Recommended Reads from the FAIS Executive Board - FAIS Africa

Explore a curated selection of articles recommended by the FAIS Executive Board. These readings reflect topics our leadership considers important, insightful, and relevant to the advancement of allergy and clinical immunology. We invite you to discover new perspectives, emerging ideas, and thought-provoking contributions shaping our field!

• Recommended by Justin Komguep Nono. FAIS’ Central Africa Regional Representative.

💡 Consensus Statement. Published: 18 November 2025.

📘Guidelines for T cell nomenclature

✍️ David Masopust et al. Nature Reviews Immunology Journal.

The article Guidelines for T cell nomenclature proposes a consensus, more precise naming system for T-cells by redefining classical subsets and introducing a new “modular nomenclature” that describes each T-cell population according to its biological properties rather than broad, inconsistently used labels. This change aims to improve clarity, reproducibility and communication across immunology research by standardizing how scientists define and report T-cell subsets.

• Recommended by Theresa Rossouw. FAIS’ Treasurer:

💡 Article published: 28 November 2025.

📘Characterisation of human in vitro tumour-associated macrophage models to define translational relevance

✍️ Dyer, A., Dudley, R., Ahuja, S. et al. Scientific Reports Journal

This article shows that the authors developed and validated new human in vitro models of tumour-associated macrophages (TAMs) that faithfully mimic the suppressive, immunosuppressive macrophage states found in human cancers — offering more realistic systems for studying tumour–immune interactions.

• Recommended by Tomabu Adjobimey. FAIS’ Western Africa Regional Representative:

💡 Review Published: 9 September 2025.

📘Deep learning in next-generation vaccine development for infectious diseases

✍️ Manojit Bhattacharya et al. Molecular Therapy: Nucleic Acids Journal.

Tomabu’s quote: “This comprehensive review provides an insightful overview of how deep learning is reshaping modern vaccine development, from computational epitope prediction to the design and characterization of multi-epitope vaccine constructs. It highlights the evolution from classical immunoinformatic to integrated AI-driven frameworks and shows how deep learning accelerates and improves next-generation vaccine design. I believe this perspective is timely and highly relevant to our community, especially given the growing intersection between immunology, computational biology, and global health.”