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Record W2032067602 · doi:10.1017/s0031182008004757

High-yield amplification of<i>Cryptosporidium parvum</i>in interferon γ receptor knockout mice

2008· article· en· W2032067602 on OpenAlexaff
Julia von Oettingen, Milli Nath-Chowdhury, Brian J. Ward, Arne C. Rodloff, Michael J. Arrowood, Momar Ndao

Bibliographic record

VenueParasitology · 2008
Typearticle
Languageen
FieldImmunology and Microbiology
TopicParasitic Infections and Diagnostics
Canadian institutionsMcGill UniversityMontreal General Hospital
Fundersnot available
KeywordsCryptosporidium parvumBiologyFecesMicrobiologyIn vivoInoculationEimeriaApicomplexaCryptosporidiumInterferonVeterinary medicineVirologyImmunologyProtozoal diseaseBiotechnology

Abstract

fetched live from OpenAlex

To date, large-scale production of Cryptosporidium parvum oocysts has only been achieved by amplification in neonatal calves and sheep. Many laboratories currently depend on supplies from external sources and store oocysts for prolonged periods which results in progressive loss of viability. Six to 8-week-old interferon gamma receptor knockout (IFN gamma R-KO) mice on a C57BL/6 background were inoculated by gavage (2000 oocysts/animal). Fecal pellets were collected daily from 7 days post-infection (p.i.) up to 2 weeks p.i. Intestinal oocyst yield was assessed at days 11, 12 and 14 p.i. by homogenization of intestinal tissues. Ether extraction and one or more NaCl flotations were used to purify oocysts. Total recoveries averaged 2.6 x 10(6) oocysts/mouse from fecal material and 3.8 x 10(7) oocysts/mouse from intestinal tissues. Overall, 2.3 x 10(9) purified oocysts were obtained from 60 mice. Recovered oocysts were capable of sporulation and were shown to be infectious both in vitro and in vivo. Oocyst amplification was achieved in only 11-14 days with minimal expense. The simplicity of this method presents a practical alternative for the routine passage, maintenance and storage of C. parvum in biomedical laboratories.

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 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 categoriesInsufficient payload (model declined to judge)
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 score0.028
Threshold uncertainty score0.999

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)0.0010.002

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 head0.020
GPT teacher head0.265
Teacher spread0.246 · 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 teacher head, not a consensus.

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

Citations22
Published2008
Admission routes1
Has abstractyes

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