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Lgr5 Contributes to Intestinal Metaplasia During Gastric Carcinogenesis: A Meta analysis

2016· review· en· W2235461151 on OpenAlexaff
Ye Han, Qiaoming Zhi, Xiaofeng Xue, Bin Yuan, Hong Zhao, Yuting Kuang, Lifeng Zhang

Bibliographic record

VenueAnti-Cancer Agents in Medicinal Chemistry · 2016
Typereview
Languageen
FieldMedicine
TopicCancer Cells and Metastasis
Canadian institutionsSaskatchewan Cancer Agency
Fundersnot available
KeywordsInternal medicineCarcinogenesisIntestinal metaplasiaMeta-analysisLGR5MedicineGastroenterologyCancerMetastasisOncologyPathologicalCancer stem cell

Abstract

fetched live from OpenAlex

Lgr5, which is a somatic stem cell biomarker, plays an important role during the carcinogenesis and tumor progression. But in gastric cancer, the functions of Lgr5 still remain controversial. Our meta-analysis is performed to evaluate the potential associations between Lgr5 and the outcome of patients with gastric cancer (GC). In our study, a total of 6 studies comprising 1092 patients were included. Our results demonstrated that high expression of Lgr5 was not associated to the depth of tumor invasion (pooled OR=1.395, CI95%=0.652-2.958, P=0.392, random-effect), gender of patients (pooled OR=1.264, 95%CI=0.933-1.713, P=0.13, fixed effect), tumor distance metastasis (pooled OR=1.1, 95%CI=0.734-3.754, P=0.772, random-effect), tumor size (pooled OR=0.977, 95%CI=0.705-1.353, P=0.887, random-effect), TNM stages (pooled OR=1.304, 95%CI=0.449-3.789, p=0.625, random-effect) and lymph node metastasis (pooled OR=1.507, 95%CI=0.829-2.738, P=0.178, random-effect). But interestingly, the expression of Lgr5 was associated with the age of GC patients (pooled OR=1.731, 95%CI=1.082-2.769, P=0.02) and Lauren type of GC (OR=2.284, 95%CI=1.611-3.238, P<0.001). Our findings indicated that Lgr5 might contribute to the intestinal metaplasia during gastric carcinogenesis. This difference in pathological Lauren's classification is of practical significance for us to make about appropriate treatment options in gastric cancer.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.500
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0080.003
Bibliometrics0.0010.004
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.108
GPT teacher head0.397
Teacher spread0.289 · 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 designMeta-analysis
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

Citations2
Published2016
Admission routes1
Has abstractyes

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