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Record W2980215047 · doi:10.1128/mbio.02169-19

A Genome-Wide Knockout Screen in Human Macrophages Identified Host Factors Modulating <i>Salmonella</i> Infection

2019· article· en· W2980215047 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuemBio · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSalmonella and Campylobacter epidemiology
Canadian institutionsInstitute of Infection and Immunity
FundersCanadian Institutes of Health ResearchNational Research Foundation of KoreaGovernment of CanadaWellcome TrustWellcome
KeywordsSalmonellaBiologySalmonella infectionPhenotypeSalmonella entericaMicrobiologyGeneGeneticsBacteria

Abstract

fetched live from OpenAlex

Salmonella exploits macrophages to gain access to the lymphatic system and bloodstream to lead to local and potentially systemic infections. With an increasing number of antibiotic-resistant isolates identified in humans, Salmonella infections have become major threats to public health. Therefore, there is an urgent need to identify alternative approaches to anti-infective therapy, including host-directed therapies. In this study, we used a simple genome-wide screen to identify 183 candidate host factors in macrophages that can confer resistance to Salmonella infection. These factors may be potential therapeutic targets against Salmonella infections.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.404
Threshold uncertainty score0.682

Codex and Gemma teacher scores by category

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)0.0010.000

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 head0.022
GPT teacher head0.240
Teacher spread0.217 · 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