--- _id: '404' abstract: - lang: eng text: "We construct martingale solutions to stochastic thin-film equations by introducing a (spatial) semidiscretization and establishing convergence. The discrete scheme allows for variants of the energy and entropy estimates in the continuous setting as long as the discrete energy does not exceed certain threshold values depending on the spatial grid size $h$. Using a stopping time argument to prolongate high-energy paths constant in time, arbitrary moments of coupled energy/entropy functionals can be controlled. Having established Hölder regularity of approximate solutions, the convergence proof is then based on compactness arguments---in particular on Jakubowski's generalization of Skorokhod's theorem---weak convergence methods, and recent tools on martingale convergence.\r\n\r\n" article_processing_charge: No article_type: original author: - first_name: Julian L full_name: Fischer, Julian L id: 2C12A0B0-F248-11E8-B48F-1D18A9856A87 last_name: Fischer orcid: 0000-0002-0479-558X - first_name: Günther full_name: Grün, Günther last_name: Grün citation: ama: Fischer JL, Grün G. Existence of positive solutions to stochastic thin-film equations. SIAM Journal on Mathematical Analysis. 2018;50(1):411-455. doi:10.1137/16M1098796 apa: Fischer, J. L., & Grün, G. (2018). Existence of positive solutions to stochastic thin-film equations. SIAM Journal on Mathematical Analysis. Society for Industrial and Applied Mathematics . https://doi.org/10.1137/16M1098796 chicago: Fischer, Julian L, and Günther Grün. “Existence of Positive Solutions to Stochastic Thin-Film Equations.” SIAM Journal on Mathematical Analysis. Society for Industrial and Applied Mathematics , 2018. https://doi.org/10.1137/16M1098796. ieee: J. L. Fischer and G. Grün, “Existence of positive solutions to stochastic thin-film equations,” SIAM Journal on Mathematical Analysis, vol. 50, no. 1. Society for Industrial and Applied Mathematics , pp. 411–455, 2018. ista: Fischer JL, Grün G. 2018. Existence of positive solutions to stochastic thin-film equations. SIAM Journal on Mathematical Analysis. 50(1), 411–455. mla: Fischer, Julian L., and Günther Grün. “Existence of Positive Solutions to Stochastic Thin-Film Equations.” SIAM Journal on Mathematical Analysis, vol. 50, no. 1, Society for Industrial and Applied Mathematics , 2018, pp. 411–55, doi:10.1137/16M1098796. short: J.L. Fischer, G. Grün, SIAM Journal on Mathematical Analysis 50 (2018) 411–455. date_created: 2018-12-11T11:46:17Z date_published: 2018-01-30T00:00:00Z date_updated: 2023-09-11T13:59:22Z day: '30' ddc: - '510' department: - _id: JuFi doi: 10.1137/16M1098796 external_id: isi: - '000426630900015' file: - access_level: open_access checksum: 89a8eae7c52bb356c04f52b44bff4b5a content_type: application/pdf creator: dernst date_created: 2019-11-07T12:20:25Z date_updated: 2020-07-14T12:46:22Z file_id: '6992' file_name: 2018_SIAM_Fischer.pdf file_size: 557338 relation: main_file file_date_updated: 2020-07-14T12:46:22Z has_accepted_license: '1' intvolume: ' 50' isi: 1 issue: '1' language: - iso: eng month: '01' oa: 1 oa_version: Published Version page: 411 - 455 publication: SIAM Journal on Mathematical Analysis publication_status: published publisher: 'Society for Industrial and Applied Mathematics ' publist_id: '7425' quality_controlled: '1' scopus_import: '1' status: public title: Existence of positive solutions to stochastic thin-film equations type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 50 year: '2018' ... --- _id: '9813' abstract: - lang: eng text: 'File S1 contains figures that clarify the following features: (i) effect of population size on the average number/frequency of SI classes, (ii) changes in the minimal completeness deficit in time for a single class, and (iii) diversification diagrams for all studied pathways, including the summary figure for k = 8. File S2 contains the code required for a stochastic simulation of the SLF system with an example. This file also includes the output in the form of figures and tables.' article_processing_charge: No author: - first_name: Katarína full_name: Bod'ová, Katarína id: 2BA24EA0-F248-11E8-B48F-1D18A9856A87 last_name: Bod'ová orcid: 0000-0002-7214-0171 - first_name: Tadeas full_name: Priklopil, Tadeas id: 3C869AA0-F248-11E8-B48F-1D18A9856A87 last_name: Priklopil - first_name: David full_name: Field, David id: 419049E2-F248-11E8-B48F-1D18A9856A87 last_name: Field orcid: 0000-0002-4014-8478 - first_name: Nicholas H full_name: Barton, Nicholas H id: 4880FE40-F248-11E8-B48F-1D18A9856A87 last_name: Barton orcid: 0000-0002-8548-5240 - first_name: Melinda full_name: Pickup, Melinda id: 2C78037E-F248-11E8-B48F-1D18A9856A87 last_name: Pickup orcid: 0000-0001-6118-0541 citation: ama: Bodova K, Priklopil T, Field D, Barton NH, Pickup M. Supplemental material for Bodova et al., 2018. 2018. doi:10.25386/genetics.6148304.v1 apa: Bodova, K., Priklopil, T., Field, D., Barton, N. H., & Pickup, M. (2018). Supplemental material for Bodova et al., 2018. Genetics Society of America. https://doi.org/10.25386/genetics.6148304.v1 chicago: Bodova, Katarina, Tadeas Priklopil, David Field, Nicholas H Barton, and Melinda Pickup. “Supplemental Material for Bodova et Al., 2018.” Genetics Society of America, 2018. https://doi.org/10.25386/genetics.6148304.v1. ieee: K. Bodova, T. Priklopil, D. Field, N. H. Barton, and M. Pickup, “Supplemental material for Bodova et al., 2018.” Genetics Society of America, 2018. ista: Bodova K, Priklopil T, Field D, Barton NH, Pickup M. 2018. Supplemental material for Bodova et al., 2018, Genetics Society of America, 10.25386/genetics.6148304.v1. mla: Bodova, Katarina, et al. Supplemental Material for Bodova et Al., 2018. Genetics Society of America, 2018, doi:10.25386/genetics.6148304.v1. short: K. Bodova, T. Priklopil, D. Field, N.H. Barton, M. Pickup, (2018). date_created: 2021-08-06T13:04:32Z date_published: 2018-04-30T00:00:00Z date_updated: 2023-09-11T13:57:42Z day: '30' department: - _id: NiBa - _id: GaTk doi: 10.25386/genetics.6148304.v1 main_file_link: - open_access: '1' url: https://doi.org/10.25386/genetics.6148304.v1 month: '04' oa: 1 oa_version: Published Version publisher: Genetics Society of America related_material: record: - id: '316' relation: used_in_publication status: public status: public title: Supplemental material for Bodova et al., 2018 type: research_data_reference user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf year: '2018' ... --- _id: '5780' abstract: - lang: eng text: Bioluminescence is found across the entire tree of life, conferring a spectacular set of visually oriented functions from attracting mates to scaring off predators. Half a dozen different luciferins, molecules that emit light when enzymatically oxidized, are known. However, just one biochemical pathway for luciferin biosynthesis has been described in full, which is found only in bacteria. Here, we report identification of the fungal luciferase and three other key enzymes that together form the biosynthetic cycle of the fungal luciferin from caffeic acid, a simple and widespread metabolite. Introduction of the identified genes into the genome of the yeast Pichia pastoris along with caffeic acid biosynthesis genes resulted in a strain that is autoluminescent in standard media. We analyzed evolution of the enzymes of the luciferin biosynthesis cycle and found that fungal bioluminescence emerged through a series of events that included two independent gene duplications. The retention of the duplicated enzymes of the luciferin pathway in nonluminescent fungi shows that the gene duplication was followed by functional sequence divergence of enzymes of at least one gene in the biosynthetic pathway and suggests that the evolution of fungal bioluminescence proceeded through several closely related stepping stone nonluminescent biochemical reactions with adaptive roles. The availability of a complete eukaryotic luciferin biosynthesis pathway provides several applications in biomedicine and bioengineering. article_processing_charge: No author: - first_name: Alexey A. full_name: Kotlobay, Alexey A. last_name: Kotlobay - first_name: Karen full_name: Sarkisyan, Karen id: 39A7BF80-F248-11E8-B48F-1D18A9856A87 last_name: Sarkisyan orcid: 0000-0002-5375-6341 - first_name: Yuliana A. full_name: Mokrushina, Yuliana A. last_name: Mokrushina - first_name: Marina full_name: Marcet-Houben, Marina last_name: Marcet-Houben - first_name: Ekaterina O. full_name: Serebrovskaya, Ekaterina O. last_name: Serebrovskaya - first_name: Nadezhda M. full_name: Markina, Nadezhda M. last_name: Markina - first_name: Louisa full_name: Gonzalez Somermeyer, Louisa id: 4720D23C-F248-11E8-B48F-1D18A9856A87 last_name: Gonzalez Somermeyer orcid: 0000-0001-9139-5383 - first_name: Andrey Y. full_name: Gorokhovatsky, Andrey Y. last_name: Gorokhovatsky - first_name: Andrey full_name: Vvedensky, Andrey last_name: Vvedensky - first_name: Konstantin V. full_name: Purtov, Konstantin V. last_name: Purtov - first_name: Valentin N. full_name: Petushkov, Valentin N. last_name: Petushkov - first_name: Natalja S. full_name: Rodionova, Natalja S. last_name: Rodionova - first_name: Tatiana V. full_name: Chepurnyh, Tatiana V. last_name: Chepurnyh - first_name: Liliia full_name: Fakhranurova, Liliia last_name: Fakhranurova - first_name: Elena B. full_name: Guglya, Elena B. last_name: Guglya - first_name: Rustam full_name: Ziganshin, Rustam last_name: Ziganshin - first_name: Aleksandra S. full_name: Tsarkova, Aleksandra S. last_name: Tsarkova - first_name: Zinaida M. full_name: Kaskova, Zinaida M. last_name: Kaskova - first_name: Victoria full_name: Shender, Victoria last_name: Shender - first_name: Maxim full_name: Abakumov, Maxim last_name: Abakumov - first_name: Tatiana O. full_name: Abakumova, Tatiana O. last_name: Abakumova - first_name: Inna S. full_name: Povolotskaya, Inna S. last_name: Povolotskaya - first_name: Fedor M. full_name: Eroshkin, Fedor M. last_name: Eroshkin - first_name: Andrey G. full_name: Zaraisky, Andrey G. last_name: Zaraisky - first_name: Alexander S. full_name: Mishin, Alexander S. last_name: Mishin - first_name: Sergey V. full_name: Dolgov, Sergey V. last_name: Dolgov - first_name: Tatiana Y. full_name: Mitiouchkina, Tatiana Y. last_name: Mitiouchkina - first_name: Eugene P. full_name: Kopantzev, Eugene P. last_name: Kopantzev - first_name: Hans E. full_name: Waldenmaier, Hans E. last_name: Waldenmaier - first_name: Anderson G. full_name: Oliveira, Anderson G. last_name: Oliveira - first_name: Yuichi full_name: Oba, Yuichi last_name: Oba - first_name: Ekaterina full_name: Barsova, Ekaterina last_name: Barsova - first_name: Ekaterina A. full_name: Bogdanova, Ekaterina A. last_name: Bogdanova - first_name: Toni full_name: Gabaldón, Toni last_name: Gabaldón - first_name: Cassius V. full_name: Stevani, Cassius V. last_name: Stevani - first_name: Sergey full_name: Lukyanov, Sergey last_name: Lukyanov - first_name: Ivan V. full_name: Smirnov, Ivan V. last_name: Smirnov - first_name: Josef I. full_name: Gitelson, Josef I. last_name: Gitelson - first_name: Fyodor full_name: Kondrashov, Fyodor id: 44FDEF62-F248-11E8-B48F-1D18A9856A87 last_name: Kondrashov orcid: 0000-0001-8243-4694 - first_name: Ilia V. full_name: Yampolsky, Ilia V. last_name: Yampolsky citation: ama: Kotlobay AA, Sarkisyan K, Mokrushina YA, et al. Genetically encodable bioluminescent system from fungi. Proceedings of the National Academy of Sciences of the United States of America. 2018;115(50):12728-12732. doi:10.1073/pnas.1803615115 apa: Kotlobay, A. A., Sarkisyan, K., Mokrushina, Y. A., Marcet-Houben, M., Serebrovskaya, E. O., Markina, N. M., … Yampolsky, I. V. (2018). Genetically encodable bioluminescent system from fungi. Proceedings of the National Academy of Sciences of the United States of America. National Academy of Sciences. https://doi.org/10.1073/pnas.1803615115 chicago: Kotlobay, Alexey A., Karen Sarkisyan, Yuliana A. Mokrushina, Marina Marcet-Houben, Ekaterina O. Serebrovskaya, Nadezhda M. Markina, Louisa Gonzalez Somermeyer, et al. “Genetically Encodable Bioluminescent System from Fungi.” Proceedings of the National Academy of Sciences of the United States of America. National Academy of Sciences, 2018. https://doi.org/10.1073/pnas.1803615115. ieee: A. A. Kotlobay et al., “Genetically encodable bioluminescent system from fungi,” Proceedings of the National Academy of Sciences of the United States of America, vol. 115, no. 50. National Academy of Sciences, pp. 12728–12732, 2018. ista: Kotlobay AA, Sarkisyan K, Mokrushina YA, Marcet-Houben M, Serebrovskaya EO, Markina NM, Gonzalez Somermeyer L, Gorokhovatsky AY, Vvedensky A, Purtov KV, Petushkov VN, Rodionova NS, Chepurnyh TV, Fakhranurova L, Guglya EB, Ziganshin R, Tsarkova AS, Kaskova ZM, Shender V, Abakumov M, Abakumova TO, Povolotskaya IS, Eroshkin FM, Zaraisky AG, Mishin AS, Dolgov SV, Mitiouchkina TY, Kopantzev EP, Waldenmaier HE, Oliveira AG, Oba Y, Barsova E, Bogdanova EA, Gabaldón T, Stevani CV, Lukyanov S, Smirnov IV, Gitelson JI, Kondrashov F, Yampolsky IV. 2018. Genetically encodable bioluminescent system from fungi. Proceedings of the National Academy of Sciences of the United States of America. 115(50), 12728–12732. mla: Kotlobay, Alexey A., et al. “Genetically Encodable Bioluminescent System from Fungi.” Proceedings of the National Academy of Sciences of the United States of America, vol. 115, no. 50, National Academy of Sciences, 2018, pp. 12728–32, doi:10.1073/pnas.1803615115. short: A.A. Kotlobay, K. Sarkisyan, Y.A. Mokrushina, M. Marcet-Houben, E.O. Serebrovskaya, N.M. Markina, L. Gonzalez Somermeyer, A.Y. Gorokhovatsky, A. Vvedensky, K.V. Purtov, V.N. Petushkov, N.S. Rodionova, T.V. Chepurnyh, L. Fakhranurova, E.B. Guglya, R. Ziganshin, A.S. Tsarkova, Z.M. Kaskova, V. Shender, M. Abakumov, T.O. Abakumova, I.S. Povolotskaya, F.M. Eroshkin, A.G. Zaraisky, A.S. Mishin, S.V. Dolgov, T.Y. Mitiouchkina, E.P. Kopantzev, H.E. Waldenmaier, A.G. Oliveira, Y. Oba, E. Barsova, E.A. Bogdanova, T. Gabaldón, C.V. Stevani, S. Lukyanov, I.V. Smirnov, J.I. Gitelson, F. Kondrashov, I.V. Yampolsky, Proceedings of the National Academy of Sciences of the United States of America 115 (2018) 12728–12732. date_created: 2018-12-23T22:59:18Z date_published: 2018-12-11T00:00:00Z date_updated: 2023-09-11T14:04:05Z day: '11' ddc: - '580' department: - _id: FyKo doi: 10.1073/pnas.1803615115 external_id: isi: - '000452866000068' file: - access_level: open_access checksum: 46b2c12185eb2ddb598f4c7b4bd267bf content_type: application/pdf creator: dernst date_created: 2019-02-05T15:21:40Z date_updated: 2020-07-14T12:47:11Z file_id: '5926' file_name: 2018_PNAS_Kotlobay.pdf file_size: 1271988 relation: main_file file_date_updated: 2020-07-14T12:47:11Z has_accepted_license: '1' intvolume: ' 115' isi: 1 issue: '50' language: - iso: eng license: https://creativecommons.org/licenses/by-nc-nd/4.0/ month: '12' oa: 1 oa_version: Published Version page: 12728-12732 publication: Proceedings of the National Academy of Sciences of the United States of America publication_identifier: issn: - '00278424' publication_status: published publisher: National Academy of Sciences quality_controlled: '1' scopus_import: '1' status: public title: Genetically encodable bioluminescent system from fungi tmp: image: /images/cc_by_nc_nd.png legal_code_url: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode name: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) short: CC BY-NC-ND (4.0) type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 115 year: '2018' ... --- _id: '428' abstract: - lang: eng text: The plant hormone gibberellic acid (GA) is a crucial regulator of growth and development. The main paradigm of GA signaling puts forward transcriptional regulation via the degradation of DELLA transcriptional repressors. GA has also been shown to regulate tropic responses by modulation of the plasma membrane incidence of PIN auxin transporters by an unclear mechanism. Here we uncovered the cellular and molecular mechanisms by which GA redirects protein trafficking and thus regulates cell surface functionality. Photoconvertible reporters revealed that GA balances the protein traffic between the vacuole degradation route and recycling back to the cell surface. Low GA levels promote vacuolar delivery and degradation of multiple cargos, including PIN proteins, whereas high GA levels promote their recycling to the plasma membrane. This GA effect requires components of the retromer complex, such as Sorting Nexin 1 (SNX1) and its interacting, microtubule (MT)-associated protein, the Cytoplasmic Linker-Associated Protein (CLASP1). Accordingly, GA regulates the subcellular distribution of SNX1 and CLASP1, and the intact MT cytoskeleton is essential for the GA effect on trafficking. This GA cellular action occurs through DELLA proteins that regulate the MT and retromer presumably via their interaction partners Prefoldins (PFDs). Our study identified a branching of the GA signaling pathway at the level of DELLA proteins, which, in parallel to regulating transcription, also target by a nontranscriptional mechanism the retromer complex acting at the intersection of the degradation and recycling trafficking routes. By this mechanism, GA can redirect receptors and transporters to the cell surface, thus coregulating multiple processes, including PIN-dependent auxin fluxes during tropic responses. acknowledgement: "We gratefully acknowledge M. Blázquez (Instituto de Biología Molecular y Celular de Plantas), M. Fendrych, C. Cuesta Moliner (Institute of Science and Technology Austria), M. Vanstraelen, M. Nowack (Center for Plant Systems Biology, Ghent), C. Luschnig (Universitat fur Bodenkultur Wien, Vienna), S. Simon (Central European Institute of Technology, Brno), C. Sommerville (Carnegie Institution for Science), and Y. Gu (Penn State University) for making available the materials used in this study;\r\n...funding from the European Research Council (ERC) under the European Union’s Seventh Framework Programme (FP7/2007-2013)/ERC Grant Agreement 282300.\r\nCC BY NC ND" article_processing_charge: No author: - first_name: Yuliya full_name: Salanenka, Yuliya id: 46DAAE7E-F248-11E8-B48F-1D18A9856A87 last_name: Salanenka - first_name: Inge full_name: Verstraeten, Inge id: 362BF7FE-F248-11E8-B48F-1D18A9856A87 last_name: Verstraeten orcid: 0000-0001-7241-2328 - first_name: Christian full_name: Löfke, Christian last_name: Löfke - first_name: Kaori full_name: Tabata, Kaori id: 7DAAEDA4-02D0-11E9-B11A-A5A4D7DFFFD0 last_name: Tabata - first_name: Satoshi full_name: Naramoto, Satoshi last_name: Naramoto - first_name: Matous full_name: Glanc, Matous id: 1AE1EA24-02D0-11E9-9BAA-DAF4881429F2 last_name: Glanc orcid: 0000-0003-0619-7783 - first_name: Jirí full_name: Friml, Jirí id: 4159519E-F248-11E8-B48F-1D18A9856A87 last_name: Friml orcid: 0000-0002-8302-7596 citation: ama: Salanenka Y, Verstraeten I, Löfke C, et al. Gibberellin DELLA signaling targets the retromer complex to redirect protein trafficking to the plasma membrane. PNAS. 2018;115(14):3716-3721. doi:10.1073/pnas.1721760115 apa: Salanenka, Y., Verstraeten, I., Löfke, C., Tabata, K., Naramoto, S., Glanc, M., & Friml, J. (2018). Gibberellin DELLA signaling targets the retromer complex to redirect protein trafficking to the plasma membrane. PNAS. National Academy of Sciences. https://doi.org/10.1073/pnas.1721760115 chicago: Salanenka, Yuliya, Inge Verstraeten, Christian Löfke, Kaori Tabata, Satoshi Naramoto, Matous Glanc, and Jiří Friml. “Gibberellin DELLA Signaling Targets the Retromer Complex to Redirect Protein Trafficking to the Plasma Membrane.” PNAS. National Academy of Sciences, 2018. https://doi.org/10.1073/pnas.1721760115. ieee: Y. Salanenka et al., “Gibberellin DELLA signaling targets the retromer complex to redirect protein trafficking to the plasma membrane,” PNAS, vol. 115, no. 14. National Academy of Sciences, pp. 3716–3721, 2018. ista: Salanenka Y, Verstraeten I, Löfke C, Tabata K, Naramoto S, Glanc M, Friml J. 2018. Gibberellin DELLA signaling targets the retromer complex to redirect protein trafficking to the plasma membrane. PNAS. 115(14), 3716–3721. mla: Salanenka, Yuliya, et al. “Gibberellin DELLA Signaling Targets the Retromer Complex to Redirect Protein Trafficking to the Plasma Membrane.” PNAS, vol. 115, no. 14, National Academy of Sciences, 2018, pp. 3716–21, doi:10.1073/pnas.1721760115. short: Y. Salanenka, I. Verstraeten, C. Löfke, K. Tabata, S. Naramoto, M. Glanc, J. Friml, PNAS 115 (2018) 3716–3721. date_created: 2018-12-11T11:46:25Z date_published: 2018-04-03T00:00:00Z date_updated: 2023-09-11T14:06:34Z day: '03' ddc: - '580' department: - _id: JiFr doi: 10.1073/pnas.1721760115 ec_funded: 1 external_id: isi: - '000429012500073' file: - access_level: open_access checksum: 1fcf7223fb8f99559cfa80bd6f24ce44 content_type: application/pdf creator: dernst date_created: 2018-12-17T12:30:14Z date_updated: 2020-07-14T12:46:26Z file_id: '5700' file_name: 2018_PNAS_Salanenka.pdf file_size: 1924101 relation: main_file file_date_updated: 2020-07-14T12:46:26Z has_accepted_license: '1' intvolume: ' 115' isi: 1 issue: '14' language: - iso: eng month: '04' oa: 1 oa_version: Published Version page: ' 3716 - 3721' project: - _id: 25716A02-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '282300' name: Polarity and subcellular dynamics in plants publication: PNAS publication_status: published publisher: National Academy of Sciences publist_id: '7395' quality_controlled: '1' scopus_import: '1' status: public title: Gibberellin DELLA signaling targets the retromer complex to redirect protein trafficking to the plasma membrane tmp: image: /images/cc_by_nc_nd.png legal_code_url: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode name: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) short: CC BY-NC-ND (4.0) type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 115 year: '2018' ... --- _id: '62' abstract: - lang: eng text: Imaging is a dominant strategy for data collection in neuroscience, yielding stacks of images that often scale to gigabytes of data for a single experiment. Machine learning algorithms from computer vision can serve as a pair of virtual eyes that tirelessly processes these images, automatically detecting and identifying microstructures. Unlike learning methods, our Flexible Learning-free Reconstruction of Imaged Neural volumes (FLoRIN) pipeline exploits structure-specific contextual clues and requires no training. This approach generalizes across different modalities, including serially-sectioned scanning electron microscopy (sSEM) of genetically labeled and contrast enhanced processes, spectral confocal reflectance (SCoRe) microscopy, and high-energy synchrotron X-ray microtomography (μCT) of large tissue volumes. We deploy the FLoRIN pipeline on newly published and novel mouse datasets, demonstrating the high biological fidelity of the pipeline’s reconstructions. FLoRIN reconstructions are of sufficient quality for preliminary biological study, for example examining the distribution and morphology of cells or extracting single axons from functional data. Compared to existing supervised learning methods, FLoRIN is one to two orders of magnitude faster and produces high-quality reconstructions that are tolerant to noise and artifacts, as is shown qualitatively and quantitatively. acknowledgement: 'Equipment was generously donated by the NVIDIA Corporation, and made available by the National Science Foundation (NSF) through grant #CNS-1629914. This research used resources of the Argonne Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC02-06CH11357.' article_number: '14247' article_processing_charge: No article_type: original author: - first_name: Ali full_name: Shabazi, Ali last_name: Shabazi - first_name: Jeffery full_name: Kinnison, Jeffery last_name: Kinnison - first_name: Rafael full_name: Vescovi, Rafael last_name: Vescovi - first_name: Ming full_name: Du, Ming last_name: Du - first_name: Robert full_name: Hill, Robert last_name: Hill - first_name: Maximilian A full_name: Jösch, Maximilian A id: 2BD278E6-F248-11E8-B48F-1D18A9856A87 last_name: Jösch orcid: 0000-0002-3937-1330 - first_name: Marc full_name: Takeno, Marc last_name: Takeno - first_name: Hongkui full_name: Zeng, Hongkui last_name: Zeng - first_name: Nuno full_name: Da Costa, Nuno last_name: Da Costa - first_name: Jaime full_name: Grutzendler, Jaime last_name: Grutzendler - first_name: Narayanan full_name: Kasthuri, Narayanan last_name: Kasthuri - first_name: Walter full_name: Scheirer, Walter last_name: Scheirer citation: ama: Shabazi A, Kinnison J, Vescovi R, et al. Flexible learning-free segmentation and reconstruction of neural volumes. Scientific Reports. 2018;8(1). doi:10.1038/s41598-018-32628-3 apa: Shabazi, A., Kinnison, J., Vescovi, R., Du, M., Hill, R., Jösch, M. A., … Scheirer, W. (2018). Flexible learning-free segmentation and reconstruction of neural volumes. Scientific Reports. Nature Publishing Group. https://doi.org/10.1038/s41598-018-32628-3 chicago: Shabazi, Ali, Jeffery Kinnison, Rafael Vescovi, Ming Du, Robert Hill, Maximilian A Jösch, Marc Takeno, et al. “Flexible Learning-Free Segmentation and Reconstruction of Neural Volumes.” Scientific Reports. Nature Publishing Group, 2018. https://doi.org/10.1038/s41598-018-32628-3. ieee: A. Shabazi et al., “Flexible learning-free segmentation and reconstruction of neural volumes,” Scientific Reports, vol. 8, no. 1. Nature Publishing Group, 2018. ista: Shabazi A, Kinnison J, Vescovi R, Du M, Hill R, Jösch MA, Takeno M, Zeng H, Da Costa N, Grutzendler J, Kasthuri N, Scheirer W. 2018. Flexible learning-free segmentation and reconstruction of neural volumes. Scientific Reports. 8(1), 14247. mla: Shabazi, Ali, et al. “Flexible Learning-Free Segmentation and Reconstruction of Neural Volumes.” Scientific Reports, vol. 8, no. 1, 14247, Nature Publishing Group, 2018, doi:10.1038/s41598-018-32628-3. short: A. Shabazi, J. Kinnison, R. Vescovi, M. Du, R. Hill, M.A. Jösch, M. Takeno, H. Zeng, N. Da Costa, J. Grutzendler, N. Kasthuri, W. Scheirer, Scientific Reports 8 (2018). date_created: 2018-12-11T11:44:25Z date_published: 2018-09-24T00:00:00Z date_updated: 2023-09-11T14:02:55Z day: '24' ddc: - '570' department: - _id: MaJö doi: 10.1038/s41598-018-32628-3 external_id: isi: - '000445336600015' file: - access_level: open_access checksum: 1a14ae0666b82fbaa04bef110e3f6bf2 content_type: application/pdf creator: dernst date_created: 2018-12-17T12:22:24Z date_updated: 2020-07-14T12:47:24Z file_id: '5699' file_name: 2018_ScientificReports_Shahbazi.pdf file_size: 4141645 relation: main_file file_date_updated: 2020-07-14T12:47:24Z has_accepted_license: '1' intvolume: ' 8' isi: 1 issue: '1' language: - iso: eng license: https://creativecommons.org/licenses/by/4.0/ month: '09' oa: 1 oa_version: Published Version publication: Scientific Reports publication_status: published publisher: Nature Publishing Group publist_id: '7992' quality_controlled: '1' related_material: link: - relation: erratum url: http://doi.org/10.1038/s41598-018-36220-7 scopus_import: '1' status: public title: Flexible learning-free segmentation and reconstruction of neural volumes tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 8 year: '2018' ...