30 research outputs found
TRY plant trait database â enhanced coverage and open access
Plant traitsâthe morphological, anatomical, physiological, biochemical and phenological characteristics of plantsâdetermine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of traitâbased plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traitsâalmost complete coverage for âplant growth formâ. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and traitâenvironmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives
Postoperative complications after pancreatoduodenectomy for malignancy: results from the Recurrence After Whippleâs (RAW) study
Background
Pancreatoduodenectomy (PD) is associated with significant postoperative morbidity. Surgeons should have a sound understanding of the potential complications for consenting and benchmarking purposes. Furthermore, preoperative identification of high-risk patients can guide patient selection and potentially allow for targeted prehabilitation and/or individualized treatment regimens. Using a large multicentre cohort, this study aimed to calculate the incidence of all PD complications and identify risk factors.
Method
Data were extracted from the Recurrence After Whippleâs (RAW) study, a retrospective cohort study of PD outcomes (29 centres from 8 countries, 2012â2015). The incidence and severity of all complications was recorded and potential risk factors for morbidity, major morbidity (ClavienâDindo grade > IIIa), postoperative pancreatic fistula (POPF), post-pancreatectomy haemorrhage (PPH) and 90-day mortality were investigated.
Results
Among the 1348 included patients, overall morbidity, major morbidity, POPF, PPH and perioperative death affected 53 per cent (n = 720), 17 per cent (n = 228), 8 per cent (n = 108), 6 per cent (n = 84) and 4 per cent (n = 53), respectively. Following multivariable tests, a high BMI (P = 0.007), an ASA grade > II (P II patients were at increased risk of major morbidity (P < 0.0001), and a raised BMI correlated with a greater risk of POPF (P = 0.001).
Conclusion
In this multicentre study of PD outcomes, an ASA grade > II was a risk factor for major morbidity and a high BMI was a risk factor for POPF. Patients who are preoperatively identified to be high risk may benefit from targeted prehabilitation or individualized treatment regimens
Capacity-based versus time-based access charges in telecommunications
Telecommunications, Capacity-based access charges, Peak-load pricing, Network regulation, L13, L51, H54, D43,