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Evaluation of a new Recombinant BCG which Contains Mycobacterial Antigen ag85B–mpt64<sub>190–198</sub>–mtb8.4 in C57/BL6 Mice

2008· article· en· W1993182031 on OpenAlexfundno aff
Ya qing Qie, J. L. Wang, Bingdong Zhu, Ying Xu, Qingyang Wang, Junming Chen, Hong‐Hai Wang

Bibliographic record

VenueScandinavian Journal of Immunology · 2008
Typearticle
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsnot available
FundersNational High-tech Research and Development ProgramPenn State College of MedicineFudan UniversityQueen's University
KeywordsImmunogenicityAntigenESAT-6Mycobacterium tuberculosisImmune systemImmunologyTuberculosisVirologyBiologyRecombinant DNAAdjuvantAntibodyMycobacterium bovisBCG vaccineVaccinationGeneMedicineGenetics

Abstract

fetched live from OpenAlex

Tuberculosis (TB) caused by Mycobacterium tuberculosis continues to be one of the major public health problems in the world. The eventual control of this disease will require the development of a safe and effective vaccine. Bacille Calmette-Guerin (BCG), the only vaccine against TB, is not perfect for its limited ability to protect against the adult form of TB. Some improvements of TB vaccines relied to strengthening the immunogenicity and/or persistence of genetically modified recombinant BCG (rBCG) strain. Antigen 85B (Ag85B) and Mtb8.4 are importantly immunodominant antigens of M. tuberculosis, and both are very promising vaccine candidate molecules. MPT64(190-198), is presented to CD8(+) T cells during mycobacterial infections. In this study, we combined these above genes into one recombinant gene of ag85B-mpt64(190-198)-mtb8.4. Then we constructed the new rBCG containing this united gene. This rBCG can induce an increased Th1-type immune response in mice, characterized by an elevated level of interferon-gamma in antigen-stimulated splenocyte culture and a strong IgG2a antibody response. Also, it can elicit longer immune responses than BCG. The results show that this rBCG is a promising candidate for further study.

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)0.004
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.739
Threshold uncertainty score0.898

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.060
GPT teacher head0.338
Teacher spread0.278 · 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.

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

Citations14
Published2008
Admission routes1
Has abstractyes

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