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Record W1998673769 · doi:10.3109/10408363.2014.886180

The bifacial role of helminths in cancer: Involvement of immune and non-immune mechanisms

2014· review· en· W1998673769 on OpenAlexaff
Κατερίνα Οικονομοπούλου, Davor Brinc, Andreas Hadjisavvas, G Christofi, Kyriacos Kyriacou, Eleftherios P. Diamandis

Bibliographic record

VenueCritical Reviews in Clinical Laboratory Sciences · 2014
Typereview
Languageen
FieldImmunology and Microbiology
TopicParasites and Host Interactions
Canadian institutionsUniversity Health NetworkMount Sinai Hospital
Fundersnot available
KeywordsImmune systemImmunologyHelminthsCarcinogenesisCancerBiologyAllergyEpigeneticsHygiene hypothesisImmune toleranceGeneticsGene

Abstract

fetched live from OpenAlex

Infectious agents have been associated with cancer due to activation of pro-carcinogenic inflammatory processes within their host. Several reports, however, indicate that specific pathogens may be able to elicit anti-tumor immune responses that can lead to protection from tumorigenesis or cancer regression. Amongst these "beneficial" pathogens are some helminthic parasites that have already been connected with prevention of autoimmune diseases and allergies, immune conditions increasingly associated with cancer. Even though helminths have co-existed with humans and their ancestors for millions of years, investigations of their impact on human (patho)physiology are relatively new and the functions of components that can explain the helminth bi-directional influence on carcinogenesis are not well understood. This review aims to discuss evidence for the helminth-induced immune, genetic, epigenetic, proteomic, hormonal and metabolic changes that may ultimately mediate the potential pro- or anti-carcinogenic role of helminths. This overview may serve future investigations in clarifying the tumorigenic role of the most common helminthic parasites. It may also inspire the development of anti-cancer regimens and vaccines, in parallel to ongoing efforts of using helminth-based components for the prevention and/or treatment of autoimmune diseases and allergies.

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)0.008
metaresearch head score (Gemma)0.006
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: Review · Consensus signal: Review
Teacher disagreement score0.982
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.001
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.482
Teacher spread0.393 · 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

Citations14
Published2014
Admission routes1
Has abstractyes

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