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Record W7066087921

Genetic analysis of differential susceptibility to infection with Candida albicans in mice

2004· dissertation· en· W7066087921 on OpenAlexaboutno aff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2004
Typedissertation
Languageen
FieldMedicine
TopicAntifungal resistance and susceptibility
Canadian institutionsnot available
Fundersnot available
KeywordsCandida albicansCongenicGenetic analysisGenePopulationCorpus albicansHost (biology)Mutation
DOInot available

Abstract

fetched live from OpenAlex

The importance of host factors in determining susceptibility to systemic Candida albicans infections is evident in both humans and mice. We have used a mouse model to study the genetic basis of susceptibility, using the inbred strains A/J and C57BL/6J, which are susceptible and resistant to infection, respectively, based on different parameters of response to infection. To identify genes responsible for this differential host response, brain and kidney fungal load were measured in 128 [A/J x C57BL/6J]F 2 mice 48 hours after infection with 5x104 C. albicans blastospores. Segregation analysis in this informative population identified complement component 5 (C5/Hc) as the major gene responsible for this differential susceptibility (LOD of 22.7 for kidney, 19.0 for brain), with a naturally-occurring mutation that causes C5 deficiency leading to enhanced susceptibility. C5 was also found to control heart fungal load, survival time, and serum TNF-alpha levels during infection. Investigation of the response to C. albicans challenge in a series of AcB/BcA recombinant congenic strains validated the importance of C5 in determining the host response, although some strains with discordant phenotypes were identified, suggestive of alternate mechanisms of genetic control.

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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.011
GPT teacher head0.262
Teacher spread0.251 · 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
Published2004
Admission routes1
Has abstractyes

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