ArticleJournal of inflammation research2019
The Binary Classification Of Chronic Diseases.
Article in Journal of inflammation research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
10 citing papers in PubMed, 14 citations in OpenAlex.
- Interferons in Autoimmunity: From Loss of Tolerance to Chronic Inflammation.Biomedicines · 2025Review
- New insights into the phenomenon of remissions and relapses in autoimmune diseases and the puzzle of benign autoantibodies in healthy individuals.Frontiers in immunology · 2025Review
- TGF-β, IL-1β, IL-6 levels and TGF-β/Smad pathway reactivity regulate the link between allergic diseases, cancer risk, and metabolic dysregulations.Frontiers in immunology · 2024Article
- Improved lung cancer clinical outcomes in patients with autoimmune rheumatic diseases.RMD open · 2023Article
- The Contrasting Seasonality Patterns of Some Cancer-Types and Herpes Zoster Can Be Explained by a Binary Classification of Immunological Reactions.Journal of inflammation research · 2022Article
- Cancer and Autoimmune Diseases: A Tale of Two Immunological Opposites?Frontiers in immunology · 2022Article
- SARS-CoV-2 Omicron (B.1.1.529) Variant: Corticosteroids Treatment/Respiratory Coinfection.Frontiers in immunology · 2022Article
- The Binary Classification of Protein Kinases.Journal of inflammation research · 2021Article
- "High Treg" Inflammations Promote (Most) Non-Hematologic Cancers While "Low Treg" Inflammations Promote Lymphoid Cancers.Journal of inflammation research · 2020Article
- The Binary Model of Chronic Diseases Applied to COVID-19.Frontiers in immunologyArticle
Corrections and comments
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Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Acute diseases start with an insult and end when insult disappears. If the trauma induces an immune reaction (which happens in most cases), this reaction must be terminated with some type of resolution mechanism, when the cause of the trauma ceases. Chronicity develops if insult is permanent or if the resolution mechanism is defective. Another way to reach disease chronicity is a positive feedback loop, whereby the immune reaction activates an internal, insult-like reaction. A distinction between chronic states characterized by a persistent, low suppressive effect and those characterized by a persistent, high suppressive effect of regulatory T cells (Treg), is proposed. This two-class division represents two ways to reach chronicity: (a) by maintaining inflammatory reaction long after insult disappears ("low Treg"), or (b) by suppressing inflammatory reaction prior to the disappearance of insult ("high Treg"). This two-class division may explain the strong association between certain pathogens and cancer, on one hand, and between several other pathogens and autoimmunity, on the other hand. The weak association between autoimmune diseases and HIV infection and the relatively weak association between autoimmune diseases and cancer may be elucidated as well. In addition, the model rationalizes why immune-modulating drugs, which are effective in cancer, are also effective in "high Treg" viral infections, while corticosteroids, which are generally effective in autoimmune diseases, are also effective in other "low Treg" diseases (such as asthma, atopic dermatitis, and "low Treg" infections) but are not effective in solid malignancies and "high Treg" infections. Moreover, the model expounds why certain bacteria inhibit tumor growth and why these very bacteria induce autoimmune diseases.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.