, Cd tolerance, Cd translocation, and phytoextraction abilities. The acetic acid, sodium chloride, and water-extractable fractions accounted for > 90% of Cd in all ZY100 tissues but only in K326 roots and stems. Moreover, the acetic acid and NaCl fractions were the predominant storage forms, while the water fraction was the transport form. The ethanol fraction also contributed significantly to Cd storage in K326 leaves. As the Cd treatment increased, more NaCl and water fractions were found in K326 leaves, while only NaCl fractions increased in ZY100 leaves. For subcellular distribution, > 93% Cd proportions were primarily stored in both cultivars' soluble or cell wall fraction. The proportion of Cd in the cell wall fraction of ZY100 roots was less than that of K326, while that proportion in the soluble fraction in ZY100 leaves was higher than in K326 leaves. These findings demonstrate that Cd accumulation patterns, detoxification, and storage strategies differ between the cultivars, providing a deeper understanding of Cd tolerance and accumulation mechanism in tobacco plants. It also guides the screening of germplasm resources or gene modification to improve the Cd phytoextraction efficiency of tobacco.

Fast peroxydisulfate oxidation of the antibiotic norfloxacin catalyzed by cyanobacterial biochar.

Peroxydisulfate (PDS) is a common oxidant for organic contaminant remediation. PDS is typically activated by metal catalysts to generate reactive radicals. Unfortunately, as radicals are non-selective and metal catalysts may cause secondary contamination, alternative selective non-radical pathways and non-metal catalysts need attention. Here we investigated PDS oxidation of commonly detected antibiotic Norfloxacin (NOR) using cyanobacterial nitrogen rich biochars (CBs) as catalysts. NOR was fully degraded by CB pyrolysed at 950 °C (CB950) within 120 min. CB950 caused threefold faster degradation than low pyrolysis temperature (PT) CBs and achieved a maximum surface area normalized rate constant of 4.38 × 10-2 min-1 m-2 L compared to widely used metal catalysts. CB950 maintained full reactivity after four repeated uses. High defluorination (82%) and mineralization (>82%) were observed for CB950/PDS. CBs were active over a broad pH range (3-10), but with twice as high rates under alkaline compared with neutral conditions. NOR is degraded by organic, •OH and SO4•- radicals in low PT CBs/PDS systems, where the presence of MnII promotes radical generation. Electron transfer reactions with radicals supplemented dominate high PT CBs/PDS systems. This study demonstrates high PT biochars from algal bloom biomass may find use as catalysts for organic contaminant oxidation.

Temporal patterns of multi-morbidity in 570157 ischemic heart disease patients: a nationwide cohort study.

BACKGROUND: Patients diagnosed with ischemic heart disease (IHD) are becoming increasingly multi-morbid, and studies designed to analyze the full spectrum are few. METHODS: Disease trajectories, defined as time-ordered series of diagnoses, were used to study the temporality of multi-morbidity. The main data source was The Danish National Patient Register (NPR) comprising 7,179,538 individuals in the period 1994-2018. Patients with a diagnosis code for IHD were included. Relative risks were used to quantify the strength of the association between diagnostic co-occurrences comprised of two diagnoses that were overrepresented in the same patients. Multiple linear regression models were then fitted to test for temporal associations among the diagnostic co-occurrences, termed length two disease trajectories. Length two disease trajectories were then used as basis for constructing disease trajectories of three diagnoses. RESULTS: In a cohort of 570,157 IHD disease patients, we identified 1447 length two disease trajectories and 4729 significant length three disease trajectories. These included 459 distinct diagnoses. Disease trajectories were dominated by chronic diseases and not by common, acute diseases such as pneumonia. The temporal association of atrial fibrillation (AF) and IHD differed in different IHD subpopulations. We found an association between osteoarthritis (OA) and heart failure (HF) among patients diagnosed with OA, IHD, and then HF only. CONCLUSIONS: The sequence of diagnoses is important in characterization of multi-morbidity in IHD patients as the disease trajectories. The study provides evidence that the timing of AF in IHD marks distinct IHD subpopulations; and secondly that the association between osteoarthritis and heart failure is dependent on IHD.

Fomepizole dosing during continuous renal replacement therapy - an observational study.

BACKGROUND: Fomepizole is the preferred antidote for treatment of methanol and ethylene glycol poisoning, acting by inhibiting the formation of the toxic metabolites. Although very effective, the price is high and the availability is limited. Its availability is further challenged in situations with mass poisonings. Therefore, a 50% reduced maintenance dose for fomepizole during continuous renal replacement therapy (CRRT) was suggested in 2016, based on pharmacokinetic data only. Our aim was to study whether this new dosing for fomepizole during CRRT gave plasma concentrations above the required 10 µmol/L. Secondly, we wanted to study the elimination kinetics of fomepizole during CRRT, which has never been studied before. METHODS: Prospective observational study of adult patients treated with fomepizole and CRRT. We collected samples from arterial line (pre-filter) = plasma concentration, post-filter and dialysate for fomepizole measurements. Fomepizole was measured using high-pressure liquid chromatography with a reverse phase column. RESULTS: Ten patients were included in the study. Seven were treated with continuous veno-venous hemodialysis (CVVHD) and three with continuous veno-venous hemodiafiltration (CVVHDF). Ninety-eight percent of the plasma samples were above the minimum plasma concentration of 10 µmol/L. Fomepizole was removed during CRRT with a median saturation/sieving coefficient of 0.85 and dialysis clearance of 28 mL/min. CONCLUSION: Fomepizole was eliminated during CCRT. The new dosing recommendations for fomepizole and CRRT appeared safe, by maintaining the plasma concentration above the minimum value of 10 µmol/L. Based on these data, the fomepizole maintenance dose during CRRT could be reduced to half as compared to intermittent hemodialysis.

A critical review of phytoremediation for acid mine drainage-impacted environments.

Acid mine drainage (AMD), a waste product of mining activities containing sulfates, iron and heavy metals, causes severe environmental degradation and pose risks to human health and sustainable development. Areas impacted by AMD are lacking remediation techniques that holistically address the ecologic, social, and economic needs of affected communities, for which phytoremediation is a promising solution. This review article introduces AMD and AMD-impacted environments and critically discusses phytomanagement, phytoprotection, and phytorestoration approaches towards AMD-impacted environments. Continued research and application of such approaches will help optimize resource and revenue-generating potentials, address biodiversity loss and carbon storage concerns of climate change, and promote sustainable agricultural management. With a focus on energy crops, phytomining critical elements, carbon storage, co-cropping, allelopathy, and ecosystem restoration, this review examines phytoremediation research that addresses positive economic and environmental opportunities for AMD-impacted environments.

Quantitative source apportionment, risk assessment and distribution of heavy metals in agricultural soils from southern Shandong Peninsula of China.

The heavy metals, including cadmium (Cd), chromium (Cr), copper (Cu), mercury (Hg), nickel (Ni), lead (Pb), zinc (Zn), and the metalloid arsenic (As) were detected in surface and core soil samples collected from a tobacco growing region in Shandong Peninsula on the east coast of China to evaluate their pollution levels, ecological and health risks, and to analyze their spatial and vertical distributions. The heavy metal sources were identified quantitatively using the positive matrix factorization (PMF) receptor model. In accordance, most of the soils did not have accumulations and were not contaminated by As, Cr, Cu, Ni, Pb, and Zn. High accumulations of Cd and Hg occurred in the soils, posing an ecological risk to the local agricultural environment, while Cr and Ni levels presented a carcinogenic health risk to humans. Four main sources of heavy metals in the soils were identified. Correspondingly Ni and Cr were mainly originated from natural sources, Hg from coal combustion, Cd from agricultural practices, Cu, Pb, and Zn from agricultural practices and industrial activities, and As from industrial activities.

Cohort profile: Copenhagen Hospital Biobank - Cardiovascular Disease Cohort (CHB-CVDC): Construction of a large-scale genetic cohort to facilitate a better understanding of heart diseases.

PURPOSE: The aim of Copenhagen Hospital Biobank-Cardiovascular Disease Cohort (CHB-CVDC) is to establish a cohort that can accelerate our understanding of CVD initiation and progression by jointly studying genetics, diagnoses, treatments and risk factors. PARTICIPANTS: The CHB-CVDC is a large genomic cohort of patients with CVD. CHB-CVDC currently includes 96 308 patients. The cohort is part of CHB initiated in 2009 in the Capital Region of Denmark. CHB is continuously growing with ~40 000 samples/year. Patients in CHB were included in CHB-CVDC if they were above 18 years of age and assigned at least one cardiovascular diagnosis. Additionally, up-to 110 000 blood donors can be analysed jointly with CHB-CVDC. Linkage with the Danish National Health Registries, Electronic Patient Records, and Clinical Quality Databases allow up-to 41 years of medical history. All individuals are genotyped using the Infinium Global Screening Array from Illumina and imputed using a reference panel consisting of whole-genome sequence data from 8429 Danes along with 7146 samples from North-Western Europe. Currently, 39 539 of the patients are deceased. FINDINGS TO DATE: Here, we demonstrate the utility of the cohort by showing concordant effects between known variants and selected CVDs, that is, >93% concordance for coronary artery disease, atrial fibrillation, heart failure and cholesterol measurements and 85% concordance for hypertension. Furthermore, we evaluated multiple study designs and the validity of using Danish blood donors as part of CHB-CVDC. Lastly, CHB-CVDC has already made major contributions to studies of sick sinus syndrome and the role of phytosterols in development of atherosclerosis. FUTURE PLANS: In addition to genetics, electronic patient records, national socioeconomic and health registries extensively characterise each patient in CHB-CVDC and provides a promising framework for improved understanding of risk and protective variants. We aim to include other measurable biomarkers for example, proteins in CHB-CVDC making it a platform for multiomics cardiovascular studies.

Rare earth elements in surface specific urban runoff in Northern Beijing.

Rare earth elements (REEs) have been increasingly diffused to the environment through mining activities and the extensive use in modern commodities, vehicular activities, coal burning and various environmental and agricultural applications. Studies of REEs in urban environments are limited with no data on REEs in urban runoff. To investigate the concentration and distribution of REEs, a total of 150 runoff samples were collected from trafficked areas, rooftops and residential parking lots in a moderate to densely populated area in Beijing, China. The runoff samples were separated into dissolved and particulate phases and analyzed by ICP-MS. The REEs were mainly (>80%) found in the runoff particulate material. The sum of REEs (ΣREE) total concentrations in urban stormwater runoff samples ranged from 0.16 to 185 µg/l. The observed mean total concentration of ΣREE in the runoff samples were 3-14 folds higher and dissolved fractions 1.5 to 6 times higher than published concentrations for recipients such as sewage channels and rivers. The distribution of REEs in runoff was dominated by light REE. Cluster analysis and Pearson's correlations revealed a strong association between the individual REEs pointing to a similar source. Higher Ce concentrations compared to other REEs indicated strong influence from traffic emission particulates. The La/Sm (5.90-8.05), La/Ce (0.53-0.58) and Ce/Yb (31.0-42.7) ratios pointed to REE sources from traffic emissions and coal burning thus defining an urban fingerprint.

Population projections of an endangered cactus suggest little impact of climate change.

Population projections coupled with downscaled climate projections are a powerful tool that allows predicting future population dynamics of vulnerable plants in the face of a changing climate. Traditional approaches used to predict the vulnerability of plants to climate change (e.g. species distribution models) fail to mechanistically describe the basis of a population's dynamics and thus cannot be expected to correctly predict its temporal trends. In this study, we used a 23-year demographic dataset of the acuña cactus, an endangered species, to predict its population dynamics to the end of the century. We used integral projection models to describe its vital rates and population dynamics in relation to plant volume and key climatic variables. We used the resulting climate-driven IPM along with climatic projections to predict the population growth rates from 1991 to 2099. We found the average population growth rate of this population between 1991 and 2013 to be 0.70 (95% CI 0.61-0.79). This result confirms that the population of acuña cactus has been declining and that this decline is due to demographic structure and climate conditions. However, the projection model also predicts that, up to 2080, the population will remain relatively stable mainly due to the survival of its existing adult individuals. Notwithstanding, the long-term viability of the populations can only be achieved through the recruitment of new individuals.

Preparation of a silicon-iron amendment from acid-extracted copper tailings for remediating multi-metal-contaminated soils.

Industrial by-products provide materials for remediation measures. In this study, a silicon-iron amendment was prepared from residue originating from acid-extracted copper (Cu) tailings based on thermal activation at temperatures ranging from 550 °C to 1150 °C for 30 min with the use of additives (CaO, Na2CO3, NaOH). The remediation performance of the amendment was evaluated through soil incubation and greenhouse pot experiments with vetiver (Vetiveria zizanioides). The results showed that the highest levels of soluble Si (6.11% of the total Si) and Fe (2.3% of the total Fe) in the amendment were achieved with thermal activation at 1150 °C for 30 min using an optimal ratio between residue and additives (residue: CaO: Na2CO3: NaOH = 1: 0.4: 0.4: 0.2). Heavy metal release indicated that the amendment could be safely used for soil remediation. The incubation experiments showed that the DTPA-extractable Cd, Cr and Pb in contaminated soils decreased with increasing amendment rate, which was not observed for As. The amendment-induced decrease in the Cd, Cr and Pb availability in contaminated soils could be explained by pH-change induced immobilization, Fe-induced chemisorption, Si-induced co-precipitation, and Ca-induced ion exchange. Correlation analysis suggested that there were significant negative correlations between DTPA-extractable Cd, Cr and Pb and the pH, Fe, Si, and Ca in soil pore water and soil. The most suitable amendment rate was determined to be 1% by balancing the efficacy and wise utilization of the amendment. The pot experiment demonstrated that the amendment promoted the vetiver growth and stimulated the accumulation of Cd and Cr in the roots. The amendment was proved to be promising for the phytostabilization of Cd, Cr and Pb in contaminated soils. Further investigations are required to determine whether the amendment is a tool for the long-term remediation of multi-metal-contaminated soils at the field scale.

Linking glycemic dysregulation in diabetes to symptoms, comorbidities, and genetics through EHR data mining.

Diabetes is a diverse and complex disease, with considerable variation in phenotypic manifestation and severity. This variation hampers the study of etiological differences and reduces the statistical power of analyses of associations to genetics, treatment outcomes, and complications. We address these issues through deep, fine-grained phenotypic stratification of a diabetes cohort. Text mining the electronic health records of 14,017 patients, we matched two controlled vocabularies (ICD-10 and a custom vocabulary developed at the clinical center Steno Diabetes Center Copenhagen) to clinical narratives spanning a 19 year period. The two matched vocabularies comprise over 20,000 medical terms describing symptoms, other diagnoses, and lifestyle factors. The cohort is genetically homogeneous (Caucasian diabetes patients from Denmark) so the resulting stratification is not driven by ethnic differences, but rather by inherently dissimilar progression patterns and lifestyle related risk factors. Using unsupervised Markov clustering, we defined 71 clusters of at least 50 individuals within the diabetes spectrum. The clusters display both distinct and shared longitudinal glycemic dysregulation patterns, temporal co-occurrences of comorbidities, and associations to single nucleotide polymorphisms in or near genes relevant for diabetes comorbidities.