| 1. |
- Botvinik-Nezer, Rotem, et al.
(författare)
-
Variability in the analysis of a single neuroimaging dataset by many teams
- 2020
-
Ingår i: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 582, s. 84-88
-
Tidskriftsartikel (refereegranskat)abstract
- Data analysis workflows in many scientific domains have become increasingly complex and flexible. Here we assess the effect of this flexibility on the results of functional magnetic resonance imaging by asking 70 independent teams to analyse the same dataset, testing the same 9 ex-ante hypotheses(1). The flexibility of analytical approaches is exemplified by the fact that no two teams chose identical workflows to analyse the data. This flexibility resulted in sizeable variation in the results of hypothesis tests, even for teams whose statistical maps were highly correlated at intermediate stages of the analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Notably, a meta-analytical approach that aggregated information across teams yielded a significant consensus in activated regions. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset(2-5). Our findings show that analytical flexibility can have substantial effects on scientific conclusions, and identify factors that may be related to variability in the analysis of functional magnetic resonance imaging. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for performing and reporting multiple analyses of the same data. Potential approaches that could be used to mitigate issues related to analytical variability are discussed. The results obtained by seventy different teams analysing the same functional magnetic resonance imaging dataset show substantial variation, highlighting the influence of analytical choices and the importance of sharing workflows publicly and performing multiple analyses.
|
|
| 2. |
- Deyab, G, et al.
(författare)
-
Antirheumatic treatment is associated with reduced serum Syndecan-1 in Rheumatoid Arthritis
- 2021
-
Ingår i: PloS one. - : Public Library of Science (PLoS). - 1932-6203. ; 16:7, s. e0253247-
-
Tidskriftsartikel (refereegranskat)abstract
- The endothelial glycocalyx (EG) is essential for proper function of the endothelium and for vascular integrity, but its role in premature atherogenesis in rheumatoid arthritis (RA) has not been studied yet. EG impairment can play a role in pathogenesis of vascular disease, and one of its characteristics is shedding of syndecan-1 from endothelial cells. Syndecan-1 shedding is mediated by matrix metalloproteinase-9 (MMP-9) and counteracted by tissue inhibitor of metalloproteinases (TIMP)-1. Cardiovascular disease risk in RA is reversible by disease modifying antirheumatic drugs (DMARDs), but the exact modes of action are still unclear. Therefore, we examined effects of DMARDs on syndecan-1, MMP-9 and TIMP-1 in RA patients, and searched for associations between these parameters and inflammatory activity. From the observational PSARA study, we examined 39 patients starting with methotrexate (MTX) monotherapy (in MTX naïve patients, n = 19) or tumor necrosis factor inhibitors (TNFi) in combination with MTX (in MTX non-responders, n = 20) due to active RA. Serum syndecan-1, MMP-9 and TIMP-1 were measured at baseline and after six weeks of treatment. Serum syndecan-1 (p = 0.008) and TIMP-1 (p<0.001) levels decreased after six weeks of anti-rheumatic treatment. Levels of MMP-9 also decreased, but the difference was not statistically significant. The improvement in syndecan-1 levels were independent of changes in inflammatory activity. There was no significant difference in changes in syndecan-1 levels from baseline to 6 weeks between the MTX and TNFi groups, however the change was significant within the MTX group. Six weeks of antirheumatic treatment was associated with reduction in serum levels of syndecan-1, which might reflect reduced syndecan-1 shedding from EG. Thus, it is possible that EG-preserving properties of DMARDs might contribute to their cardioprotective effects. These effects may be at least partly independent of their anti-inflammatory actions. Our findings do not support the notion that syndecan-1 shedding in RA is mediated mainly by increased MMP-9 or decreased TIMP-9 serum concentration.
|
|
| 3. |
- Duffy, J. M. N., et al.
(författare)
-
Top 10 priorities for future infertility research: an international consensus development study
- 2020
-
Ingår i: Human Reproduction. - : Oxford University Press (OUP). - 0268-1161 .- 1460-2350. ; 35:12, s. 2715-2724
-
Tidskriftsartikel (refereegranskat)abstract
- STUDY QUESTION: Can the priorities for future research in infertility be identified? SUMMARY ANSWER: The top 10 research priorities for the four areas of male infertility, female and unexplained infertility, medically assisted reproduction and ethics, access and organization of care for people with fertility problems were identified. WHAT IS KNOWN ALREADY: Many fundamental questions regarding the prevention, management and consequences of infertility remain unanswered. This is a barrier to improving the care received by those people with fertility problems. STUDY DESIGN, SIZE, DURATION: Potential research questions were collated from an initial international survey, a systematic review of clinical practice guidelines and Cochrane systematic reviews. A rationalized list of confirmed research uncertainties was prioritized in an interim international survey. Prioritized research uncertainties were discussed during a consensus development meeting. Using a formal consensus development method, the modified nominal group technique, diverse stakeholders identified the top 10 research priorities for each of the categories male infertility, female and unexplained infertility, medically assisted reproduction and ethics, access and organization of care. PARTICIPANTS/MATERIALS, SETTING, METHODS: Healthcare professionals, people with fertility problems and others (healthcare funders, healthcare providers, healthcare regulators, research funding bodies and researchers) were brought together in an open and transparent process using formal consensus methods advocated by the James Lind Alliance. MAIN RESULTS AND THE ROLE OF CHANCE: The initial survey was completed by 388 participants from 40 countries, and 423 potential research questions were submitted. Fourteen clinical practice guidelines and 162 Cochrane systematic reviews identified a further 236 potential research questions. A rationalized list of 231 confirmed research uncertainties was entered into an interim prioritization survey completed by 317 respondents from 43 countries. The top 10 research priorities for each of the four categories male infertility, female and unexplained infertility (including age-related infertility, ovarian cysts, uterine cavity abnormalities and tubal factor infertility), medically assisted reproduction (including ovarian stimulation, IUI and IVF) and ethics, access and organization of care were identified during a consensus development meeting involving 41 participants from I I countries. These research priorities were diverse and seek answers to questions regarding prevention, treatment and the longer-term impact of infertility. They highlight the importance of pursuing research which has often been overlooked, including addressing the emotional and psychological impact of infertility, improving access to fertility treatment, particularly in lower resource settings and securing appropriate regulation. Addressing these priorities will require diverse research methodologies, including laboratory-based science, qualitative and quantitative research and population science. LIMITATIONS, REASONS FOR CAUTION: We used consensus development methods, which have inherent limitations, including the representativeness of the participant sample, methodological decisions informed by professional judgment and arbitrary consensus definitions. WIDER IMPLICATIONS OF THE FINDINGS: We anticipate that identified research priorities, developed to specifically highlight the most pressing clinical needs as perceived by healthcare professionals, people with fertility problems and others, will help research funding organizations and researchers to develop their future research agenda.
|
|
| 4. |
- Gladding, PA, et al.
(författare)
-
Multiomics, virtual reality and artificial intelligence in heart failure
- 2021
-
Ingår i: Future cardiology. - : Future Medicine Ltd. - 1744-8298 .- 1479-6678. ; 17:8, s. 1335-1347
-
Tidskriftsartikel (refereegranskat)abstract
- Aim: Multiomics delivers more biological insight than targeted investigations. We applied multiomics to patients with heart failure (HF) and reduced ejection fraction (HFrEF), with machine learning applied to advanced ECG (AECG) and echocardiography artificial intelligence (Echo AI). Patients & methods: In total, 46 patients with HFrEF and 20 controls underwent metabolomic profiling, including liquid/gas chromatography–mass spectrometry and solid-phase microextraction volatilomics in plasma and urine. HFrEF was defined using left ventricular (LV) global longitudinal strain, EF and N-terminal pro hormone BNP. AECG and Echo AI were performed over 5 min, with a subset of patients undergoing a virtual reality mental stress test. Results: A-ECG had similar diagnostic accuracy as N-terminal pro hormone BNP for HFrEF (area under the curve = 0.95, 95% CI: 0.85–0.99), and correlated with global longitudinal strain (r = -0.77, p < 0.0001), while Echo AI-generated measurements correlated well with manually measured LV end diastolic volume r = 0.77, LV end systolic volume r = 0.8, LVEF r = 0.71, indexed left atrium volume r = 0.71 and indexed LV mass r = 0.6, p < 0.005. AI-LVEF and other HFrEF biomarkers had a similar discrimination for HFrEF (area under the curve AI-LVEF = 0.88; 95% CI: -0.03 to 0.15; p = 0.19). Virtual reality mental stress test elicited arrhythmic biomarkers on AECG and indicated blunted autonomic responsiveness (alpha 2 of RR interval variability, p = 1 × 10-4) in HFrEF. Conclusion: Multiomics-related machine learning shows promise for the assessment of HF.
|
|
