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Record W3112605892 · doi:10.1093/carcin/bgaa106

Chemokines in hepatocellular carcinoma: a meta-analysis

2020· review· en· W3112605892 on OpenAlexaff
Xiongfeng Pan, Atipatsa Chiwanda Kaminga, Shi Wu Wen, Aizhong Liu

Bibliographic record

VenueCarcinogenesis · 2020
Typereview
Languageen
FieldMedicine
TopicChemokine receptors and signaling
Canadian institutionsOttawa HospitalUniversity of Ottawa
FundersHunan Provincial Key Laboratory of Clinical Epidemiology
KeywordsMeta-analysisHepatocellular carcinomaChemokineCCL20CXCR4OncologyInternal medicineMedicineSorafenibConfidence intervalChemokine receptorCochrane LibraryImmunologyReceptor

Abstract

fetched live from OpenAlex

Accumulating evidence suggests that chemokines may play an important role in the formation and mediating of the immune microenvironment of hepatocellular carcinoma (HCC). The purpose of this meta-analysis was to explore the differences in blood or tissues chemokines concentrations between HCC patients and controls. Online databases, namely PubMed, Web of Science, Embase and Cochrane Library, were systematically searched for relevant articles published on or before 15 January 2020. Standardized mean differences (SMDs) with corresponding 95% confidence intervals of the chemokines concentrations were calculated as group differences between the HCC patients and the controls. Sixty-five studies met the inclusion criteria for the meta-analysis. Altogether they consisted of 26 different chemokines compared between 5828 HCC patients and 4909 controls; and 12 different chemokines receptors compared between 2053 patients and 2285 controls. The results of meta-analysis indicated that concentrations of CCL20, CXCL8 and CXCR4 in the HCC patients were significantly higher than those in the controls (SMD of 6.18, 1.81 and 1.04, respectively). Therefore, higher concentration levels of CCL20, CXCL8 and CXCR4 may indicate the occurrence of HCC Future research should explore the putative mechanisms underlying this linkage. Meanwhile, attempts can be made to replicate the existing findings in prospective cohort populations and explore the cause-and-effect relationships pertaining to this linkage in order to develop new diagnostic and therapeutic strategies for HCC.

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), Meta-epidemiology (broad), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.493
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0120.012
Bibliometrics0.0010.004
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.182
GPT teacher head0.347
Teacher spread0.165 · 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

Citations14
Published2020
Admission routes1
Has abstractyes

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