Bibliografía

Descifrando los entresijos moleculares de la Dinámica Molecular a través de ASGARD

1. Rodríguez-Martínez A, Nelen J, Carmena-Bargueño M, Martínez-Cortés C, Luque I, Pérez-Sánchez H. ASGARD. A simple and automatic GROMACS tool to analyze Molecular Dynamic simulations [Internet]. ChemRxiv; 2023 [cited 2023 May 10]. Available from: https://chemrxiv.org/engage/chemrxiv/articledetails/6396f3ea0a8127664bde68a7
2. Abraham MJ, Murtola T, Schulz R, Páll S, Smith JC, Hess B, et al. GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX. 2015;1:19–25.
3. Hansson T, Oostenbrink WF. C. and van Gunsteren. Molecular dynamics simulations. Current Opinion in Structural Biology. 2002;12(2):190–6.
4. Ahmad B, Batool M, Ain Q ul, Kim MS, Choi S. Exploring the Binding Mechanism of PF-07321332 SARS-CoV-2 Protease Inhibitor through Molecular Dynamics and Binding Free Energy Simulations. 2021 Aug 24;22(17):9124.
5. Zhao Q, Ding L, Xia M, Huang X, Isobe K, Handa A, et al. Role of lysozyme on liquid egg white foaming properties: Interface behavior, physicochemical characteristics and protein structure. Food Hydrocolloids. 2021 Nov;120:106876.
6. Marzi M, Vakil MK, Bahmanyar M, Zarenezhad E. Paxlovid: Mechanism of Action, Synthesis, and In Silico Study. Wani TA, editor. BioMed Research International. 2022 Jul 7;2022:1–16.

Estudio de la plasticidad en interneuronas de un modelo de esquizofrenia de doble impacto

• Kahn, R. S., Sommer, I. E., Murray, R. M., Meyer-Lindenberg, A., Weinberger, D. R., Cannon, T. D., O'Donovan, M., Correll, C. U., Kane, J. M., van Os, J., & Insel, R. (2015). Schizophrenia. Nature Reviews. Disease Primers, 1(1)10.1038/nrdp.2015.67
• Andersen, S. L., & Pine, D. S. (2014). Neurobiology of Schizophrenia Onset. Current topics in behavioral neurosciences (pp. 267-295). Springer Berlin / Heidelberg. 10.1007/7854_2013_243
• Vincent, C., Gilabert-Juan, J., Gibel-Russo, R., Alvarez-Fischer, D., Krebs, M., Le Pen, G., Prochiantz, A., & Di Nardo, A. A. (2021). Non-cell autonomous OTX2 transcription factor regulates anxiety-related behavior in the mouse. Cold Spring Harbor Laboratory. 10.1101/710848.

• Gilabert-Juan, J., Belles, M., Saez, A. R., Carceller, H., Zamarbide-Fores, S., Moltó, M. D., & Nacher, J. (2013). A “double hit” murine model for schizophrenia shows alterations in the structure and neurochemistry of the medial prefrontal cortex and the hippocampus. Neurobiology of Disease, 59, 126-140. S0969-9961(13)00202-7 [pii]

¿Influye la música en el desarrollo de los tumores cereblales?

•   Apodaca, G. (2002). Modulation of membrane traffic by mechanical stimuli. American Journal of Physiology-renal Physiology, 282(2), F179-F190. https://doi.org/10.1152/ajprenal.2002.282.2.f179  Bhagat, M. S., Pugazhendhi, A., & Mungray, A. A. (2021). Effect of sound waves and inclination of membrane on the performance of the osmotic microbial fuel cell. Water-Energy Nexus, 4, 113-122. https://doi.org/10.1016/j.wen.2021.07.003
• Brand, A. H., & Perrimon, N. (1993). Targeted gene expression as a means of altering cell fates and generating dominant phenotypes. Development, 118(2), 401-415. https://doi.org/10.1242/dev.118.2.401
• Jeong, M., Shim, C., Lee, J., Kwon, H., Kim, Y., Lee, S. R., Byun, M., & Park, S. (2007). Plant gene responses to frequency-specific sound signals. Molecular Breeding, 21(2), 217-226. https://doi.org/10.1007/s11032-007-9122-x 
• T.Kanderi, V. & Gupta. (2023) Glioblastoma multiforme, National Center for Biotechnology
• Information. Available at: https://pubmed.ncbi.nlm.nih.gov/32644380/
• Kwak, D., T, C., Wang, C., Scholz, H., Danielsen, A. K., & Jensenius, A. R. (2022). Music for Cells? A Systematic Review of Studies Investigating the Effects of Audible Sound Played Through Speaker-Based Systems on Cell Cultures. Music & Science, 5, 205920432210809. https://doi.org/10.1177/20592043221080965
• Osswald, M., Jung, E., Sahm, F., Solecki, G., Venkataramani, V., Blaes, J., Weil, S., Horstmann, H.,
• Wiestler, B., Syed, M. H., Huang, L., Ratliff, M., Jazi, K. K., Kurz, F. T., Schmenger, T., Lemke, D., Gömmel, M., Pauli, M., Liao, Y., . . . Winkler, F. (2015). Brain tumour cells interconnect to a functional and resistant network. Nature, 528(7580), 93-98. https://doi.org/10.1038/nature16071
• Portela, M., Venkataramani, V., Casas-Tintó, S., Seco, E., Losada-Perez, M., & Winkler, F. (2019). Glioblastoma cells vampirize WNT from neurons and trigger a JNK/MMP signaling loop that enhances glioblastoma progression and neurodegeneration. PLOS Biology, 17(12), e3000545. https://doi.org/10.1371/journal.pbio.3000545

Silibinina(A): Un potencial inhibidor natural de la lipasa pancreática para tratar la obesidad

• Meier, J. J. Efficacy of Semaglutide in a Subcutaneous and an Oral Formulation. Endocrinol. (Lausanne). 2021, 12. https://doi.org/10.3389/FENDO.2021.645617/PDF.
• Wishart, D. S.; Feunang, Y. D.; Guo, A. C.; Lo, E. J.; Marcu, A.; Grant, J. R.; Sajed, T.; Johnson, D.; Li, C.; Sayeeda, Z.; Assempour, N.; Iynkkaran, I.; Liu, Y.; Maciejewski, A.; Gale, N.; Wilson, A.; Chin, L.; Cummings, R.; Le, D.; Pon, A.; Knox, C.; Wilson, M. DrugBank 5.0: A Major Update to the DrugBank Database for 2018 – PubMed. Nucleic Acids Res. 2017, 46 (D1), D1074–D1082. https://doi.org/10.1093/nar/gkx1037.
• Egloff, M.-P.; Marguet, F.; Buono, G.; Verger, R.; Cambillau, C.; Van Tilbeurgh, H. A Resolution Structure of the Pancreatic Lipase-Colipase Complex. Biochemistry 1995, 34, 2751–2762.
• Shaw, D. E. Desmond Molecular Dynamics System. New York, NY 2021

Plásticos en la dieta y su impacto en la microbiota y salud Humana

• Aguilera, M., Gómez-Vázquez, E., López-Moreno, A., Luque, G., Matilla-Serrano, A., Monteoliva Sánchez, M., Ortiz, P., Ruiz-Rodríguez, A., Suárez, A., & Torres-Sánchez, A. (2023). Microbiota intestinal y probióticos en nutrición. AVICAM.
• Ampatzoglou, A., Gruszecka-Kosowska, A., & Aguilera-Gómez, M. (2022). Microbiota analysis for risk assessment of xenobiotics: Toxicomicrobiomics, incorporating the gut microbiome in the risk assessment of xenobiotics and identifying beneficial components for One Health. EFSA Journal. European Food Safety Authority, 20. https://doi.org/10.2903/j.efsa.2022.e200915
• Balaguer-Trias, J., Deepika, D., Schuhmacher, M., & Kumar, V. (2022). Impact of Contaminants on Microbiota: Linking the Gut–Brain Axis with Neurotoxicity. International Journal of Environmental Research and Public Health, 19(3), Article 3.
• https://doi.org/10.3390/ijerph19031368
• Chen, M., Yang, Y., Baral, K., Fu, Y., Meng, Y., Zhang, Y., Sun, F., & Zhao, M. (2023). Relationship between bisphenol A and the cardiovascular disease metabolic risk factors in American adults: A population-based study. Chemosphere, 324, 138289. https://doi.org/10.1016/j.chemosphere.2023.138289
• Collins, S. L., & Patterson, A. D. (2020). The gut microbiome: An orchestrator of xenobiotic metabolism. Acta Pharmaceutica Sinica B, 10(1), 19-32. https://doi.org/10.1016/j.apsb.2019.12.001
• Della Rocca, Y., Traini, E. M., Diomede, F., Fonticoli, L., Trubiani, O., Paganelli, A., Pizzicannella, J., & Marconi, G. D. (2023). Current Evidence on Bisphenol A Exposure and the Molecular Mechanism Involved in Related Pathological Conditions. Pharmaceutics, 15(3), 908. https://doi.org/10.3390/pharmaceutics15030908
• Dogra, S. K., Doré, J., & Damak, S. (2020). Gut Microbiota Resilience: Definition, Link to Health and Strategies for Intervention. Frontiers in Microbiology, 11. https://www.frontiersin.org/articles/10.3389/fmicb.2020.572921
• Hong, X., Zhou, Y., Zhu, Z., Li, Y., Li, Z., Zhang, Y., Hu, X., Zhu, F., Wang, Y., Fang, M., Huang, Y., & Shen, T. (2023). Environmental endocrine disruptor Bisphenol A induces metabolic derailment and obesity via upregulating IL-17A in adipocytes. Environment International, 172, 107759. https://doi.org/10.1016/j.envint.2023.107759
• Kyrila, G., Katsoulas, A., Schoretsaniti, V., Rigopoulos, A., Rizou, E., Doulgeridou, S., Sarli, V., Samanidou, V., & Touraki, M. (2021). Bisphenol A removal and degradation pathways in microorganisms with probiotic properties. Journal of Hazardous Materials, 413, 125363. https://doi.org/10.1016/j.jhazmat.2021.125363

Candida como agente etiológico de la meningitis

• Aksamit, A. J. (2021). Chronic Meningitis. New England Journal of Medicine, 385(10), 930–936. https://doi.org/10.1056/NEJMra2032996
• Cohen-Wolkowiez, M., Smith, P. B., Mangum, B., Steinbach, W. J., Alexander, B. D., Cotten, C. M., Clark, R. H., Walsh, T. J., & Benjamin, D. K. (2007). Neonatal Candida meningitis: significance of cerebrospinal fluid parameters and blood cultures. Journal of Perinatology, 27(2), 97–100. https://doi.org/10.1038/sj.jp.7211628
• Dadar, M., Tiwari, R., Karthik, K., Chakraborty, S., Shahali, Y., & Dhama, K. (2018). Candida albicans – Biology, molecular characterization, pathogenicity, and advances in diagnosis and control – An update. Microbial Pathogenesis, 117, 128–138. https://doi.org/10.1016/j.micpath.2018.02.028
• Liu, Y., Mittal, R., Solis, N. V., Prasadarao, N. V., & Filler, S. G. (2011). Mechanisms of Candida albicans Trafficking to the Brain. PLOS Pathogens, 7(10), e1002305. https://doi.org/10.1371/JOURNAL.PPAT.1002305
• Marra, C. M., Rohatgi, S., Bloom, A. K., Kahle, K. T., & Haj, A. K. (2022). Case 25-2022: A 25Year-Old Woman with Headache and Blurred Vision. New England Journal of Medicine, 387(7), 641–650. https://doi.org/10.1056/NEJMcpc2201241
• Mayer, F. L., Wilson, D., & Hube, B. (2013). Candida albicans pathogenicity mechanisms. Virulence, 4(2), 119. https://doi.org/10.4161/VIRU.22913
• Robert P. Lehr Jr., Ph. D. (n.d.). BRAIN FUNCTION. Centre for Neuro Skills. Retrieved from https://www.neuroskills.com/brain-injury/brain-function/
• Thakur, K. T., & Wilson, M. R. (2018). Chronic Meningitis. CONTINUUM Lifelong Learning in Neurology, 24(5,    Neuroinfectious          Disease),        1298–1326. https://doi.org/10.1212/CON.0000000000000664

Descodificando la caja negra: Mejorando y guiando el descubrimiento de fármacos usando inteligencia artificial e interpretabilidad de las subestructuras moleculares

• Bajusz, D., Rácz, A., & Héberger, K. (2017). Chemical Data Formats, Fingerprints, and Other Molecular Descriptions for Database Analysis and Searching. In Reference Module in Chemistry, Molecular Sciences and Chemical Engineering. https://doi.org/10.1016/B978-0-12-409547-2.12345-5
• Banegas-Luna, A. J., & Pérez-Sánchez, H. (2023). SIBILA: A novel interpretable ensemble of general-purpose machine learning models applied to medical contexts (arXiv:2205.06234). arXiv. http://arxiv.org/abs/2205.06234
• Castelvecchi, D. (2016). Can we open the black box of AI? Nature News, 538(7623), 20. https://doi.org/10.1038/538020a
• Lundberg, S. M., & Lee, S.-I. (2017). A Unified Approach to Interpreting Model Predictions. Advances in Neural Information Processing Systems, 30. https://proceedings.neurips.cc/paper_files/paper/2017/hash/8a20a8621978632d76c43dfd28b67767-Abstract.html
• Ribeiro, M. T., Singh, S., & Guestrin, C. (2016). “Why Should I Trust You?”: Explaining the Predictions of Any Classifier (arXiv:1602.04938). arXiv. https://doi.org/10.48550/arXiv.1602.04938
• Sun, D., Gao, W., Hu, H., & Zhou, S. (2022). Why 90% of clinical drug development fails and how to improve it? Acta Pharmaceutica Sinica B, 12(7), 3049–3062. https://doi.org/10.1016/j.apsb.2022.02.002
• Vogt, I. (2008). Analysis of Biological Screening Data and Molecular Selectivity Profiles Using Fingerprints and Mapping Algorithms [Thesis, Universitäts- und Landesbibliothek Bonn]. https://bonndoc.ulb.uni-bonn.de/xmlui/handle/20.500.11811/3692

Genética y ecología para estudiar la adaptación local

Revisión del sistema inmune y sus compromisos ecológicos en anfibios

• Brannelly, L. A., Ohmer, M. E., Saenz, V., & Richards‐Zawacki, C. L. (2019). Effects of hydroperiod on growth, development, survival and immune defences in a temperate amphibian. Functional Ecology, 33, 1952-1961.
• Corn, P. S. (2005). Climate change and amphibians. Animal Biodiversity and Conservation, 28, 59-67.
• Cotter, S. C., Simpson, S. J., Raubenheimer, D., & Wilson, K. (2011). Macronutrient balance mediates trade-offs between immune function and life history traits. Functional Ecology, 25, 186-198.
• Houlahan, J.E., Findlay, C.S., Schmidt, B.R., Meyer, A.H., & Kuzmin, S.L. (2000).
• Quantitative evidence for global amphibian population declines. Nature, 404, 752-755.
• Isaksson, C., Sheldon, B. C., & Uller, T. (2011). The challenges of integrating oxidative stress into life-history biology. BioScience, 61, 194-202.
• Johnson, P. T., Rohr, J. R., Hoverman, J. T., Kellermanns, E., Bowerman, J., & Lunde, K. B. (2012). Living fast and dying of infection: host life history drives interspecific variation in infection and disease risk. Ecology Letters, 15, 235-242.
• Kirschman, L. J., Crespi, E. J., & Warne, R. W. (2018). Critical disease windows shaped by stress exposure alter allocation trade- offs between development and immunity. Journal of animal ecology, 87, 235-246.
• McCallum, M. L., & Trauth, S. E. (2007). Physiological trade-offs between inmunity and reproduction in the northern cricket frog (Acris crepitans). Herpetologica, 63, 269-274.
• Pounds, J.A., Bustamante, M.R., Coloma, L.A., Consuegra, J.A., Fogden, M.P.L.,
• Foster, P.N., La Marca, E., Masters, K.L., Merino-Viteri, A., Puschendorf, R., Ron, S.R., Sánchez-Azofeifa, G.A., Still, C.J., & Young, B.E. (2006a). Widespread amphibian extinctions from epidemic disease driven by global warming. Nature, 439, 161-167.