Teaching Methodologies
The proposed pedagogical model comprises a set of teaching and learning methodologies (TL) that combine strategies for pedagogical innovation through moments of active, student-centered learning, aiming to promote the trilogy of knowledge in its dimensions: know-what (knowledge), know-how (skills), and know-being (competencies).
Matrix T
TL1 – Interactive expository teaching, with content presentation and active individual learning moments focused on problem-solving, using audiovisual tools and appropriate platforms: Mentimeter activities (Wordcloud, Q&A, Ranking tools).
Matrix TP
TL2 – Cooperative expository teaching, with active group learning moments (Jigsaw activities), centered on the research, analysis, presentation, and discussion of scientific articles in the field.
Continuous assessment will be significant and consist of the following elements:
1. Individual written test (40%)
2. Active participation in theoretical and theoretical-practical sessions (20%), including: active student involvement in sessions, assessing the ability to apply integrated knowledge, critical thinking, and active communication.
3. Group work (40%) The main evaluative component will be the presentation of a scientific article, developed in small groups. The presentation will be oral in front of a jury made up of experts from different areas of specialization.
Approval Criteria
The final grade will be determined by the weighting of the above-mentioned assessment components. For approval, students must achieve a minimum score of 10 (on a scale from 0 to 20) in the weighted average of the identified components. Attendance and active participation are encouraged, with a mandatory presence of at least 75% of the sessions.
Learning Results
O1. Characterize the diversity, function, and metabolic activity of the microbiota (intestinal, cutaneous, mucosal).
– Explain molecular and cellular pathways through which the microbiome influences immunometabolism and host homeostasis.
O2. Assess the role of the microbiota in immune homeostasis, tolerance, and inflammatory signaling.
– Evaluate how microbial-derived metabolites regulate immune cell activation and chronic inflammation.
O3. Correlate immunometabolic alterations and dysbiosis with metabolic disorders, aging, and cancer progression.
– Understand how microbiota-driven metabolic shifts shape the tumor microenvironment and sterile inflammation.
O4. Examine the impact of prebiotics, probiotics, symbiotics, and postbiotics on microbiota composition and immune metabolism.
– Integrate molecular, clinical, and omics-based approaches to design personalized immunometabolic interventions.
Program
Module 1: Introduction to the Microbiota and Microbiome
– Intestinal, skin, and mucosal-associated microbiota
– Interaction between the microbiome, metabolism, and immunity
Module 2: Immunometabolism and Microbiota Communication
– Immune cell types and metabolic regulation
– Immunometabolic crosstalk and microbiota influence
– Impact of immunometabolism on chronic inflammation and autoimmunity
Module 3: Immunometabolism in Metabolic Diseases, Aging, and Cancer
– Immunometabolic dysfunction and inflammation in diabetes and obesity
– Immune aging and sterile inflammation
– Crosstalk between the intestinal microbiota and tumor microenvironment, focusing on immunometabolism in cancer
Module 4: Modulating Microbiota-Immune Communication
– Dietary patterns and their impact on microbiota and immunometabolism
– Prebiotics, probiotics, symbiotics, and postbiotics
Internship(s)
NAO
Bibliography
Pellon, A. et al. (2025). Friends to remember: innate immune memory regulation by the microbiota. Trends in microbiology, S0966-842X(24)00318-4. Advance online publication. https://doi.org/10.1016/j.tim.2024.12.002
Flory, M. et al. (2024). Impact of gut microbiota and its metabolites on immunometabolism in colorectal cancer. Immunometabolism (Cobham, Surrey), 6(4), e00050. https://doi.org/10.1097/IN9.0000000000000050
Fang, H. et al. (2025). Postbiotic Impact on Host Metabolism and Immunity Provides Therapeutic Potential in Metabolic Disease. Endocrine reviews, 46(1), 60-79. https://doi.org/10.1210/endrev/bnae025
Ferreira, C. et al. (2024). Polyphenols: immunonutrients tipping the balance of immunometabolism in chronic diseases. Frontiers in immunology, 15, 1360065. https://doi.org/10.3389/fimmu.2024.1360065