ReviewAnimal models and experimental medicine2025
Research advancements and evaluation of multifactor-induced murine models for gastric cancer.
Review in Animal models and experimental medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Research advancements and evaluation of multifactor-induced murine models for gastric cancer.Animal models and experimental medicine · 2025Review
- Mechanisms and applications of N-Methyl-N'-nitro-N-nitrosoguanidine in animal tumor models: current situation and challenges.Frontiers in oncology · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
As one of the most prevalent gastrointestinal malignancies in humans, gastric cancer (GC) is often detected at an advanced stage, resulting in a poor prognosis and ranking it the fifth leading cause of cancer-related deaths. Due to their high genomic correlation with humans, mice are ideal in vivo models for investigating GC-related pathogenesis and therapeutic interventions. This review provides an overview of different GC models, including genetically engineered, transplantation-based models, and chemically or biologically induced models, and discusses the recent advancements for each type, highlighting their unique contributions to the field. In addition, it summarizes the strengths, limitations, and typical applications of these models and offers a critical assessment of their applicability in research while acknowledging their current limitations in fully mirroring human GC progression. Furthermore, we analyze how each model accurately recapitulates the complexities of human GC and evaluate their potential for clinical translation. This review provides a reference for model selection in future GC research.
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Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.