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Immunomodulating Botanicals: An Overview of the Bioactive Phytochemicals for the Management of Autoimmune Disorders

2024· book-chapter· en· W4393202599 on OpenAlex
Ami P. Thakkar, Amisha Vora, Harpal S. Buttar, Ginpreet Kaur

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBENTHAM SCIENCE PUBLISHERS eBooks · 2024
Typebook-chapter
Languageen
FieldMedicine
TopicHerbal Medicine Research Studies
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsTraditional medicineMedicine

Abstract

fetched live from OpenAlex

Immunomodulation refers to the mechanism by which the response of the immune system is modified by the regulation of antibody synthesis, leading to either an increase or a decrease in its levels in the circulation and body organs. Owing to their immunomodulation and remedial benefits, a broad range of herbal remedies have been shown to be effective in the treatment of autoimmune diseases such as multiple sclerosis, rheumatoid arthritis, myasthenia gravis, and systemic lupus erythematosus. The ancient Indian system of Ayurveda and different other alternative therapeutic methods have acknowledged the potential benefits of herbal-based remedies to upregulate or suppress the immune response in the human body. The conventional pharmacotherapies used for the management of autoimmune ailments are documented to cause serious drug-induced adverse reactions (ADRs). Whereas, some phytotherapies have proven safe, reliable, and efficient alternatives for the existing drug regimens with lesser ADRs. For instance, Withania somnifera, Andrographis paniculate, Tinospora cordifolia, Glycyrrhiza glabra, and Berberis arista are a few herbs whose bioactive phytoconstituents have been reported to possess powerful immunomodulation properties. Based on their purported immunomodulatory mechanisms, they can be used for the management of autoimmune conditions. The focus of this review is to highlight the key inflammatory biomarkers such as TNF-α and interleukin 1, 6 involved in the distortion of the immune system in humans. Also, we will discuss the usefulness of animal models for understanding the underlying mechanisms of autoimmune disorders. In addition, we will describe the patents of phytomedicine formulations filed by different manufacturers for the management of autoimmune disorders, as well as futuristic opportunities that should be explored for discovering the therapeutic functions of alternate remedies for treating autoimmune diseases.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.717
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.004
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.089
GPT teacher head0.381
Teacher spread0.292 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it