MétaCan
Menu
Back to cohort
Record W4378744885 · doi:10.1007/s11739-023-03320-w

Gut inflammation and tumorigenesis: every site has a different tale to tell

2023· review· en· W4378744885 on OpenAlexaff
Alessandro Vanoli, Paola Parente, Matteo Fassan, Luca Mastracci, Federica Grillo

Bibliographic record

VenueInternal and Emergency Medicine · 2023
Typereview
Languageen
FieldMedicine
TopicHelicobacter pylori-related gastroenterology studies
Canadian institutionsUniversity Hospital Foundation
FundersUniversità degli Studi di Pavia
KeywordsMedicineAdenocarcinomaDysplasiaInflammatory bowel diseaseInflammationGastrointestinal tractPathologyCarcinogenesisHelicobacter pyloriEnteropathyNeuroendocrine tumorsCancerGastroenterologyInternal medicineDisease

Abstract

fetched live from OpenAlex

Gut inflammation has been correlated with cancerogenesis by disrupting gastrointestinal homeostasis. Numerous chronic inflammatory disorders of the tubular gastrointestinal tract (e.g., gastroesophageal reflux disease, Helicobacter pylori-induced and autoimmune chronic gastritis, celiac disease, and inflammatory bowel diseases) have been variably associated with an increased neoplastic risk. Gastrointestinal inflammation-induced neoplasms include epithelial tumors (esophageal squamous cell carcinoma and adenocarcinoma, gastric adenocarcinoma and neuroendocrine tumors, small bowel adenocarcinoma and neuroendocrine tumors, and colorectal cancer) and lymphomas (such as gastric marginal zone lymphomas and enteropathy-associated T cell lymphoma). In the last decades, numerous studies have investigated the pathogenetic mechanisms and the microenvironmental/microbiome changes that trigger genetic and/or epigenetic alterations eventually leading to tumorigenesis, often through a histologically recognizable inflammation-dysplasia-carcinoma cancerogenic sequence. In the present review, an overview of the current knowledge on the links between inflammatory diseases and neoplasms of the tubular GI tract, applying a site-by-site approach, is provided.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.875
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.090
GPT teacher head0.351
Teacher spread0.261 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations19
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueInternal and Emergency MedicineSame topicHelicobacter pylori-related gastroenterology studiesFrench-language works237,207