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Record W2913459845 · doi:10.1038/s41598-018-38371-z

Lambda bacteriophage nanoparticles displaying GP2, a HER2/neu derived peptide, induce prophylactic and therapeutic activities against TUBO tumor model in mice

2019· article· en· W2913459845 on OpenAlexaff
Atefeh Razazan, Jessica Nicastro, Roderick Slavcev, Nastaran Barati, Atefeh Arab, Fatemeh Mosaffa, Mahmoud Reza Jaafari, Javad Behravan

Bibliographic record

VenueScientific Reports · 2019
Typearticle
Languageen
FieldMedicine
TopicMonoclonal and Polyclonal Antibodies Research
Canadian institutionsRegional Municipality of WaterlooBlackberry (Canada)Princess Margaret Cancer CentreUniversity of Waterloo
FundersMashhad University of Medical Sciences
KeywordsBacteriophageCapsidCTL*PeptideCytotoxic T cellPhage displayImmune systemVirologyHER2/neuCancer researchBiologyVirusMolecular biologyCancerImmunologyEscherichia coliBiochemistryGeneCD8In vitro

Abstract

fetched live from OpenAlex

Generating a protective and long-lasting immune response is the primary goal in the expanding field of immunotherapeutic research. In current study we designed an immunogenic bacteriophage- based vaccine to induce a cytotoxic T lymphocyte activity against a mice tumor model over-expressing HER2/neu. Bacteriophage λ displaying a HER2/neu derived peptide GP2 was constructed and used as an anti-cancer vaccine in a BALB/c mouse xenograft tumor model. The results of our study indicated that phage nanoparticles displaying GP2 as a fused peptide to the gpD phage capsid protein induced a robust CTL response. Furthermore, the chimeric phage nanoparticles protected mice against HER2/neu-positive tumor challenge in both prophylactic and therapeutic settings. In conclusion, we propose that λ phage nanoparticles decorated with GP2 peptide merit further investigation for the development of peptide-based vaccines against HER2/neu overexpressing tumors.

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 score0.000
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0000.000

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 head0.022
GPT teacher head0.279
Teacher spread0.257 · 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

Citations41
Published2019
Admission routes1
Has abstractyes

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