Permafrost Immunity

The lymphatic system: a pathway for meta-inflammation in permafrost immunity

The lymphatic system is the anatomical substratum of immunity. Lymphatics collect tissue exudates, which contain cell debris, peptides, micronutrients and pathogens, as well as immune naive and memory effector cells from the body tissues and organs into the lymph. Lined by endothelial cells cemented together by tight junctions to ensure their impermeability, lymphatics contain valves that prevent the backward flow of the lymph as it moves forward toward the right and left venous angles, the anatomical site of confluence with the venous blood. Meta-inflammation increases the permeability of lymphatics, rendering the elderly more susceptible to novel and ancient airborne viruses released by melting glaciers and permafrost. Simple public health protocols (e.g., mask-wearing, quarantine) are essential to minimize colliding epidemics/pandemics, and favor permafrost immunity.

Permafrost viremia and immune tweening

The immune system, an exquisitely regulated physiological system, utilizes a wide spectrum of soluble factors and multiple cell populations and subpopulations at diverse states of maturation to monitor and protect the organism against foreign organisms. Immune surveillance is ensured by distinguishing self-antigens from self-associated with non-self (e.g., viral) peptides presented by major histocompatibility complexes (MHC). Pathology is often identified as unregulated inflammatory responses (e.g., cytokine storm), or recognizing self as a non-self entity (i.e., auto-immunity). Artificial intelligence (AI), and in particular specific machine learning (ML) paradigms (e.g., Deep Learning [DL]) proffer powerful algorithms to better understand and more accurately predict immune responses, immune regulation and homeostasis, and immune reactivity to challenges (i.e., immune allostasis) by their intrinsic ability to interpret immune parameters, pathways and events by analyzing large amounts of complex data and drawing predictive inferences (i.e., immune tweening). We propose here that DL models play an increasingly significant role in better defining and characterizing immunological surveillance to ancient and novel virus species released by thawing permafrost.