The query targets "Yuhan Fu," but the supplied citation metrics belong to "Yu-ting Fu" (h-index 2, 6 citations, 3 papers) whose titles (salted casings, wildlife conservation, liquid desiccant dehumidifiers) do not match any of the six reviewed papers β a clear author-disambiguation conflict. OpenAlex lists at least three distinct "Yuhan Fu" profiles (h-indices 4β5, 363, 131, and 97 citations) with no ORCID linkage to the papers below, so any single-profile metric assignment is uncertain and likely conflated. This review therefore judges the scientific work on its own merit, treating author-level metrics as unreliable provenance.
Tuberculosis genomics (2022β2023): Two regional Chinese studies anchor the biomedical work. The larger BMC Genomics analysis (424 WGS samples, 357 RR-TB) reports adjusted ORs of 1.332 (MIRU10), 1.257 (MIRU39), and 1.400 (QUB4156), all statistically significant, with open data (SRP134826, CRA000786) supporting reproducibility β though the observational design cannot establish causality and results may not generalize beyond Chinese CDC-sourced strains . The smaller Anqing study (194 isolates, only 19 RR-TB) reports an implausibly wide OR of 195.2 (95% CI 46.3β823.5) for rpoB mutation predicting resistance, and contains an internal inconsistency: 19 vs 27 RR-TB strains between text and table β a red flag for reporting rigor .
Cancer immunology (2026, JCI): The tescalcin study is the strongest work β a mechanistic chain (H3K4me3 β TESC β ER CaΒ²βΊ β CALR exposure β APC phagocytosis β CD8βΊ T-cell response) supported by a prospective trial cohort (NCT03869034; AUC=0.88 for predicting ICB response), multiple mouse models including a spontaneous hepatoma, rescue with the D128A mutant, and deposited multi-omics data . Limitations: correlative human data, mouse-to-human translational gaps, and untested inhibitor safety.
Chemistry/catalysis (2018β2024): The ChemCatChem DRM paper (quality 9, novelty 9) is a well-characterized mechanistic study (100 h time-on-stream, coke 3.0% vs 4.8β16.3% for controls) but lacks public raw data . The SAC review is comprehensive (224 refs) but risks selective coverage of positive results .
Veterinary virology (2026 preprint): CPV-VLP work is methodologically sound for a preprint (23.5 nm assembly, HAI ~1:29) but suffers from n=5 groups, no canine challenge data, and no endotoxin assessment .
The corpus shows genuine methodological breadth (bioinformatics pipelines, wet-lab immunology, catalysis, VLP engineering) and increasing sophistication over time, peaking with the JCI paper's multi-modal causal design. However, the TB work shows reporting inconsistencies and implausibly wide confidence intervals typical of small, single-region samples, and identity/metrics remain unverifiable. What would change this assessment: confirmation of which OpenAlex profile belongs to the author, independent replication of the MIRUβrpoB association in non-Chinese populations, and canine-host challenge data for the VLP claims.
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