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- Glasbey, JC, et al.
(författare)
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- 2021
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swepub:Mat__t
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- Pöntinen, M., et al.
(författare)
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Euclid: Identification of asteroid streaks in simulated images using deep learning
- 2023
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Ingår i: Astronomy and Astrophysics. - : EDP Sciences. - 0004-6361 .- 1432-0746. ; 679
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Tidskriftsartikel (refereegranskat)abstract
- The material composition of asteroids is an essential piece of knowledge in the quest to understand the formation and evolution of the Solar System. Visual to near-infrared spectra or multiband photometry is required to constrain the material composition of asteroids, but we currently have such data, especially in the near-infrared wavelengths, for only a limited number of asteroids. This is a significant limitation considering the complex orbital structures of the asteroid populations. Up to 150 000 asteroids will be visible in the images of the upcoming ESA Euclid space telescope, and the instruments of Euclid will offer multiband visual to near-infrared photometry and slitless near-infrared spectra of these objects. Most of the asteroids will appear as streaks in the images. Due to the large number of images and asteroids, automated detection methods are needed. A non-machine-learning approach based on the Streak Det software was previously tested, but the results were not optimal for short and/or faint streaks. We set out to improve the capability to detect asteroid streaks in Euclid images by using deep learning. We built, trained, and tested a three-step machine-learning pipeline with simulated Euclid images. First, a convolutional neural network (CNN) detected streaks and their coordinates in full images, aiming to maximize the completeness (recall) of detections. Then, a recurrent neural network (RNN) merged snippets of long streaks detected in several parts by the CNN. Lastly, gradient-boosted trees (XGBoost) linked detected streaks between different Euclid exposures to reduce the number of false positives and improve the purity (precision) of the sample. The deep-learning pipeline surpasses the completeness and reaches a similar level of purity of a non-machine-learning pipeline based on the StreakDet software. Additionally, the deep-learning pipeline can detect asteroids 0.25–0.5 magnitudes fainter than StreakDet. The deep-learning pipeline could result in a 50% increase in the number of detected asteroids compared to the StreakDet software. There is still scope for further refinement, particularly in improving the accuracy of streak coordinates and enhancing the completeness of the final stage of the pipeline, which involves linking detections across multiple exposures.
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| 8. |
- Adams, D., et al.
(författare)
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Patisiran, an RNAi Therapeutic, for Hereditary Transthyretin Amyloidosis
- 2018
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Ingår i: New England Journal of Medicine. - : Massachusetts Medical Society. - 0028-4793 .- 1533-4406. ; 379:1, s. 11-21
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Patisiran, an investigational RNA interference therapeutic agent, specifically inhibits hepatic synthesis of transthyretin.METHODS: In this phase 3 trial, we randomly assigned patients with hereditary transthyretin amyloidosis with polyneuropathy, in a 2:1 ratio, to receive intravenous patisiran (0.3 mg per kilogram of body weight) or placebo once every 3 weeks. The primary end point was the change from baseline in the modified Neuropathy Impairment Score+7 (mNIS+7; range, 0 to 304, with higher scores indicating more impairment) at 18 months. Other assessments included the Norfolk Quality of Life-Diabetic Neuropathy (Norfolk QOL-DN) questionnaire (range, -4 to 136, with higher scores indicating worse quality of life), 10-m walk test (with gait speed measured in meters per second), and modified body-mass index (modified BMI, defined as [weight in kilograms divided by square of height in meters] x albumin level in grams per liter; lower values indicated worse nutritional status).RESULTS: A total of 225 patients underwent randomization (148 to the patisiran group and 77 to the placebo group). The mean (+/- SD) mNIS+7 at baseline was 80.9 +/- 41.5 in the patisiran group and 74.6 +/- 37.0 in the placebo group; the least-squares mean (+/- SE) change from baseline was -6.0 +/- 1.7 versus 28.0 +/- 2.6 (difference, -34.0 points; P<0.001) at 18 months. The mean (+/- SD) baseline Norfolk QOL-DN score was 59.6 +/- 28.2 in the patisiran group and 55.5 +/- 24.3 in the placebo group; the least-squares mean (+/- SE) change from baseline was -6.7 +/- 1.8 versus 14.4 +/- 2.7 (difference, -21.1 points; P<0.001) at 18 months. Patisiran also showed an effect on gait speed and modified BMI. At 18 months, the least-squares mean change from baseline in gait speed was 0.08 +/- 0.02 m per second with patisiran versus -0.24 +/- 0.04 m per second with placebo (difference, 0.31 m per second; P<0.001), and the least-squares mean change from baseline in the modified BMI was -3.7 +/- 9.6 versus -119.4 +/- 14.5 (difference, 115.7; P<0.001). Approximately 20% of the patients who received patisiran and 10% of those who received placebo had mild or moderate infusion-related reactions; the overall incidence and types of adverse events were similar in the two groups.CONCLUSIONS: In this trial, patisiran improved multiple clinical manifestations of hereditary transthyretin amyloidosis.
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| 9. |
- Rabe, Patrick, et al.
(författare)
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X-ray free-electron laser studies reveal correlated motion during isopenicillin N synthase catalysis
- 2021
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Ingår i: Science Advances. - : American Association for the Advancement of Science (AAAS). - 2375-2548. ; 7:34
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Tidskriftsartikel (refereegranskat)abstract
- Isopenicillin N synthase (IPNS) catalyzes the unique reaction of L-delta-(alpha-aminoadipoyl)-L-cysteinyl-D-valine (ACV) with dioxygen giving isopenicillin N (IPN), the precursor of all natural penicillins and cephalosporins. X-ray free-electron laser studies including time-resolved crystallography and emission spectroscopy reveal how reaction of IPNS:Fe(II):ACV with dioxygen to yield an Fe(III) superoxide causes differences in active site volume and unexpected conformational changes that propagate to structurally remote regions. Combined with solution studies, the results reveal the importance of protein dynamics in regulating intermediate conformations during conversion of ACV to IPN. The results have implications for catalysis by multiple IPNS-related oxygenases, including those involved in the human hypoxic response, and highlight the power of serial femtosecond crystallography to provide insight into long-range enzyme dynamics during reactions presently impossible for nonprotein catalysts.
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