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- Aartsen, M. G., et al.
(author)
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The IceCube Neutrino Observatory : instrumentation and online systems
- 2017
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In: Journal of Instrumentation. - : IOP PUBLISHING LTD. - 1748-0221. ; 12
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Journal article (peer-reviewed)abstract
- The IceCube Neutrino Observatory is a cubic-kilometer-scale high-energy neutrino detector built into the ice at the South Pole. Construction of IceCube, the largest neutrino detector built to date, was completed in 2011 and enabled the discovery of high-energy astrophysical neutrinos. We describe here the design, production, and calibration of the IceCube digital optical module (DOM), the cable systems, computing hardware, and our methodology for drilling and deployment. We also describe the online triggering and data filtering systems that select candidate neutrino and cosmic ray events for analysis. Due to a rigorous pre-deployment protocol, 98.4% of the DOMs in the deep ice are operating and collecting data. IceCube routinely achieves a detector uptime of 99% by emphasizing software stability and monitoring. Detector operations have been stable since construction was completed, and the detector is expected to operate at least until the end of the next decade.
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- Metcalfe, N. B., et al.
(author)
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Solving the conundrum of intra-specific variation in metabolic rate: A multidisciplinary conceptual and methodological toolkit New technical developments are opening the door to an understanding of why metabolic rate varies among individual animals of a species
- 2023
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In: Bioessays. - 0265-9247. ; 45:6
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Journal article (peer-reviewed)abstract
- Researchers from diverse disciplines, including organismal and cellular physiology, sports science, human nutrition, evolution and ecology, have sought to understand the causes and consequences of the surprising variation in metabolic rate found among and within individual animals of the same species. Research in this area has been hampered by differences in approach, terminology and methodology, and the context in which measurements are made. Recent advances provide important opportunities to identify and address the key questions in the field. By bringing together researchers from different areas of biology and biomedicine, we describe and evaluate these developments and the insights they could yield, highlighting the need for more standardisation across disciplines. We conclude with a list of important questions that can now be addressed by developing a common conceptual and methodological toolkit for studies on metabolic variation in animals.
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- Halvorsen, A., et al.
(author)
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Epidemiology of traumatic spinal cord injury in Norway in 2012-2016: a registry-based cross-sectional study
- 2019
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In: Spinal Cord. - : Springer Science and Business Media LLC. - 1362-4393 .- 1476-5624. ; 57:4, s. 331-338
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Journal article (peer-reviewed)abstract
- Study design A registry-based cross-sectional study. Objectives To analyse the epidemiological and demographic characteristics of persons with traumatic spinal cord injury (TSCI) in Norway. Setting TSCI patients admitted for primary rehabilitation to one of the three specialised spinal cord injury (SCI) departments (located in Bergen, Trondheim, and Oslo) and consented to the Norwegian Spinal Cord Injury Registry (NorSCIR). Methods Analysis of data from NorSCIR during a 5-year period (2012-2016) was performed. Data were collected by using the International SCI Core Data Set as recommended by the International Spinal Cord Society (ISCoS). Results The lowest incidence of TSCI was 11.4/million (2012), and the highest incidence was 15.9/million (2014). In the study period, 349 individuals were registered with TSCI. In total, 76% were male, and the mean age was 47 (SD +/- 19) years. We observed dominance in the 60-74 years age group. The distribution between tetraplegia and paraplegia was 48%/42%. For those initially classified as American Spinal Cord Injury Association Impairment Scale (AIS) grade A (complete injury), 77% remained grade A at discharge. Considerable changes during primary rehabilitation after incomplete lesions were observed. Most patients (68%) were discharged home after primary rehabilitation. Falls were the main cause of TSCI (47%) and occurred more often during the weekend. Conclusion Through a National Medical Quality Registry based on internationally provided data sets, we are able to present systematic and updated data from Norway.
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- Halvorsen, A., et al.
(author)
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Non-traumatic spinal cord injury in Norway 2012-2016: analysis from a national registry and comparison with traumatic spinal cord injury
- 2019
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In: Spinal Cord. - : Springer Science and Business Media LLC. - 1362-4393 .- 1476-5624. ; 57:4, s. 324-330
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Journal article (peer-reviewed)abstract
- Study design Registry-based cross-sectional study. Objectives To describe and analyze epidemiological and demographic characteristics of non-traumatic spinal cord injury (NTSCI) and to compare persons with NTSCI and traumatic spinal cord injury (TSCI). Setting A total of 225 non-traumatic and 349 traumatic SCI patients were admitted for primary rehabilitation at one of the three specialized SCI departments in Norway (located in Bergen, Trondheim, and Oslo) from 2012 to 2016. Patients who consented to registration in the Norwegian Spinal Cord Injury Registry (NorSCIR) were included. Methods Data were collected using the International SCI Core Data Set, as recommended by the International Spinal Cord Society (ISCoS). Demographics and injury characteristics were analyzed descriptively. The NTSCI and TSCI groups were compared using a Mann-Whitney U test and chi-square test. Results The mean age of the NTSCI patients was 55 years, and 59% were male. The incidence of NTSCI was 7.7-10.4 per million person-years, which is lower than the incidence of TSCI. NTSCI individuals were older, less severely injured, and their length of stay at the hospital was shorter than the TSCI individuals. The results may be influenced by the inclusion criterion in the registry. This makes the analyzed sample for NTSCI less complete. However, the majority of patients with non-progressive NTSCI are included in the NorSCIR. Conclusion For the first time, we are able to provide the national epidemiological status on NTSCI based on available data from the national registry. Further studies are required to improve the capture of NTSCI for future incidence studies.
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- Feng, Xiaoshuang, et al.
(author)
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Lung cancer risk discrimination of prediagnostic proteomics measurements compared with existing prediction tools
- 2023
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In: Journal of the National Cancer Institute. - : Oxford University Press. - 0027-8874 .- 1460-2105. ; 115:9, s. 1050-1059
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Journal article (peer-reviewed)abstract
- BACKGROUND: We sought to develop a proteomics-based risk model for lung cancer and evaluate its risk-discriminatory performance in comparison with a smoking-based risk model (PLCOm2012) and a commercially available autoantibody biomarker test.METHODS: We designed a case-control study nested in 6 prospective cohorts, including 624 lung cancer participants who donated blood samples at most 3 years prior to lung cancer diagnosis and 624 smoking-matched cancer free participants who were assayed for 302 proteins. We used 470 case-control pairs from 4 cohorts to select proteins and train a protein-based risk model. We subsequently used 154 case-control pairs from 2 cohorts to compare the risk-discriminatory performance of the protein-based model with that of the Early Cancer Detection Test (EarlyCDT)-Lung and the PLCOm2012 model using receiver operating characteristics analysis and by estimating models' sensitivity. All tests were 2-sided.RESULTS: The area under the curve for the protein-based risk model in the validation sample was 0.75 (95% confidence interval [CI] = 0.70 to 0.81) compared with 0.64 (95% CI = 0.57 to 0.70) for the PLCOm2012 model (Pdifference = .001). The EarlyCDT-Lung had a sensitivity of 14% (95% CI = 8.2% to 19%) and a specificity of 86% (95% CI = 81% to 92%) for incident lung cancer. At the same specificity of 86%, the sensitivity for the protein-based risk model was estimated at 49% (95% CI = 41% to 57%) and 30% (95% CI = 23% to 37%) for the PLCOm2012 model.CONCLUSION: Circulating proteins showed promise in predicting incident lung cancer and outperformed a standard risk prediction model and the commercialized EarlyCDT-Lung.
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