Francisco Javier Gaibao Carmona

Neuroinflammation has emerged as a fundamental pathophysiological mechanism linking neurological disorders with systemic inflammatory diseases. Increasing evidence demonstrates that chronic immune activation contributes significantly to neuronal dysfunction, cognitive impairment, neurodegeneration, and multisystem clinical manifestations through complex interactions involving microglial activation, cytokine signaling, oxidative stress, endothelial dysfunction, mitochondrial injury, and blood–brain barrier disruption. The objective of this review was to analyze the role of neuroinflammation as an interdisciplinary bridge between neurology, immunology, and internal medicine while evaluating its clinical, molecular, and translational implications. A narrative review methodology based on the Scientific Method and Process-Based Methodology was employed. Scientific literature indexed in international databases including PubMed, Scopus, ScienceDirect, SpringerLink, and Frontiers was analyzed. The review prioritized peer-reviewed studies published primarily between 2020 and 2025 addressing neuroimmune communication, neurodegeneration, metabolic disorders, autoimmune diseases, infectious syndromes, and gut–brain axis interactions. The analyzed evidence demonstrated that neuroinflammatory mechanisms are strongly associated with metabolic diseases such as obesity and type 2 diabetes mellitus, autoimmune disorders including systemic lupus erythematosus, infectious conditions such as sepsis and long COVID syndrome, and neurodegenerative diseases. Persistent inflammatory activation was consistently related to cognitive impairment, chronic fatigue, depression, autonomic dysfunction, chronic pain, and progressive neuronal injury. Furthermore, the gut–brain axis emerged as a major regulator of neuroimmune communication, reinforcing the systemic nature of neuroinflammation.

The integration of Artificial Intelligence, digital twins, and predictive analytics is reshaping General Surgery toward a more precise, data-driven, and patient-centered model. This review analyzes the current applications, contributions, and limitations of these technologies across the surgical care pathway, with a particular focus on their relevance in pediatric contexts and their implementation in diverse healthcare settings, including Mexico, Colombia, and Ecuador. A structured narrative review methodology was employed, selecting recent high-impact studies from multidisciplinary fields such as surgery, biomedical engineering, and data science. The findings were categorized into preoperative planning, intraoperative guidance, postoperative monitoring, and predictive risk assessment. Results indicate that digital twins play a critical role in individualized surgical planning, artificial intelligence enhances intraoperative precision through real-time data processing, and predictive analytics supports proactive postoperative care by identifying potential complications. The analysis also highlights the central role of the surgeon as the primary decision-maker, emphasizing the concept of augmented intelligence, where technological tools complement rather than replace clinical expertise. While promising, the implementation of these technologies faces challenges related to infrastructure, data availability, ethical considerations, and system integration, particularly in developing healthcare contexts.

Precision oncology has traditionally focused on genomic profiling to guide targeted therapies; however, increasing evidence suggests that genetic alterations alone are insufficient to fully explain tumor behavior, therapeutic response, and clinical heterogeneity. This review aims to analyze precision oncology beyond genetics by integrating metabolic flexibility, tumor microenvironment dynamics, immune profiling, and systemic physiological factors, with particular emphasis on dermatology and internal medicine in international contexts, including Mexico, Colombia, and Ecuador. A structured narrative review was conducted using the scientific method as a guiding framework, allowing for the systematic identification, analysis, and integration of relevant literature. The findings demonstrate that tumor metabolism, particularly metabolic flexibility, plays a central role in adaptation and resistance. Additionally, the tumor microenvironment and immune profiling are critical determinants of treatment response, especially in the context of immunotherapy. The concept of the kidney as a sensor organ highlights the importance of systemic physiology in oncologic outcomes, particularly regarding drug clearance, toxicity, and metabolic balance. Furthermore, cardiometabolic conditions such as obesity, diabetes, and chronic inflammation significantly influence tumor progression and therapeutic effectiveness. The integration of these dimensions supports a systems-based model of precision oncology, where tumor biology and host factors interact dynamically. This approach is particularly relevant for dermatology and internal medicine, as it allows for a more comprehensive understanding of both local and systemic disease processes. In addition, the proposed framework offers practical applicability in diverse healthcare settings, including regions with limited access to advanced molecular technologies.