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Record W7133033012

Listeriolysin O Induces a Phagosome Stress Response during Listeria monocytogenes Growth in Spacious Vacuoles

2022· dissertation· W7133033012 on OpenAlexaff
Kate Elizabeth Bottomley

Bibliographic record

VenueTSpace · 2022
Typedissertation
Language
FieldBiochemistry, Genetics and Molecular Biology
TopicListeria monocytogenes in Food Safety
Canadian institutionsAmgen (Canada)
Fundersnot available
KeywordsListeriolysin OPhagosomeListeria monocytogenesVacuoleCytolysinSecretionListeriaIntracellular
DOInot available

Abstract

fetched live from OpenAlex

Despite a traditional view of Listeria monocytogenes as a cytosolic pathogen, our group previously found that in macrophages a subset of Listeria occupies spacious vacuolar compartments. Intriguingly, this replication niche is achieved through secretion of low levels of listeriolysin O (LLO), a listerial pore forming cytolysin known to promote vacuolar escape. While cells coordinate a variety of systems for repair and removal to counteract compromised membrane integrity, spacious Listeria-containing phagosomes (SLAPs) block maturation into microbicidal phagolysosomes. The mechanisms by which LLO initiates this niche for growth in macrophages has remained unclear. My research has focused on characterizing these persistent structures and how they evade degradation. I have discovered a complex network of proteins, lipids, and lack thereof, attributing to sustained Listeria infection in SLAPs. Altogether, this characterization serves as a valuable resource for future host-pathogen studies, and emphasizes the many subversive tools developed by pathogens to ensure intracellular survival.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.049
GPT teacher head0.368
Teacher spread0.319 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations0
Published2022
Admission routes1
Has abstractyes

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