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Record W4387462047 · doi:10.34172/bi.2023.27829

Introduction of a new recombinant vaccine based on GRP78 for breast cancer immunotherapy and evaluation in a mouse model

2023· article· en· W4387462047 on OpenAlexaff
Hamed Zare, Hamid Bakherad, Arman Nasr Esfahani, Mohamad Norouzi, Hossein Aghamollaei, Seyed Latif Mousavi Gargari, Fatemeh Mahmoodi, Mahdi Aliomrani, Walead Ebrahimizadeh

Bibliographic record

VenueBioimpacts · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEndoplasmic Reticulum Stress and Disease
Canadian institutionsMcGill University Health Centre
FundersIsfahan University of Medical Sciences
KeywordsImmunotherapyBreast cancerImmune systemMedicineImmunologyCancerCancer immunotherapyCancer vaccineCytokineCancer researchAntibodyInternal medicine

Abstract

fetched live from OpenAlex

Introduction: Breast cancer is one of the most prevalent malignancies in women. Several treatment options are available today, including surgery, chemotherapy, and radiotherapy. Immunotherapy, as a highly specific therapy, involves adaptive immune responses and immunological memory. In our present research, we used the recombinant C-terminal domain of the GRP78 (glucose- regulated protein 78) protein to induce an immune response and investigate its therapeutic impact in the 4T1 breast cancer model. Methods: 4T1 tumor cells. Subsequently, tumor size and survival rate measurements, MTT, and cytokine assays were performed. Results: The animals receiving the cGRP78 vaccine showed significantly more favorable survival and slower tumor growth rates compared with unvaccinated tumor-bearing mice as the negative control mice. Circulating levels of tumoricidal cytokines such as IFNγ were higher, whereas tolerogenic cytokines such as IL-2, 6, and 10 either did not increase or had a decreasing trend in mice receiving cGRP78. Conclusion: cGRP78 vaccines generated potent immunotherapeutic effects in a breast cancer mouse model. This novel strategy of targeting the GRP78 protein can promote the development of cancer vaccines and immunotherapies for breast cancer malignancies.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.535
Threshold uncertainty score0.278

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)0.0000.000

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 head0.019
GPT teacher head0.306
Teacher spread0.287 · 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 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

Citations6
Published2023
Admission routes1
Has abstractyes

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