Fostering accessible online education using Galaxy as an e-learning platform

The COVID-19 pandemic is shifting teaching to an online setting all over the world. The Galaxy framework facilitates the online learning process and makes it accessible by providing a library of high-quality community-curated training materials, enabling easy access to data and tools, and facilitates sharing achievements and progress between students and instructors. By combining Galaxy with robust communication channels, effective instruction can be designed inclusively, regardless of the students’ environments

The Galaxy platform for accessible, reproducible, and collaborative data analyses: 2024 update

YesGalaxy (https://galaxyproject.org) is deployed globally, predominantly through free-to-use services, supporting user-driven research that broadens in scope each year. Users are attracted to public Galaxy services by platform stability, tool and reference dataset diversity, training, support and integration, which enables complex, reproducible, shareable data analysis. Applying the principles of user experience design (UXD), has driven improvements in accessibility, tool discoverability through Galaxy Labs/subdomains, and a redesigned Galaxy ToolShed. Galaxy tool capabilities are progressing in two strategic directions: integrating general purpose graphical processing units (GPGPU) access for cutting-edge methods, and licensed tool support. Engagement with global research consortia is being increased by developing more workflows in Galaxy and by resourcing the public Galaxy services to run them. The Galaxy Training Network (GTN) portfolio has grown in both size, and accessibility, through learning paths and direct integration with Galaxy tools that feature in training courses. Code development continues in line with the Galaxy Project roadmap, with improvements to job scheduling and the user interface. Environmental impact assessment is also helping engage users and developers, reminding them of their role in sustainability, by displaying estimated CO2 emissions generated by each Galaxy job.NIH [U41 HG006620, U24 HG010263, U24 CA231877, U01 CA253481]; US National Science Foundation [1661497, 1758800, 2216612]; computational resources are provided by the Advanced Cyberinfrastructure Coordination Ecosystem (ACCESS-CI), Texas Advanced Computing Center, and the JetStream2 scientific cloud. Funding for open access charge: NIH. ELIXIR IS and Travel grants; EU Horizon Europe [HORIZON-INFRA-2021-EOSC-01-04, 101057388]; EU Horizon Europe under the Biodiversity, Circular Economy and Environment program (REA.B.3, BGE 101059492); German Federal Ministry of Education and Research, BMBF [031 A538A de.NBI-RBC]; Ministry of Science, Research and the Arts Baden-Württemberg (MWK) within the framework of LIBIS/de.NBI Freiburg. Galaxy Australia is supported by the Australian BioCommons which is funded through Australian Government NCRIS investments from Bioplatforms Australia and the Australian Research Data Commons, as well as investment from the Queensland Government RICF program

The Galaxy platform for accessible, reproducible, and collaborative data analyses: 2024 update

YesGalaxy (https://galaxyproject.org) is deployed globally, predominantly through free-to-use services, supporting user-driven research that broadens in scope each year. Users are attracted to public Galaxy services by platform stability, tool and reference dataset diversity, training, support and integration, which enables complex, reproducible, shareable data analysis. Applying the principles of user experience design (UXD), has driven improvements in accessibility, tool discoverability through Galaxy Labs/subdomains, and a redesigned Galaxy ToolShed. Galaxy tool capabilities are progressing in two strategic directions: integrating general purpose graphical processing units (GPGPU) access for cutting-edge methods, and licensed tool support. Engagement with global research consortia is being increased by developing more workflows in Galaxy and by resourcing the public Galaxy services to run them. The Galaxy Training Network (GTN) portfolio has grown in both size, and accessibility, through learning paths and direct integration with Galaxy tools that feature in training courses. Code development continues in line with the Galaxy Project roadmap, with improvements to job scheduling and the user interface. Environmental impact assessment is also helping engage users and developers, reminding them of their role in sustainability, by displaying estimated CO2 emissions generated by each Galaxy job.NIH [U41 HG006620, U24 HG010263, U24 CA231877, U01 CA253481]; US National Science Foundation [1661497, 1758800, 2216612]; computational resources are provided by the Advanced Cyberinfrastructure Coordination Ecosystem (ACCESS-CI), Texas Advanced Computing Center, and the JetStream2 scientific cloud. Funding for open access charge: NIH. ELIXIR IS and Travel grants; EU Horizon Europe [HORIZON-INFRA-2021-EOSC-01-04, 101057388]; EU Horizon Europe under the Biodiversity, Circular Economy and Environment program (REA.B.3, BGE 101059492); German Federal Ministry of Education and Research, BMBF [031 A538A de.NBI-RBC]; Ministry of Science, Research and the Arts Baden-Württemberg (MWK) within the framework of LIBIS/de.NBI Freiburg. Galaxy Australia is supported by the Australian BioCommons which is funded through Australian Government NCRIS investments from Bioplatforms Australia and the Australian Research Data Commons, as well as investment from the Queensland Government RICF program.Please note, contributors are listed in alphabetical order

Proteome Profiling of Primary Pancreatic Ductal Adenocarcinomas Undergoing Additive Chemoradiation Link ALDH1A1 to Early Local Recurrence and Chemoradiation Resistance

Pancreatic ductal adenocarcinoma (PDAC) has a poor prognosis with frequent post-surgical local recurrence. The combination of adjuvant chemotherapy with radiotherapy is under consideration to achieve a prolonged progression-free survival (PFS). To date, few studies have determined the proteome profiles associated with response to adjuvant chemoradiation. We herein analyzed the proteomes of primary PDAC tumors subjected to additive chemoradiation after surgical resection and achieving short PFS (median 6 months) versus prolonged PFS (median 28 months). Proteomic analysis revealed the overexpression of Aldehyde Dehydrogenase 1 Family Member A1 (ALDH1A1) and Monoamine Oxidase A (MAOA) in the short PFS cohort, which were corroborated by immunohistochemistry. In vitro, specific inhibition of ALDH1A1 by A37 in combination with gemcitabine, radiation, and chemoradiation lowered cell viability and augmented cell death in MiaPaCa-2 and Panc 05.04 cells. ALDH1A1 silencing in both cell lines dampened cell proliferation, cell metabolism, and colony formation. In MiaPaCa-2 cells, ALDH1A1 silencing sensitized cells towards treatment with gemcitabine, radiation or chemoradiation. In Panc 05.04, increased cell death was observed upon gemcitabine treatment only. These findings are in line with previous studies that have suggested a role of ALDH1A1 chemoradiation resistance, e.g., in esophageal cancer. In summary, we present one of the first proteome studies to investigate the responsiveness of PDAC to chemoradiation and provide further evidence for a role of ALDH1A1 in therapy resistance

Spatially resolved silicon solar cell characterization using infrared imaging methods

We present a comprehensive overview over infrared imaging techniques for (electrical) silicon solar cell characterization. Recent method development in local series resistance imaging is reviewed in more detail and new results in local breakdown investigations on multicrystalline (mc) silicon solar cells are reported. We observe local junction breakdown sites on industrial mc-cells at reverse voltages as low as -7V and breakdown in great areas of the cell at voltages around -14V. As these breakdown sites (as well as local shunts) can cause hot spots which can damage the cell and the module, we also present an ultra-fast, simple and quantitative method for hot-spot detection. Typical measurement times in the order of 10 milliseconds are achieved