EU Wide Monitoring Survey of Polar Persistent Pollutants in European River Waters

This study provides the first EU-wide reconnaissance of the occurrence of polar organic persistent pollutants in European river waters. 122 individual water samples from over 100 European rivers, streams or similar water bodies from 27 European Countries were analysed for 35 selected compounds, comprising pharmaceuticals (e.g. carbamazepine, diclofenac), antibiotics (sulfamethoxazole), pesticides (e.g. 2,4-D, mecoprop, bentazone, terbutylazine), perfluorinated compounds PFCs (PFOS, PFOA), benzotriazoles (corrosion inhibitors), hormones (estrone, estradiol), and alkylphenolics (bisphenol A, nonylphenol). Only the dissolved (liquid) water phase, and not the suspend material was investigated. Around 40 laboratories actively participated in this sampling and monitoring exercise organised by the Joint Research Centre¿s Institute for Environment and Sustainability (JRC-IES) of the European Commission (EC) in autumn 2007. The selection of sampling sites was done by the participating EU Member States. The most frequently and at the highest concentration levels detected compounds were benzotriazole, caffeine, carbamazepine, tolyltriazole, and nonylphenoxy acetic acid (NPE1C). Other important substances identified were naproxen, bezafibrate, ibuprofen, gemfibrozil, PFOS, PFOA, sulfamethoxazole, isoproturon, diuron, and nonylphenol. The highest median concentrations of all samples were measured for benzotriazole (226 ng/L), caffeine (72 ng/L), carbamazepine (75 ng/L), tolyltriazole (140 ng/L), and NPE1C (233 ng/L). Relatively high perfluorooctanoate (PFOA) levels were detected in the Rivers Danube, Scheldt, Rhone, and Wyre, and ¿elevated¿ perfluorooctansulfonate (PFOS) concentrations in the Rivers Scheldt, Seine, Krka, Severn, Rhine, and Llobregat. A higher median concentration for all river samples was found for PFOS (6 ng/L), compared to PFOA (3 ng/L). Only about 10 % of the river water samples analysed could be classified as ¿very clean¿ in terms of chemical pollution, since they contained only a few compounds in very low concentrations. The most pristine water samples came from Estonia, Lithuania, and Sweden. For the target compounds chosen, we are proposing limit values in surface waters which are not based on eco-toxicological considerations; these warning levels are (for most compounds) close to the 90th percentile of all water samples analysed. A first EU-wide data set has been created on the occurrence of polar persistent pollutants in river surface waters to be used for continental scale risk assessment and related decision support.JRC.H.5-Rural, water and ecosystem resource

Hyperplasia vs hypertrophy in tissue regeneration after extensive liver resection

AIM To address to what extent hypertrophy and hyperplasia contribute to liver mass restoration after major tissue loss. METHODS The ability of the liver to regenerate is remarkable on both clinical and biological grounds. Basic mechanisms underlying this process have been intensively investigated. However, it is still debated to what extent hypertrophy and hyperplasia contribute to liver mass restoration after major tissue loss. We addressed this issue using a genetically tagged system. We were able to follow the fate of single transplanted hepatocytes during the regenerative response elicited by 2/3 partial surgical hepatectomy (PH) in rats. Clusters of transplanted cells were 3D reconstructed and their size distribution was evaluated over time after PH. RESULTS Liver size and liver DNA content were largely recovered 10 d post-PH, as expected (e.g. , total DNA/liver/100 g b.w. was 6.37 ± 0.21 before PH and returned to 6.10 ± 0.36 10 d after PH). Data indicated that about 2/3 of the original residual hepatocytes entered S-phase in response to PH. Analysis of cluster size distribution at 24, 48, 96 h and 10 d after PH revealed that about half of the remnant hepatocytes completed at least 2 cell cycles. Average size of hepatocytes increased at 24 h (248.50 μm2 ± 7.82 μm2, P = 0.0015), but returned to control values throughout the regenerative process (up to 10 d post-PH, 197.9 μm2 ± 6.44 μm2, P = 0.11). A sizeable fraction of the remnant hepatocyte population does not participate actively in tissue mass restoration. CONCLUSION Hyperplasia stands as the major mechanism contributing to liver mass restoration after PH, with hypertrophy playing a transient role in the process

A humanness dimension to visual object coding in the brain

Neuroimaging studies investigating human object recognition have primarily focused on a relatively small number of object categories, in particular, faces, bodies, scenes, and vehicles. More recent studies have taken a broader focus, investigating hypothesized dichotomies, for example, animate versus inanimate, and continuous feature dimensions, such as biologically similarity. These studies typically have used stimuli that are identified as animate or inanimate, neglecting objects that may not fit into this dichotomy. We generated a novel stimulus set including standard objects and objects that blur the animate-inanimate dichotomy, for example, robots and toy animals. We used MEG time-series decoding to study the brain's emerging representation of these objects. Our analysis examined contemporary models of object coding such as dichotomous animacy, as well as several new higher order models that take into account an object's capacity for agency (i.e. its ability to move voluntarily) and capacity to experience the world. We show that early (0–200 ​ms) responses are predicted by the stimulus shape, assessed using a retinotopic model and shape similarity computed from human judgments. Thereafter, higher order models of agency/experience provided a better explanation of the brain's representation of the stimuli. Strikingly, a model of human similarity provided the best account for the brain's representation after an initial perceptual processing phase. Our findings provide evidence for a new dimension of object coding in the human brain – one that has a “human-centric” focus

Deep and surface hemodynamic signal from functional time resolved transcranial near infrared spectroscopy compared to skin flowmotion

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Effectiveness of patients’ involvement in a medical and nursing pain education programme: a protocol for an open-label randomised controlled trial including qualitative data

Introduction Pain is a multidimensional experience that varies among individuals and has a significant impact on their health. A biopsychosocial approach is recommended for effective pain management; however, health professionals’ education is weak on this issue. Patient involvement is a promising didactic methodology in developing a more holistic perspective, however there is a lack of reliable evidence on this topic. The aim of the present study is to evaluate the effectiveness of patient involvement in pain education in undergraduate medicine and nursing students. Methods and analysis An open-label randomised controlled trial including qualitative data will be conducted. After an introductory lesson, each student will be randomly assigned to the intervention group, which includes an educational session conducted by a patient–partner along with an educator, or to the control group in which the session is exclusively conducted by an educator. Both sessions will be carried out according to the Case-Based Learning approach. Primary outcomes will be students’ knowledge, attitudes, opinions and beliefs about pain management, whereas the secondary outcome will be students’ satisfaction. The Pain Knowledge and Attitudes (PAK) and Chronic Pain Myth Scale (CPMS) will be administered preintervention and postintervention to measure primary outcomes. Students’ satisfaction will be measured by a questionnaire at the end of the session. Two focus groups will be conducted to evaluate non-quantifiable aspects of learning. Ethics and dissemination The protocol of this study was approved by the independent Area Vasta Emilia Nord ethics committee

Effect of prolonged stimulation on cerebral hemodynamic: A time-resolved fNIRS study

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A PM10 chemically characterised nation-wide dataset for Italy. Geographical influence on urban air pollution and source apportionment

: Urban textures of the Italian cities are peculiarly shaped by the local geography generating similarities among cities placed in different regions but comparable topographical districts. This suggested the following scientific question: can such different topographies generate significant differences on the PM10 chemical composition at Italian urban sites that share similar geography despite being in different regions? To investigate whether such communalities can be found and are applicable at Country-scale, we propose here a novel methodological approach. A dataset comprising season-averages of PM10 mass concentration and chemical composition data was built, covering the decade 2005-2016 and referring to urban sites only (21 cities). Statistical analyses, estimation of missing data, identification of latent clusters and source apportionment modelling by Positive Matrix Factorization (PMF) were performed on this unique dataset. The first original result is the demonstration that a dataset with atypical time resolution can be successfully exploited as an input matrix for PMF obtaining Country-scale representative chemical profiles, whose physical consistency has been assessed by different tests of modelling performance. Secondly, this dataset can be considered a reference repository of season averages of chemical species over the Italian territory and the chemical profiles obtained by PMF for urban Italian agglomerations could contribute to emission repositories. These findings indicate that our approach is powerful, and it could be further employed with datasets typically available in the air pollution monitoring networks

Prognostic indicators and outcomes of hospitalised COVID-19 patients with neurological disease: An individual patient data meta-analysis

BACKGROUND: Neurological COVID-19 disease has been reported widely, but published studies often lack information on neurological outcomes and prognostic risk factors. We aimed to describe the spectrum of neurological disease in hospitalised COVID-19 patients; characterise clinical outcomes; and investigate factors associated with a poor outcome. METHODS: We conducted an individual patient data (IPD) meta-analysis of hospitalised patients with neurological COVID-19 disease, using standard case definitions. We invited authors of studies from the first pandemic wave, plus clinicians in the Global COVID-Neuro Network with unpublished data, to contribute. We analysed features associated with poor outcome (moderate to severe disability or death, 3 to 6 on the modified Rankin Scale) using multivariable models. RESULTS: We included 83 studies (31 unpublished) providing IPD for 1979 patients with COVID-19 and acute new-onset neurological disease. Encephalopathy (978 [49%] patients) and cerebrovascular events (506 [26%]) were the most common diagnoses. Respiratory and systemic symptoms preceded neurological features in 93% of patients; one third developed neurological disease after hospital admission. A poor outcome was more common in patients with cerebrovascular events (76% [95% CI 67-82]), than encephalopathy (54% [42-65]). Intensive care use was high (38% [35-41]) overall, and also greater in the cerebrovascular patients. In the cerebrovascular, but not encephalopathic patients, risk factors for poor outcome included breathlessness on admission and elevated D-dimer. Overall, 30-day mortality was 30% [27-32]. The hazard of death was comparatively lower for patients in the WHO European region. INTERPRETATION: Neurological COVID-19 disease poses a considerable burden in terms of disease outcomes and use of hospital resources from prolonged intensive care and inpatient admission; preliminary data suggest these may differ according to WHO regions and country income levels. The different risk factors for encephalopathy and stroke suggest different disease mechanisms which may be amenable to intervention, especially in those who develop neurological symptoms after hospital admission

Prognostic indicators and outcomes of hospitalised COVID-19 patients with neurological disease: An individual patient data meta-analysis.

BackgroundNeurological COVID-19 disease has been reported widely, but published studies often lack information on neurological outcomes and prognostic risk factors. We aimed to describe the spectrum of neurological disease in hospitalised COVID-19 patients; characterise clinical outcomes; and investigate factors associated with a poor outcome.MethodsWe conducted an individual patient data (IPD) meta-analysis of hospitalised patients with neurological COVID-19 disease, using standard case definitions. We invited authors of studies from the first pandemic wave, plus clinicians in the Global COVID-Neuro Network with unpublished data, to contribute. We analysed features associated with poor outcome (moderate to severe disability or death, 3 to 6 on the modified Rankin Scale) using multivariable models.ResultsWe included 83 studies (31 unpublished) providing IPD for 1979 patients with COVID-19 and acute new-onset neurological disease. Encephalopathy (978 [49%] patients) and cerebrovascular events (506 [26%]) were the most common diagnoses. Respiratory and systemic symptoms preceded neurological features in 93% of patients; one third developed neurological disease after hospital admission. A poor outcome was more common in patients with cerebrovascular events (76% [95% CI 67-82]), than encephalopathy (54% [42-65]). Intensive care use was high (38% [35-41]) overall, and also greater in the cerebrovascular patients. In the cerebrovascular, but not encephalopathic patients, risk factors for poor outcome included breathlessness on admission and elevated D-dimer. Overall, 30-day mortality was 30% [27-32]. The hazard of death was comparatively lower for patients in the WHO European region.InterpretationNeurological COVID-19 disease poses a considerable burden in terms of disease outcomes and use of hospital resources from prolonged intensive care and inpatient admission; preliminary data suggest these may differ according to WHO regions and country income levels. The different risk factors for encephalopathy and stroke suggest different disease mechanisms which may be amenable to intervention, especially in those who develop neurological symptoms after hospital admission

The temporal dynamics of visual object recognition

Thesis by publication.Includes bibliographical references.Chapter one: General introduction -- Chapter two: Evaluating the temporal dynamics of object representations as a function of animacy and real-world size -- Chapter three: Neural coding of visual objects: New insights into categorical representations -- Chapter four: Reaction times predict dynamic brain representations measured with MEG for only some object categorisation tasks -- Chapter five: General discussionVisual object recognition is a complex problem, with much still to be discovered about how the visual system achieves this task. Several studies have examined the emergence of object category structure, focusing particularly on animacy as an overarching principle of the neural organisation of object representations. Results from fMRI studies have highlighted additional organisational principles for category structure, such as real-world size, and biological class, however the temporal dynamics of these category organisations are yet to be established. The aim of this thesis is to build upon our understanding of visual object recognition, with a specific focus on evaluating the temporal dynamics of object category structure as measured with MEG. Using representational similarity analysis applied to MEG data, the first empirical chapter compares the temporal dynamics of animacy and real-world size dimensions of object representations. The results replicate previous findings for the animacy time-course, however there was no evidence for a distinct time-course associated with real-world size. The second empirical chapter examines alternatives to the animacy category organisation of object representations, using a novel stimulus set that includes objects which do not clearly belong to the typically evaluated 'animate' or 'inanimate' categories (e.g., robots and human-/animal-like toys). This study evaluates a range of models based on current theories of object categorisation including animacy, and the biological classes based 'animacy continuum', as well as novel behaviourally-generated models related to human-similarity and experience. Results show that the model of human-similarity is the best predictor of object representations late in the time-course of visual object processing. The aim of the third empirical chapter is to link these human-similarity results from the MEG data to behaviour. This study shows that object categorisation reaction times predict representational distance not only for object animacy (as shown in previous studies), but also when objects are grouped according to human-similarity. In contrast, other plausible object category organisations for the same stimulus set (i.e., living/non-living; has movement/no movement) do not show the same relationship between brain activation patterns and behaviour. To conclude, the findings from these three studies are discussed within the broader context of the current literature related to object representations in the human brain. This thesis highlights the efficacy of a new human-similarity model of object category representations and critically evaluates what aspects of decodable neural representations are informative for understanding the link between brain and behaviour.Mode of access: Internet.1 online resource (xii, 176 pages) illustration