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Record W2105542546 · doi:10.3748/wjg.v20.i47.17699

Toll-like receptor signaling in colorectal cancer: Carcinogenesis to cancer therapy

2014· review· en· W2105542546 on OpenAlex

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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueWorld Journal of Gastroenterology · 2014
Typereview
Languageen
FieldImmunology and Microbiology
TopicImmune Response and Inflammation
Canadian institutionsnot available
FundersNational Cancer InstituteNational Institutes of HealthGary Bennett Family Fund
KeywordsTLR3Toll-like receptorInnate immune systemBiologySignal transductionInflammationCancer researchImmune systemCarcinogenesisTLR4CancerCell biologyImmunologyPattern recognition receptorTLR5

Abstract

fetched live from OpenAlex

Toll-like receptors (TLRs) are germ line encoded innate immune sensors that recognize conserved microbial structures and host alarmins, and signal expression of major histocompatibility complex proteins, costimulatory molecules, and inflammatory mediators by macrophages, neutrophils, dendritic cells, and other cell types. These protein receptors are characterized by their ability to respond to invading pathogens promptly by recognizing particular TLR ligands, including flagellin and lipopolysaccharide of bacteria, nucleic acids derived from viruses, and zymosan of fungi. There are 2 major TLR pathways; one is mediated by myeloid differentiation factor 88 (MYD88) adaptor proteins, and the other is independent of MYD88. The MYD88-dependent pathway involves early-phase activation of nuclear factor of kappa light polypeptide gene enhancer in B-cells 1 (NF-κB1) and all the TLRs, except TLR3, have been shown to activate this pathway. TLR3 and TLR4 act via MYD88-independent pathways with delayed activation of NF-κB signaling. TLRs play a vital role in activating immune responses. TLRs have been shown to mediate inflammatory responses and maintain epithelial barrier homeostasis, and are highly likely to be involved in the activation of a number of pathways following cancer therapy. Colorectal cancer (CRC) is one of the most common cancers, and accounts for almost half a million deaths annually worldwide. Inflammation is considered a risk factor for many common malignancies including cancers of the colorectum. The key molecules involved in inflammation-driven carcinogenesis include TLRs. As sensors of cell death and tissue remodeling, TLRs may have a universal role in cancer; stimulation of TLRs to activate the innate immune system has been a legitimate therapeutic strategy for some years. TLRs 3/4/7/8/9 are all validated targets for cancer therapy, and a number of companies are developing agonists and vaccine adjuvants. On the other hand, antagonists may favor inhibition of signaling responsible for autoimmune responses. In this paper, we review TLR signaling in CRC from carcinogenesis to cancer therapy.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.979
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.023
GPT teacher head0.305
Teacher spread0.282 · 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