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Facilitating the Advancement of Research and Education for Undergraduate Students by Incorporating Laser Scanning Confocal Microscopy (FAREUS-LSCM)
PROJECT SUMMARY/ABSTRACT The University of Puerto Rico at Aguadilla (UPR-Aguadilla) requests funding to acquire a Nikon AX Galvo Confocal Laser Scanning Microscope (LSCM) with a TI2-E inverted platform and a four- laser configuration (405/488/561/640 nm) to establish transformative imaging capabilities at our resource-limited institution serving 96% Pell Grant recipients. This state-of-the-art instrument addresses a critical infrastructure gap, enabling high-resolution fluorescence imaging, live-cell microscopy, and quantitative analysis essential for competitive biomedical research and undergraduate education. The LSCM will directly support four active research projects spanning parasitology (monogenean host-specificity studies), plant pathology (coffee biocontrol development), environmental chemistry (metalloprotein biomarkers), and neuroscience (astrocyte dysfunction in diabetic epilepsy) while integrating into core laboratory courses including Immunology (BIOL 4009) and Undergraduate research courses (BIOL 3108 and QUIM 4999). Our multidisciplinary faculty, in partnership with the Neuroimaging and Electrophysiology Facility (NIEF) Excellence Imaging Center, offers expertise in confocal microscopy, encompassing advanced imaging and specialized sample preparation techniques. This collaboration ensures effective implementation of the technology, sustained technical support, and high-quality training programs that will enhance research productivity and broaden educational impact. The broad, long-term objective is to transform UPR-Aguadilla from a primarily teaching institution into a research-active campus capable of producing graduate-school-ready students equipped with cutting-edge technical skills. Access to advanced confocal microscopy will stimulate new research collaborations, enhance faculty productivity, and provide 30-40 students annually with hands-on experience in modern imaging technologies currently absent from our curriculum. The instrument will strengthen our partnership with the emerging Natural History Museum of Puerto Rico for specimen digitization and support comprehensive outreach programs targeting 25-50 high school students annually through "Seeing Science Up Close" workshops. Expected outcomes include 1- 2 peer-reviewed publications within three years, establishment of 1-2 new institutional collaborations, and measurable enhancement of biomedical research capacity. This investment will significantly advance STEM education and research opportunities at UPR-Aguadilla while expanding access to cutting-edge scientific instrumentation for students pursuing biomedical careers and contributing to the development of skilled researchers in the biomedical sciences.
Digitization as a driving force for collaboration in neuroscience
Many of the collaborations we encounter in our scientific careers are centered on a common idea that can be associated with certain resources, such as a dataset, an algorithm, or a model. All partners in a collaboration need to develop a common understanding of these resources, and need to be able to access them in a simple and unambiguous manner in order to avoid incorrect conclusions especially in highly cross-disciplinary contexts. While digital computers have entered to assist scientific workflows in experiment and simulation for many decades, the high degree of heterogeneity in the field had led to a scattered landscape of highly customized, lab-internal solutions to organizing and managing the resources on a project-by-project basis. Only with the availability of modern technologies such as the semantic web, platforms for collaborative coding or the development of data standards overarching different disciplines, we have tools at our disposal to make resources increasingly more accessible, understandable, and usable. However, without overarching standardization efforts and adaptation of such technologies to the workflows and needs of individual researchers, their adoption by the neuroscience community will be impeded. From the perspective of computational neuroscience, which is inherently dependent on leveraging data and methods across the field of neuroscience for inspiration and validation, I will outline my view on past and present developments towards a more rigorous use of digital resources and how they improved collaboration, and introduce emerging initiatives to support this process in the future (e.g., EBRAINS http://ebrains.eu, NFDI-Neuro http://www.nfdi-neuro.de).
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