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Record W4391680244 · doi:10.1042/bst20230087

Epigenetic changes induced by parasitic worms and their excretory-secretory products

2024· review· en· W4391680244 on OpenAlexaff
William Harnett, Margaret M. Harnett

Bibliographic record

VenueBiochemical Society Transactions · 2024
Typereview
Languageen
FieldImmunology and Microbiology
TopicImmune responses and vaccinations
Canadian institutionsInstitute of Infection and Immunity
FundersMedical Research CouncilBiotechnology and Biological Sciences Research CouncilDirectorate for Biological Sciences
KeywordsBiologyContext (archaeology)Immune systemEpigeneticsStromal cellEffectorImmunologyPhenotypeCancer researchGeneGenetics

Abstract

fetched live from OpenAlex

Parasitic worms are pathogens of major medical and veterinary importance. They have evolved highly effective and sophisticated strategies of immune system manipulation, typically involving actively excreted/secreted (E-S) products. These molecules dampen and regulate the host immune responses that would otherwise result in parasite expulsion, thereby enabling the worms to survive in the host for many years, and they can also help prevent the potentially serious tissue damage that the worms can induce. Reflecting these E-S product-associated anti-inflammatory activities, there is also increasing evidence that parasitic worms and their products may serendipitously protect against allergic and autoimmune conditions and in addition, comorbidities of ageing that are associated with inflammatory responses, like type 2 diabetes and obesity. Research in this area has to date generally focused on identifying the cellular and effector targets of immunomodulation induced by the worm E-S products. However, increasing evidence that they can induce stably imprinted phenotypes of haematopoietic and stromal cells which promote their long-lasting survival has recently ignited interest in the ability of the molecules to epigenetically rewire cells to 'resolve and repair' phenotypes. Here, we review and discuss these new data in the context of their potential for exploitation in identifying novel gene signatures for the development of advanced and safe therapeutics for chronic inflammatory 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.

How this classification was reachedexpand

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.936
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.032
GPT teacher head0.290
Teacher spread0.258 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations10
Published2024
Admission routes1
Has abstractyes

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