Qing He
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Previous Organizations / Institutes
The organizations / institutes from the scholar's other articles in the past ten years
Research Subjects
Qing He has a total of 16 co-authors. Here are the top co-authors by number of shared publications:
- Chenxu Yu
Department of Agricultural and Biosystems Engineering, Iowa State University, Ames, IA 50011, USA
2 shared publications - Binbin Weng
School of Electrical and Computer Engineering, University of Oklahoma, Norman, OK 73019, USA
1 shared publication Gary S. Leiserowitz
Division of Gynecologic Oncology, University of California Davis Medical Center, Sacramento, CA, USA
1 shared publicationHanna J. Koster
Department of Biomedical Engineering, University of California, Davis, USA
1 shared publicationHannah J. O'TOole
Department of Biomedical Engineering, University of California, Davis, USA
1 shared publicationJingyi Yang
Affiliation Department of Agricultural and Biosystems Engineering, Iowa State University, Ames, IA, United States of America
1 shared publication
Latest Publications
- Open Access
- 18 July 2025
- Published by Elsevier in Biosensors and Bioelectronics
- Vol. 288, 117800
Integration of label-free surface enhanced Raman spectroscopy (SERS) of extracellular vesicles (EVs) with Raman tagged labels to enhance ovarian cancer diagnostics
- 18 July 2025
- Published by Elsevier in Biosensors and Bioelectronics
- Vol. 288, 117800
Open AccessIntegration of label-free surface enhanced Raman spectroscopy (SERS) of extracellular vesicles (EVs) with Raman tagged labels to enhance ovarian cancer diagnostics
- Open Access
- 24 December 2022
- Published by MDPI AG in Marine Drugs
- Vol. 21 (1) , 14
Advances in Algin and Alginate-Hybrid Materials for Drug Delivery and Tissue Engineering
In this review, we aim to provide a summary of recent research advancements and applications of algin (i.e., alginic acid) and alginate-hybrid materials (AHMs) in medical fields. Algin/alginate are abundant natural products that are chemically inert and biocompatible, and they have superior gelation properties, good mechanical strengths, and biodegradability. The AHMs have been widely applied in wound dressing, cell culture, tissue engineering, and drug delivery. However, medical applications in different fields require different properties in the AHMs. The drug delivery application requires AHMs to provide optimal drug loading, controlled and targeted drug-releasing, and/or visually guided drug delivery. AHMs for wound dressing application need to have improved mechanical properties, hydrophilicity, cell adhesion, and antibacterial properties. AHMs for tissue engineering need improved mechanical properties that match the target organs, superior cell affinity, and cell loading capacity. Various methods to produce AHMs that meet different needs were summarized. Formulations to form AHMs with improved stability, drug/cell-loading capacity, cell adhesion, and mechanical properties are active research areas. This review serves as a road map to provide insights into the strategies to develop AHMs in medical applications.
- 24 December 2022
- Published by MDPI AG in Marine Drugs
- Vol. 21 (1) , 14
Open AccessAdvances in Algin and Alginate-Hybrid Materials for Drug Delivery and Tissue Engineering
In this review, we aim to provide a summary of recent research advancements and applications of algin (i.e., alginic acid) and alginate-hybrid materials (AHMs) in medical fields. Algin/alginate are abundant natural products that are chemically inert and biocompatible, and they have superior gelation properties, good mechanical strengths, and biodegradability. The AHMs have been widely applied in wound dressing, cell culture, tissue engineering, and drug delivery. However, medical applications in different fields require different properties in the AHMs. The drug delivery application requires AHMs to provide optimal drug loading, controlled and targeted drug-releasing, and/or visually guided drug delivery. AHMs for wound dressing application need to have improved mechanical properties, hydrophilicity, cell adhesion, and antibacterial properties. AHMs for tissue engineering need improved mechanical properties that match the target organs, superior cell affinity, and cell loading capacity. Various methods to produce AHMs that meet different needs were summarized. Formulations to form AHMs with improved stability, drug/cell-loading capacity, cell adhesion, and mechanical properties are active research areas. This review serves as a road map to provide insights into the strategies to develop AHMs in medical applications.
- Open Access
- 15 April 2022
- Published by MDPI AG in Biosensors
- Vol. 12 (4) , 250
Label-Free Differentiation of Cancer and Non-Cancer Cells Based on Machine-Learning-Algorithm-Assisted Fast Raman Imaging
This paper proposes a rapid, label-free, and non-invasive approach for identifying murine cancer cells (B16F10 melanoma cancer cells) from non-cancer cells (C2C12 muscle cells) using machine-learning-assisted Raman spectroscopic imaging. Through quick Raman spectroscopic imaging, a hyperspectral data processing approach based on machine learning methods proved capable of presenting the cell structure and distinguishing cancer cells from non-cancer muscle cells without compromising full-spectrum information. This study discovered that biomolecular information–nucleic acids, proteins, and lipids—from cells could be retrieved efficiently from low-quality hyperspectral Raman datasets and then employed for cell line differentiation.
- 15 April 2022
- Published by MDPI AG in Biosensors
- Vol. 12 (4) , 250
Open AccessLabel-Free Differentiation of Cancer and Non-Cancer Cells Based on Machine-Learning-Algorithm-Assisted Fast Raman Imaging
This paper proposes a rapid, label-free, and non-invasive approach for identifying murine cancer cells (B16F10 melanoma cancer cells) from non-cancer cells (C2C12 muscle cells) using machine-learning-assisted Raman spectroscopic imaging. Through quick Raman spectroscopic imaging, a hyperspectral data processing approach based on machine learning methods proved capable of presenting the cell structure and distinguishing cancer cells from non-cancer muscle cells without compromising full-spectrum information. This study discovered that biomolecular information–nucleic acids, proteins, and lipids—from cells could be retrieved efficiently from low-quality hyperspectral Raman datasets and then employed for cell line differentiation.
- Open Access
- 5 May 2021
- Published by Public Library of Science (PLoS) in PLOS ONE
- Vol. 16 (5) , e0250650
Surface-enhanced Raman spectroscopic chemical imaging reveals distribution of pectin and its co-localization with xyloglucan inside onion epidermal cell wall
The primary plant cell wall is a complex matrix composed of interconnected polysaccharides including cellulose, hemicellulose, and pectin. Changes of this dynamic polysaccharide system play a critical role during plant cell development and differentiation. A better understanding of cell wall architectures can provide insight into the plant cell development. In this study, a Raman spectroscopic imaging approach was developed to visualize the distribution of plant cell wall polysaccharides. In this approach, Surface-enhanced Raman scattering (SERS through self-assembled silver nanoparticles) was combined with Raman labels (4-Aminothiophenol. 4ATP) and targeted enzymatic hydrolysis to improve the sensitivity, specificity, and throughput of the Raman imaging technique, and to reveal the distribution of pectin and its co-localization with xyloglucan inside onion epidermal cell (OEC) wall. This technique significantly decreased the required spectral acquisition time. The resulted Raman spectra showed a high Raman signal. The resulted Raman images successfully revealed and characterized the pectin distribution and its co-localization pattern with xyloglucan in OEC wall.
- 5 May 2021
- Published by Public Library of Science (PLoS) in PLOS ONE
- Vol. 16 (5) , e0250650
Open AccessSurface-enhanced Raman spectroscopic chemical imaging reveals distribution of pectin and its co-localization with xyloglucan inside onion epidermal cell wall
The primary plant cell wall is a complex matrix composed of interconnected polysaccharides including cellulose, hemicellulose, and pectin. Changes of this dynamic polysaccharide system play a critical role during plant cell development and differentiation. A better understanding of cell wall architectures can provide insight into the plant cell development. In this study, a Raman spectroscopic imaging approach was developed to visualize the distribution of plant cell wall polysaccharides. In this approach, Surface-enhanced Raman scattering (SERS through self-assembled silver nanoparticles) was combined with Raman labels (4-Aminothiophenol. 4ATP) and targeted enzymatic hydrolysis to improve the sensitivity, specificity, and throughput of the Raman imaging technique, and to reveal the distribution of pectin and its co-localization with xyloglucan inside onion epidermal cell (OEC) wall. This technique significantly decreased the required spectral acquisition time. The resulted Raman spectra showed a high Raman signal. The resulted Raman images successfully revealed and characterized the pectin distribution and its co-localization pattern with xyloglucan in OEC wall.