| 1. |
- Alam, M. T., et al.
(författare)
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The self-inhibitory nature of metabolic networks and its alleviation through compartmentalization
- 2017
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723 .- 2041-1723. ; 8, s. Article no 16018-
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Tidskriftsartikel (refereegranskat)abstract
- Metabolites can inhibit the enzymes that generate them. To explore the general nature of metabolic self-inhibition, we surveyed enzymological data accrued from a century of experimentation and generated a genome-scale enzyme-inhibition network. Enzyme inhibition is often driven by essential metabolites, affects the majority of biochemical processes, and is executed by a structured network whose topological organization is reflecting chemical similarities that exist between metabolites. Most inhibitory interactions are competitive, emerge in the close neighbourhood of the inhibited enzymes, and result from structural similarities between substrate and inhibitors. Structural constraints also explain one-third of allosteric inhibitors, a finding rationalized by crystallographic analysis of allosterically inhibited L-lactate dehydrogenase. Our findings suggest that the primary cause of metabolic enzyme inhibition is not the evolution of regulatory metabolite-enzyme interactions, but a finite structural diversity prevalent within the metabolome. In eukaryotes, compartmentalization minimizes inevitable enzyme inhibition and alleviates constraints that self-inhibition places on metabolism.
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| 2. |
- Bogdanov, A. L., et al.
(författare)
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Fabrication of arrays of nanometer size test structures for scanning probe microscope tips characterization
- 1994
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Ingår i: Journal of Vacuum Science & Technology B: Microelectronics Processing and Phenomena. - : American Vacuum Society. - 0734-211X. ; 12:6, s. 3681-3684
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Konferensbidrag (refereegranskat)abstract
- A problem in scanning probe microscopy (SPM) is the unknown shape of the probing tip. Generally, the image is a convolution between the shape of the tip and the surface. Information of the shape of the probe may be gained by imaging very sharp tips. Here we present a method for making two-dimensional arrays of very sharp tips. The tip arrays were made of silicon using electron beam lithography with subsequent ion-beam etching. To achieve the best possible resolution, ultrasonic excitation was used during development of the bilayered PMMA resist. Thus, openings in the resist with size nearly equal to the spot size of the writing e-beam have been obtained. A further decrease of the radius of the tips was obtained by the choice of appropriate thickness for the masking NiCr layer. The tips were conical with a height up to 100 nm with a radius of the tip down to 10 nm. The tips were suitable for study of the shape of AFM probe tips, under condition that the tip array samples were rinsed in water prior to the measurement. Without the rinsing procedure, strong sticking forces between the probe and the sample would have eroded both of them. The regularity of the array provided an easy way to calibrate the lateral motion of the scanner
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| 3. |
- Hentati-Sundberg, Jonas, et al.
(författare)
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Seabird surveillance: combining CCTV and artificial intelligence for monitoring and research
- 2023
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Ingår i: Remote Sensing in Ecology and Conservation. - : Wiley. - 2056-3485. ; 9:4, s. 568-581
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Tidskriftsartikel (refereegranskat)abstract
- Ecological research and monitoring need to be able to rapidly convey information that can form the basis of scientifically sound management. Automated sensor systems, especially if combined with artificial intelligence, can contribute to such rapid high-resolution data retrieval. Here, we explore the prospects of automated methods to generate insights for seabirds, which are often monitored for their high conservation value and for being sentinels for marine ecosystem changes. We have developed a system of video surveillance combined with automated image processing, which we apply to common murres Uria aalge. The system uses a deep learning algorithm for object detection (YOLOv5) that has been trained on annotated images of adult birds, chicks and eggs, and outputs time, location, size and confidence level of all detections, frame-by-frame, in the supplied video material. A total of 144 million bird detections were generated from a breeding cliff over three complete breeding seasons (2019–2021). We demonstrate how object detection can be used to accurately monitor breeding phenology and chick growth. Our automated monitoring approach can also identify and quantify rare events that are easily missed in traditional monitoring, such as disturbances from predators. Further, combining automated video analysis with continuous measurements from a temperature logger allows us to study impacts of heat waves on nest attendance in high detail. Our automated system thus produces comparable, and in several cases significantly more detailed, data than those generated from observational field studies. By running in real time on the camera streams, it has the potential to supply researchers and managers with high-resolution up-to-date information on seabird population status. We describe how the system can be modified to fit various types of ecological research and monitoring goals and thereby provide up-to-date support for conservation and ecosystem management.
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