Anquan Shang | Medicine | Best Researcher Award

Prof. Anquan Shang | Medicine | Best Researcher Award

The Second People’s Hospital of Lianyungang | China

Prof. Anquan Shang is a distinguished Associate Chief Laboratory Technician and Clinical Laboratory Physician with an H-index of 26. At the age of 39, he has made significant contributions to the field of clinical laboratory diagnostics. As a master’s supervisor, he plays a crucial role in mentoring future medical professionals. He is currently affiliated with Shanghai Jiao Tong University and has extensive experience in tumor marker research and clinical diagnostics.

Profile👤

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Strengths for the Awards✨

  • Strong Research Productivity 

    • H-index of 26, indicating high citation impact.
    • Over 70 SCI and core journal publications as first or corresponding author.
    • Multiple high-impact factor papers in oncology, microbiology, and immunology.
  • Impressive Funding & Grants 

    • Secured multiple national and provincial-level research grants.
    • Led and participated in 13+ major projects in oncology, infection, and precision diagnostics.
  • Leadership & Recognition 

    • Head of key clinical departments and training programs in prestigious hospitals.
    • Recognized in Shanghai and Jiangsu talent programs, highlighting academic excellence.
  • Significant Innovations & Impact 

    • Contributions to liquid biopsy, tumor biomarkers, and infection diagnostics.
    • 5+ patents, demonstrating translational research impact.
  • Professional Network & Influence 

    • Active in national and international research communities.
    • Reviewer and editor for multiple scientific journals.

🎓 Education

His academic journey began with a specialization in medical laboratory technology at Xiangfan Vocational and Technical College (2005-2008). He then pursued a bachelor’s degree in medical laboratory science at Jiangsu University (2011-2014), followed by a master’s degree in clinical laboratory diagnostics at Ningxia Medical University (2014-2017). He furthered his expertise with a Ph.D. in clinical laboratory diagnostics from Tongji University (2017-2020), establishing a strong foundation for his research career.

🏥 Experience

Currently, he is a postdoctoral researcher in clinical laboratory diagnostics at Ruijin Hospital, affiliated with Shanghai Jiao Tong University (2025-present), focusing on tumor biomarker research. Since 2023, he has led the Clinical Laboratory Medicine Department at Lianyungang Second People’s Hospital, a key clinical specialty in Jiangsu Province. Previously, he completed another postdoctoral fellowship at Tongji University (2020-2022), researching tumor microenvironment and biomarkers. His clinical experience spans roles as a laboratory technician at various hospitals between 2008 and 2014, steadily advancing to leadership positions.

🔬 Research Interests On Medicine

His research focuses on:

1️⃣ Tumor immunology 🧬

2️⃣ Infection microecology and immune microenvironment remodeling 🦠

3️⃣ Precision molecular diagnostics for chronic diseases 🏥

4️⃣ Liquid biopsy techniques for early disease detection 💉

🏆 Awards

He has received numerous prestigious awards, including the Yancheng City Natural Science Achievement Award (3 times), the Yancheng Medical New Technology Introduction Award (5 times), and the Huaihai Science and Technology Progress Award (2nd Prize, twice). From 2019-2022, he was consecutively recognized as an Outstanding Young Scientific Researcher by the Shanghai Medical Association Laboratory Medicine Branch.

📚 Publications

  • Title: Exosomal circPACRGL promotes progression of colorectal cancer via the miR-142-3p/miR-506-3p-TGF-β1 axis
    Authors: A Shang, C Gu, W Wang, X Wang, J Sun, B Zeng, C Chen, W Chang, …
    Publication Year: 2020
    Citations: 372

  • Title: Long non-coding RNA HOTTIP enhances IL-6 expression to potentiate immune escape of ovarian cancer cells by upregulating the expression of PD-L1 in neutrophils
    Authors: A Shang, W Wang, C Gu, C Chen, B Zeng, Y Yang, P Ji, J Sun, J Wu, …
    Publication Year: 2019
    Citations: 147

  • Title: Exosomal KRAS mutation promotes the formation of tumor-associated neutrophil extracellular traps and causes deterioration of colorectal cancer by inducing IL-8 expression
    Authors: A Shang, C Gu, C Zhou, Y Yang, C Chen, B Zeng, J Wu, W Lu, W Wang, …
    Publication Year: 2020
    Citations: 100

  • Title: Tumor microenvironment: lactic acid promotes tumor development
    Authors: Y Gao, H Zhou, G Liu, J Wu, Y Yuan, A Shang
    Publication Year: 2022
    Citations: 80

  • Title: Exosomal miR-183-5p promotes angiogenesis in colorectal cancer by regulation of FOXO1
    Authors: A Shang, X Wang, C Gu, W Liu, J Sun, B Zeng, C Chen, P Ji, J Wu, …
    Publication Year: 2020
    Citations: 77

  • Title: Relationship between HER2 and JAK/STAT-SOCS3 signaling pathway and clinicopathological features and prognosis of ovarian cancer
    Authors: AQ Shang, J Wu, F Bi, YJ Zhang, LR Xu, LL Li, FF Chen, WW Wang, …
    Publication Year: 2017
    Citations: 77

  • Title: Knockdown of long noncoding RNA PVT1 suppresses cell proliferation and invasion of colorectal cancer via upregulation of microRNA-214-3p
    Authors: AQ Shang, WW Wang, YB Yang, CZ Gu, P Ji, C Chen, BJ Zeng, JL Wu, …
    Publication Year: 2019
    Citations: 70

  • Title: IGF2BP2 promotes the progression of colorectal cancer through a YAP‐dependent mechanism
    Authors: J Cui, J Tian, W Wang, T He, X Li, C Gu, L Wang, J Wu, A Shang
    Publication Year: 2021
    Citations: 62

  • Title: miR‐381‐3p restrains cervical cancer progression by downregulating FGF7
    Authors: A Shang, C Zhou, G Bian, W Chen, W Lu, W Wang, D Li
    Publication Year: 2019
    Citations: 62

  • Title: Vaginal microecological characteristics of women in different physiological and pathological period
    Authors: L Shen, W Zhang, Y Yuan, W Zhu, A Shang
    Publication Year: 2022
    Citations: 59

🔚 Conclusion

With a strong academic background, leadership in clinical laboratory medicine, and groundbreaking research in tumor immunology and molecular diagnostics, he continues to make significant contributions to medical science. His extensive experience, prestigious awards, and influential publications highlight his dedication to advancing clinical diagnostics and improving patient outcomes.

Alphonse Houssou Hounye | medicine | Best Researcher Award

Dr. Alphonse Houssou Hounye | Medicine | Best Researcher Award

Second Xiangya Hospital | Central south university | China

Dr. Hounye Alphonse Houssou is a dedicated mathematician and researcher currently affiliated with the General Surgery Department at the Second Xiangya Hospital, Central South University, China. With a focus on bioinformatics, image processing, and statistical machine learning, Dr. Houssou is recognized for his significant contributions to scientific research, particularly in cancer prognosis and machine learning models.

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Strengths for the Awards

Dr. Alphonse Hounye Houssou demonstrates exceptional strengths in the field of scientific research, particularly in bioinformatics, image processing, and machine learning. His contributions include:

  1. Extensive Research Output: With 32 research papers and 21 SCI-indexed publications, including eight as the first author, Dr. Houssou has proven his ability to publish high-quality and impactful research.
  2. Innovative Contributions: His work on high-dimensional omics data analysis has led to groundbreaking findings, such as identifying hub immune-related genes (TRIM67, CORT, PSPN, SCAMP5, RFXAP) in pancreatic cancer prognosis.
  3. Recognition and Awards: He has earned multiple prestigious awards, including the ITCIE Award, Best Researcher Award (International Research Awards), and the Outstanding International Student Award (2022–2023).
  4. Leadership and Collaboration: Dr. Houssou has collaborated with over 10 institutions, participated in COVID-19-related research projects, and contributed to academic seminars, showcasing his leadership and teamwork abilities.

Education 🎓

Dr. Hounye Alphonse Houssou obtained a B.S. in Mathematics from Abomey-Calavi University, Benin, and earned an M.S. in Mathematical Statistics from JiangXi University of Finance and Economics, China, in 2015 and 2020, respectively. Currently, he is pursuing a Ph.D. at the School of Mathematics and Statistics, Central South University, China.

Experience 🏢

With extensive academic and professional experience, Dr. Houssou has been part of numerous innovative research projects. He has also contributed to COVID-19-related academic seminars and exhibited leadership across multidisciplinary teams. Additionally, he actively collaborates with over 10 research institutions globally, contributing to groundbreaking scientific advancements.

Research Interests On medicine🔬

Dr. Houssou’s research interests include:

  • Bioinformatics
  • Image Processing
  • Statistical and Deep Machine Learning

His work focuses on analyzing high-dimensional omics data, developing individualized risk assessments, and uncovering disease biomarkers for improved diagnostics and treatments, particularly in oncology.

Awards 🏆

Dr. Houssou has received several prestigious accolades:

  • ITCIE Award for research excellence
  • Best Researcher Award (International Research Award on Advanced Nanomaterials and Nanotechnology)
  • Outstanding International Student Award (2022–2023)

These awards reflect his contributions to advanced scientific research and innovation.

Publications 📚

  • Title: Characterization of PANoptosis-related genes in Crohn’s disease by integrated bioinformatics, machine learning, and experiments
    Authors: Yang, Y., Hounye, A.H., Chen, Y., Shi, G., Xiao, Y.
    Year: 2024
    Citations: 2
  • Title: A graph-optimized deep learning framework for recognition of Barrett’s esophagus and reflux esophagitis
    Authors: Hou, M., Wang, J., Liu, T., Wang, K., Chen, S.
    Year: 2024
    Citations: 0
  • Title: Explainable machine learning model identified potential biomarkers in liver cancer survival prediction
    Authors: Pan, Q., Houssou Hounye, A., Miao, K., Hou, M., Xiong, L.
    Year: 2024
    Citations: 0
  • Title: Automated heart disease prediction using improved explainable learning-based technique
    Authors: Bizimana, P.C., Zhang, Z., Hounye, A.H., Hammad, M., El-Latif, A.A.A.
    Year: 2024
    Citations: 3
  • Title: Explainable cancer factors discovery: Shapley additive explanation for machine learning models demonstrates the best practices in the case of pancreatic cancer
    Authors: Su, L., Hounye, A.H., Pan, Q., Hou, M., Xiong, L.
    Year: 2024
    Citations: 1
  • Title: Exploring explainable machine learning and Shapley additive explanations (SHAP) technique to uncover key factors of HNSC cancer: An analysis of the best practices
    Authors: Miao, K., Houssou Hounye, A., Su, L., Hou, M., Xiong, L.
    Year: 2024
    Citations: 5
  • Title: Integrated explainable machine learning and multi-omics analysis for survival prediction in cancer with immunotherapy response
    Authors: Hounye, A.H., Xiong, L., Hou, M.
    Year: 2024
    Citations: 0
  • Title: SCARNet: using convolution neural network to predict time series with time-varying variance
    Authors: Zhao, S., Kong, M., Li, R., Hou, M., Cao, C.
    Year: 2024
    Citations: 1
  • Title: Modeling SARS coronavirus-2 omicron variant dynamic via novel fractional derivatives with immunization and memory trace effects
    Authors: Liu, T., Yin, X., Liu, Q., Houssou Hounye, A.
    Year: 2024
    Citations: 1
  • Title: Evaluation of drug sensitivity, immunological characteristics, and prognosis in melanoma patients using an endoplasmic reticulum stress-associated signature based on bioinformatics and pan-cancer analysis
    Authors: Hounye, A.H., Hu, B., Wang, Z., Hou, M., Qi, M.
    Year: 2023
    Citations: 0

Conclusion ✅

Dr. Hounye Alphonse Houssou is a dynamic researcher dedicated to advancing machine learning applications in bioinformatics and medical diagnostics. His impactful contributions to cancer prognosis, along with numerous publications and awards, underscore his role as a leading scientist in the field.