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Assessment of the serodiagnostic potential of nine novel proteins from<i>Mycobacterium tuberculosis</i>

2001· article· en· W2042334041 on OpenAlexaff
Alison J Moran, Janice D. Treit, Janice L Whitney, Bassam Abomoelak, Raymond L. Houghton, Yasir A. W. Skeiky, D Pedral-Sampaio, Roberto BadarÃ, Francis E. Nano

Bibliographic record

VenueFEMS Microbiology Letters · 2001
Typearticle
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsUniversity of Victoria
FundersNational Institute of Allergy and Infectious Diseases
KeywordsMycobacterium tuberculosisAntigenTuberculosisRecombinant DNAVirologySerologyBiologyAntibodyMicrobiologyTuberculosis diagnosisImmunologyGeneMedicineGeneticsPathology

Abstract

fetched live from OpenAlex

To identify antigens that would improve the accuracy of serological diagnosis of active tuberculosis, we cloned the genes encoding nine potentially immunogenic secreted or surface-associated proteins of Mycobacterium tuberculosis. Recombinant proteins were reacted with sera from HIV-negative individuals with extrapulmonary tuberculosis (EP-TB) or HIV-positive individuals with pulmonary tuberculosis (TBH). Specific and high level antibody responses were obtained for four recombinant proteins, of which antigen GST-822 was recognized by 60% of EP-TB and 42% of TBH and antigen MBP-506 was recognized by 45% of EP-TB and 61% of TBH. These results suggest that these proteins are strong candidates as subunits in a polyvalent serodiagnostic test.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0000.000

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 head0.014
GPT teacher head0.277
Teacher spread0.263 · 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

Citations26
Published2001
Admission routes1
Has abstractyes

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