61 research outputs found
Targeting PFKFB3 radiosensitizes cancer cells and suppresses homologous recombination
The glycolytic PFKFB3 enzyme is widely overexpressed in cancer cells and an emerging anti-cancer target. Here, we identify PFKFB3 as a critical factor in homologous recombination (HR) repair of DNA double-strand breaks. PFKFB3 rapidly relocates into ionizing radiation (IR)-induced nuclear foci in an MRN-ATM-ÎłH2AX-MDC1-dependent manner and co-localizes with DNA damage and HR repair proteins. PFKFB3 relocalization is critical for recruitment of HR proteins, HR activity, and cell survival upon IR. We develop KAN0438757, a small molecule inhibitor that potently targets PFKFB3. Pharmacological PFKFB3 inhibition impairs recruitment of ribonucleotide reductase M2 and deoxynucleotide incorporation upon DNA repair, and reduces dNTP levels. Importantly, KAN0438757 induces radiosensitization in transformed cells while leaving non-transformed cells unaffected. In summary, we identify a key role for PFKFB3 enzymatic activity in HR repair and present KAN0438757, a selective PFKFB3 inhibitor that could potentially be used as a strategy for the treatment of cancer
Prospects for e+e- physics at Frascati between the phi and the psi
We present a detailed study, done in the framework of the INFN 2006 Roadmap,
of the prospects for e+e- physics at the Frascati National Laboratories. The
physics case for an e+e- collider running at high luminosity at the phi
resonance energy and also reaching a maximum center of mass energy of 2.5 GeV
is discussed, together with the specific aspects of a very high luminosity
tau-charm factory. Subjects connected to Kaon decay physics are not discussed
here, being part of another INFN Roadmap working group. The significance of the
project and the impact on INFN are also discussed. All the documentation
related to the activities of the working group can be found in
http://www.roma1.infn.it/people/bini/roadmap.html.Comment: INFN Roadmap Report: 86 pages, 25 figures, 9 table
Specific food preferences of older adults with a poor appetite. A forced-choice test conducted in various care settings
A poor appetite in older adults is an important determinant of reduced food intake and undernutrition. Food preferences may influence food intake. The aim of this study was to investigate food preferences of older adults with a poor appetite and compare these with preferences of older adults with a good appetite. Older adults (nâ=â349, aged 65â101 years) in nursing/residential care homes, hospitals or at home receiving home care participated in a computer-based forced-choice food preference assessment. Self-reported appetite in the past week was classified as âgoodâ or âpoorâ using a validated instrument. Food preferences were determined by counting the relative frequency of choices for food images according to 11 dichotomous categories: high/low 1) protein; 2) fat; 3) carbohydrates; 4) fiber; 5) variation; and 6) animal/vegetarian proteins; 7) sweet/savory taste; 8) solid/liquid texture; 9) dairy/non-dairy; with/without 10) sauce or 11) color variation. Specific food preferences in participants with a poor appetite were identified by one-sample t-tests comparing frequencies to the expected value of 48. Preference differences between those with a good and a poor appetite were analyzed using GLM adjusting for confounders. The results showed that older adults with a poor appetite (nâ=â113; 32.4%) preferred variation (51.6 vs. 48, Pâ<â0.001), color variation (55.9 vs. 48, Pâ<â0.01), non-dairy (53.0 vs. 48, Pâ<â0.001), high-fiber (51.8 vs. 48, Pâ<â0.05), and solid texture (53.5 vs. 48, Pâ<â0.05). Participants with a poor appetite had a higher frequency score for variation than participants with a good appetite (51.6 vs. 48.5, Pâ<â0.001). In conclusion, older adults with a poor appetite may have specific food preferences. Their preference for variation differs from those with a good appetite. These results may be used to develop meals that are preferred by older adults with poor appetite in order to increase food intake and prevent undernutrition
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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-WĂŒrttemberg (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
Recommended from our members
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-WĂŒrttemberg (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
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