Climate change and emerging pathogens: Toward nature-based solutions

First identified as a pathogen in Malaysia and Singapore in 1999, Nipah virus (NiV) caused nearly 300 human cases and over 100 fatalities. It also killed about 1 million pigs. Three years later (2002), it was reported in Pteropus bats in Malaysia, in Cambodia & Thailand, (2005), and as far as Madagascar (2007) and Ghana (2008). India (Kerala) reported its first human NiV-caused fatalities in September 2023. Taken together, these trends emphasize its public health threat. In humans, NiV infection initially leads to fever, headache, body aches and muscle pain, nausea and vomiting. The symptoms rapidly evolve into sore throat, cough and atypical pneumonia leading to severe respiratory distress. The cadre of NiV-induced pathology (Nipah disease, NiD) then includes severe dizziness and drowsiness, progressive alteration in cognition and consciousness, acute encephalitis and seizures. Public health protocols (e.g., mask-wearing, quarantine), essential to contain and control CoViD-19, seem insufficient to contain NiD spread because NiV transmission occurs primarily via direct contacts with body fluids of infected carriers, but presumably not by airborne transmission. As in the case of SARS-C0V2, health care providers (i.e., physicians, dentists, nurses, dental assistants) are greatest risks not only of contracting but of spreading NiV infection. NiV is a high-pathogenicity pathogen, against which, at present, we have no anti-viral medications or preventive vaccine. Taken together, the evidence to date heightens the threat of an upcoming NiD pandemic.

Section: Oral Immunitymentioning

confidence: 99%

Nipah: The looming post-covid pandemic

Chiappelli

2024

“…Taken together, data show that cytokines in states of chronic inflammation (i.e., meta-inflammation, inflamm-aging) impair the regulation and function of lymphatics, and favor senescence not only of immunity, but also of its anatomical substratum, the lymphatic system. It follows that meta-inflammation cytokines may significantly contribute to increasing the susceptibility of the elderly to viral epidemics and pandemics, including influenza and CoViD-19, Ebola, Monkeypox, Nipah, Dengue, Zika and other related air-borne, fomite-borne, or vector-transmitted infectious diseases, be they known and current, or novel and ancient pathogens released by melting glaciers and permafrost [ 10 , 11 ]. Air-borne viruses, from Influenza virus strains (e.g., H1-16N1-9) to Corona virus strains (e.g., MERS, SARS-CoV1-2 and their variants and sub-variants) to Paramyxoviruses (e.g., measles, mumps) and Rhinoviruses (i.e., common cold) are of particular concern not because they can lead to serious epidemics and pandemics (cf., Spanish Flu, CoViD-19) by most immediately penetrating and infecting the nasal and the oral mucosa, and the respiratory tract.…”

Section: Descriptionmentioning

confidence: 99%

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

Chiappelli

2023

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.

“…Thawing permafrost releases trapped heavy metals and greenhouse gasses, and a myriad of ancient and novel bacteria, viruses, fungi and parasites. Our immune system is ill-equipped to counter these new challenges, and requires considerable adaptation [ 7 , 8 ] - a process physiologists term allostasis, the process of transition to and recovery of the equilibrium state of immune homeostasis. In brief, when faced with a foreign pathogen, the immune system launches a multi-faceted immune response to efficiently promote immune allostasis.…”

Section: Permafrost Viremia and Chronic Inflammationmentioning

confidence: 99%

“…Proteomics and related techniques have generated a wealth of data on adaptive immune modulation and regulation, and large-scale data sets (i.e., meta-data) have led to the elaboration, testing and evaluation of general ML, and specific DL models for the identification and testing of complex and high-dimensional immune repertoires, including predicting the immunological status of a host to colliding infections with diverse novel and established virus species, and the engineering of relevant immune therapeutics [ 15 ], and vaccine development [ 16 ]. Having identified these pathways and parameters, immunologists may propose potential treatments such as Autologous Immune Enhancement Therapy (AIET), a process by which native (CD45RA+) T cells are removed from the patient's body where they are manipulated to mature into memory (CD45R0+) T cells by controlled exposure to new and ancient pathogens, and re-administered into the host to boost the immune response [ 8 ].…”

Section: Deep Machine Learning For Cellular Immunitymentioning

confidence: 99%

“…To be clear, AI, and specifically certain models of ML such as DL and its variants, will find a valuable place in the field of viral immunity, particularly in the context of the emerging threat of novel and ancient pathogens released by melting permafrost [ 7 , 8 ]. A more effective and comprehensive understanding of permafrost viral immunity will require improved targeted AI-aided immune tweening by compartmentalizing different components of the immune system as separate variables, and by the underlying assumption that said factors may not be influenced by one another.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Permafrost viremia and immune tweening

Chiappelli

2023

Self Cite

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.