Experiments
Searchable full-text extractions: founding hypothesis, core claims, experimental setups, key results and statistics — pulled out of each paper as structure. Search a cell line, an assay or an entity (e.g. HUH7) and find every paper that worked with it. This corpus stands on its own: most entries carry no reproduction assessment (yet).
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Has reproduction · 49
LRP1 as a potential diagnostic and immunomodulatory target in endometriosis: evidence from multi-omics and single-cell analyses.
PMID 42064072 · PMC13124487 · Frontiers in immunology · 2026 · 7 claims · 8 setups
LRP1 is the top hub gene with the highest diagnostic performance for distinguishing ectopic from eutopic endometrium in EMS
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Has reproduction · 50
The molecular landscape of sepsis severity in infants: enhanced coagulation, innate immunity, and T cell repression.
PMID 38817614 · PMC11137207 · Frontiers in immunology · 2024 · 7 claims · 7 setups
Most published adult/other-cohort sepsis gene signatures have limited utility for infant sepsis; only 2 of 7 achieved >80% accuracy in infants
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Has reproduction · 92
Large-scale integration of single-cell transcriptomic data captures transitional progenitor states in mouse skeletal muscle regeneration.
PMID 34773081 · PMC8589952 · Communications biology · 2021 · 8 claims · 7 setups
Large-scale integration of 111 sc/snRNAseq datasets captures rare, transitional myogenic progenitor states (commitment and fusion) that are poorly represented in individual datasets.
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Has reproduction · 71
Single-Cell Transcriptomic Landscape of Right-Sided Colon Cancer Reveals Cellular and Molecular Features of Metastatic Potential.
PMID 41898210 · PMC13024220 · Biomedicines · 2026 · 8 claims · 8 setups
Liver metastatic potential in RCC is marked by stem-like tumor states, metabolic plasticity, and microenvironmental remodeling.
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Has reproduction · 93
Epistemic uncertainty challenges aging clock reliability in predicting rejuvenation effects.
PMID 39072888 · PMC11561706 · Aging cell · 2024 · 8 claims · 8 setups
DNA methylation profiles observed across cellular reprogramming are poorly represented in the training data of existing aging clocks, introducing high out-of-distribution/epistemic uncertainty in their age estimates