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Record W2887956262 · doi:10.1093/labmed/lmy047

Toll-Like Receptor 4 as an Immune Receptor Against<i>Mycobacterium tuberculosis</i>: A Systematic Review

2018· review· en· W2887956262 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.

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

Bibliographic record

VenueLaboratory Medicine · 2018
Typereview
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsUniversity of Manitoba
FundersZabol University of Medical Sciences
KeywordsMycobacterium tuberculosisTuberculosisImmune systemTLR4Toll-like receptorImmunologyBiologyTollReceptorMedicineInnate immune systemPathologyGenetics

Abstract

fetched live from OpenAlex

OBJECTIVE: To review the main Mycobacterium tuberculosis (Mtb) pathogen-associated molecular patterns (PAMPs) and the roles played by toll-like receptor (TLR)4 in determination of Mtb infection outcome. METHODS: Several scientific databases, including Scopus, PubMed, and Google Scholar, were used for searching appropriate research articles from the literature for information on our topic. RESULTS: TLR4 plays positive roles in induction of immune responses against Mtb and participates in eradication of the infection. Some limited investigations approved the roles of TLR4 in induction of apoptosis in macrophages during tuberculosis (TB) and attenuation of immune responses in some situations. CONCLUSIONS: TB outcome appears to be dependent on TLR4/Mtb interaction and several factors, including bacterial load and immune or nonimmune cells, as hosts. Also, other TLR/Mtb interactions can affect TLR4 responses.

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)0.008
metaresearch head score (Gemma)0.014
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Meta-epidemiology (broad), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.315
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.014
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0160.001
Bibliometrics0.0010.003
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.008

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 head0.039
GPT teacher head0.372
Teacher spread0.333 · 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