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Record W1536561871 · doi:10.1089/027245701300060445

Establishment of Hybridoma Cell Lines Producing Monoclonal Antibodies Against Hepatitis B Virus Surface Antigens (a, d, and r) and Development of Sensitive ELISA Diagnostic Test

2001· article· en· W1536561871 on OpenAlexaff
Xinli Tang, Xiugang Zhang, Huimin Xu

Bibliographic record

VenueHybridoma · 2001
Typearticle
Languageen
FieldMedicine
TopicMonoclonal and Polyclonal Antibodies Research
Canadian institutionsCanadian Food Inspection Agency
Fundersnot available
KeywordsHBsAgMonoclonal antibodyHepatitis B virusMolecular biologyVirologyAntigenHorseradish peroxidaseAntibodyCell cultureChemistryBiologyVirusImmunologyEnzymeBiochemistry

Abstract

fetched live from OpenAlex

A new treble-coated enzyme-linked immunoadsorbent assay (ELISA) kit of detecting Hepatitis B virus (HBV) surface antigen subtypes a, d and r (HBsAg-a, -d, -r) was developed by using four established hybridoma cell lines, of which two specifically secrete monoclonal antibodies (MAbs) against HBsAg-a (anti-HBsAg-a), one against -d (anti-HBsAg-d), and one against -r (anti-HBsAg-r). The approach of hybridoma cell lines' establishment were by fusing myeloma cells (SP2/0) with splenocytes from BALB/c mice immunized with a mixture of HBsAg-a, -d, -r. The ascitic MAb productivity of the four cell lines was at the titres of 1:10(6)-1:10(8). A treble-coated ELISA based HBV diagnostic kit was developed for detecting all of the three responding subtypes of HBsAgs. A 96-well ELISA microplate was coated with anti-HBSAg-a, -d, -r at a ratio of 3: 1: 0.5, with a horseradish peroxidase (HRP) conjugated anti-HBsAg-a as the labelled antibody. For clinical application, the new developed diagnostic kit detected HBsAgs of adr, adw, ayr, and ayw at a rate of lower than 0.25, 0.25, 0.5, and 0.5 ng/mL, respectively. Results indicated that this kit was more rapid and sensitive than that other current ELISA-based kits coated with a single MAb (e.g., anti-HBsAg-a).

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.227
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.020
GPT teacher head0.269
Teacher spread0.249 · 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 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

Citations4
Published2001
Admission routes1
Has abstractyes

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