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Record W2011089730 · doi:10.1111/imr.12268

Immunoevasion and immunosuppression of the macrophage by <i><scp>M</scp>ycobacterium tuberculosis</i>

2015· review· en· W2011089730 on OpenAlexafffund
Zakaria Hmama, Sandra Peña‐Díaz, Sunil Joseph, Yossef Av‐Gay

Bibliographic record

VenueImmunological Reviews · 2015
Typereview
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsInstitute of Infection and ImmunityUniversity of British Columbia
FundersCanadian Institutes of Health Research
KeywordsImmunosuppressionTuberculosisImmunologyMacrophageBiologyVirologyMedicinePathologyGenetics

Abstract

fetched live from OpenAlex

By virtue of their position at the crossroads between the innate and adaptive immune response, macrophages play an essential role in the control of bacterial infections. Paradoxically, macrophages serve as the natural habitat to Mycobacterium tuberculosis (Mtb). Mtb subverts the macrophage's mechanisms of intracellular killing and antigen presentation, leading ultimately to the development of tuberculosis (TB) disease. Here, we describe mechanisms of Mtb uptake by the macrophage and address key macrophage functions that are targeted by Mtb-specific effector molecules enabling this pathogen to circumvent host immune response. The macrophage functions described in this review include fusion between phagosomes and lysosomes, production of reactive oxygen and nitrogen species, antigen presentation and major histocompatibility complex class II expression and trafficking, as well as autophagy and apoptosis. All these are Mtb-targeted key cellular pathways, normally working in concert in the macrophage to recognize, respond, and activate 'proper' immune responses. We further analyze and discuss major molecular interactions between Mtb virulence factors and key macrophage proteins and provide implications for vaccine and drug development.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.077
GPT teacher head0.379
Teacher spread0.303 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations295
Published2015
Admission routes2
Has abstractyes

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