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Record W4405850907 · doi:10.1101/2024.12.23.629453

Characterizing postoperative T and B cell dysfunction in cancer surgery patients, using COVID-19 as a model antigen

2024· preprint· en· W4405850907 on OpenAlexaff
Oladunni Olanubi, Rafeah Alam, Christiano Tanese de Souza, Richard Hu, Angela M. Crawley, Rebecca C. Auer

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2024
Typepreprint
Languageen
FieldMedicine
TopicCancer Immunotherapy and Biomarkers
Canadian institutionsOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsImmune systemCD8AntigenMedicineDiseaseSurgical stressT cellAntibodyImmunologyCellCancerCytotoxic T cellCoronavirus disease 2019 (COVID-19)B cellInternal medicineBiologyIn vitro

Abstract

fetched live from OpenAlex

Abstract For most cancers, surgery is an effective intervention method for cure but, despite the benefits, many patients recur with metastatic disease. Surgery has been shown to impair immune function by causing suppression of immune cells. In this study, we used a COVID-19 immunological toolkit to answer questions regarding the effects of surgery on antigen specific CD8 + T cells and B cells by exploiting the responses to the spike protein in vaccinated cancer patients. We demonstrate that surgical stress results in a reduction in the number of CD8 + T cell that produce cytokines and B cells that secrete antibodies in response to antigen. This study will improve our understanding of surgery-induced T cell and B cell dysfunction

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.031
GPT teacher head0.272
Teacher spread0.241 · 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 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

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

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