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Feng Gao

Researcher at Washington University in St. Louis

Publications -  326
Citations -  13828

Feng Gao is an academic researcher from Washington University in St. Louis. The author has contributed to research in topics: Breast cancer & Cancer. The author has an hindex of 59, co-authored 315 publications receiving 11747 citations. Previous affiliations of Feng Gao include Hospital of the University of Pennsylvania & University of Washington.

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Expression of programmed death ligand 1 (PD-L1) is associated with poor prognosis in human breast cancer

TL;DR: This is the first study to demonstrate that PD-L1 expression is an independent negative prognostic factor in human breast cancer, which has important implications for the application of antibody therapies targeting the PD-1/PD- L1 signaling pathway in this disease.
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In vivo molecular photoacoustic tomography of melanomas targeted by bioconjugated gold nanocages.

TL;DR: High-resolution photoacoustic tomography (PAT) with extraordinarily optical absorbing gold nanocages (AuNCs) can serve as a novel contrast agent for in vivo molecular PAT of melanomas with both exquisite sensitivity and high specificity.
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Trends in Stage Distribution for Patients with Non-small Cell Lung Cancer: A National Cancer Database Survey

TL;DR: It is likely that increased acceptance and widespread use of 18fluorodeoxyglucose-positron emission tomography scan and routine brain imaging could account for the recent and significant stage migration in patients with NSCLC.
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Higher Than Normal Plasma Interleukin-6 Concentrations in Cancer Patients With Depression: Preliminary Findings

TL;DR: Higher than normal plasma IL-6 concentrations were associated with a diagnosis of major depression in cancer patients and may contribute to sickness behavior that has overlapping symptoms with major depression.
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Validated prediction model for the development of primary open-angle glaucoma in individuals with ocular hypertension.

TL;DR: A quantitative calculator to estimate the 5-year risk of developing POAG, based on the pooled OHTS-EGPS predictive model, has high precision and will be useful for clinicians and patients in deciding the frequency of tests and examinations during follow-up and advisability of initiating preventive treatment.