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| 13. |
- Allocca, Giancarlo, et al.
(författare)
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Validation of 'Somnivore', a Machine Learning Algorithm for Automated Scoring and Analysis of Polysomnography Data
- 2019
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Ingår i: Frontiers in Neuroscience. - : Frontiers Media S.A.. - 1662-4548 .- 1662-453X. ; 13
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Tidskriftsartikel (refereegranskat)abstract
- Manual scoring of polysomnography data is labor-intensive and time-consuming, and most existing software does not account for subjective differences and user variability. Therefore, we evaluated a supervised machine learning algorithm, Somnivore (TM), for automated wake-sleep stage classification. We designed an algorithm that extracts features from various input channels, following a brief session of manual scoring, and provides automated wake-sleep stage classification for each recording. For algorithm validation, polysomnography data was obtained from independent laboratories, and include normal, cognitively-impaired, and alcohol-treated human subjects (total n = 52), narcoleptic mice and drug-treated rats (total n = 56), and pigeons (n = 5). Training and testing sets for validation were previously scored manually by 1-2 trained sleep technologists from each laboratory. F-measure was used to assess precision and sensitivity for statistical analysis of classifier output and human scorer agreement. The algorithm gave high concordance with manual visual scoring across all human data (wake 0.91 +/- 0.01; N1 0.57 +/- 0.01; N2 0.81 +/- 0.01; N3 0.86 +/- 0.01; REM 0.87 +/- 0.01), which was comparable to manual inter-scorer agreement on all stages. Similarly, high concordance was observed across all rodent (wake 0.95 +/- 0.01; NREM 0.94 +/- 0.01; REM 0.91 +/- 0.01) and pigeon (wake 0.96 +/- 0.006; NREM 0.97 +/- 0.01; REM 0.86 +/- 0.02) data. Effects of classifier learning from single signal inputs, simple stage reclassification, automated removal of transition epochs, and training set size were also examined. In summary, we have developed a polysomnography analysis program for automated sleep-stage classification of data from diverse species. Somnivore enables flexible, accurate, and high-throughput analysis of experimental and clinical sleep studies.
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| 15. |
- Heid, J, et al.
(författare)
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Age-dependent increase of oxidative stress regulates microRNA-29 family preserving cardiac health
- 2017
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Ingår i: Scientific reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 7:1, s. 16839-
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Tidskriftsartikel (refereegranskat)abstract
- The short-lived turquoise killifish Nothobranchius furzeri (Nfu) is a valid model for aging studies. Here, we investigated its age-associated cardiac function. We observed oxidative stress accumulation and an engagement of microRNAs (miRNAs) in the aging heart. MiRNA-sequencing of 5 week (young), 12–21 week (adult) and 28–40 week (old) Nfu hearts revealed 23 up-regulated and 18 down-regulated miRNAs with age. MiR-29 family turned out as one of the most up-regulated miRNAs during aging. MiR-29 family increase induces a decrease of known targets like collagens and DNA methyl transferases (DNMTs) paralleled by 5´methyl-cytosine (5mC) level decrease. To further investigate miR-29 family role in the fish heart we generated a transgenic zebrafish model where miR-29 was knocked-down. In this model we found significant morphological and functional cardiac alterations and an impairment of oxygen dependent pathways by transcriptome analysis leading to hypoxic marker up-regulation. To get insights the possible hypoxic regulation of miR-29 family, we exposed human cardiac fibroblasts to 1% O2 levels. In hypoxic condition we found miR-29 down-modulation responsible for the accumulation of collagens and 5mC. Overall, our data suggest that miR-29 family up-regulation might represent an endogenous mechanism aimed at ameliorating the age-dependent cardiac damage leading to hypertrophy and fibrosis.
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