Xiaoguang Liu on Muck Rack

Xiaoguang Liu

As seen in: Nature, Wiley Online Library, ScienceDirect, Frontiers, MDPI, Taylor & Francis Online, ACS Publications, JAMA (The Journal of the American Medical Association), Journal of Chemical & Engineering Data, Royal Society of Chemistry, Cell Press and
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Articles

Radiometal-Based PET Imaging: Coordination Chemistry as a Determinant of In Vivo Performance

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By Xiaoguang Liu, Wenbo Liu, Min Lai
| Wiley Online Library Verified
1 Introduction Positron emission tomography (PET) based on radiometal complexes has become a central modality for molecular imaging, enabling the visualization of biological processes over time scales that are inaccessible to short-lived organic tracers [1]. In parallel with advances in radionuclide production and targeting vector engineering, radiometal PET has expanded rapidly into applications ranging from peptide imaging to immuno-PET and, more recently, theranostic strategies [2].
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Unraveling configurational pathways to regional environmental performance: a multi-period fsQCA analysis of China’s governance dynamics

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By Shizheng Tan, Xiaoguang Liu, Wei Li, Pengfei Li
| Nature Verified
Abstract Amid global climate change and environmental degradation, effective environmental governance has become a central concern for scholars and policymakers. This study proposes a pressure–state–response–environment (PSRE) framework that links external pressures (public and peer pressure), regional states (population, affluence, and technology), and organizational responses (government regulation and environmental fiscal expenditure) to assess environmental performance (EP).
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Cancer-specific survival patterns in patients with bone metastasis: a registry-based analysis of 13,742 patients

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By Yanchao Tang, Jie Sun, Gangqiang Zhang, Feng Wei, Xiaoguang Liu, Zelin Yun, Juncai Lei
| Nature Verified
Abstract With increasing opportunities for patients with bone metastasis (BM) to benefit from local surgical intervention, accurate survival analysis across different primary cancers remains challenging. Current analytical frameworks commonly rely on single-center, pan-cancer cohorts and provide insufficient integration of cancer-specific characteristics.
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