Literatura científica selecionada sobre o tema "Sucrose Non-Fermentable"
Crie uma referência precisa em APA, MLA, Chicago, Harvard, e outros estilos
Consulte a lista de atuais artigos, livros, teses, anais de congressos e outras fontes científicas relevantes para o tema "Sucrose Non-Fermentable".
Ao lado de cada fonte na lista de referências, há um botão "Adicionar à bibliografia". Clique e geraremos automaticamente a citação bibliográfica do trabalho escolhido no estilo de citação de que você precisa: APA, MLA, Harvard, Chicago, Vancouver, etc.
Você também pode baixar o texto completo da publicação científica em formato .pdf e ler o resumo do trabalho online se estiver presente nos metadados.
Artigos de revistas sobre o assunto "Sucrose Non-Fermentable"
Hargono, Hargono, Bakti Jos, Abdullah Abdullah e Teguh Riyanto. "Inhibition Effect of Ca2+ Ions on Sucrose Hydrolysis Using Invertase". Bulletin of Chemical Reaction Engineering & Catalysis 14, n.º 3 (1 de dezembro de 2019): 646. http://dx.doi.org/10.9767/bcrec.14.3.4437.646-653.
Texto completo da fonteBajaj, Anubha. "Exiguous and Scarce-SMARCB1 Deficient Medullary Renal Cell Carcinoma". Cell & Cellular Life Sciences Journal 8, n.º 2 (2023): 1–4. http://dx.doi.org/10.23880/cclsj-16000188.
Texto completo da fonteChoi, Sung Kyung, Myoung Jun Kim e Jueng Soo You. "SMARCB1 Acts as a Quiescent Gatekeeper for Cell Cycle and Immune Response in Human Cells". International Journal of Molecular Sciences 21, n.º 11 (1 de junho de 2020): 3969. http://dx.doi.org/10.3390/ijms21113969.
Texto completo da fonteRoberts, Michael, e J. Timothy Wright. "Food sugar substitutes: a brief review for dental clinicians". Journal of Clinical Pediatric Dentistry 27, n.º 1 (1 de setembro de 2003): 1–4. http://dx.doi.org/10.17796/jcpd.27.1.bl98u70371655hp8.
Texto completo da fonteDobrescu, Andreea Cristina, Henrique César Teixeira Veras, Cristiano Varrone e Jan Dines Knudsen. "Novel Propagation Strategy of Saccharomyces cerevisiae for Enhanced Xylose Metabolism during Fermentation on Softwood Hydrolysate". Fermentation 7, n.º 4 (29 de novembro de 2021): 288. http://dx.doi.org/10.3390/fermentation7040288.
Texto completo da fonteKakar, Smita, Xianyang Fang, Lucyna Lubkowska, Yan Ning Zhou, Gary X. Shaw, Yun-Xing Wang, Ding Jun Jin, Mikhail Kashlev e Xinhua Ji. "Allosteric Activation of Bacterial Swi2/Snf2 (Switch/Sucrose Non-fermentable) Protein RapA by RNA Polymerase". Journal of Biological Chemistry 290, n.º 39 (13 de agosto de 2015): 23656–69. http://dx.doi.org/10.1074/jbc.m114.618801.
Texto completo da fonteRoberts, Michael W., e J. Timothy Wright. "Nonnutritive, Low Caloric Substitutes for Food Sugars: Clinical Implications for Addressing the Incidence of Dental Caries and Overweight/Obesity". International Journal of Dentistry 2012 (2012): 1–8. http://dx.doi.org/10.1155/2012/625701.
Texto completo da fonteMoelich, Nadine, Nicoline Potgieter, Francien S. Botha, James Wesley-Smith e Candice Van Wyk. "The search for a healthy sugar substitute in aid to lower the incidence of Early Childhood Caries: a comparison of sucrose, xylitol, erythritol and stevia". South African Dental Journal 77, n.º 08 (23 de novembro de 2022): 465–71. http://dx.doi.org/10.17159/2519-0105/2022/v77no8a2.
Texto completo da fonteNguyen, Thinh T., Joanne G. A. Savory, Travis Brooke-Bisschop, Randy Ringuette, Tanya Foley, Bradley L. Hess, Kirk J. Mulatz, Laura Trinkle-Mulcahy e David Lohnes. "Cdx2 Regulates Gene Expression through Recruitment of Brg1-associated Switch-Sucrose Non-fermentable (SWI-SNF) Chromatin Remodeling Activity". Journal of Biological Chemistry 292, n.º 8 (12 de janeiro de 2017): 3389–99. http://dx.doi.org/10.1074/jbc.m116.752774.
Texto completo da fonteDel Savio, Elisa, e Roberta Maestro. "Beyond SMARCB1 Loss: Recent Insights into the Pathobiology of Epithelioid Sarcoma". Cells 11, n.º 17 (24 de agosto de 2022): 2626. http://dx.doi.org/10.3390/cells11172626.
Texto completo da fonteTeses / dissertações sobre o assunto "Sucrose Non-Fermentable"
Bretones, Santamarina Jorge. "Integrated multiomic analysis, synthetic lethality inference and network pharmacology to identify SWI/SNF subunit-specific pathway alterations and targetable vulnerabilities". Electronic Thesis or Diss., université Paris-Saclay, 2024. http://www.theses.fr/2024UPASL049.
Texto completo da fonteNowadays the cancer community agrees on the need for patient-tailored diagnostics and therapies, which calls for the design of translational studies combining experimental and statistical approaches. Current challenges include the validation of preclinical experimental models and their multi-omics profiling, along with the design of dedicated bioinformatics and mathematical pipelines (i.e. dimension reduction, multi-omics integration, mechanism-based digital twins) for identifying patient-specific optimal drug combinations.To address these challenges, we designed bioinformatics and statistical approaches to analyze various large-scale data types and integrate them to identify targetable vulnerabilities in cancer cell lines. We developed our pipeline in the context of alterations of the SWItch Sucrose Non-Fermentable (SWI/SNF) chromatin remodeling complex. SWI/SNF mutations occur in ~20% of all cancers, but such malignancies still lack efficient therapies. We leveraged a panel of HAP1 isogenic cell lines mutated for SWI/SNF subunits or other epigenetic enzymes for which transcriptomics, proteomics and drug screening data were available.We worked on four methodological axes, the first one being the design of an optimized pathway enrichment pipeline to detect pathways differentially activated in the mutants against the wild-type. We developed a pruning algorithm to reduce gene and pathway redundancy in the Reactome database and improve the interpretability of the results. We evidenced the bad performance of first-generation enrichment methods and proposed to combine the topology-based method ROntoTools with pre-ranked GSEA to increase enrichment performance .Secondly, we analyzed drug screens, processed drug-gene interaction databases to obtain genes and pathways targeted by effective drugs and integrated them with proteomics enrichment results to infer targetable vulnerabilities selectively harming mutant cell lines. The validation of potential targets was achieved using a novel method detecting synthetic lethality from transcriptomics and CRISPR data of independent cancer cell lines in DepMap, run for each studied epigenetic enzyme. Finally, to further inform multi-agent therapy optimization, we designed a first digital representation of targetable pathways for SMARCA4-mutated tumors by building a directed protein-protein interaction network connecting targets inferred from multi-omics HAP1 and DepMap CRISPR analyses. We used the OmniPath database to retrieve direct protein interactions and added the connecting neighboring genes with the Neko algorithm.These methodological developments were applied to the HAP1 panel datasets. Using our optimized enrichment pipeline, we identified Metabolism of proteins as the most frequently dysregulated pathway category in SWI/SNF-KO lines. Next, the drug screening analysis revealed cytotoxic and epigenetic drugs selectively targeting SWI/SNF mutants, including CBP/EP300 or mitochondrial respiration inhibitors, also identified as synthetic lethal by our Depmap CRISPR analysis. Importantly, we validated these findings in two independent isogenic cancer-relevant experimental models. The Depmap CRISPR analysis was also used in a separate project to identify synthetic lethal interactions in glioblastoma, which proved relevant for patient-derived cell lines and are being validated in dedicated drug screens.To sum up, we developed computational methods to integrate multi-omics expression data with drug screening and CRISPR assays and identified new vulnerabilities in SWI/SNF mutants which were experimentally revalidated. This study was limited to the identification of effective single agents. As a future direction, we propose to design mathematical models representing targetable protein networks using differential equations and their use in numerical optimization and machine learning procedures as a key tool to investigate concomitant druggable targets and personalize drug combinations
Capítulos de livros sobre o assunto "Sucrose Non-Fermentable"
Halfordl, N. G. "Molecular and biochemical analyses of plant Snfl-related protein kinases". In Protein Phosphorylation in Plants, 129–40. Oxford University PressOxford, 1996. http://dx.doi.org/10.1093/oso/9780198577775.003.0010.
Texto completo da fonte