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Transforming Growth Factor-Beta 1 Induces Neutrophil Apoptosis in Colorectal Cancer Liver Metastases

2023· preprint· en· W4375841114 on OpenAlexaff
Miran Rada, Migmar Tsamchoe, Jessica de Bloom, Diane Kim, Stephanie Petrillo, Anthoula Lazaris, Peter Metrakos

Bibliographic record

VenuePreprints.org · 2023
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Lipids, and Metabolism
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsDownregulation and upregulationApoptosisCancer researchColorectal cancerIn vitroTransforming growth factor betaPoly ADP ribose polymeraseTransforming growth factorChemistryMetastasisInternal medicineMedicineCancerPolymeraseBiochemistryEnzymeGene

Abstract

fetched live from OpenAlex

Vessel co-option correlates with resistance against anti-angiogenic agents and chemotherapy in colorectal cancer liver metastasis (CRCLM). We previously identified higher intensity of neutrophils in the tumour microenvironment of vessel co-opting CRCLM lesions compared to their angiogenic counterparts. Herein, we demonstrated that over 50% of the neutrophils in vessel co-opting lesions are expressing pro-apoptotic markers including cleaved caspase-3 and poly (ADP-ribose) polymerase-1 (PARP-1). Our previous publications suggested upregulation of transforming growth factor-beta (TGFβ1) in the microenvironment of vessel co-option CRCLM. Therefore, we examined the effect of TGFβ1 on the expression of cleaved caspase-3 and PARP-1 in neutrophils in vitro. Significantly, we noticed the upregulation of pro-apoptotic markers upon exposure to TGFβ1. This finding might pave the way to determine the role of neutrophils in developing vessel co-option in CRCLM in the future.

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 score0.002
Threshold uncertainty score0.006

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)0.0020.000

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 head0.084
GPT teacher head0.327
Teacher spread0.243 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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