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- Ballan, M., et al.
(författare)
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Nuclear physics midterm plan at Legnaro National Laboratories (LNL)
- 2023
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Ingår i: European Physical Journal Plus. - 2190-5444. ; 138:8, s. 3-26
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Tidskriftsartikel (refereegranskat)abstract
- The next years will see the completion of the radioactive ion beam facility SPES (Selective Production of Exotic Species) and the upgrade of the accelerators complex at Istituto Nazionale di Fisica Nucleare – Legnaro National Laboratories (LNL) opening up new possibilities in the fields of nuclear structure, nuclear dynamics, nuclear astrophysics, and applications. The nuclear physics community has organised a workshop to discuss the new physics opportunities that will be possible in the near future by employing state-of-the-art detection systems. A detailed discussion of the outcome from the workshop is presented in this report.
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- Cosmi, F., et al.
(författare)
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Treatment with insulin is associated with worse outcome in patients with chronic heart failure and diabetes
- 2018
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Ingår i: European Journal of Heart Failure. - : Wiley. - 1388-9842. ; 20:5, s. 888-895
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Tidskriftsartikel (refereegranskat)abstract
- Aims Up to one-third of patients with diabetes mellitus and heart failure (HF) are treated with insulin. As insulin causes sodium retention and hypoglycaemia, its use might be associated with worse outcomes. Methods and results We examined two datasets: 24 012 patients with HF from four large randomized trials and an administrative database of 4 million individuals, 103 857 of whom with HF. In the former, survival was examined using Cox proportional hazards models adjusted for baseline variables and separately for propensity scores. Fine-Gray competing risk regression models were used to assess the risk of hospitalization for HF. For the latter, a case-control nested within a population-based cohort study was conducted with propensity score. Prevalence of diabetes mellitus at study entry ranged from 25.5% to 29.5% across trials. Insulin alone or in combination with oral hypoglycaemic drugs was prescribed at randomization to 24.4% to 34.5% of the patients with diabetes. The rates of death from any cause and hospitalization for HF were higher in patients with vs. without diabetes, and highest of all in patients prescribed insulin [propensity score pooled hazard ratio for all-cause mortality 1.27 (1.16-1.38), for HF hospitalization 1.23 (1.13-1.33)]. In the administrative registry, insulin prescription was associated with a higher risk of all-cause death [odds ratio (OR) 2.02, 95% confidence interval (CI) 1.87-2.19] and rehospitalization for HF (OR 1.42, 95% CI 1.32-1.53). Conclusions Whether insulin use is associated with poor outcomes in HF should be investigated further with controlled trials, as should the possibility that there may be safer alternative glucose-lowering treatments for patients with HF and type 2 diabetes mellitus.
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- Lønborg, C., et al.
(författare)
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A global database of dissolved organic matter (DOM) concentration measurements in coastal waters (CoastDOM v1)
- 2024
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Ingår i: Earth System Science Data. - : Copernicus Publications. - 1866-3508 .- 1866-3516. ; 16:2, s. 1107-1119
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Tidskriftsartikel (refereegranskat)abstract
- Measurements of dissolved organic carbon (DOC), nitrogen (DON), and phosphorus (DOP) concentrations are used to characterize the dissolved organic matter (DOM) pool and are important components ofbiogeochemical cycling in the coastal ocean. Here, we present the first edition of a global database (CoastDOMv1; available at https://doi.org/10.1594/PANGAEA.964012, Lønborg et al., 2023) compiling previously published and unpublished measurements of DOC, DON, and DOP in coastal waters. These data are complementedby hydrographic data such as temperature and salinity and, to the extent possible, other biogeochemical variables(e.g. chlorophyll a, inorganic nutrients) and the inorganic carbon system (e.g. dissolved inorganic carbon andtotal alkalinity). Overall, CoastDOM v1 includes observations of concentrations from all continents. However,most data were collected in the Northern Hemisphere, with a clear gap in DOM measurements from the SouthernHemisphere. The data included were collected from 1978 to 2022 and consist of 62 338 data points for DOC,20 356 for DON, and 13 533 for DOP. The number of measurements decreases progressively in the sequenceDOC > DON > DOP, reflecting both differences in the maturity of the analytical methods and the greater focuson carbon cycling by the aquatic science community. The global database shows that the average DOC concentration in coastal waters (average ± standard deviation (SD): 182±314 µmolC L−1; median: 103 µmolC L−1) is13-fold higher than the average coastal DON concentration (13.6 ± 30.4 µmol N L−1; median: 8.0 µmol N L−1),which is itself 39-fold higher than the average coastal DOP concentration (0.34 ± 1.11 µmol P L−1; median:0.18 µmol P L−1). This dataset will be useful for identifying global spatial and temporal patterns in DOM and willhelp facilitate the reuse of DOC, DON, and DOP data in studies aimed at better characterizing local biogeochemical processes; closing nutrient budgets; estimating carbon, nitrogen, and phosphorous pools; and establishing abaseline for modelling future changes in coastal waters.
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- Schwarz, E, et al.
(författare)
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Reproducible grey matter patterns index a multivariate, global alteration of brain structure in schizophrenia and bipolar disorder
- 2019
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Ingår i: Translational psychiatry. - : Springer Science and Business Media LLC. - 2158-3188. ; 9:1, s. 12-
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Tidskriftsartikel (refereegranskat)abstract
- Schizophrenia is a severe mental disorder characterized by numerous subtle changes in brain structure and function. Machine learning allows exploring the utility of combining structural and functional brain magnetic resonance imaging (MRI) measures for diagnostic application, but this approach has been hampered by sample size limitations and lack of differential diagnostic data. Here, we performed a multi-site machine learning analysis to explore brain structural patterns of T1 MRI data in 2668 individuals with schizophrenia, bipolar disorder or attention-deficit/ hyperactivity disorder, and healthy controls. We found reproducible changes of structural parameters in schizophrenia that yielded a classification accuracy of up to 76% and provided discrimination from ADHD, through it lacked specificity against bipolar disorder. The observed changes largely indexed distributed grey matter alterations that could be represented through a combination of several global brain-structural parameters. This multi-site machine learning study identified a brain-structural signature that could reproducibly differentiate schizophrenia patients from controls, but lacked specificity against bipolar disorder. While this currently limits the clinical utility of the identified signature, the present study highlights that the underlying alterations index substantial global grey matter changes in psychotic disorders, reflecting the biological similarity of these conditions, and provide a roadmap for future exploration of brain structural alterations in psychiatric patients.
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